URBAN WETLAND ECOLOGY AND FLOODS IN KUMASI, GHANA
Transcript of URBAN WETLAND ECOLOGY AND FLOODS IN KUMASI, GHANA
URBAN WETLAND ECOLOGY AND FLOODS IN KUMASI, GHANA
Benjamin Betey Campion
Institut für Geographie an der Universität Bremen
May, 2012
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URBAN WETLAND ECOLOGY AND FLOODS IN KUMASI, GHANA
Benjamin Betey Campion
Institut für Geographie an der Universität Bremen
May, 2012
Submitted for the degree of Doctor of Natural Sciences (Dr. rer. nat.) Supervisors: 1. Prof. Dr. Jörg-Friedhelm Venzke
2. Prof. Dr. Michael Flitner
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DECLARATION
I, Benjamin Betey Campion, hereby declare that this thesis has been independently written by me and is original.
Where information has been derived from other sources, I confirm that this has been indicated in the thesis.
Bremen, …27. 09.2012.…………………….…….. …………. Date Benjamin Betey Campion
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ACKNOWLEDGEMENT My soul gives thanks to the Lord my God for taking me this far. May the Name of God be blessed forever!
I am very grateful to Prof. Dr. Jörg-Friedhelm Venzke for the bold initiative he took and accepted me as his student. Finding such a father figure from the internet is a million dollar lottery ticket. Prof. Venzke, your friendship, encouragement, sense of humour, humility and simplicity have been my inspiration and support in writing this thesis. I love your open door approach to supervision. I am also very grateful to Prof. Dr. Michael Flitner for accepting to be the second supervisor. Thank you for the invaluable suggestions and criticisms in shaping me into an up-and-coming scientist.
I also received tremendous moral and scientific support from Bruni Hans, Birte Habel, PD. Dr. Karin Steinecke, Dr. Steffen Schwantz and Dr. Marco Langer. I love this small family that nurtured me. You will always be cherished for everything you did to make my stay in Uni-Bremen, UFT, Abeitsgruppe Klima- und Vegetationsgeographie, and above all, Room 0060 a wonderful one. I am also grateful and indebted to my colleagues in the Faculty of Renewable Natural Resources, KNUST, for their support. Prof. Steve Amisah, thank you for advising me to get a PhD.
For the second time, the Katholischer Akademischer Ausländer-Dienst (KAAD) deemed me fit for their highly competitive scholarship. I am highly indebted to you and appreciate your contribution in shaping my life this far. Marko, Simone and the many others at the KAAD office, thank you and God will richly bless you for the trust and confidence you had in me. I look forward to a future of sharing the task of developing humanity with you. Thank you.
To my inspirational friends: Dr. Callistus Mahama, Dr. Nana Ato Arthur, Seth Mensah Abobi, Dr. Julius Fobil, Cephas Kwesi Zuh, Isaac Sackey, Kwabena Asubonteng, and Dr. David Yegbey, thank you.
I will never forget the continuous and diverse support of the Campions: Kofi, Jatuat, Teni, Jakper, Yaw, Yenukwah, Victor, Dumbian, Lardi, Tisob, Sanjaung, Kibirsiar and Cynthia. You are the pillar behind this work. Thank you and let us uphold the family spirit. I could not have made it without a partner. A friend for life, my hope in times of despair, my all: Elma.
“You placed gold on my finger You brought love like I've never known You gave life to our children And to me, a reason to go on. …… But most of all, you're my best friend” (Don Williams).
Palmaak and Iloam, you are my motivation and reason for studying. Thank you for always accepting me after the long periods away from home.
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DEDICATION To my dad who said, ‘Ben, go to school’; and to my mum who made it all possible.
John Limuub Campion & Mary Konjit Lambon
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LIST OF ACRONYMS As Arsenic Cd Cadmium CF Contamination Factor Cr Chromium Cu Copper DEMC District Environmental Management Committee DO Dissolved Oxygen EF Enrichment Factor EPA Environmental Protection Agency FRNR Faculty of Renewable Natural Resources Hg Mercury HSD Hydrological Services Department IFRC International Federation of Red Cross and Red Crescent Societies Igeo Geo-accumulation Index IPCC Intergovernmental Panel on Climate Change ITCZ Intertropical Convergence Zone KMA Kumasi Metropolitan Assembly KNUST Kwame Nkrumah University of Science and Technology MDGs Millennium Development Goals MDS non-Metric Multidimensional Scaling NADMO National Disaster Management Organisation NEPAD New Partnership for African Development Ni Nickel P Phosphorus Pb Lead PCA Principal Components Analysis PLI Pollution Load Index PRS Poverty Reduction Strategy TCPD Town and Country Planning Department TDS Total Dissolved Solids Zn Zinc
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TABLE OF CONTENTS DECLARATION ...................................................................................................................iii
ACKNOWLEDGEMENT .................................................................................................... iv
DEDICATION ....................................................................................................................... v
LIST OF ACRONYMS ........................................................................................................ vi
TABLE OF CONTENTS......................................................................................................vii
LIST OF FIGURES .............................................................................................................. xi
LIST OF TABLES ...............................................................................................................xiv
LIST OF PHOTOGRAPHS ................................................................................................. xv
APPENDICES .....................................................................................................................xvi
LIST OF PUBLICATIONS FROM THIS THESIS ........................................................... xvii
ABSTRACT....................................................................................................................... xviii
ZUSAMMENFASSUNG ....................................................................................................xix
1 RESEARCH THEME AND THEORETICAL FRAMEWORK ....................................... 1
1.1 INTRODUCTION....................................................................................................... 1
1.2 RESEARCH BACKGROUND AND JUSTIFICATION ........................................... 2
1.2.1 Urban Environmental Issues ................................................................................ 2
1.2.2 Research Justification .......................................................................................... 4
1.3 RESEARCH GOAL .................................................................................................... 7
1.4 RESEARCH OBJECTIVES ....................................................................................... 7
1.5 RESEARCH QUESTIONS......................................................................................... 7
1.6 CONCEPTUAL AND THEORETICAL FRAMEWORKS ....................................... 8
1.7 HYPOTHESES ......................................................................................................... 12
2 WETLANDS, URBANISATION AND FLOOD NEXUS ............................................. 14
2.1 INTRODUCTION..................................................................................................... 14
2.2 WETLANDS ............................................................................................................. 14
2.2.1 Morphology and Hydrodynamics of Wetlands .................................................. 17
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2.2.2 Distribution, Values and Degradation of Wetlands ........................................... 18
2.3 URBANISATION ..................................................................................................... 21
2.3.1 Concept and History of Urbanisation ................................................................ 21
2.3.2 Modern Trends in Urbanisation ......................................................................... 23
2.3.3 Urbanisation Trends in sub-Saharan Africa....................................................... 25
2.4 URBANISATION AND THE ENVIRONMENT .................................................... 26
2.5 WETLANDS AND URBANISATION .................................................................... 28
2.5.1 Urban Wetlands Vegetation ............................................................................... 31
2.5.2 Wetlands, Urbanisation and Agriculture............................................................ 32
2.5.3 Wetlands, Urbanisation and Floods ................................................................... 35
2.6 URBAN POVERTY AND WETLANDS................................................................. 37
2.6.1 Urban Poverty in Africa ..................................................................................... 37
2.6.2 Urban Poverty and the Environmental Kuznets Curve ...................................... 38
2.7 CLIMATE CHANGE, URBANISATION AND WETLANDS............................... 40
2.8 REMOTE SENSING AND URBAN LANDSCAPE PLANNING AND MANAGEMENT................................................................................................................. 42
3 POLITICAL ECOLOGY OF WETLANDS IN KUMASI.............................................. 45
3.1 INTRODUCTION..................................................................................................... 45
3.2 METHODOLOGY .................................................................................................... 46
3.2.1 Physical and Socio-economic Survey of Wetland Communities of Kumasi..... 46
3.2.2 Data Analysis ..................................................................................................... 48
3.3 RESULTS.................................................................................................................. 48
3.3.1 The Physical Characteristics of Kumasi ............................................................ 48
3.3.2 Socio-economic Characteristics of Wetland Communities in Kumasi .............. 52
3.3.3 Community Efforts at Wetland Management in Kumasi .................................. 60
3.4 DISCUSSION ........................................................................................................... 63
4 FLOODS AND ENVIRONMENTAL MANAGEMENT IN KUMASI, GHANA ........ 67
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4.1 INTRODUCTION..................................................................................................... 67
4.2 ENVIRONMENTAL MANAGEMENT AND THE NATIONAL ENVIRONMENTAL ACTION PLAN ............................................................................... 69
4.2.1 The Environmental Protection Agency.............................................................. 69
4.2.2 Water Resources Commission ........................................................................... 70
4.2.3 Lands Commission............................................................................................. 72
4.2.4 Local Government and Environmental Management ........................................ 73
4.3 WETLANDS, FLOOD PREVENTION AND MANAGEMENT ............................ 74
4.3.1 Stakeholders’ Capacity for Managing Wetlands and Floods ............................. 74
4.4 DISCUSSION ........................................................................................................... 79
5 WETLAND ECOLOGY AND VEGETATION GEOGRAPHY IN THE KUMASI METROPOLIS ........................................................................................................................ 85
5.1 INTRODUCTION..................................................................................................... 85
5.2 METHODOLOGY .................................................................................................... 86
5.2.1 Reconnaissance Survey of Wetlands in Kumasi and Selection of Study Sites .. 86
5.2.2 Ecological Survey of Wetlands in Kumasi ........................................................ 87
5.2.3 Data Analysis ..................................................................................................... 91
5.3 RESULTS.................................................................................................................. 91
5.3.1 Anthropogenic Activities in the Wetland Areas of Kumasi .............................. 91
5.3.2 Wetland Edaphic Characteristics, Heavy Metals and Stream Physicochemical Characteristics .................................................................................................................. 94
5.3.3 Wetland Vegetation of Kumasi........................................................................ 107
5.4 DISCUSSION ......................................................................................................... 123
6 CLIMATE, LANDUSE CHANGES AND FLOODING IN THE KUMASI METROPOLIS ...................................................................................................................... 128
6.1 INTRODUCTION................................................................................................... 128
6.2 METHODOLOGY .................................................................................................. 129
6.2.1 Rainfall and Flood Data Collection and Analysis............................................ 129
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6.2.2 Assessment of Urbanisation of Kumasi ........................................................... 129
6.3 RESULTS................................................................................................................ 130
6.3.1 Rainfall Patterns and Trends in Kumasi .......................................................... 130
6.3.2 Floods in Kumasi ............................................................................................. 139
6.3.3 Landcover Change in Kumasi.......................................................................... 146
6.4 DISCUSSION ......................................................................................................... 150
7 GENERAL DISCUSSION, CONCLUSIONS AND RECOMMENDATIONS ........... 154
7.1 GENERAL DISCUSSION...................................................................................... 154
7.2 CONCLUSIONS ..................................................................................................... 157
7.3 RECOMMENDATIONS ........................................................................................ 159
8 REFERENCES .............................................................................................................. 162
9 APPENDICES ............................................................................................................... 179
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LIST OF FIGURES Figure 1.1. Conceptual framework for the investigation of urbanisation, socio-economic activities and incidence of floods in Kumasi ........................................................................... 10
Figure 1.2. A composite model of the effects of human interference on a wetland ecosystem in an urban setting .................................................................................................................... 11
Figure 2.1. An illustration of the continuum between the terrestrial, wetland and aquatic systems ..................................................................................................................................... 15
Figure 2.2. Distribution of wetlands in the world .................................................................... 20
Figure 2.3. Major vegetable farming areas in the Kumasi Metropolis .................................... 35
Figure 3.1. Map of Ghana with an insert showing limits of the Kumasi Metropolitan Assembly and the study sites ................................................................................................... 49
Figure 3.2. Population growth trajectory of the city of Kumasi .............................................. 50
Figure 3.3. The occupation of respondents from flood prone suburbs of Kumasi .................. 54
Figure 3.4. Residential types and homeownership of respondents in the different suburbs of Kumasi ..................................................................................................................................... 55
Figure 3.5. Respondents’ sources of land for construction of houses in the different suburbs of Kumasi ................................................................................................................................. 57
Figure 3.6. Reasons for choice of wetland area for construction of houses in the flood prone suburbs of Kumasi ................................................................................................................... 58
Figure 3.7. Factors or instruments that will motivate residents of the various flood prone communities to relocate ........................................................................................................... 59
Figure 3.8. The predominant uses of wetlands in the various suburbs of Kumasi .................. 61
Figure 3.9. Perception of wetland protection in Kumasi ......................................................... 61
Figure 3.10. Reasons for the continual destruction of wetlands in the various suburbs of Kumasi ..................................................................................................................................... 62
Figure 3.11. A proposed model to describe the decision to move or stay in the flood prone suburbs of Kumasi ................................................................................................................... 65
Figure 4.1. Assessment of stakeholders’ responsibility for the management of floods and wetlands in Kumasi .................................................................................................................. 74
Figure 4.2. Spatial distribution of houses marked for demolition and attitude towards demolition of houses in waterways by the Kumasi Metropolitan Assembly........................... 77
Figure 4.3. A conceptual model for management of floods and wetlands within the Kumasi Metropolis ............................................................................................................................... 83
Figure 5.1. A schematic diagram of a sample study site along a stream X showing the transects and quadrat layout ..................................................................................................... 87
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Figure 5.2. Landcover and Landuse activities within 100 m from the stream channel at the different study sites in Kumasi ................................................................................................ 93
Figure 5.3. Soil map of the Kumasi showing study sites . ....................................................... 95
Figure 5.4. A cluster diagram of the correlation matrix of the various environmental variables measured in the different suburbs of Kumasi ........................................................................ 100
Figure 5.5. A principal components analysis plot of the measured environmental parameters ................................................................................................................................................ 101
Figure 5.6. Heavy metals enrichment in the stream sediments of the different suburbs of Kumasi in the rainy season .................................................................................................... 102
Figure 5.7. Heavy metals enrichment in the stream sediments of the different suburbs of Kumasi in the dry season ....................................................................................................... 103
Figure 5.8. Heavy metals accumulation in the stream sediments of the different suburbs of Kumasi in the rainy season .................................................................................................... 104
Figure 5.9. Heavy metals accumulation in the stream sediments of the different suburbs of Kumasi in the dry season ....................................................................................................... 105
Figure 5.10. Seasonal differences in pollution by metals in the stream sediments of the different suburbs of Kumasi................................................................................................... 106
Figure 5.11. Number of species identified at the various wetland sites in Kumasi ............... 116
Figure 5.12. Species richness, evenness and Shannon diversity at the study sites in Kumasi................................................................................................................................................ 116
Figure 5.13. Species diversity indices with respect to distance from the water channel at the different sampling sites in Kumasi ........................................................................................ 117
Figure 5.14. Analysis of similarities of the community composition among wetland sites in Kumasi according to (a) presence or absence of surface water and (b) distance from the water channel ................................................................................................................................... 119
Figure 5.15. A hierarchical cluster of the community composition among wetland sites in Kumasi according to (a) presence or absence of surface water and (b) distance from the water channel ................................................................................................................................... 121
Figure 5.16. A non-metric multidimensional scaling plot of the community composition among wetland sites in Kumasi using the presence or absence of surface water as a factor . 122
Figure 5.17. A non-metric multidimensional scaling plot of the wetland sites in Kumasi using the measured environmental parameters................................................................................ 122
Figure 5.18. A principal components analysis plot of the sampled wetland sites in Kumasi superimposed with vector plots (circle and lines) of the measured environmental parameters................................................................................................................................................ 123
Figure 6.1. Average monthly rainfall pattern of Kumasi from 1961 to 2010 ........................ 131
Figure 6.2. Historical annual rainfall pattern of Kumasi from 1961 to 2010 ........................ 131
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Figure 6.3. Trends in rainfall of Kumasi for the months of January from 1960 to 2010 ....... 133
Figure 6.4. Trends in rainfall of Kumasi for the months of February from 1960 to 2010 ..... 133
Figure 6.5. Trends in rainfall of Kumasi for the months of March from 1960 to 2010 ......... 134
Figure 6.6. Trends in rainfall of Kumasi for the months of April from 1960 to 2010........... 134
Figure 6.7. Trends in rainfall of Kumasi for the months of May from 1960 to 2010 ............ 135
Figure 6.8. Trends in rainfall of Kumasi for the months of June from 1960 to 2010 ............ 135
Figure 6.9. Trends in rainfall of Kumasi for the months of July from 1960 to 2010 ............ 136
Figure 6.10. Trends in rainfall of Kumasi for the months of August from 1960 to 2010 ..... 136
Figure 6.11. Trends in rainfall of Kumasi for the months of September from 1960 to 2010 137
Figure 6.12. Trends in rainfall of Kumasi for the months of October from 1960 to 2010 .... 137
Figure 6.13. Trends in rainfall of Kumasi for the months of November from 1960 to 2010 138
Figure 6.14. Trends in rainfall of Kumasi for the months of December from 1960 to 2010 . 138
Figure 6.15. Trends in total annual rainfall of Kumasi from 1960 to 2010 ........................... 139
Figure 6.16. Respondents’ flood experience in the various suburbs of Kumasi.................... 140
Figure 6.17. Relationship between different rainfall events and total monthly rainfall for Kumasi from 1961 to 2010 .................................................................................................... 141
Figure 6.18. Trends in heavy rainfall events in Kumasi from 1961 to 2010 ......................... 142
Figure 6.19. Recession time of water at the various flood prone suburbs of Kumasi ........... 144
Figure 6.20. Adaptations of residents to floods in the various suburbs of Kumasi ............... 144
Figure 6.21. Flood response model of new and old residents of flood prone suburbs of Kumasi ................................................................................................................................... 145
Figure 6.22. Landcover changes within the jurisdiction of the Kumasi Metropolitan Assembly between 1986 and 2007.......................................................................................................... 147
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LIST OF TABLES Table 2.1. Likely effects of urbanisation on wetland hydrology and geomorphology ............ 18
Table 2.2. Anthropogenic effects on urban wetlands............................................................... 29
Table 2.3. Likely effects of urbanisation on wetland ecology ................................................. 29
Table 3.1. Stakeholder list and the respective data collection tools used in the survey of wetlands in Kumasi, Ghana ..................................................................................................... 47
Table 4.1. Ghana’s international commitments to the environment ........................................ 68
Table 4.2. Stakeholder capacity assessment on wetlands and flood prevention and management in Kumasi............................................................................................................ 76
Table 5.1. Classes of the geoaccumulation index used to define sediment quality ................. 89
Table 5.2. The Braun-Blanquet scale and the description of the values used for sampling of wetland species in Kumasi ....................................................................................................... 90
Table 5.3. Edaphic characteristics of wetland sites sampled in the Kumasi Metropolis ......... 98
Table 5.4. Physicochemical characteristics of water running through the wetlands in Kumasi.................................................................................................................................................. 98
Table 5.5. Species identified in the different wetlands of Kumasi and their importance values................................................................................................................................................ 109
Table 6.1. Descriptive statistics of monthly rainfall pattern of Kumasi from 1961 to 2010 . 132
Table 6.2. Rainfall events and reported floods in some suburbs of Kumasi in 2009 ............ 140
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LIST OF PHOTOGRAPHS Photograph 1. Some uses of wetlands in the Kumasi Metropolis............................................ 97
Photograph 2. State of some of the wetlands in the Kumasi Metropolis ............................... 108
Photograph 3. Some high importance value wetland species in the Kumasi Metropolis ...... 114
Photograph 4. More high importance value wetland species in the Kumasi Metropolis ...... 115
Photograph 5. House being built on stilts in a flood prone suburb in the Kumasi Metropolis................................................................................................................................................ 148
Photograph 6. Raised walkways in the compound of a flood prone house in the Kumasi Metropolis .............................................................................................................................. 148
Photograph 7. Embankment built around a flood prone house in the Kumasi Metropolis.... 149
Photograph 8. Embankment built around the main door to an apartment in a flood prone suburb of the Kumasi Metropolis .......................................................................................... 149
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APPENDICES Appendix 1. Survey instrument used for the wetland associated communities in Kumasi ... 179
Appendix 2. Survey instrument used for wetland associated NGOs and government agencies in Kumasi ............................................................................................................................... 185
Appendix 3. Field data sheet used for wetland vegetation and ecological studies in Kumasi................................................................................................................................................ 186
Appendix 4. Study sites and anthropogenic activities within 100 m from the water channel................................................................................................................................................ 187
Appendix 5. A Wilcoxon Signed Ranks Test comparison of the seasonal differences in physicochemical parameters of the wetlands in Kumasi ....................................................... 187
Appendix 6. Metal concentration (mg/kg) in sediments of the different study sites in Kumasi................................................................................................................................................ 189
Appendix 7. Pearson correlation matrix of heavy metals and other measured environmental variables (significant relationships shown in bold) ............................................................... 190
Appendix 8. Principal Component Analysis of environmental variables and heavy metals assessed in the wetlands of Kumasi ....................................................................................... 191
Appendix 9. Comparison of means of heavy metal enrichment factors for rainy and dry season in Kumasi ................................................................................................................... 192
Appendix 10. Comparison of means of heavy metal geoaccumulation indices for rainy and dry season in Kumasi ............................................................................................................. 193
Appendix 11. Comparison of means of Pollution Load Indices for the different sites in the rainy and dry season in Kumasi ............................................................................................. 194
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LIST OF PUBLICATIONS FROM THIS THESIS The following manuscripts have been prepared with material from this thesis and submitted
for publication:
1. Campion, B. B. & Venzke, J. -F. (2011). Spatial patterns and determinants of wetland
vegetation distribution in the Kumasi Metropolis, Ghana. Wetlands Ecology and
Management, 19(5): 423-431
2. Campion, B. B. & Venzke, J. -F. Rainfall variability, floods and adaptations of the
urban poor to flooding in Kumasi, Ghana. This manuscript has been accepted for publication
in Natural Hazards published by Springer.
3. Campion, B. B. & Venzke, J. -F. Beyond defining wetlands to feeling wet: the
political ecology of wetlands in Kumasi, Ghana. This manuscript is under review by
Wetlands Ecology and Management published by Springer.
In all these papers, I developed the concept of the study, collected data and wrote the manuscript
with scientific advice from Venzke, J. –F.
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ABSTRACT Urbanisation and climate change are two of the greatest environmental challenges the world
is experiencing. Wetlands bear the heaviest effects of urbanisation in Kumasi, Ghana. Also,
current forecasts show that climate change will very much affect sub-Saharan Africa and may
cause flooding in many areas. Already, Kumasi has been battling with a growing incidence
and scale of floods, mostly, at the suburbs closer to wetland areas. This research therefore
sought to investigate the interlocked issues of urbanisation, climate change, wetland ecology
and degradation and flooding in Kumasi. The vegetation, edaphic characteristics, hydrology
and physicochemical conditions of the wetlands were analysed. Various stakeholders were
interviewed on wetlands management, floods and adaptations to living with floods. Rainfall
data from 1961 to 2010 was analysed for trends. The landuse change from vegetated to built
environment was also analysed. Whilst there were some plant species common to all the
wetlands, the species composition for each wetland was unique. In each wetland, the level of soil
water saturation was found to influence species composition. The percentage organic carbon of
the wetland soils was the strongest factor that explained the observed spatial heterogeneity of
wetland vegetation in Kumasi. All the wetlands were found to be polluted by all the heavy
metals investigated. Furthermore, the built-up and bare areas within the Kumasi Metropolitan
Assembly (KMA) have been growing at a rate of 1.9 % per annum between 1986 and 2007.
Conversely, the results indicated no significant change in rainfall of Kumasi for the flood
prone months of June and July and, therefore, the floods were not due to climate change. Two
types of floods were, however, identified in the suburbs studied: flash floods due to heavy
rainfall events and “effluent stream floods” caused by a rise in the water table during the peak
rainy seasons. Adaptations to floods by residents included dredging of streams, erection of embankments around houses or apartments, moving property to higher grounds, building
networks of raised walkways and building houses on stilts. People continued to live in the flood
prone areas because, other forms of capital developed after living in these suburbs for a while,
far outweighed the push factors to relocate. Based on these findings, it was recommended that
the KMA should use the presence of effluent floods and the typical wetland vegetation
identified by this research as defining factors to delineate the wetland boundaries.
Considering the limited financial resources available to the KMA for an engineering-biased
urban drainage system, the approach to managing floods in Kumasi should be a combination
of the reconstruction of the natural wetlands and community specific social interventions.
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ZUSAMMENFASSUNG Verstädterung und Klimaänderungen stellen zwei der großen Herausforderungen für die
globale Umwelt dar. Urbanisierungsflächen stehen demzufolge unter hohem Nutzungsdruck;
dies gilt besonders für Feuchtgebiete. Eine hohe Verstädterungsrate, eine langsam vonstatten
gehende Raumplanung sowie die Unfähigkeit und Ungleichheit in der Bereitstellung
grundlegender sanitärer Anlagen führen in Ghana zur Bildung städtischer Ballungsräume mit
unterschiedlicher Umweltgüte. Armenviertel (slums) und informelle Siedlungen entwickeln
sich dabei meist in und um Überschwemmungsgebiete. Zudem zeigen aktuelle Vorhersagen,
dass der Klimawandel insbesondere den subsaharischen Raum Afrikas u. a. mit zunehmenden
Überschwemmungsereignissen betreffen wird. Bereits über einen langen Zeitraum mussten
sich die Behörden in Kumasi mit einer zunehmenden Anzahl an
Überschwemmungsereignissen in Armenviertel und informellen Siedlungen
auseinandersetzen.
Die vorliegende Arbeit stellt die notwendigen Informationen bereit, die einen ganzheitlichen
Lösungsansatz zu der komplexen Problematik aus Verstädterung, Verlust und Degradation
von natürlichen Feuchtgebieten sowie Überschwemmungsereignissen in Kumasi bieten.
Folgende Zielvorgaben stehen dabei im Fokus:
� Beschreibung und Charakteristik städtischer Feuchtgebiete in Kumasi, Ghana,
� Bestimmung von Überflutungsparameter sowie Bewältigungsstrategien gegenüber
Überflutungen in Kumasi,
� Überprüfung der Anwendbarkeit der Umwelt-Kuznets-Kurve (Environmental Kuznets
Curve [EKC]) als Instrument der Planung für überflutungsgefährdete Stadtteile in
Kumasi.
Um diese Ziele zu erreichen, wurden zunächst sämtliche Feuchtgebiete des Großraumes
Kumasi registriert. Neben Angaben zu den Vegetations-, Boden- und hydrologischen
Verhältnissen wurden die physisch-chemischen Zustände der Feuchtgebiete analysiert. Die
Informationen zu Feuchtgebietsmanagement, Überflutungen und Anpassungsstrategien an die
Lebensbedingungen wurden durch Befragungen verschiedener Interessensvertreter
gewonnen. Zudem wurden die Niederschlagsereignisse der vergangenen 50 Jahre
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ausgewertet. Darüber hinaus wurde auch der Effekt des Landnutzungswandels von
vegetationsbedeckten zu bebauten Flächen untersucht.
Alle untersuchten Feuchtgebiete gehören zu einem Flusssystem. Während einige der
Pflanzenarten in jedem Überflutungsbereich anzutreffen sind, besitzt jedes Feuchtgebiet
trotzdem eine spezifische Artenzusammensetzung. In jedem Feuchtgebiet folgt die Verteilung
der Vegetationsgesellschaften einem hydrologischen Gradienten; die Bodenwassersättigung
ist der dominante Faktor für die entsprechenden Artenzusammensetzungen. Der prozentuale
Anteil an organischem Kohlenstoff bildet eine weitere wesentliche Komponente zur
räumlichen Heterogenität von Vegetationsgesellschaften in Feuchtgebieten. Während
saisonale Unterschiede die chemischen Zustände des Wassers prägen (pH, DO), gibt es
hingegen keine saisonalen Veränderungen im Vegetationsbestand der Feuchtgebiete. Die
Artenvielfalt in den Feuchtgebieten wird nicht durch die benachbarte Landnutzung
beeinflusst; sondern vielmehr durch die hydrologischen und edaphischen Verhältnisse
innerhalb der Feuchtgebiete selbst. Aufgrund der Verhältnisse nahe der KNUST [Kwame
Nkrumah University of Science and Technology]-Polizeistation werden hier die höchsten
Raten an Kohlenstoffbindung erreicht. In allen untersuchten Feuchtgebieten kann eine
Kontamination mit Schwermetallen festgestellt werden. Wahrscheinlich stammt der Anteil an
Hg, Ni, Zn und Pb aus derselben Quelle, während die Immissionen von Cu und Cr andere
Quellen haben.
Überflutungen in Kumasi sind nicht als Folge veränderter Niederschlagmuster in den
Regenmonaten Juni und Juli zu verstehen. Es gibt zwei Typen von Überschwemmungen, die
einen Einfluss auf die untersuchten Feuchtgebietsgesellschaften ausüben: plötzlich
auftretende Überflutungen aufgrund starker Niederschlagsereignisse sowie Folgen eines
steigenden Grundwasserspiegels, der zur Bildung von Flussläufen beiträgt. Die bebaute und
vegetationsfreie Fläche innerhalb der Großstadtregion von Kumasi (Kumasi Metropolitan
Assembly [KMA]) ist im Zeitraum von 1986 bis 2007 um 1,9 % pro Jahr angestiegen. Dieser
Nutzungswandel führt aufgrund eines reduzierten Infiltrationsvermögen, kürzeren
Ablaufzeiten und folglich höheren Abflussmaxima zu höherem Oberflächenabfluss. Dies ist
die Hauptursache für plötzlich auftretende Überflutungen in Kumasi. Hingegen dauert die
Überflutungszeit an der Oberfläche als Folge ansteigenden Grundwasserpegels während der
Hauptregenzeit länger an.
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Die Einwohner haben sich an die Überflutungssituation weitgehend angepasst. Die
Anpassungsstrategien sind der Bau von Drainagegräben und der Bau von Dämmen um
Gebäude, Verlagerung von Besitz in höher gelegene Bereiche, Aufbau eines höher liegenden
Fußwegenetzes sowie Hausbau auf Pfählen. Wegen dieser Anpassungsmöglichkeiten ist die
ortsansässige Bevölkerung nur bereit fortzuziehen, wenn alternative Wohnmöglichkeiten
angeboten werden. Entsprechende Entscheidungen in den überflutungsgefährdeten Vororten
von Kumasi folgen dabei nicht immer den Vorgaben der EKC. Auch bei steigendem
Einkommen wandert die ortsansässige Bevölkerung nicht ab, auch nicht unter staatlichem
Druck. Die anderen Formen der Lebenssicherung, die sich nach einer gewissen
Aufenthaltszeit in diesen Vororten entwickelt haben, überwiegen die Gründe, die
Feuchtgebiete wegen der Überflutungsgefahr zu verlassen.
Die Mehrheit der für diese Studie befragten Interessensvertreter ist der Auffassung, dass die
Feuchtgebiete sehr wichtig sind und daher geschützt werden sollten. Die wichtigsten
Verantwortlichen für das Feuchtgebiets- und Überschwemmungsmanagement sind die
lokalen Clanchefs sowie die KMA. Zu den wichtigsten Aufgabenbereichen gehören die
Verbesserung von Landnutzungsplänen, Abbruch flutgefährdeter Gebäude und die Errichtung
öffentlicher Parks.
Aus den Ergebnissen geht hervor, dass die KMA das Auftreten von Grundwasserbedingten
Überflutungsereignisse sowie von charakteristischer Feuchtgebietsvegetation, die in dieser
Studie erfasst worden ist, als bestimmende Faktoren zur Abgrenzung von Feuchtgebieten
herangezogen werden sollten. Diese Methodik wurde besonders in den Feuchtgebieten nahe
der KNUST-Polizeistation, in den FRNR [Faculty Renewable Natural Resources]-
Bauernhöfen, in Atonsu, Family Chapel, Dakwadwom, Spetinpom und Golden Tulip Hotel
exemplarisch angewendet. Nach Festlegung der Grenzen der Überschwemmungsgebiete
sollten zunächst alle dort vorhandenen Bauten zerstört werden. In den mit neuen Namen
gekennzeichneten, sich mit Vegetation überziehenden Feuchtgebieten werden sich die
natürlichen Ökosystemfunktionen regenerieren. Dazu sollte die KMA die Zusammenarbeit
von Asantehene (König von Ashanti) anstreben, um mögliche Widerstände gegenüber den
Planungsmaßnahmen einzuschränken.
Zukünftig sollten stadtökologische Fragestellungen in den Blickpunkt wissenschaftlicher
Studien mehr berücksichtigt werden. Dazu gehören die mögliche Nutzung von Vegetation zur
xxii
Behandlung von städtischem Abwasser sowie die Bedeutung von Feuchtgebietsvegetation
zum Hochwassermanagement und zur Kohlenstoffbindung. Zudem sollten diese
wissenschaftlichen Untersuchungen die Grundlage für die Bewirtschaftungsmaßnahmen in
abgegrenzten Feuchtgebietsregionen darstellen, um die Biodiversität zu erhalten sowie den
Erholungswert dieser Räume zu steigern.
Um den direkten Eintrag von Schadstoffen in die Gewässer zu verringern, sollte die KMA die
Unterbringung von Abfallsammelbecken in Feuchtgebieten einstellen. Wo es für notwendig
erscheint, sollte eine Mauer um eine derartige Anlage eingerichtet werden, um Überläufe der
Abwässer zu verhindern.
Die Feuchtgebiete um die KNUST-Polizeistation sollte aufgrund ihres ökologischen Wertes
für die Erhaltung von Torfvorkommen geschützt werden. Dieser Standort könnte aufgrund
seines Potenzials als „Kohlenstoffsenke“ im Rahmen des CO2-Handels zur Abschwächung
des Klimawandels als mögliche Einnahmequelle für die KMA fungieren. Beispielsweise böte
die Errichtung einer Gartenstadt eine praktische Umsetzung des von den Vereinten Nationen
verabschiedeten Gesetzes zur „Reduzierung von Emission aus Abholzung und Wald-
Degradierung“ (REDD+). Dies sollte der zukünftige Weg von Kumasi sein, um den
Forderungen der Konvention für globale Städtepartnerschaften für Biodiversität
nachzukommen.
Aufgrund der begrenzten finanziellen Möglichkeiten der KMA zur Errichtung eines technisch
adäquaten städtischen Drainagesystems zur Bewältigung des Überschwemmungsproblems
wären eine Kombination aus Umgestaltungen der Feuchtgebiete, wie schon oben
beschrieben, sowie sozialpolitische Maßnahmen notwendig. Ein derartiges
Überschwemmungsmanagement sollte in jedem Vorort dazu dienen, Schwerpunkte bei der
Reduzierung von Überschwemmungsflächen und -häufigkeiten zu setzen. In diesem
Zusammenhang müssen KMA und die „National Disaster Management Organisation“
erkennen, dass die Einbindung der lokalen Clanchefs, Abgeordneter und relevanter NGO’s
wichtig sind.
1
1 RESEARCH THEME AND THEORETICAL FRAMEWORK
1.1 INTRODUCTION Ghana became a signatory to the Ramsar Convention in 1988. However, more than two
decades later, wetlands are still considered as ‘waste lands’, ‘flood zones’ or ‘mosquito
breeding grounds’ and as such, dredged to facilitate drainage of the water, reclaimed for other
uses, or simply designated as dumping sites for all types of refuse (Ministry of Lands and
Forestry, 1999a). Even with various efforts to protect or improve the wetlands according to
the dictates of the Convention, recent developments in human geography and socioeconomics
continue to be the major threats to wetlands in Ghana.
Urbanisation is one of the greatest environmental changes the developing world is
uszndergoing. The urban land area is therefore under severe pressure for various uses and
wetlands bear the heaviest of them all (Ramsar Convention Secretariat, 2007). Even with
technological progress in city infrastructure, a growing population puts pressure on
biodiversity (Eppinka et al., 2004). Therefore, to safeguard and possibly enhance the
livelihood of many urban and peri-urban communities who subsist on wetlands, it is
imperative that the benefits of the natural wetland ecosystems, including their values for
subsistence economies, are recognised when planning and implementing development
projects (Silvius et al., 2000). This requires identification and delineation these urban wetland
‘ecosystem’ boundaries for their management and sustainability to reduce their conflicting
and competing uses for housing, infrastructure and agriculture.
The problems that climate change, urbanisation and floods present are becoming impossible
to differentiate. The scale, frequency and cost of urban floods are on the rise and are
sometimes attributed to climate change without the requisite support from research. Global
climate change impacts natural vegetation, affects ecological and physiological processes,
alters growing season length, biomass production, competition and leads to shifts in species
ranges and possible extinctions (Levy et al., 2004; Intergovernmental Panel on Climate
Change [IPCC], 2007). Climate change mitigation has therefore been the motivation for
efforts to further understand carbon budgets and carbon accounting at local scales to
contribute to regional and global carbon budget information (Risbey et al., 2007; Tschakert et
al., 2008). The need for information on carbon pathways in major urban areas in Ghana can
2
therefore not be overemphasised. Terrestrial ecosystems represent a large store of carbon,
approximately, three times that of the atmosphere (Levy et al., 2004). Also, metre for metre,
wetlands lock up more carbon than any other terrestrial ecosystems in active exchange with
the atmosphere. For this reason, as interest in climate change mitigation grows, interest in
wetlands intensifies in parallel (Ramsar Convention Secretariat, 2006; Maltby & Barker,
2009). With such growing interest, wetland ecosystems in Kumasi have the potential to serve
effectively as the basis for mitigating and adapting to climate change.
1.2 RESEARCH BACKGROUND AND JUSTIFICATION
1.2.1 Urban Environmental Issues Urbanisation is a threat to many natural habitats and species because species richness,
evenness, and density on farms, lawns or gardens in urban areas are directly controlled by
man (Niemelä, 1999). These human-dictated urban vegetation communities form the template
for other functional groups of species (Taylor, 1993; Barrat-Segretain & Amoros, 1996).
Urbanisation may also lead to increased patch fragmentation (natural, semi-natural or
artificial) and changes in structure (biomass, density, stratification, etc.) and floristic
composition and spatial diversity (Ehrenfeld, 2000; Altobelli et al., 2007; Grimm et al.,
2008). Like most sub-Saharan countries, urbanisation has been a dominant demographic
trend in Ghana. By the year 2020, urban population in Ghana will more than double that at
2000 whilst rural population would have increased by only 3 % (Ghana Statistical Service,
2002a). Given that urban landuse and footprint will continue to expand, the prognosis for
maintaining diversity and function of biological communities and their associated ecosystem
services within and near Ghanaian cities seems dire. Unlike the natural habitats, the
biodiversity of urban habitats is poorly documented in Ghanaian cities, and thus baseline
information is scarce and the possibilities of applying ecological knowledge in urban
planning are limited (Niemelä, 1999).
Factors such as rates of population growth, urbanisation, inappropriate macroeconomic,
social, and technological policies and choices have been considered as some of the causes
and implications of habitat change in Africa (Kidane-Mariam, 2003; Satterthwaite, 2003). For
example, in Ghana, almost all the non-agricultural economic activities take place in the urban
areas. Therefore, peri-urban and rural landowners are usually excited about the potential
opportunities that will be available to them when the urban economy and space merge with
the peri-urban. This leads to an increase in demand for land for infrastructure, industry,
3
service and housing, thereby, causing a drastic landuse change in these transition zones. The
land values rise dramatically and much income is accrued from the sale of lands as they are
put to more productive and profitable uses. Due to the high economic incentives and
developers’ need for lands at already populated areas, wetlands are also sold, although, at
cheaper prices (Payne, 1997; Brook & Dávila, 2000). Urbanisation and economic expansion
then outpace environmental controls and planning (Grimm et al., 2008). With the high rates
of urbanisation, slow pace of urban spatial planning, inability and inequalities in the
provision of basic sanitation services in Ghana, the cities differentiate into spatial clusters of
different environmental quality. The worst zones are the clusters of informal communities or
slums associated with wetlands (World Bank, 2007). The situation is further compounded by
the deliberate filling and dumping of solid and liquid wastes into these wetlands and along
waterways (Water Resources Commission, 2008). In most towns and cities, skip bins are
peculiarly placed at wetlands leading to the gradual conversion of the area into rubbish
dumps (Fobil & Atuguba, 2004).
The two major Ghanaian cities, Kumasi and Accra have been battling with a growing
frequency and scale of floods. These floods are mostly associated with informal and slum
communities in wetland areas. The nature and growth of these cities however make it
difficult to identify the real cause of the floods. Whilst the multitude of physical factors
described above cannot be overlooked, changing climatic conditions may also be a likely
cause of floods.
Slum population in many Sub-Saharan cities accounts for more than 70 % of the urban
population and are dependent on natural resources associated with the already pressured
wetlands (Rietbergen et al., 2002). Poverty alleviation measures for these slum communities
(e.g. industrialisation, agriculture, flood control and protection works etc.) are also drivers of
ecosystem and environmental degradation (World Meteorological Organisation, 2006;
Satterthwaite, 2003). These communities are also the most vulnerable, both physically and
socially, to environmental hazards like the annual floods and tend to be the least influential
economically and politically. Wetland degradation is therefore likely to continue to increase
in slum areas because of the increasing incidence of urban poverty (Baharoglu & Kessides,
2000; Baker & Schuler, 2004).
4
The above vulnerability situation may be widespread in Ghana because the country has no
urban policy. National responses to urbanisation have so far been very piecemeal and not
sufficiently integrated and holistic. According to the United Nations Human Settlements
Programme (UN-HABITAT), the challenges and priorities facing Ghana among others, are
urban planning and management, urban environment and development and vulnerability
reduction (UN-HABITAT, 2008a). Following these rising urban environmental problems, the
Ministry of Local Government and Rural Development announced that it was in the process
of developing a national urban policy (GNA, 2010b). This is supposed to functionally
integrate social, economic, institutional, cultural, environmental and spatial aspects of urban
development. However, the ecological justification of such a policy, if formulated, is likely to
be weak because of the substantial dearth of information on urban ecosystems in Ghana.
1.2.2 Research Justification Global interest in wetlands, climate change and urbanisation has been on the increase in
recent years. Notable recent efforts are the United Nations Conference on Environment and
Development (UNCED) and its aftermath Conventions on Biodiversity and Climate Change,
the International Peat Society Commission on Land use Planning and Environment, IUCN
Wetlands Programme, Ramsar Convention, UN World Charter for Nature, UNESCO Man
and the Biosphere Reserve Programme, UNESCO Convention for the Protection of World
Cultural and Natural Heritage, World Wide Fund for Nature (WWF), the United Nations
Environment Programme’s Cities as Sustainable Ecosystems initiative and the International
Human Dimensions Programme on Global Environmental Change.
The Ramsar Convention Secretariat (2008) has called on all Parties to review the state of
their urban and peri-urban wetlands and to put in place schemes for restoration and
rehabilitation; formulate landuse planning and management to minimize any future impacts
on urban wetlands; and become involved in the Convention on Biological Diversity’s Global
Partnership on Cities and Biodiversity. Another output of the Conference is the call for
preparation of guidelines for managing urban wetlands, in accordance with an ecosystem
approach, taking into account issues such as climate change, ecosystem services and
livelihoods. The following year, the UN chose ‘Planning our Urban Future’ as its theme for
the 2009 World Habitat Day Celebration. The World Disasters Report 2010 also focused on
urban risk impacts of changing precipitation patterns (International Federation of Red Cross
and Red Crescent Societies [IFRC], 2010).
5
These international concerns are relevant to Ghana. Being a member of the international
community and signatory to several treaties and conventions, the Government of Ghana
recognises the importance of wetlands (Ministry of Lands and Forestry, 1999a). Ghana’s
wetland commitments are incorporated into an extensive poverty reduction strategy (PRS)
process that integrates environmental issues with development and poverty reduction
(Griebenow & Kishore, 2009). Principal commitments in the PRS are the Millennium
Development Goals (MDGs), the Kyoto Protocol, the New Partnership for African
Development (NEPAD) and the Convention on Biological Diversity (National Development
Planning Commission, 2005). The peer to peer review by NEPAD of the PRS process
recommended that Ghana should ensure effective environmental sustainability in programme
and policy designs of ministries, departments and agencies of government and improve their
capacity to practice environmental sustainability (African Peer Review Mechanism
Secretariat, 2005). These recommendations have not been implemented by the Kumasi
Metropolitan Assembly (KMA) and all the other assemblies.
In assessing Ghana’s efforts at attaining environmental sustainability (i.e. MDG 7), it is
critical to note that, some of the most cost-intensive interventions have so far not been
addressed. These include developing systems for environmental monitoring, landuse
management, management of watersheds and freshwater ecosystems and biodiversity
conservation among others (Sachs et al., 2004). Projections by the National Development
Planning Commission (2005) and National Development Planning Commission & UNDP
(2010) show that Ghana may not meet the targets of the MDG 7 and therefore set out three
critical areas to be considered:
� institutional resources for monitoring and evaluation, regulation and enforcement and
environmental management;
� resources (human and financial) development for education and training; and
� specific investment in institutional capacity and policy reforms.
It also proposed the development of a landuse master plan that demarcates all lands in
dispute; initiation of measures to stem land degradation; minimization of the impact of
climate change/variability; and promotion of human centred biodiversity conservation
initiatives.
Environmental research and information to meet these targets have been lacking, not only in
Ghana but in developing countries as a whole (Sánchez-Rodríguez et al., 2005). With the
6
issue of climate change rapidly gaining the right political attention and momentum, scientists
need to take advantage of this trend of events to identify possible local climate impacts. It is
now known that climate change will very much affect sub-Saharan Africa (Niasse et al.,
2004; Millennium Ecosystem Assessment, 2005; Intergovernmental Panel on Climate
Change [IPCC], 2007; Satterthwaite, 2008), especially, its water resources (Reinelt et al.,
1998; Choi et al., 2003; United Nations Department of Economic and Social Affairs, 2005;
Jenerettea et al., 2006; Obuobie et al., 2006) and may cause flooding in many areas (Fedeski
& Gwilliam, 2007; IPCC, 2007; International Recovery Platform, 2009; McClean, 2010).
This information on sub-Saharan African countries is generated from running climate models.
However, no studies have been conducted on specific local climate change effects and
adaptations by the vulnerable urban wetland communities in Kumasi, Ghana.
Relevant research conducted in Kumasi and its environs have been on pollution and peri-
urban agriculture (Brook & Davila, 2000; Keraita et al., 2002; Cornish & Kielen, 2003;
Keraita et al., 2003; Cofie et al., 2005), livelihood changes in peri-urban environments
(Holland et al., 1996; Danso et al., 2002; Quansah et al., 2005; Danso et al., 2006; Drechsel,
2006; McGregor et al., 2006), urban planning (Mabogunje, 1990), land and land tenure
(Blake & Kasanga, 1997; Botchie et al., 2007). There is certainly a shortfall in depth and
direction of research that would provide a basis for climate mitigation in the urban
environment in Kumasi, Ghana. Also, the GPRS II does not provide room for GIS-based
ecological and poverty maps and climate change scenarios to offer practical information and
innovation required to better inform development policy. There is no information to use to
develop instruments for the vulnerable to cope with the impacts of climate change by
themselves. There is no information on the effects of climate change on urban wetland
vegetation dynamics, wetland hydrology and carbon sequestration in the light of the
increasing pollution, urbanisation, agriculture and for carbon budgeting. In order to
understand the link between urbanisation and the incidence of flooding, there is the need to
know the spatial extent and characteristics of wetlands, land cover changes and fragmentation
as an information input for better spatial planning in Kumasi. This research is therefore an
attempt to provide the needed information for a holistic solution to the interlocked issues of
climate change, urbanisation, wetlands degradation and flooding in Kumasi.
7
1.3 RESEARCH GOAL This research therefore sought to contribute to knowledge on the state of wetlands (ecology,
carbon stocks, and drivers of change), incidence of flooding and stakeholder needs for
management of wetlands in Kumasi. It will also be an initial attempt to develop the
information base for indicators of wetland biotic integrity in the Kumasi Metropolitan area as
influenced by urbanisation.
1.4 RESEARCH OBJECTIVES � To describe and characterise urban wetlands in Kumasi
� To identify the determinants of floods and coping strategies to flooding in Kumasi
� To test the applicability of the Environmental Kuznets Curve in the decision making
of members of flood prone communities in Kumasi
1.5 RESEARCH QUESTIONS In order to achieve these objectives, this research answered the following questions:
1. What are the characteristics of wetlands in Kumasi and in which ways are they
changing spatially and temporally?
a. What are the physical and chemical characteristics of wetlands in Kumasi how are
they related to the adjacent socio-economic activities?
b. What are the ecological drivers of change in these urban wetland ecosystems?
c. What are the wetland vegetation species and the spatial and temporal differences
in distribution of these species in Kumasi?
d. What is the carbon sequestration potential of these urban wetland ecosystems?
2. What are the effects of climate and landcover-landuse change on the incidence
of floods in Kumasi?
a. Is there any relationship between the incidence of floods and the climatic
(precipitation) characteristics of Kumasi?
b. What are the landuse-landcover changes in Kumasi and how do they affect the
incidence of floods in Kumasi?
3. How does the economy of wetland communities influence their environmental
concerns?
a. What are the socio-economic activities associated with wetland communities in
Kumasi?
8
b. Does the trend of wetland degradation in Kumasi follow the Environmental
Kuznets Curve?
i. How far to left of the continuum of the Environmental Kuznets Curve are
members of these wetland communities in Kumasi?
ii. What do these communities need to reach the peak or flatten the Curve?
4. How are wetland associated communities and authorities managing the
associated wetlands and floods?
a. What are the existing wetland management practices and adaptations to life by
wetland associated communities to life in such environments?
b. What are the opportunities for implementing the Ghana Wetlands Management
Strategy in Kumasi?
1.6 CONCEPTUAL AND THEORETICAL FRAMEWORKS This research is based on the following conceptual framework represented in Figure 1.1. The
total amount of wetlands in Kumasi is considered as a non-renewable stock. This wetland
stock is being reduced through the influence of urbanisation from the conversion of wetland
areas into built environment. Also, these wetland areas, by virtue of their nature, do not
attract high prices and in most places are not even sold. They are therefore invaded by poor
people and converted into informal or slum settlements and the remaining wetland areas are
associated with intense economic activities of these wetland inhabitants. The dense built up
environment and clearing of vegetation in the wetlands therefore lead to increased frequency
and scale of flooding of these suburbs. Storm drains are then built as a flood mitigation
strategy but these have not been successful in solving the problem of floods.
This research assumes that, there are two pathways available to the KMA for the
management of the wetlands and flooding: (i) continue with the business-as-usual
engineering solution or (ii) put in place some wetland management interventions based on
activities and programmes that will be investigated in this study (research themes [RT]).
The latter will lead to an improved stock and state of wetlands in Kumasi offering positive
environmental services including the reduction in floods and or its effects.
The business-as-usual and engineering solution will result in a vicious cycle of
environmental ills. This is because, with increasing urbanisation, the city will frequently have
to expand the storm drains to cope with the increasing runoff. Meanwhile, degradation and
9
loss of the wetland areas continue. The consequence of this is an increase in the frequency
and intensity of floods and loss of environmental quality.
The above conceptual framework is based on the assumption that, urban processes and
natural wetland ecosystems can co-exist. This is because, the perception of wetlands as a
limit to urban expansion and economic growth could be changed to a rather active role in
reducing urban poverty, achieving higher living standards and increasing human development
levels in a sustainable manner (Costantini & Monni, 2008). However, to achieve this, the
very complex links between urbanisation, wetlands, floods and human activities have to be
understood. The theoretical basis of this research, therefore, piggybacks an adapted model of
McDonnell & Pickett (1990) and Ehrenfeld (2000) on urbanisation and ecological
phenomena (Figure 1.2). This research envisages that, there are interactions between the
features of urban areas (column A) and ecological phenomena (column B). Manifestations of
these interactions in Kumasi are shown in column C. Ehrenfeld (2000) proposed some
components and indicator variables for assessment of such urban wetlands (column D).
In this model, the urban environment is divided into four entities: 1. human physical
constructs, 2. the natural areas, 3. humans with their accompanying socio-economic activities
and 4. climate. The human dwellings, roads, factories, offices etc. make up the physical
abiotic developments; the urban greens, parks, wetlands etc. form the natural areas; the
human influence is characterised by various socio-economic activities such as trading,
carpentry, agriculture etc.; and all these interact and are influenced by the local climate.
These form the drivers of change (A) of the environment. Urbanisation provides an
opportunity for all these factors to closely interact (B) to produce the current wetlands of
Kumasi, C (results). These wetlands have reduced ecological value because of encroachment
and activities of the informal and slum communities. The research themes (D) are derived
from phenomena taking place in rows 1, 2, 3 and 4. That is, this research seeks to investigate
how the changes in the phenomena represented by the rows 1, 2, 3 and 4 of column D lead to
the manifestations in column C in Kumasi.
10
RT
Fi
gure
1.1
. C
once
ptua
l fr
amew
ork
for
the
inve
stig
atio
n of
urb
anis
atio
n, s
ocio
-eco
nom
ic a
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ities
and
inci
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e of
flo
ods
in K
umas
i(R
T= r
esea
rch
them
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r ar
eas
bein
g in
vest
igat
ed)
outc
ome
decis
ion
curr
ent
stat
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tcom
e
11
Figu
re 1
.2.
A c
ompo
site
mod
el o
f th
e ef
fect
s of
hum
an i
nter
fere
nce
on a
wet
land
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syst
em i
n an
urb
an s
ettin
g (a
dapt
ed f
rom
McD
onne
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Pic
kett,
199
0; E
hren
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, 20
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A
D
C
B
3 So
cio-e
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mic
fact
ors
Resu
lt
1 2 4
Popu
latio
n an
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mm
unity
effe
cts
Man
agem
ent
and
capi
tal
appo
rtion
men
t
Stru
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al fe
atur
es
of
urba
n ar
eas
Wet
land
area
s
Dive
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f Cha
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Phys
ical
and
chem
ical
envir
onm
ent
Biot
ic an
d en
viron
men
tal
effe
cts
of u
rban
isatio
n
Clim
atic
effe
cts
Rese
arch
Cur
rent
sta
te o
f ur
ban
wet
land
Ecos
yste
ms
Ecol
ogy
(soi
l, ve
geta
tion,
hy
drol
ogy,
phy
sicoc
hem
ical
ch
arac
teris
tics)
Urb
anisa
tion
(spa
tial
and
tem
pora
l ch
ange
s in
phys
ical
struc
ture
s, po
llutio
n)
Socio
-eco
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ic co
nditio
ns
(floo
ds,
wet
land
man
agem
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anth
ropo
geni
c ac
tiviti
es)
? ?
Red
uced
va
lue
and
func
tion
of
wet
land
s
Floo
ds,
Slum
s
?
12
1.7 HYPOTHESES The following hypotheses have been formulated to guide this study.
I. According to the Federal Interagency Committee for Wetlands Delineation (1989), Keddy
(2000) and Maltby & Barker (2009), wetland vegetation composition is dependent on the
hydrological characteristics of the site. That is, water level fluctuations and depth of
inundation during the year are important in the development of plant associations (Reinelt et
al., 1998; Sassa et al., 2010). In an urban setting, however, the vegetation is often
manipulated for aesthetics and design, biological conservation, and for reduction in some
forms of pollutants (Botkin & Beverage, 1997; Owen, 1999). The urban vegetation is
therefore often a mix of biological deserts and areas that are rich in biodiversity. Therefore,
the structure, floristic composition and spatial distribution of urban wetland vegetation may
rather be the result of deliberate human interventions to satisfy human interests or adjacent
anthropogenic economic activities (Altobelli et al., 2007). It can therefore be argued that, in
urban wetland environments, the anthropogenic influences or interests rather than the
hydrology determine the vegetation.
Ho: Wetland vegetation composition in the Kumasi Metropolis is not determined by the
hydrological characteristics of the wetland.
II. Nature is the original source of all heavy metals. The presence or absence of a heavy metal
in any environment therefore depends on the site characteristics. Recent developments in less
developed countries have led to a wave of rapid urbanisation (UNFPA, 2007). Even though
these urban areas currently cover less than 3 % of the total land area of the earth, they are
places of intense economic activities (Millennium Ecosystem Assessment, 2000). The direct
effect of urbanisation and the associated intense activities is pollution of ecosystems
(Sánchez-Rodríguez et al., 2005). For this reason, while heavy metals may be ubiquitous in
urban environments due to natural processes, the increased human activities due to
urbanisation and population growth could make a significant contribution beyond their natural
concentrations (Sekabira et al., 2010). Spatial variations in heavy metals in urban
environments could therefore be a reflection of the local anthropogenic activities.
Ho: Concentration of heavy metals in the wetland sediments of Kumasi is not greater than the
natural sediment concentration.
13
III. Flooding has claimed more lives than any other single natural catastrophe (IPCC, 2007).
In the decade 1986-1995, flooding accounted for 31 % of the global economic losses from
natural catastrophes and 55 % of the casualties (Petrov et al., 2005). Also, recent analyses by
the IPCC (2007) show that sub-Saharan Africa will experience the worst effects of climate
change. On the other hand, when urbanisation occurs, some or all of the functions and values
of wetlands are affected by direct activities such as dredging, filling, draining or outlet
modification, while others are affected by secondary activities, such as increased impervious
surfaces, leading to increased quantity of inflow water (Mumphrey & Whalen, 1977; Reinelt
& Horner, 1991; Brody et al., 2007). Roy (2009) therefore concludes that the causality and
vulnerability of urban areas to floods are clearly linked to the very nature of the urbanisation
process. The floods at the various suburbs may therefore be outcomes of the urbanisation
process rather than climate change. From the above arguments, it is therefore hypothesized
that:
Ho: The flooding in the suburbs of Kumasi is not due to climate change.
IV. Studies show that an inverted U-shaped relationship exists between environmental
degradation and per capita income (Magnani, 2001; Dinda, 2004; Costantini & Monni, 2008;
Wagner, 2008). Panayotou (1993) therefore adduces from this relationship that, economic
growth could be a powerful way for improving environmental quality in developing countries.
That is, efforts at improving the economy of developing countries will lead to improved
environmental quality. However, will there be an automatic improvement in environmental
quality as income levels increase or it requires conscious institutional and policy reforms? If
such a relationship exists, does the current environmental quality in the flood prone suburbs of
Kumasi correspond to the economic status of its residents? Are the wetland slum communities
an indicator of a stage of economic development of Kumasi? If such an inverted U-shaped
relationship is true, why are rich countries or economies still degrading their wetlands? It is
therefore hypothesized that:
Ho: The relationship between income and wetland degradation in the various suburbs of
Kumasi will not follow an inverted-U-shaped relationship.
14
2 WETLANDS, URBANISATION AND FLOOD NEXUS
2.1 INTRODUCTION Extensive literature on wetlands, urban wetlands, tropical wetlands, urbanisation, urbanisation
in developing countries, urban ecology, urban poverty, flooding, climate change and carbon
budgets was thoroughly reviewed. From this review, research gaps pertaining to wetlands,
urbanisation and floods in Kumasi were identified. Also, the appropriate research methods
were developed to ensure that methods are standard scientific procedure and comparable to
similar research conducted elsewhere. Literature used in this review were generally peer
reviewed documents from the following databases and resources: CAB Direct, African
Journals Online (AJOL), ELDIS, ScienceDirect, Elsevier, Kwame Nkrumah University of
Science and Technology (KNUST) and University of Bremen library resources and
Government of Ghana reports and policy documents. The search was conducted using
wetlands, urban, flooding, urban planning, urban poverty, ecosystem change, climate change,
urban ecology, Kumasi, Ghana etc. as search words.
The search results showed that on the global level, significant research has been published in
these thematic areas. Much of these publications are, however, focused on developed
countries. There is relatively very little research conducted in these thematic areas involving
Kumasi, Ghana or sub-Saharan Africa. This review is, therefore, very much based on the
specific literature obtained and others which may not be that specific to the study area or
region, but relevant to the assessment of the research and knowledge gaps on wetlands,
urbanisation, poverty, climate change and flooding in Kumasi, Ghana.
2.2 WETLANDS Man has had a very long association with wetlands at different places. The concept of
wetlands therefore has different meanings or sentiments because of the distinctive
relationships with different interest groups in different parts of the world (Maltby & Barker,
2009). The different meanings may be related to the culture or history of a people or
socioeconomic uses to which it has been put etc. Man, in changing from the wanderer to a
settler, has been associated with water bodies. This man-water interaction has been beneficial
and hazardous to both ends of the continuum and the meanings of wetlands sometimes reflect
these experiences. However, the term wetland is a recent vocabulary compared to man’s
association with it (Keddy, 2000). Wetlands are usually associated with floods, swamps,
wastelands, mosquito-infested mud holes etc. It is therefore worthy to note that some of the
15
earlier delineations of wetlands in the USA were for their possible conversion to damp sites
(Federal Register, 1980).
According to Haslam (2003), ‘wetland’ is originally a North American term and is generally
referred to, interchangeably, as bogs, fens, marsh, swamps, sloughs, morasses, moor, mires,
flood meadows etc. in non-ecological literature on the other side of the Atlantic. Wetlands
have a combination of aquatic and terrestrial conditions that produce complex ecosystems that
do not fit completely into aquatic or terrestrial ecology (Figure 2.1). As transitional zones or
ecotones, they have characteristics and species typical of the communities they divide (Mitsch
& Gosselink, 1993). Therefore, the characteristics of wetlands are determined largely by
hydrologic processes which may exhibit daily, seasonal or longer-term fluctuations, in
relation to regional climate and geographic location of the site (Halls, 1997).
Figure 2.1. An illustration of the continuum between the terrestrial, wetland and aquatic systems (source: Mitsch & Gosselink, 1993)
From the illustration in Figure 2.1, wetlands are ecological areas which may be marshes,
peatlands, floodplains, rivers and lakes, and coastal areas such as salt marshes, mangroves,
and seagrass beds, but also coral reefs as well as human-made wetlands such as waste-water
treatment ponds and reservoirs. Because of this broad spectrum of ecosystems and the long
16
historical list of interchangeable words used to describe wetlands in different locations by
different cultures, the definition of wetlands has been of much controversy. For example, in
the 2005 Millennium Ecosystem Assessment report, ‘wetlands’ and ‘inland waters’ are used
interchangeably. Also, “wetlands and mangroves” and “lakes, rivers, wetlands, and shallow
groundwater aquifers” are mentioned as habitat types (Millennium Ecosystem Assessment,
2005). It is not surprising that such a renowned publication by a team of experts will have
problems defining wetlands. Most authors therefore prefer to mention the various wetland
ecosystem types rather than attempt a definition.
One of the earliest formal definitions is that of Ramsar as “areas of marsh, fen, peatland or
water, whether natural or artificial, permanent or temporary, with water that is static or
flowing, fresh, brackish or salt, including areas of marine water the depth of which at low tide
does not exceed six metres” (Ramsar Convention Secretariat, 2006). This definition embraces
almost all land area. Large tracts of land are sometimes temporary flooded due to
anthropogenic activities or changes to the landscape. Also, changes in rainfall patterns
sometimes create large flood zones that may only be temporal. In places where demand for
land is very high, e.g. urban areas, such a broad definition will only exacerbate landuse
conflicts. A less “land grabbing” definition is that by US Army Corps of Engineers and the
US Environmental Protection Agency which considered wetlands as “areas that are inundated
or saturated by surface or ground water at a frequency and duration sufficient to support, and
that under normal circumstances do support, a prevalence of vegetation typically adapted for
life in saturated soil conditions” (Federal Interagency Committee for Wetlands Delineation,
1989). This definition does not include artificial wetlands because under normal
circumstances, they may hitherto have been a different land type and therefore, not supported
wetland vegetation. It is also worthy to note that this definition was formulated as a guideline
for selecting places to be designated as landfill sites in the USA and therefore did not include
coastal zones as wetlands.
Keddy (2000) emphasizes on inundation and defines wetlands as product of a cause-effect
relationship. According to Keddy, ‘a wetland is an ecosystem that arises when inundation by
water produces soils dominated by anaerobic processes and forces the biota, particularly
rooted plants to exhibit adaptations to tolerate flooding’. The use of ‘forces’ in the definition
undermines the fact that wetlands are a natural part of the environment with plants and
animals adapted to such an environment. Therefore, there is no forcing of biota to adapt. The
description of wetlands forcing biota makes wetlands look like a recent artificial creation such
17
that the biota that are ‘caught up’ in such a new environment are forced to adapt. With these
diverse definitions and shortfalls, some wetland interest groups (International Mire
Conservation Group and International Peat Society with support from the Dutch Ministry of
Foreign Affairs, IUCN, Alterra, Wetlands International and Environment Canada)
commissioned a study that revised the definition as follows: “a wetland is an area (of marsh,
fen, peatland or water, whether natural or artificial, permanent or temporal) that is inundated
(up to a depth of 6 m at low tide) or saturated by water (surface/ground, static/flowing,
fresh/brackish) at a frequency and for a duration sufficient to support a prevalence of
vegetation typically adapted for life in saturated soil conditions” (Joosten & Clarke, 2002).
This all-encompassing definition could be considered the most sufficient for delineation,
conservation and management of wetlands. According to Maltby & Barker (2009), the
definitions of wetlands communicate the importance of substrate, vegetation and water in the
identification, development and persistence of wetlands. It is therefore often argued that a
robust definition that can provide effective guidance towards wetlands identification and
delineation must include these three elements. For the purpose of this study therefore, the
definition of Joosten & Clarke (2002) will be adopted. The Government of Ghana however,
uses the Ramsar definition.
2.2.1 Morphology and Hydrodynamics of Wetlands Wetland morphology is as diverse as the landscape in which it is situated. The source and
state of the water, topography and geology all determine the morphology of the wetland. The
prevailing climatic conditions, wetland morphology and hydrology determine the wetland
ecosystem attributes: species composition of the plant community, primary productivity,
organic deposition and flux and nutrient cycling (Halls, 1997; Ot’ahel’ová et al., 2007). In an
urban setting, wetlands are further impacted by anthropogenic activities leading to
modifications in the vegetation, hydrological and morphological conditions as shown in Table
2.1. Upstream activities affect the watershed hydrology through changes in the average runoff
supply and changes in the frequency and severity of extreme events, including flooding and
drought. However, these have been difficult to assess due to complexities in the processes at
work as well as a non-uniform and, in many parts of the world, deteriorating monitoring
network (Millennium Ecosystem Assessment, 2005). In Ghana, gauges are rare on rivers and
data on runoff is therefore difficult to come by.
18
Table 2.1. Likely effects of urbanisation on wetland hydrology and geomorphology (Ehrenfeld, 2000)
Hydrology:
� Decreased surface storage of stormwater results in increased surface runoff (Decreased surface water input to wetland)
� Increased stormwater discharge relative to baseflow discharge results in increased erosive force within stream channels, which results in increased sediment inputs to recipient coastal systems
� Changes occur in water quality (increased turbidity, increased nutrients, metals, organic pollutants, decreased O2, etc.)
� Culverts, outfalls, etc., replace low-order streams; this results in more variable baseflow and low-flow conditions
� Decreased groundwater recharge results in decreased groundwater flow, which reduces baseflow and may eliminate dry-season streamflow
� Increased flood frequency and magnitude result in more scour of wetland surface, physical disturbance of vegetation
� Increase in range of flow rates (low flows are diminished; high flows are augmented) may deprive wetlands of water during dry weather
� Greater regulation of flows decreases magnitude of spring flush
Geomorphology:
� Decreased sinuosity of wetland/upland edge reduces amount of ecotone habitat
� Decreased sinuosity of stream and river channels results in increased velocity of stream water discharge to receiving wetlands
� Alterations in shape of slopes (e.g., convexity) affects water gathering or water-disseminating properties
� Increased cross-sectional area of stream channels (due to erosional effects of increased flood peak flow) increases erosion along banks
2.2.2 Distribution, Values and Degradation of Wetlands The variations in the definitions of wetlands make it a near impossibility to know the total
area and distribution of the world’s wetlands (Barbier, 1994; Finlayson et al., 2000). It is,
however, generally estimated to be about 6 % of the earth surface (Haslam, 2003; Ramsar
Convention Secretariat, 2006; World Meteorological Organisation, 2006; Maltby & Barker
19
2009). Wetlands are very fragmented and represented in all parts of the world (Figure 2.2.)
varying in flora and fauna with diverse ecological functions and anthropogenic uses.
Whilst the definition of wetlands is in controversy, its values and functions are undisputed.
When properly measured, the total economic value of a wetland's ecological functions,
services and resources may exceed the economic gains of converting the area to alternative
uses (Phillips, 1998; Turner et al., 2000). Challenges, however, arise in applying economic
tools such as cost benefit analysis to assess wetlands because of the non-availability of data,
especially, in developing countries (Phillips, 1998). In particular, economic analysis of the
environmental functions of tropical wetlands is underdeveloped. However, the
physical/hydrological and environmental services provided by wetlands around the world
have been well documented and can easily be assessed using various scientific methods. The
hydrological services of wetlands include its prevention of storm damage, flood and water
control (Barbier, 1994; Shutes et al., 1999; Haslam, 2003; World Meteorological
Organisation, 2006), coastal protection and aquifer recharge (Zedler & Leach, 1998), waste
management and improvement of water quality (Biney, 1990; Barbier, 1994; Green & Upton,
1994; Zedler & Leach, 1998; Shutes, 2001; Haslam, 2003; Ramsar Convention Secretariat,
2006; Cooper, 2009) and climate change mitigation (Joosten & Clarke, 2002; IPCC, 2007;
Ramsar Convention Secretariat, 2007). Also, lower soil horizons of wetlands support sulphate
reduction to sulphides and provide the environment for metal-sulphide precipitation by
trapping heavy metals in sediments (Maltby & Barker, 2009).
Wetlands are habitats of enormous biological productivity and high conservation value,
especially, for migratory birds. They typically have high species diversity and are habitats for
various stages in the life cycle of species (Barbier, 1994; Zedler & Leach, 1998; Haslam,
2003; Botkin & Beverage, 1997). Apart from benefit to animals, the socioeconomic
development of many cities can be traced to their association with wetlands through the
provision of potable water (Biney 1990; Barbier, 1994; Millennium Ecosystem Assessment,
2005; Ramsar Convention Secretariat, 2006), expression of cultural values, capture fisheries,
aquaculture and extraction of agricultural and horticultural products (Biney, 1990; Mitsch &
Gosselink, 1993; Barbier, 1994; Millennium Ecosystem Assessment, 2005). The use of
wetlands for recreation and tourism is being heavily exploited in England, the Northern
Territory of Australia, and Kashmir, northern Germany (Zedler & Leach, 1998; Millennium
Ecosystem Assessment, 2005).
20
Fi
gure
2.2
. Dis
trib
utio
n of
wet
land
s in
the
world
(M
illen
nium
Eco
syst
em A
sses
smen
t, 20
05)
21
There are increasing anthropogenic demands for water and other natural resources and
services provided by wetlands and these impact adversely on wetlands (Ramsar Convention
Secretariat, 2007). The capacity of wetlands to continue to provide these resources and
services is therefore declining. A major cause of this decline is the increasing abstraction of
water, especially, for agriculture (Barbier, 1994; Joosten & Clarke, 2002; Millennium
Ecosystem Assessment, 2005; Ramsar Convention Secretariat, 2007), port expansion,
industrialisation and urbanisation (World Meteorological Organisation, 2006). Many surface
and groundwater-dependent wetland systems and their catchments are already water-stressed,
and demand for water is projected to continue to increase (Millennium Ecosystem
Assessment, 2005). For example, access to freshwater is declining for 1-2 billion people
worldwide and this, in turn, negatively affects food production, human health, and economic
development, and has a potential to increase societal conflict (Ramsar Convention Secretariat,
2008).
Following the varied uses of wetlands described above and its consequent degradation, the
allocation of wetland resources requires careful analysis of their values, in particular, their
indirect use values of environmental regulatory functions. The failure to take these values into
account is often a major factor behind decisions that lead to overexploitation or excessive
degradation of wetland systems (Barbier, 1994). The Government of Ghana in celebrating the
World Wetlands Day, 2010, reiterated its commitment to review policies or amend the
relevant legislations that impede the protection of the country's wetlands to ensure long-term
ecological viability (GNA, 2010a). It is unfortunate however, that, this review, if it ever
happens, will not have a strong backing of empirical data, information and literature from the
Ghanaian context.
2.3 URBANISATION
2.3.1 Concept and History of Urbanisation The term urban areas are settlements or localities defined as "urban" by national statistical
agencies. The cut-off points for identifying urban areas or populations therefore vary from
country to country (Millennium Ecosystem Assessment, 2005). The most common ways of
classifying urban settlements are by population, economic conditions, and location. The
minimum population density criterion commonly ranges between 400 and 1,000 persons/km2
(Qadeer, 2004; Pacione, 2009). When population size is used, other economic or social
indices are described. The minimum population size ranges between 1,000 and 5,000
residents; and maximum agricultural employment is usually in the vicinity of 50–75 %
22
(UNFPA, 2007). In each case, however, cut-off points outside these ranges can easily be
found. For example, in Sweden, the urban population threshold is 200 inhabitants; 10,000 in
Benin, Switzerland and Burkina Faso; 20,000 in Nigeria and 30,000 in Japan (Pacione, 2009).
A settlement with a minimum of 5,000 persons is used to describe urban settings in Ghana
(Ghana Statistical Service, 2002a). Although country-specific definitions will remain central
to defining and assessing urban centres for many years to come, the basis for a more uniform
definition is emerging from work using remote sensing and geographical information systems
(Fedeski & Gwilliam, 2007). According to Pacione (2009), whatever the reasons are for
urbanisation, it is likely to be a thing of the past in the near future. This is because, with
globalisation and advances in telecommunication technologies, time becomes instantaneous
and the urban frame will be useless and spatial congregation becomes unnecessary. Man will
return to more ‘rural’ and isolated settlement types but still perform all urban functions.
Following these arguments, the definition of an urban setting is expected to become more
controversial in the future.
Also following recent spatial development trends, urban and suburban landuse form a
continuum as much urban land area is occupied by dense-to-moderate residential housing.
Thus, there are no clear physical boundaries between urban, suburban lands and rural lands, or
between the urban cores of the larger cities and suburbia (Ehrenfeld, 2000). However, to
differentiate economically, urban residents are less likely to work in agriculture and more
likely to work in industry or services. For example, in India, more than 75 % of adult male
population in a town has to be engaged in non-agricultural work to be considered urban
(Pacione, 2009).
As seen above, there is no international agreement on the defining characteristics of urban,
nor are there any scientifically accepted criteria by which to identify urban areas and
populations. Moreover, some urban researchers believe that the distinction between rural and
urban is becoming less relevant (Cohen, 2004) and that the boundary definitions are
inevitably somewhat arbitrary. Even though there are differences in what is urban, the concept
is well studied among sociologists and geographers. Statistically, urbanisation reflects an
increasing proportion of the population living in settlements defined as urban, primarily
through net rural to urban migration. The level of urbanisation is the percentage of the total
population living in towns and cities while the rate of urbanisation is the rate at which it
grows (Millennium Ecosystem Assessment, 2005; UNFPA, 2007).
23
2.3.2 Modern Trends in Urbanisation In the olden days, man was an agricultural being and most of the daily activities involved
procurement of food. With time, technological advances changed the face of agriculture
(Kaplan et al., 2009; Pacione, 2009). Higher productivity in agriculture resulted in food
surplus sufficient to feed non-farmers. This led to division of labour such that, other than
farming, people could become full time craftsmen, traders, soldiers, religious leaders,
politicians etc. Increased geographical mobility and diffusions of goods, technologies and
ideas resulted in concentration of populations. Rather than the earlier focus on agriculture,
trade hubs, political centres and massive public projects to improve human wellbeing started
to become important (Jacobs et al., 1997; Bhattacharya, 2002; Millennium Ecosystem
Assessment, 2005; Smith, 2005; Kaplan et al., 2009). The larger human settlements grew as
cultural centres of literacy, arts, religion and science. This then led to establishment of
political hubs of imperial power and later, economic domination of cities over rural areas
(Harvey, 1985a, b). Then came the period between 1750 and 1950 when most regions in
North America and Europe experienced industrialisation resulting in a wave of urbanisation to
produce the urban industrial societies. Since then, urbanisation and urban growth have
continued to be major demographic trends in all parts of the world (Millennium Ecosystem
Assessment, 2005). The increased urbanisation resulted in increase from only two cities
containing 10 million people in 1950 to seven by 1975 (World Bank, 1991).
Recent developments in less developed countries have led to a second wave of rapid
urbanisation where the number of urbanites will grow from 309 million in 1950 to 3.9 billion
in 2030 (UNFPA, 2007) with Africa being the most urbanising (Bhattacharya, 2002; Kaplan
et al., 2009). According to the Millennium Ecosystem Assessment (2005), decolonisation and
the development of independent nation states had heavy influences on urbanisation in Africa
and much of Asia as controls on the rights of the inhabitants to live in or move to urban
centres were dismantled, and in part because the building of the institutions for independent
governments increased urban employment. The UNFPA (2007) projects the urban population
of Africa and Asia to double between 2000 and 2030 and Grimm et al. (2008) estimates that
more than 95 % of the net increase in the global population will be in cities of the developing
world. Meanwhile, the urban population of the developed world is expected to grow relatively
little: from 870 million to 1.01 billion within the same time frame. At the global level
therefore, all future population growth will thus be in towns and cities. Already, in 2008 the
proportion of the world’s human population residing in urban areas reached 50 % as a result
of rapid urban growth in developing countries (United Nations, 2008; UN-HABITAT,
24
2008b). Urban places will therefore be of fundamental importance for the distribution of
population; in the organisation of economic production, distribution and exchange; in the
structuring of social reproduction and cultural life; and in the allocation and exercise of power
(Pacione, 2009).
It is also argued that the main driver of current urbanisation is economic growth. In general,
the most urbanised nations are those with the highest per capita incomes, and the nations with
the largest increases in urbanisation are those with the largest economic growth (World Bank,
1991; Millennium Ecosystem Assessment, 2005). The current rates of urbanisation in
developing countries could therefore have global economic implications. It can shape
prospects for global economic growth, poverty alleviation, population stabilisation and
environmental sustainability. Cities are already the locus of nearly all major economic, social,
demographic and environmental transformations. They cover only about 2 % of the earth’s
surface, yet consume 75 % of all resources and produce 75 % of all waste (UNFPA, 2007).
Therefore, improving urban planning to make cities more sustainable and increase the quality
of urban life will require integrated urban planning and management and cooperation among
responsible stakeholders (Berkowitz et al., 2003; United Nations Department of Economic
and Social Affairs, 2005). Such stakeholders, however, have different and often conflicting
priorities or insufficient resources to carry out their mandate. This is particularly so in
developing countries which do not have the financial and economic resources to meet the ever
increasing challenges of their uncontrollable urban expansion.
The growth of cities throughout the world presents new challenges to meet societal needs,
which are vulnerable to both climate and population changes. For example, urban water
withdrawal often extends far beyond city boundaries, as municipalities seek to secure new
water sources from the hinterlands (Jenerettea et al., 2006). Cities consume less than 10 % of
the total water used globally (Millennium Ecosystem Assessment, 2005). However, it is the
concentrated nature of that demand which poses a heavy burden on the limited local water
supplies. This is both in terms of volume of demand and pollution from wastewater discharge.
The high costs of collecting, treating and distributing clean drinking water, as well as the costs
of wastewater collection and treatment, are a major burden on public budgets and are beyond
the capacity of municipal or national governments in most developing countries like Ghana
(Millennium Ecosystem Assessment, 2005; Grimm et al., 2008). Any effort at improving
wetlands will therefore be a step in the right direction to reduce the immediate and future
water burden of these growing cities.
25
2.3.3 Urbanisation Trends in sub-Saharan Africa Urban population growth in sub-Saharan Africa is close to 5 % per annum and is the highest
growth rate in the world (Kaplan et al., 2009). Contrary to current urbanisation trends of
developed countries, the urbanisation of Sub-Saharan African countries can best be described
as low density urban sprawl. Urban sprawl, loosely defined as dispersed and inefficient urban
growth (Hasse & Lathrop, 2003; Mundia & Aniya, 2006) has undesirable effects. According
to Brueckner & Fansler (1983) and The World Bank (2000), the phenomenon of urban sprawl
is a symptom of an economic system gone awry. This dramatic expansion of settlements at
the expense of open spaces and natural resources has sparked intense interest and debate on
urban sprawl (Mumphrey & Whalen, 1977; Brueckner & Fansler, 1983; Mitsch & Gosselink,
2000; Hasse & Lathrop, 2003).
Cities in Africa are not serving as engines of growth and structural transformation. Instead,
they are part of the cause and a major symptom of the economic and social crises that have
evolved the continent (The World Bank, 2000). The predominance of agricultural and mineral
trade and the lack of manufacturing have made them more dependent on rural than on urban
economic activities and more susceptible to changes in commodity market prices (Kidane-
Mariam, 2003; Millennium Ecosystem Assessment, 2005). Furthermore, the gains in human
well-being are not distributed evenly among individuals or social groups or among countries
or the ecosystems of the world. Sub-Saharan African urbanisation is one mostly engineered
by deprivation of rural areas (The World Bank, 2000; 2007). In fact, a vast majority of rural-
urban migrants do so to escape the extreme deprivation of amenities. Also, according to
Kaplan et al. (2009), the combination of agrarian economy and high family sizes cause rural
landlessness and poverty making people seek opportunities in the city. There is therefore a net
increase in city dwellings; a lot of which are uncompleted and without access roads,
electricity, water and telephone facilities (The World Bank, 1991; Berkowitz et al., 2003;
Millennium Ecosystem Assessment, 2005; The World Bank, 2007). In these urban centres,
the gap between the advantaged and the disadvantaged is increasing (Baharoglu & Kessides,
2000; White et al., 2001; National Development Planning Commission, 2005; Ravallion et
al., 2007a, b).
According to the records, 7.8 % of the population of Ghana lived in urban centres in 1921. By
1960, urban population had risen to 23.1 % and further to 32 % in 1984 and 43.8 % in 2000
(Ghana Statistical Service, 2002a) and estimated to exceed 50 % in 2008 (UN-HABITAT,
2008). The rapid urbanisation puts enormous pressure on the utilisation of natural resources
26
and the provision of infrastructure and amenities like water supply, sanitation, waste
management, transportation, and housing. The adverse impact of rapid urbanisation has also
exacerbated the incidence of unplanned changes in landuse in the larger cities, especially
Accra and Kumasi (Brook & Dávila, 2000; The World Bank, 2007). Poor residents of these
cities tend to concentrate in the outskirts, in non-functional government structures and land
and along urban wetlands as informal settlements and slums.
2.4 URBANISATION AND THE ENVIRONMENT A significant literature exist on ecosystems within urban areas (The World Bank, 1991;
Zedler & Leach, 1998; Shutes et al., 1999; Rees, 2003; Janssen et al., 2005; Ravallion et al.,
2007a, b); ecology of urban areas, treating urban systems as ecosystems (Botkin & Beverage,
1997; Ehrenfeld, 2000; Keddy, 2000; Capello & Faggian, 2002; Millennium Ecosystem
Assessment, 2005; Berkowitz et al., 2003; Janssen et al., 2005; Secretariat of the Convention
on Biological Diversity, 2005; Ramsar Convention Secretariat, 2007), urban planning
(Mabogunje, 1990; Davey, 1993; Pauleit & Duhme, 2000; Abbaspour & Gharagozlou, 2005;
Obeng-Odoom, 2007), and impacts of urban areas on global environmental change e.g. heat
island effect (Berkowitz et al., 2003; Pongrácz et al., 2006; 2010; Huang et al., 2009;
Takebayashi & Moriyama, 2009), and pollution (Berkowitz et al., 2003; Hidalgo et al., 2008).
The diversity and trends of these studies reflect the themes of interest and concern of the
scientific community.
Urban areas have major influences on the environment in terms of concentration of
consumption and waste discharge, concentrated industrialisation and intensive use of energy and
resources. The relationship between urban economic growth and development and the ecological
effects of this growth is often insidious and manifest when they are almost irrepressible. Cities
have therefore been perceived as parasites on the environment and spitting out wastes to the
detriment of “natural” ecosystems (UNU-IAS Urban Ecosystems Management Group, 2004).
With the development and rise of the modern environmental movements in the 1960s and
1970s, it became fashionable to consider everything to do with cities as bad and everything to
do with wilderness as good. Cities were considered polluted, dirty, artificial, and lack wildlife; therefore, urban environments are bad. While the wilderness is unpolluted and full of wildlife
therefore, it is good (Botkin & Beverage, 1997). Even in recent times, Rees (2003) described
urban areas as the human equivalent of the livestock feedlot: a spatially limited area
characterized by a large population of humans living at a high density and supported by
biophysical processes mostly occurring somewhere else.
27
Cities may not be an ecological disaster, because they generate almost 80 % of the global
economic output (Pauleit & Duhme, 2000). According to the United Nations Department of
Economic and Social Affairs (2005), cities with high population densities use substantially
less land, energy and water per person than low-density cities or suburban or rural areas with
large and widely spaced individual houses. Urban agglomerations tend to have larger populations
and more likely to be the site of large facilities and higher-level administrative functions and
create comparatively densely settled areas involved in the manufacturing and service industry
(Berkowitz et al., 2003; Millennium Ecosystem Assessment, 2005; United Nations Department
of Economic and Social Affairs, 2005). More land is thereby freed for nature. Urbanisation is
therefore not in itself inherently bad for ecosystems.
In contrast, most rural areas are made up of large tracts of land that have been converted to
agricultural monocultures and individual houses widely spaced out in the landscape that do not
support wildlife. Dense urban settlements may therefore be less environmentally burdensome
than rural and suburban sprawl (Brueckner & Fansler, 1983; Capello & Faggian, 2002;
Millennium Ecosystem Assessment, 2005). Also, urban centres facilitate human access to and
management of ecosystem services through, for example, the scale and proximity economies
of piped water systems. Botkin & Beverage (1997) put it very well in their ‘Cities as
Environments’ publication that, urban implosion has dual benefits: improving the lives of most
people and helping to conserve rural land and wilderness. The environmental sustainability of a
city should therefore be in terms of the future health of the environment within the city. That
is, the environment in which the city’s inhabitants dwell is influenced, for better or worse, by
the city’s own growth and change (William, 1990; Fedeski & Gwilliam, 2007).
Urban settlements are agglomerations of people and their activities. Human activities in urban
environments therefore constitute a natural part of urban ecosystem dynamics. Collins et al.
(2000) described a number of conditions that shaped the urban ecosystem. First, compared with
rural ecosystems, urban vegetation ecosystems are highly patchy and the spatial patch structure
is characterized by a high point-to-point variation and degree of isolation between patches.
Second, disturbances such as fire and flooding are suppressed in urban areas, and human-induced
disturbances are more prevalent. Third, because of the higher temperatures in urban systems,
in temperate climates there are longer vegetation growth periods. Fourth, ecological
successions are altered, suppressed or truncated in urban green areas. The uniqueness of urban
vegetation ecosystems can therefore not be overemphasised. The urban spatial diversity and
opportunities are often harnessed in landscaping and aesthetics. Therefore, as people increasingly
28
live in cities, the cities act as both human ecosystem habitats and drivers of local ecosystem
change. The challenge therefore should be how to foster urban systems that contribute to human
well-being and reduce ecosystem service burdens at all scales (Millennium Ecosystem
Assessment, 2005).
Cities are increasingly being recognised as ecosystems by themselves (Botkin & Beverage,
1997; Ehrenfeld, 2000; Berkowitz et al., 2003). The ecosystem approach is used in the analysis
and implementation of the objectives of the Convention on Biological Diversity (CBD). The
principles amount to a strategy for the integrated or holistic management of urban resources
through modern scientific adaptive management practices (Secretariat of the Convention on
Biological Diversity, 2005). Following this Convention, the Global Partnership on Cities and
Biodiversity was formed to support cities in the sustainable management of their biodiversity; to
assist cities to implement practices that support national, regional and international strategies,
plans, and agendas on biodiversity, and to learn from existing initiatives. The Curitiba
Declaration on Cities and Biodiversity adopted in 2007 reaffirms the resolve of mayors of
cities to improving the lives of urban residents to meet the objectives of the Convention on
Biodiversity (Secretariat of the Convention on Biological Diversity, 2007). This has come about
because, historically planners and decision-makers tended to neglect ecosystem services and
relations between ecosystems and human well-being, at least until a local or international crisis
has forced such concerns onto the policy agenda. In order to grow sustainable cities, we need a
renewed emphasis on the positive aspects of urban environments. It is possible for those who are
interested in wildlands and those who are interested in urban environments to both achieve
their goals. This can be achieved by combining environmental scientific knowledge with
spatial planning.
2.5 WETLANDS AND URBANISATION The spread of urbanisation leads to wetland ecosystem fragmentation and exploitation
(Ramsar Convention Secretariat, 2007). Landuse changes and over-use of water leads to
wetland loss and degradation in many parts of the world and at rates faster than other ecosystems
(Millennium Ecosystem Assessment, 2005). This is jeopardising the current and future provision
of their services for human well-being. As the wetland area increasingly gets urbanised, the
environment and in particular, flora and fauna are affected (Tables 2.2 and 2.3). Looking at
these pressures on wetlands, society cannot afford a hands-off approach to management.
Rather, wetland managers must clearly state the goals of management towards maintaining
functions of the wetlands for a sustainable urban environment.
29
Table 2.2. Anthropogenic effects on urban wetlands (Zedler & Leach, 1998) Component Problem Hydrology altered hydroperiod due to dams, flood control channels, excess runoff,
decreased water quality due to contaminants and eutrophication; Habitat loss, fragmentation and degradation; Pests feral animals and increased predation on native animals; invasions of
aggressive plants and negative impacts on native vegetation; Infrastructure Maintenance or dredging for shipping canals, expansion of marinas, filling
for highway expansion, replacement or installation of utilities; Visitors pressure for recreation (e.g., bird-watching, canoeing, bike trails) and
vandalism;
Table 2.3. Likely effects of urbanisation on wetland ecology (Ehrenfeld, 2000) Organism Effect Flora: large numbers of exotic species present; large and numerous sources for
continuous re-invasion of exotics; large amounts of land with recently disturbed soils suitable for weedy,
invasive species; depauperate species pool; restricted pool of pollinators and fruit dispersers; chemical changes and physical impediments to growth associated with the
presence of trash; small remnant patches of habitat not connected to other natural vegetation; human-enhanced dispersal of some species; trampling along wetland edges and periodically unflooded areas; Fauna: species with small home ranges, high reproductive rates, high dispersal rates
favoured; large predators virtually non-existent; “edge” species favoured over forest-interior species; absence of upland habitat adjacent to wetlands; absence of wetland/upland ecotones; human presence disruptive of normal behaviours.
Because of these disturbances, wetlands have taxonomic groups with the highest proportion of
threatened species (Millennium Ecosystem Assessment, 2005). According to Williams
(1990), tropical wetland vegetation species tend to have narrow ecological requirements, with
habitats that are accordingly highly fragile. This is even worst considering the rate of
urbanisation and limited capacities of environmental agencies to monitor and control pollution
in the developing countries. The driving force behind the establishment of the Ramsar
Convention was the continuing destruction of wetlands and the impact of this destruction on
populations of waterbirds (Ramsar Convention Secretariat, 2007). Yet, more than four decades
30
later, the “degradation and loss of wetlands is continuing more rapidly than for other ecosystems”
(Millennium Ecosystem Assessment, 2005). The declining condition of inland waters is putting
the services derived from these ecosystems at risk. The increase in pollution and degradation
of wetlands has reduced the capacity of these wetlands to filter and assimilate waste. It is
established that inland water ecosystems are in worse condition overall than any other broad
ecosystem type (Millennium Ecosystem Assessment, 2005; Ramsar Convention Secretariat,
2007).
Urban land has competing uses for man. The qualities that make a location good for a city
may often also make it an important location for biological conservation. For example, river
mouths, confluences, riparian areas, deltas are good sites for cities because of the access to
transportation, leisure and water for all purposes. However, these locations are modified and
polluted after settlement with the ecosystem cleaning services taking place mostly beyond
urban boundaries. The water requirements of aquatic ecosystems adjacent the expanding
human settlement and freshwater demands increase pressure on the ecosystem. This leads to
changes in flow regime (Reinelt et al., 1998), transport of sediments and chemical pollutants,
modification of habitat, and disruption of migration routes of aquatic biota (Millennium
Ecosystem Assessment, 2005). Landuse change also affects evapotranspiration, infiltration
rates, and runoff quantity and timing (Owen, 1999; Berkowitz et al., 2003; Fedeski &
Gwilliam, 2007; Roy, 2009). Changes of particular importance for human well-being are the
contrasting reductions in the overall quality and quantity of available runoff versus
concentrated peaks of runoff causing flooding. Also, the urban rainwater with absorbed
pollutants from the air falls on road surfaces, parking lots, vehicles, corrosive railings, brick,
and copper roofs thereby resuspending pollutants in the runoff. Wetland plants attenuate the
stormwater flow, bind sediment, and directly accumulate metals (Shutes et al., 1999; Shutes,
2001; Fritioff, 2005). Vegetation also influences urban environmental conditions and energy
fluxes by selective reflection and absorption of solar radiation and may also influence air
quality and human health (Small, 2001). Information on the abundance, quality and spatial
distribution of urban vegetation is therefore very vital for designing systems for the provision
of ecosystem services, park and natural area management and urban planning.
Urbanisation is a relatively permanent landuse change. In general, the first order hydrologic
impacts associated with urbanisation result from increasing impervious area (Choi et al.,
2003; Reinelt et al., 1998; Brody et al., 2007). The hydrologic changes are associated with
changes from major classes of landcover and landuse e.g. from forest to urban system (as the
31
case is in Kumasi). This leads to decreased infiltration and an increase in runoff with the
associated increase in pollution loads, decrease in temporal reliability of environmental systems
and disturbance of wetland biota (Reinelt et al., 1998; Zedler & Leach, 1998). Reduced
infiltration can also lead to longer lifespan of pools with stagnant water, thus providing
increased breeding opportunities for mosquitoes (Millennium Ecosystem Assessment, 2005;
Ramsar Convention Secretariat, 2007). Urban wetlands are also the destination for
contaminants from roads, gutters, storm drains, and occasional wastewater spills.
Whilst the conservation of ecosystems services is undisputedly good for mankind, the urban
dweller rarely plays a significant part in conserving it. There is continued lack of
understanding and appreciation of the complex processes involved because, many of these
services take place at some distance from the urban consumers (Millennium Ecosystem
Assessment, 2005). Also, the effect of the urban dweller’s actions and inactions and the
control and management of these ecosystems go beyond the city boundaries. It is unfortunate
however, that, the people most adversely affected by the loss of ecosystem services tend to be
the least influential economically and politically (such as the urban poor, future generations,
and residents living far from where the decisions are being made) (Millennium Ecosystem
Assessment, 2005).
2.5.1 Urban Wetlands Vegetation Plant species found in wetlands are considered as wetland vegetation. Because migration of
oxygen in waterlogged soils and into root zones is slow and proceeds at an unacceptable or
intolerable rate for most organisms, these areas are often populated by plants adapted to poor
oxygen conditions in the root zone (Lyon, 1993; Haslam, 2003). The major factors believed to
influence wetland biodiversity include hydrology, geomorphology, substratum, chemistry,
adjacent terrestrial system, grazing, anthropogenic influences and individual plant tolerance or
response to the stresses of flood and drought (Harper et al., 1995; Owen, 1999; Casanova &
Brock, 2000; Fortney et al., 2004; Maltby & Barker, 2009; Miller & Fujii, 2010). Conversely,
wetland species play a key role in the water quality, structure and functioning of stream
ecosystems (Barrat-Segretain et al., 1998; Shutes, 2001; World Meteorological Organisation,
2006; Sassa et al., 2010). Streamside vegetation also controls the supplies of allochthonous
and autochthonous organic matter, filters the nutrients and pollutants, helps stabilise banks
and influences the water temperature and light through shading (Zedler & Leach, 1998;
Shutes, 2001; Baarta et al., 2010).
32
Urban wetlands often have unusual physical features and conditions which are the result of
human interventions. These include disturbed soil profiles e.g. through agricultural activities,
mounds of soil from old ditch-digging or channel-widening activities, heterogeneous
materials e.g. from waste dumping or stream deposition, hard concrete surfaces etc. (Reinelt
et al., 1998; Ehrenfeld, 2000; Millennium Ecosystem Assessment, 2005). These forms of
disturbances create spatial and temporal heterogeneity in wetland ecosystems and act as
important mechanisms in maintaining species richness (Pickett et al., 1989; Chaneton &
Facelli, 1991; Barrat-Segretain et al., 1998; Fortney et al., 2004; Ot’ahel’ová et al., 2007;
Grimm et al., 2008). Biological diversity in an urban setting could therefore be a direct
reflection of the spatial diversity provided by the urban landscape.
Apart from the edaphic and hydrologic conditions, landuse is also said to affect the
vegetation. In a study on the watersheds of Wisconsin lakes, U.S.A., agricultural development
explained more of the variation in macrophyte community species richness and abundance
than did urban landuse and that agriculture and urban land uses differ as causal agents (Sassa et
al., 2010). That is, urbanisation and agricultural developments create different perturbation
gradients that appear to affect aquatic plant species differently. With these diverse ranges of
influencing factors and consequences, attempts at wetland restoration have therefore been a
great challenge for many wetland ecologists because of the different and sometimes combined
and synergistic effects of causal agents of degradation. For example, Baarta et al. (2010)
attempted to predict macrophyte development in response to restoration measures. Modelling
the status quo showed that completely isolated water bodies are over grown with macrophytes
resulting in an intensified terrestrialisation process. In contrast, complete reconnection to the
main channel caused a loss of macrophyte abundance and species in most aquatic habitats.
2.5.2 Wetlands, Urbanisation and Agriculture Urban agriculture is defined as an enterprise located within or on the fringes of a town, a city or a
metropolis, which grows or raises, processes and distributes a diversity of food and non-food
products, (re-)using largely human and material resources, products and services found in and
around that urban area, and in turn supplying human and material resources, products and
services largely to that same urban area (Mougeot, 1999; FAO, 2007). According to
Egziabher et al. (1994), urban farming is a basic urban function as ancient as cities
themselves. Asia is leading the way in the sector, with highly complex and efficient systems
for the production and marketing of agricultural products.
33
The idea of urban agriculture got some boost as city planners envisaged an idea of a
sustainable city and tried to achieve it through spatial planning that included agriculture and
wild areas. For example, Sir Ebenezer Howard (1850-1928) in “Garden Cities of Tomorrow”
describes a utopian city in which man lives harmoniously with the rest of nature. His ‘park town’
or ‘garden city’ concepts describe a city that is surrounded and interconnected by greenbelts,
forming a system of countryside and urban landscapes. His idea was to combat urban
overcrowding by the establishment of garden cities of about 30,000 inhabitants, self-contained
in terms of employment, food production, recreation etc. (Mumford, 1961). With such a
concept, variety of habitats ranging from fairly natural ones to highly modified ones are
therefore maintained (Niemelä, 1999). In developing countries’ literature however, urban
agriculture or green areas are more of an evolving economic activity than a result of spatial
planning (Armar-Klemesu & Maxwell, 1999; Egziabher et al., 2004; Faithful & Finlayson,
2005; Erenstein et al., 2006; Foeken, 2006; Foeken & Owuor, 2008; Magigi, 2008) and
governments are introducing institutional and other policy changes that recognize or tolerate,
manage, and promote the activity.
Urban agriculture may be practiced for food (Egziabher et al., 1994; Armar-Klemesu &
Maxwell, 1999; Mougeot, 1999), as a livelihood and asset strategy (Armar-Klemesu & Maxwell,
1999; Erenstein et al., 2006; Foeken & Owuor, 2008), income (Foeken, 2006) and has the
potential to significantly contribute to the city’s sanitation needs (Lydecker & Drechsel,
2010). It is also known that, an increasing proportion of the target group for poverty
alleviation in developing countries is now found in urban areas (Adams et al., 2004; National
Development Planning Commission, 2005; Ravallion et al., 2007a, b). Many of these urban
poor find employment or improve the quality of their daily diet through agriculture in the
open urban spaces. In times of economic crisis, urban agriculture sustains livelihood of most
people and assists with resolving or coping with diverse development challenges.
Urban agriculture is spurred by a complex web of factors still to be understood, not the least
of which are urban poverty and food insecurity (Mougeot, 1999; Adams et al., 2004;
Ravallion et al., 2007b). Even though Pacione (2009) considers the urban populace to be less
employed in agriculture, the 1988 census ranked urban agriculture as Dar es Salaam’s second
largest employer, after small traders and labourers. Urban agriculture occupied 11 % of the
population aged 10 or more (Egziabher et al., 1994). However, few papers from literature
overtly condemn urban agriculture under any form. All near opposition papers are concerned
with the issue of urban planning (Magigi, 2008), public health (Afrane et al., 2004; Matthys et
34
al., 2006; Obuobie et al., 2006; Klinkenberg et al., 2008) and the environment (Adam et al.,
1999; Keraita et al., 2003; Faithful & Finlayson, 2005; Erenstein et al., 2006; Mireri et al.,
2007).
According to Magigi (2008), urban agriculture is a big economic activity in Africa because of
the unguided land development, poor policy and legislative enforcement, out-dated policy
inherited from colonial period and inadequate community involvement in spatial landuse
planning processes. This assertion may be true because urban land values are usually very high
and such lands cannot be used for agriculture if they are not originally part of the urban planning
scheme. In Ghana, urban landuse plans do not include allocation of land for agriculture.
Therefore, lands used for urban agriculture belongs to either government institutions or private
developers or are open areas designated as wetlands along streams (Adam et al., 1999; Brook
& Dávila, 2000; Oboubie et al., 2006). Due to the hilly landscape of Kumasi, most streams
run through inland valleys unsuitable for construction and are therefore prime sites for
cultivation of vegetables, sugar cane and taro (Figure 2.3).
Historically, agriculture has been the main cause of wetland loss (Egziabher et al., 1994;
FAO, 1998; Eppinka et al., 2004; Millennium Ecosystem Assessment, 2005; Ramsar
Convention Secretariat, 2006). This is through direct pollution by fertilizers, water abstraction
for irrigation, drainage of excessively waterlogged places or conversion to paddy farms, and
mining of peatlands, to mention a few. Whilst wetland conversion to agriculture is a common
phenomenon, the permanent wetland loss from agriculture to urban infrastructure or housing
through the urbanisation process has not been given the needed attention (Mathias & Moyle,
1992; Thibault & Zippererb, 1994). These shifts are very much evident in peri-urban areas of
most developing country cities. However, the livelihood of most peri-urban communities
depends to a large extent on the productivity of the natural systems, in particular wetlands
(Brook & Dávila, 2000; Keraita et al., 2003). Therefore, to safeguard and possibly enhance
livelihoods of many urban and peri-urban communities who subsist on wetlands, it is
imperative that the benefits of the natural wetland ecosystems be recognised when planning
and implementing development projects (Silvius et al., 2000; Grimm et al., 2008).
35
Figure 2.3. Major vegetable farming areas in the Kumasi Metropolis (Oboubie et al., 2006)
2.5.3 Wetlands, Urbanisation and Floods The urban development landscape in most developing countries ranges from rich
neighbourhoods with infrastructure to poor slum and or informal settlements. These poor city
neighbourhoods are more prone to flooding and other natural disasters than wealthy
neighbourhoods. These unfavourable initial conditions and disasters then serve as both drivers
and consequences of development patterns (Millennium Ecosystem Assessment, 2005;
Adelekan, 2010). Without adequate spatial planning, governance, regulation, and public
spending, increasing numbers of the urban population are living in wetlands and other
ecologically sensitive areas. This development pattern is making some suburbs of a large
number of African cities vulnerable to natural disasters (Adelekan, 2010). It is predicted that
future flood damages will depend greatly on settlement patterns, landuse decisions, quality of
flood forecasting, warning and response systems (ActionAid International, 2006; Millennium
Ecosystem Assessment, 2005; Adelekan, 2010).
Flooding is a natural phenomenon (ActionAid International, 2006). Very often in nature,
watersheds get flooded. This natural phenomenon has however become problematic because
man is increasingly drawing nearer to these natural systems. The watershed flood frequency
36
and scale has therefore been intensified by human activities. With improved life styles,
industrialisation and urbanisation, watersheds are constantly being inundated with expensive
capital goods and infrastructure. The costs of damage due to floods have therefore continually
risen (United Nations Inter-Agency Secretariat of the International Strategy for Disaster
Reduction, 2005; World Meteorological Organisation, 2006; McClean, 2010). Flood research
has, therefore, intensified and different methods have been applied in urban flooding in
different places with different price tags.
For example, in 1951, a flood along the main stem of the Kansas River was estimated to have
affected mostly urban areas because about 90 % (approximately US $479,000,000) of the
damage experienced occurred in urban areas. This great loss was used to justify the
construction of a stair-step series of lakes in the Kansas River Basin to act as storm water
collection sinks (Koilmorgen, 1953). Since then, the flood control plans for the Kansas River
Basin alone have been so extended and elaborated that they bear a price tag of billions of
dollars. More shattering than the rising costs are the rising number of acres of land that is to
be flooded by building more and more dams. These flood control mechanisms contravene
both the spirit and purpose of resource conservation. Another good intention with a wrong
approach was the building of a series of levées and dredging of channels as a control method
of the December 1955 flooding of Santa Cruz. This only resulted in extreme siltation and loss
of control of the river. Another flood of Santa Cruz in January 1982 proved that the solution
to flooding in urban areas needs a more integrated approach than artificial embankments
(Griggs & Paris, 1982). In practice therefore, floods can never be eliminated entirely.
However, the vulnerability to floods can be mitigated by integration of physical developments
with behaviour and actions especially by residents in flood prone areas (United Nations Inter-
Agency Secretariat of the International Strategy for Disaster Reduction, 2005; APFM, 2006;
Egyir, 2008; Akwei, 2010; McClean, 2010).
The scale and frequency of floods has been on the increase in some suburbs of Kumasi,
Ghana. For instance, residents of Aboabo and Atonsu all in the Aboabo Basin are frequent
victims of floods (Egyir, 2008; Akwei, 2010). However, most of the wetland research
conducted in Kumasi has been on vegetable farming and water quality in river basins of
Kumasi (Keraita et al., 2003; Obuobie et al., 2006; Keraita et al., 2008a, b; Lydecker, &
Drechsel, 2010). Egyir (2008) and Akwei (2010) worked on physical flood control and coping
strategies to flooding in the Aboabo Basin. The watershed hydrology and causes of annual
floods have not been determined by any research but public opinion attributes the floods to
37
obstructed water ways and climate change (Akwei, 2010; Ghana News Agency, 2010). How
much and which of the annual floods is attributable to each of these factors is not known.
According to Bhaskar & Singh (1988), Odemerho (1993), and the United Nations Inter-
Agency Secretariat of the International Strategy for Disaster Reduction (2005), the problems
of floods in third World cities are compounded by the rapid rate of urban expansion into
urban fringe areas often unaccompanied by the development of storm drainage systems.
The effectiveness of wetlands for flood abatement may vary depending on the size of the
wetland, type and condition of vegetation (Ot’ahel’ová et al., 2007), slope, and location of the
wetland in the flood path and the saturation of wetland soils before flooding (Bhaskar &
Singh, 1988). Urbanisation destroys these qualities of wetlands and aggravates flooding
because large parts of the ground are covered with roofs, roads and pavements and building
drains. As a result, even quite moderate storms produce high overland flows quickly filling up
river channels (Griggs & Paris, 1982; United Nations Inter-Agency Secretariat of the
International Strategy for Disaster Reduction, 2005; McClean, 2010). Therefore with
increased climate and landscape variability, most floods are getting out of hand and cannot be
predicted accurately.
Early flood control and protection approaches have been based on structural solutions like
embankments, bypass channels, dams, reservoirs, storm drains etc. This approach resulted in
changes in flow regimes, separation of rivers from flood plains and in most cases increased
flood regimes (Koilmorgen, 1953; Griggs & Paris, 1982). There is now a shift from flood
control to flood management (Integrated Flood Management) with the recognition that floods
are a natural river phenomenon (World Meteorological Organisation, 2006; Adelekan, 2010).
Flood management is more holistic and carried out through a public policy framework. This
integrated flood management approach is, however, not developed in Ghana. Food
management is reactionary through the National Disaster Management Organisation
(NADMO) in collaboration with the District Assemblies. In most places, mitigation measures
depend on resources available to the District Assembly and political expediency.
2.6 URBAN POVERTY AND WETLANDS
2.6.1 Urban Poverty in Africa The post-independence experience of African countries in environmental management has
been characterized by a series of overlapping crises. Most countries are experiencing very
rapid urbanisation, environmental degradation, and increasing poverty (Kidane-Mariam,
38
2003) and a shift or relocation of poverty to the urban areas (IPCC, 2007). These urban poor
are usually easy to locate in the urban landscape. According to the UN-HABITAT (1996),
lack of access to land by these poor, facilitates the development and expansion of slum and
squatter communities within urban areas. This situation is not only typical of Africa. For
example, at end of World War II, cities housed less than a third of the poor in the United
States and this had risen to more than half by the end of the century and these poor people are
spatially concentrated in extremely poor urban neighbourhoods (Kaplan et al., 2009). This
means a relocation of population, poverty and environmental pressures to urban areas. The
challenge now is for a concerted and synergised approach to dealing with this urban poverty-
environmental nexus.
The link between poverty and environment is complex and goes in both directions. The poor
depend heavily on a number of environmental services for their livelihoods and are very
vulnerable to the loss or degradation of environmental conditions (Adams et al., 2004). At the
same time, poverty and unequal access to resources often compel people to use available
natural and environmental resources unsustainably. For these reasons, Griebenow & Kishore
(2009) suggested that strategies to address poverty needed to address environmental problems
as well, and conversely strategies to improve the environment needed to address poverty.
However, in these already financially depraved slum or informal settlements, the lack of
appropriate institutional structures drives ecological and environmental trends towards the
negative. The condition of the environment and human settlements in the urban areas of
developing countries has therefore drawn the attention of the academic community,
international development agencies, regional intergovernmental organisations, nations, and
civic societies at various geographical scales and is well captured in Goal 7 of the MDGs.
Almost all African countries have therefore embarked upon the preparation and
implementation of broad and specific policies and strategies of environmental management
towards meeting this goal and to eliminate urban slums and reduce poverty (African Peer
Review Mechanism Secretariat, 2005; National Development Planning Commission, 2005).
The complex linkages between poverty and environment are therefore supposed to be
mainstreamed in each country’s poverty reduction strategy (Griebenow & Kishore, 2009).
2.6.2 Urban Poverty and the Environmental Kuznets Curve The cause-effect relationship between environmental degradation, poverty and disasters is
complex and has been the subject of many analyses (Beckerman, 1992; Kidane-Mariam,
2003; Stern, 2004; Sánchez-Rodríguez et al., 2005; Constantini & Monni, 2008; International
39
Recovery Platform, 2009). It is widely believed that poverty and other economic conditions
determine the priority placed on environmental issues (Killeen & Khan, 2002; Rietbergen et
al., 2002; Esty et al., 2005; Gunter et al., 2005; Rahman, 2006). That poor people directly
extract environmental resources thereby destroying habitats. However, many poor people live
closely with natural resources and rely heavily on low-input production systems gives. They
therefore have the motivation and advantage in the development of new environmentally
friendly products and services that improves their lives (Rietbergen et al., 2002).
Ecologists wary of the effects of increasing wealth on the environment, arguing that,
economic growth and conservation are incompatible goals (Czech, 2003). Economists, on the
other hand, expect economic growth to be a cure for global environmental challenges; that
wealthier countries have the luxury of investing more to conserve and protect ecosystems
(Cropper & Griffiths, 1994; Adams et al., 2004), fundamental aspects of human well-being,
and the quality of life (Mills & Waite, 2009). According to Costantini & Monni (2008) and
the Secretariat of the Convention on Biological Diversity (2007) environmental resources can
be sustainably harnessed to play an active role in reducing poverty, achieving higher living
standards and increasing human development levels. The difficulty, however, is to define that
optimum or ideal use of the environment which would be sustainable and at the same time,
achieve the economic and developmental goals envisaged by policy makers to reduce poverty.
Environmental degradation tends to increase as structure of the economy changes from rural
to urban or agricultural to industrial, but it starts to fall with another structural change from
energy intensive industry to services and knowledge based technology-intensive industry
(Munasinghe, 1999; Magnani, 2001; Panayotou, 2003; Dinda, 2004; Costantini & Monni,
2008; Wagner, 2008). At the latter stage environmental degradation starts to decrease because
people tend to make preventive environmental expenditures, donations to environmental
organisations or choose less environmentally damaging products. Thus, rich people value the
clean environment and make conscious efforts to preserve it. This systematic relationship
between income and change in environmental quality forms an inverted-U-shaped curve
called the Environmental Kuznets Curve (EKC) (Dinda, 2004).
The turning points of EKCs vary for different pollutants, environmental indicators, variables
used in the model, country, and the policy environment (Magnani, 2000, 2001; Stern, 2004).
For most of the pollution indicators, the estimated turning point lies within the income range
of 3,137 (Panayotou, 1993) to US$ 908,178 (Stern and Common, 2001). No studies have been
published on EKC and wetlands to know the estimated turning point. The closest study is that
40
of McPherson & Nieswiadomy (2005) on threatened species with the turning point between
10,000 and US $15,000 (US $1995 purchasing power parity) per capita income.
Even though the EKC has shown that income–environmental degradation relationship exists,
there is still no consensus on the trajectory (Panayotou, 2003; Barbier, 2004; Dinda, 2004;
Wagner, 2008). For example, Munasinghe (1999) suggests that, developing countries could
take alternative routes that do not reach high levels of environmental degradation by
identifying and addressing the economic imperfections that might exacerbate growth-related
environmental harm. That is, higher levels of development could be attained at lower
environmental cost. Also, the relationship between income and environmental care depends
on the distribution of benefits and costs of polluting activities (Magnani, 2001). The driving
force for flattening of the EKC may therefore not depend on incomes but distribution of costs
and benefits of pollution and the policy interventions that are put in place to protect the poor
and weak from bearing the burden of pollution.
As human populations increase, the marginal per capita value of wetlands first increases
because of increased wetland scarcity per capita. Thus a higher human population implies that
there is less wetland per capita available and therefore, on the average, fewer but more
precious wetlands. But the marginal value of wetlands increases with human development
only to a point because wetland functions begin to be lost through the urbanisation process
(Mitsch & Gosselink, 2000). A planned urbanisation programme and good policy
environment might decrease encroachment on wetlands and other natural areas thereby
securing environmental quality. Therefore Panayotou (1997) and Eppinka et al. (2004) are of
the view that, rather than economic growth, a more secured property rights, better
enforcement and effective environmental regulations will help ‘flatten’ the EKC. Property
rights will reduce the externalities associated with the use of wetlands as environmental
goods.
2.7 CLIMATE CHANGE, URBANISATION AND WETLANDS A major non-climate attribute affecting the ecosystem and its vulnerability to climate is the
increasing urbanisation of the developing world. Close to half of the world’s population now
lives in urban areas. Increasing urbanisation means that the impacts of climate change on
human settlements, if they occur, will increasingly affect urban populations (IPCC, 2007;
Adelekan, 2010). A significant part of the activities leading to the achievement of Goal 7 of
the MDGs (environmental sustainability) will therefore be played out in the urban
environment (Secretariat of the Convention on Biological Diversity, 2007). The hazards to
41
which some cities are exposed are likely to become either more severe or more frequent, and
so the increased risk should be anticipated, if not predicted (Fedeski & Gwilliam, 2007; IPCC,
2007). According to Niasse et al. (2004), the physical and socio-economic characteristics of
West Africa predispose it to be among the most vulnerable regions to climate change
worldwide.
A changing climate can modify all elements of the water cycle: change both the frequency
and intensity of precipitation, evapotranspiration, soil moisture, groundwater recharge,
snowmelt and therefore runoff (Fedeski & Gwilliam, 2007). It is therefore believed that the
most widespread potential impact of climate change on human settlements is flooding
(Fedeski & Gwilliam, 2007; IPCC, 2007; International Recovery Platform, 2009; McClean,
2010). Riverine and coastal settlements are believed to be particularly at risk, but urban
flooding could be a problem anywhere storm drains, water supply, and waste management
systems are not designed with enough system capacity or sophistication to avoid being
overwhelmed (IPCC, 2007). Also, there is likely to be increased cost of losses due to flooding
because of the abundance of more precious and capital goods and services in urban areas
(McClean, 2010). Urbanisation itself explains much of the increase in runoff relative to
precipitation in settled areas and contributes to flood situations (IPCC, 2007). It is estimated
that, by the year 2050, more than 70 % (and 90 % by the 2080s) of people in settlements that
potentially would be flooded are likely to be located in a few regions: west Africa, east
Africa, the southern Mediterranean, south Asia, and southeast Asia (Niasse et al., 2004;
Millennium Ecosystem Assessment, 2005; IPCC, 2007).
Due to climate change and urbanisation, large and growing numbers of people are at high risk
of adverse ecosystem changes, a worsening trend of human suffering and economic losses
from natural disasters (Nelson et al., 2009). There is also increasing demand for ecosystem
services because of increasing consumption per person, multiplied by a growing human
population (Millennium Ecosystem Assessment, 2005). Effects of climate change will be felt
most directly through changes in the distribution and availability of water, thereby increasing
pressures on the health of wetlands. Restoring wetlands and maintaining hydrological cycles
is of utmost importance for addressing climate change, flood mitigation, water supply, food
provision and biodiversity conservation (Ramsar Convention Secretariat, 2007; IPCC, 2007).
According to the Ramsar Convention Secretariat (2008), the management of these wetlands
should be supported by indigenous and traditional knowledge, recognition of cultural
42
identities associated with wetlands, stewardship promoted by economic incentives, and
diversification of the support base for livelihoods.
Wetlands are often biodiversity hotspots and deliver a wide range of ecosystem services
relating to climate change mitigation (Berkowitz et al., 2003; Janssen et al., 2005; Nelson et
al., 2009). Many types of wetlands play important roles in sequestering and storing carbon
(Joosten & Clarke, 2002). However, this is not yet fully recognized in national and
international climate change response strategies, processes, and mechanisms (Ramsar
Convention Secretariat, 2007). Because of the high amounts of carbon stored, wetlands are
particularly vulnerable to climate change impacts and human disturbances of wetland systems
can cause huge emissions of stored carbon. Therefore, recognising the potentially serious
implications of climate change on wetlands, Contracting Parties to the Ramsar Convention
have been called to manage their wetlands in such a way as to increase their resilience to
climate change and extreme climatic events and to ensure that climate change responses such
as revegetation, forest management, afforestation and reforestation and their implementation
do not lead to serious damage to the ecological character of wetlands (Ramsar Convention
Secretariat, 2007).
Despite these emerging international developments on climate change and urbanisation, cities
have the power to establish local environmental policies and regulations, such as landscaping
guidelines and pollution/emissions standards to mitigate the effects of climate change. They
can also integrate biodiversity considerations into other local policies, landuse planning, and
the development and operation of infrastructure, such as transportation and water
management systems (Secretariat of the Convention on Biological Diversity, 2007). Even
with these opportunities, urban areas are still understudied in the analysis of global
environmental change, with a majority of research placing emphasis on the contributions of
emissions of greenhouse gases and the heat island effect to global climate change (Hidalgo et
al., 2008; Takebayashi & Moriyama, 2009). Much less attention has been devoted to the study
of the impacts of global environmental change on urban areas and the people who live in
them. Particularly critical are the conditions in poor countries (Sánchez-Rodríguez et al.,
2005).
2.8 REMOTE SENSING AND URBAN LANDSCAPE PLANNING AND MANAGEMENT The effects of the gradual global dominance of urban settlements extend well beyond the
urban ecosystem. Therefore, as natural areas shrink and fragment through the urbanisation
43
process, humanity needs to conserve biological diversity and ecological integrity of urban
environments for a sustainable future. Meeting the challenge of conserving regional
ecological integrity in urban and urbanizing landscapes will depend on effective urban
management and spatial planning. However, the fragmented nature, isolated and frequently
disturbed conditions of natural areas exacerbate the difficulties inherent in spatial planning and
urban landuse (Mazzotti & Morgenstern, 1997). This is because the distribution of land, water and
forest resources on the earth’s surface is rarely equitable. Therefore the processes of human
ecosystem differentiation, resource allocation and settlement have frequently had spatial
dimensions that are usually characterised by patterns of territoriality and spatial heterogeneity
on many scales (Berkowitz et al., 2003). In managing these spatially heterogeneous and
scarce resources, there is the need for frequent inventory for monitoring and evaluation to
inform policy and reduce conflicts. Large-scale ground-based monitoring of city space,
forests, agricultural lands, wetlands, etc. are however, time-consuming, labour-intensive and
are typically constrained by poor accessibility (Lyon, 1993; Smith, 1993; Vincent & Saatchi,
1999).
In recent times, urban landcover provided by satellite and airborne sensors is an important
complement to in situ measurements of physical, environmental and socioeconomic variables
(Small, 2001; Small & Lu, 2006). Satellite-based earth observation offers the possibility to
provide synoptic measurements of land cover over very large geographic areas and over long
periods of time (Brinson, 1993; Lyon, 1993; Xu et al., 2000; Harvey et al., 2001; Ozesmi &
Bauer, 2002; DeKeyser et al., 2003; Mundia & Aniya, 2006; Small & Lu, 2006; Islam et al.,
2008). The development and application of these technologies has been progressing steadily.
Remote sensing and geographic information system (GIS) technologies have been applied in
wetland studies (Thenkabail & Nolte, 1996; Lunetta et al., 1999; Töyrä et al., 1999;
Thenkabail et al., 2000; Harvey & Hill, 2001; Ozesmi & Bauer, 2002; Choi, 2003), urban
areas (Smith, 1993; Xu et al., 2000; Pongrácz et al., 2006; Altobelli et al., 2007), and spatial
planning (Pauleit & Duhme, 2000; Abbaspour & Gharagozlou, 2005).
The application of remotely sensed observations to studies of the urban wetland vegetation
has, however, been rather limited. This is because data of specific spectral and spatial
resolutions for the discrimination of vegetation types are expensive and hard to come by. For
these reasons, very few remote sensing studies have been carried out in tropical wetland
vegetation in Africa specifically Ghana (Thenkabail & Nolte, 1996; Thenkabail et al., 2000;
Mundia & Aniya, 2006). Whilst Landsat data may have its shortcomings for studies of the
44
built urban environment, it may be sufficient to detect significant spatial and temporal
variations in urban vegetation (Small, 2001). This research therefore forms one of the early
studies on urban wetland vegetation changes in Kumasi, Ghana through the application of
remote sensing technologies.
Up-to-date landuse inventory is mandatory when making plans for solving problems
associated with the rapidly growing areas to make them more sustainable and increase the
quality of urban life (United Nations Department of Economic and Social Affairs, 2005). To
meet these urban spatial planning needs, the Buffer Zone Policy of Ghana advocates for a
buffer of all natural landscapes and waterways in urban areas and integration of natural areas
into urban planning (Water Resources Commission, 2008). This policy is belated and most of
the buffer areas have already been encroached upon. To curb encroachments on natural areas, the
participatory approach as has been applied in city planning in Brazil could be used in Ghana
(United Nations Department of Economic and Social Affairs, 2005). In doing this however, it
is recommended that stakeholders give full recognition to the significance of wetlands in
spatial planning so that the values they represent can properly inform landuse and investment
priority-setting and the adoption of necessary safeguards (The Secretariat of the Ramsar
Convention, 2007). The decentralised administration in Ghana which devolved spatial
planning to the district assemblies offers an opportunity to involve all stakeholders in the
planning process.
The establishment of KUMINFO in the KNUST and the Remote Sensing Applications Unit
(now called CERGIS) in the University of Ghana were some of Ghana’s earliest formal
attempts to propagate remote sensing and GIS applications. Also, Ghana's development
agenda, driven by the Growth and Poverty Reduction Strategy (GPRS II) which is informed by
our commitments to Millennium Development Goals (MDGs), New Partnership for African
Development (NEPAD) and above all, the underlying obligations set out in the Constitution
of the Republic of Ghana, recognises the planning and management of resources for
development. However, the land tenure system and the system of land delivery in Ghanaian
cities have significant implications for spatial development and urban sprawl (UN-HABITAT,
2008a). This research will therefore provide the ecological knowledge to supplement such
efforts at improving the urban environment in Kumasi, Ghana.
45
3 POLITICAL ECOLOGY OF WETLANDS IN KUMASI
3.1 INTRODUCTION In all the regions of the world where the absolute number of poor has increased, a majority of
them are in urban areas (Baharoglu & Kessides, 2000; Devas, 2005). In Ghana, the data on
poverty shows that, urban poverty as a proportion of total poverty is also increasing (White et
al., 2001). Using the expenditure approach, the ratio of urban to rural poverty in the Ghana
1991/92 survey years was 1:35 (Ravallion et al., 2007a). Urban poverty to some extent
reflects active rural–urban migration due to the uneven distribution of facilities and
opportunities in developing countries like Ghana (Baharoglu & Kessides, 2000).
Apart from government acquired lands, land is privately owned in Ghana. The official city
layouts are therefore prepared is consultation with landowners. In such layouts, wetlands and
natural areas or parks are delineated and cannot be built upon. Most of these layouts are not
serviced, such that, the distance to amenities influences the rent on the land and plays the
initial role of spatial resource allocator since it influences location choices of potential land
buyers (Capello & Faggian, 2002). This leads to residential areas reflecting spatial differences
in wealth of residents, types of houses and availability and density of infrastructure. The poor
immigrants tend to settle in the areas that are not part of the formal layout of the city and erect
temporal structures.
A poverty profile of the city will therefore distinguish these poor from the non-poor, identify
their characteristics, facilitate the process of identifying the location of the poor and highlight
groups that may be particularly vulnerable (Baharoglu & Kessides, 2000; Baker & Schuler,
2004). Data is, however, often difficult to obtain in developing countries for poverty profiling.
Whilst data is not easily available, the physical location and characteristics of the poor are
undeniably obvious in Ghanaian urban housing landscape. The wetlands of Kumasi are prime
areas for these informal settlements.
This chapter describes the physical and socio-economic characteristics of Kumasi,
specifically, inhabitants of these informal settlements along the wetlands areas. The political
ecology in terms of land acquisition and demolitions will be discussed. The aim is to identify
plausible development pathways and the choices and actions for (re)shaping these informal
settlements for a sustainable future.
46
3.2 METHODOLOGY
3.2.1 Physical and Socio-economic Survey of Wetland Communities of Kumasi This involved the use of primary and secondary data. The secondary data are mainly from
published works on Kumasi and its environs. The primary data were collected during field
visits through the use of surveys, interviews, observations and photographs at the different
study suburbs. All governmental and non-governmental organisations that are relevant to this
research or work directly or indirectly with the wetlands were identified. Table 3.1 is a list of
stakeholder groups identified and employed in this research. These included: the Kumasi
Metropolitan Assembly (Environment and Sanitation Unit), Friends of Rivers and Water
Bodies, sub-chiefs, Town and Country Planning Department (TCPD), Hydrological Services
Department (HSD) and the National Disaster Management Organisation (NADMO). Informal
visits were first made to the identified organisations and the researcher and research ideas
introduced and relevant personnel suitable for the research identified. Official introductory
letters were then sent to these identified personnel and where necessary, the heads of
departments to introduce the research. The specific involvement of the organisations or
personnel in this research was specified and sought. From the list of stakeholders, various data
collection strategies as shown in the table were employed to solicit the needed information.
3.2.1.1 Wetland communities and the associated anthropogenic activities
With the aid of maps, satellite imagery and the reconnaissance survey, houses, social and
economic activities within 100 m from the stream channels based on the 100 m buffer range
set by the Ministry of Lands and Natural Resources (Water Resources Commission, 2008)
were selected. From this, households were randomly selected and a structured questionnaire
administered to one adult member of the household (Appendix 1). Afterwards, respondents
who had interest and knowledge about the area were selected for a focus group discussion to
probe further, summarise and draw conclusions from the information collected from the
questionnaire survey and interviews. In all, 128 respondents answered the structured
questionnaires.
All anthropogenic activities within the 100 m buffer for each wetland were identified and
recorded. Stakeholders whose activities have direct impact on the wetland e.g. modifications
in water the channel, water quality, wetland vegetation etc. were identified and interviewed.
47
Table 3.1. Stakeholder list and the respective data collection tools used in the survey of wetlands in Kumasi, Ghana
Stakeholder group Stakeholder units # of respondents Data collection
method
Wetland associated communities
Dakwadwom 20 Structured questionnaire and
focus group discussions
Ahensan 21
Aboabo 21
Kwadaso Estates 20
Atonsu 20
Spetinpom 26
Wetland Associated Businesses
Agriculture 5 Interviews
Car washing bays 5
Carpenters 5
Car fitting shops 5
Churches 5
Traditional Authorities
Traditional Elder of Dakwadwom
1 Interviews
Traditional Elder of Ahensan
1
Traditional Elder of Aboabo
1
Governmental and non-Governmental organisations
KMA, HSD, TCPD, NADMO, Friends of Rivers & Waterbodies
5 Interviews
3.2.1.2 Traditional leaders, governmental and non-governmental agencies Each suburb of Kumasi usually has a chief or traditional leader/elder that oversees to
traditional issues in his/her jurisdiction. The traditional leaders of Aboabo, Dakwadwom and
Ahensan were identified and interviewed on traditional wetland management, land tenure,
landuse planning and future of the wetland. Interview sessions were also held with the listed
governmental and non-governmental organisations. Information on research, laws and
policies, and activities on wetlands in Kumasi was sought.
48
3.2.2 Data Analysis Various univariate analyses were used to assess the socio-economic forces that drive wetland
ecosystem and to indicate the degree to which socioeconomic, demographic and
environmental variables contribute to wetland alteration in Kumasi. The results are presented
in charts, graphs and tables.
3.3 RESULTS
3.3.1 The Physical Characteristics of Kumasi
3.3.1.1 Location, history, demography and administration of Kumasi Kumasi is the second largest city in Ghana and the capital of the Ashanti Region. It lies within
latitudes 6°38' and 6°45' north and longitudes 1°41' and 1°32' west on a landscape between
250 and 350 m above sea level. Kumasi used to be known as the Garden City of Africa. This
was because, during the colonial era, planning interventions in Kumasi were in the form of
establishing green belts and recreational parks within the layouts of residential areas. Due to
the undulating topography and numerous streams that transect Kumasi, the green belts and
recreational parks were invariably situated along the major stream channels. The green belts
idea was borrowed from various ‘garden city’ plans popular in England. They were seen as
both sanitary measures and as a way of separating residential areas especially the European,
from non-European zones. The provision of a green belt of about 300 m from buildings
surrounding residential areas was designed to protect Europeans residing in these areas from
mosquito borne diseases. After independence, these green belts were designated as
recreational space and named ‘Nature Reserves’ or ‘Parks’ on zoning maps (Schmidt, 2005;
KMA, 2006). Today, this garden city status is long lost and these green belts are largely either
non-existent, their borders slowly being infringed upon for urban infrastructure and housing,
subsistence agriculture or are used as dumping grounds (Brook & Dávila, 2000). The suburbs
e.g. Dakwadwom, Ahensan, Aboabo and Atonsu situated in or close to these ‘vacant’ land
areas are frequently under floods and therefore the subject of this research.
The Kumasi District as delineated in Figure 3.1 is metropolitan because it has a population
over 250,000 (Ghana Statistical Service, 2005). The Kumasi Metropolitan Assembly (KMA)
is made up of the following Sub-Metropolitan areas: Asawase, Asokwa, Bantama, Kwadaso,
49
Figure 3.1. Map of Ghana with an insert showing limits of the Kumasi Metropolitan Assembly and the study sites [sites are labelled in letters: Atonsu Sawmill (A), High school junction (B), FRNR farms (C), KNUST Police Station (D), Family Chapel (E), Spetinpom (F), Golden Tulip Hotel (G), Kaase Guinness (H), Bekwai roundabout (J) and Dakwadwom (K)]
50
Manhyia, Nhyiaeso, Oforikrom, Old Tafo, Suame and Subin. There is the Metropolitan
Planning Board which integrates the development planning and management of the
Metropolis; monitors and evaluates development planning and management; integrates the
development planning proposals from the sub-metropolitan district councils and advise the
authority thereon. The KMA is bounded by the Bosomtwe, Ejisu-Juaben, Kwabre East,
Afigya-Kwabre, Atwima-Kwanwoma and Atwima-Nwabiagya Districts.
The urban population of the Ashanti Region (which is 51.3 %) is only second to the Greater
Accra Region (87.7 %). The Kumasi Metropolis accounts for about a third of the region’s
population. The population of Kumasi grew slowly from about 3,000 in 1901 to about
180,000 in 1960 (Figure 3.2). Since then, there has been a relatively rapid growth of Kumasi
exceeding a million in 2000 with a current growth rate of 5.9 % and a density of 5,319
individuals/km2 (Ghana Statistical Service, 2002). Between 1984 and 2000, the population
had increased over 200 %. Due to its fast physical and demographic growth, Kumasi now
extends beyond the administrative boundaries of the KMA into the neighbouring districts
(KMA, 2006).
year
1900 1920 1940 1960 1980 2000
popu
latio
n
0.0
2.0e+5
4.0e+5
6.0e+5
8.0e+5
1.0e+6
1.2e+6
1.4e+6
Figure 3.2. Population growth trajectory of the city of Kumasi (Ghana Statistical Service, 2005)
51
3.3.1.2 Climate of Kumasi The climate of Kumasi is tropical, of the wet sub-equatorial type, and strongly influenced by
the tropical continental and tropical maritime air masses. The migration of the Inter-Tropical
Convergence Zone (ITCZ) determines the seasons. Rainfall is weakly bi-modal. The major
rainfall period is between May and June and the minor rainfall period is between September
and October. The dry north-east trade winds (Harmattan) reach Kumasi around mid-
November to early December. Relative humidity on a normal day, in Kumasi, ranges from a
maximum of 100 % at 0900 GMT to 60 % at 1500 GMT. On very dry days it ranges from 40
to 84 % and 85 to 100 % on very wet days. The average minimum and maximum
temperatures in Kumasi are about 21.5 °C and 30.7 °C respectively.
3.3.1.3 Hydrology of Kumasi The Metropolis is located within the Pra basin which is divided into five sub-basins by a
series of ridges running generally in a north-south direction. These sub-basins are Kwadaso,
Subin, Aboabo, Sisai and the Wiwi. The Suatem River flows through North Suntreso and
joins the Kwadaso River at Dakwadwom to form Daban River which flows to Kaase. The
Subin River flows from the Kumasi Zoo also to Kaase. The Wiwi River flows from Nsenie
and merges into the Sisai River at Atonsu. The Sisai, Subin and Daban Rivers finally join the
Oda River, a tributary of the Pra near Asago, south of Kumasi. In the north-western sector of
the Metropolis are several small tributaries of the Owabi River. The Metropolis is therefore
drained by a relatively dense network of rivers whose natural drainage runs generally from
north to south, exhibiting dendritic patterns.
However, estate developments, agricultural encroachment and indiscriminate waste disposal
in the rivers have impacted negatively on the drainage systems and have consequently brought
some of these water bodies to the brink of extinction and increased the incidence and spread
of floods and floodwaters. Some portions of these rivers have also been converted to storm
drains e.g. the portion of the Aboabo River from the Airport roundabout to the High School
Junction. For those that are still flowing, pollution is a serious problem.
3.3.1.4 Landuse and vegetation of Kumasi The Kumasi Metropolis falls within the moist semi-deciduous South-East Ecological Zone.
About 80 % of the total land coverage of the Metropolitan area is planned (KMA, 2006). The
major land uses that make up the Metropolis are residential, industrial, commercial,
educational, civic and culture, transportation and open spaces. Among these land uses, the
predominant ones are residential, commercial, educational and industrial. The residential
52
areas take up to 44 % of the total land area in Kumasi. About 29 % is taken up by the different
land uses such as educational, civic and culture, transportation and open spaces.
Patches of vegetation reserves within the Metropolis house the Kumasi Zoological Gardens
and the KNUST Botanical Gardens. Others are the Otumfuo Children’s Park at Dakwadwom,
Kumasi Children’s Park at Amakom and the Kumasi Golf Course at Nhyiaeso. Aside these,
there are other patches of vegetation cover scattered over peri-urban areas of the Metropolis
e.g. Atasomanso, Breman and Kagyase and Owabi. Predominant local trees are Ceiba,
Triplochlon and Celtis. Due to urban sprawl, most trees have been cut to make way for
buildings, roads and other infrastructure. All lands adjacent to the main rivers have been
declared by TCPD as green belts. These green belts are meant to serve as natural flood plains
of the river but encroachment has significantly reduced their flood storage capacity. Common
vegetation in these wetland areas are shrubs, grasses and food crops and vegetables like
plantain, sugar cane, palm trees, okro, carrot, cabbage etc. associated with urban agriculture.
3.3.1.5 Relief, geology and soils of Kumasi The Metropolis is undulating and lies within the plateau of the south-west physical region
which ranges from 250-300 m above sea levels. The area is underlain with precambium rock.
There are six detailed soil types in the metropolis but the predominant soil type of the
metropolis is forest ochrosol which dominates the entire region. The soil within the basins is
silty clay loam which is moderately slow to slowly permeable resulting in fairly high runoff
rates. This rich soil type makes it possible for foodstuff to be grown in the Metropolis and its
periphery.
3.3.2 Socio-economic Characteristics of Wetland Communities in Kumasi The results of various interviews, focus group discussions with various stakeholders and the
responses of 128 residents of various wetland associated communities are represented in this
section. The specific suburbs being studied are Aboabo, Spetinpom, Atonsu, Ahensan,
Dakwadwom and Kwadaso Estates. Large portions of these suburbs are informal or slum
settlements with haphazardly arranged houses built from wood or block. There is little or no
drainage network. Most houses directly release their domestic waste water through small
channels to the open which finds its way into surrounding streams. Most of the lands used for
these houses are designated as “natural areas” according to the landuse plan of the city.
However, the land owners sell out small portions of these natural areas for various uses
leading to a gradual habitation of such zones. Alleys are very narrow or virtually non-existent
because of encroachments and erection of illegal structures along the alleys.
53
These communities also have high population densities with very little social infrastructure.
Local entrepreneurs take advantage of the dearth in services to provide substandard facilities
to these already economically depraved community. There are several private primary schools
and churches mostly housed in wooden structures. Drug and chemical stores, kiosks and
artisanal shops abound in these suburbs. Also, in these wetland areas, there are no culverts or
bridges linking communities on either side of the water channel. Wooden foot bridges are
constructed across the streams and rivers through local efforts. There is no thoroughfare in
most areas so vehicular movement in such communities is limited.
Figure 3.3 shows the occupational distribution by gender and location of the respondents
considered in this study. Although this study did not seek to investigate gender distribution in
these suburbs, majority of respondents (62 %) were male. Respondents who were porters or
involved in food processing were all female whilst trading, farming, artisanal works and
formal sector employment had both sexes involved. Trading (35 %) and artisanal work (28 %)
form the major occupations of these respondents. The traders are involved in petty trading like
running kiosks, petty and buying and selling of various second-hand goods in the city.
Majority of these traders either do not own the businesses or have ownership with a capital
base less than $100. Most of the petty traders live in Aboabo. The artisans include masons,
plumbers, carpenters, shoemakers, auto mechanics, tailors and hairdressers. Most of these
artisans live in Kwadaso Estates, Dakwadwom and Spetinpom. The porters were only in
Aboabo, Ahensan and Spetinpom and were all immigrants who have been in the metropolis
for less than 10 years.
Various types of houses were identified within 100 m from the water channel (Figure 3.4).
These were permanent block structures in the form of multi-family residential facilities
commonly called compound houses, single family self-contained structures (detached or
semi-detached), L-shaped detached or single room structures and wooden structures. The
wooden structures were found in Aboabo, Ahensan, Atonsu and Dakwadwom. Occupants
were all less than 10 years in these facilities. When the economic conditions of these residents
improve, most of them transform the wooden structures to more permanent block structures.
The predominant housing types for respondents from Aboabo are compound, wooden or L-
shaped detached houses. The houses in Aboabo unlike those of Kwadaso Estates are mostly
multifamily permanent compound structures with relatively large numbers of residents even at
the household level. Those in Kwadaso Estates are mostly single family accommodations.
54
Figure 3.3. The occupation of respondents from flood prone suburbs of Kumasi
55
Figure 3.4. Residential types and homeownership of respondents in the different
suburbs of Kumasi
Majority of the respondents (62 %) either own the houses or are part of the extended family
and do not pay rent in the houses they lived in. The largest proportion of home owners is
those in wooden and permanent single room structures in Ahensan and Atonsu. Most of the
multifamily residential facilities like the compound, detached and semi-detached houses have
tenants who are completely separate households. There is also a relatively high tenant
turnover in these areas. Most people who did not know of the annual floods usually moved
out after one or two flood experiences. The relationship between length of stay and prevalence
of floods was assessed using the Pearson Correlation. There was no relationship between
number of years of stay in an area and presence or absence of floods (r = -0.135). Access to
land for construction of houses by wetland residents is very varied in the different suburbs
(Figure 3.5). The commonest forms of access to land for building a house were family
inheritance, direct purchase from the chief or other landowner or squattering. Respondents in
Aboabo were either squatters or living in rented houses. Most of the respondents from Atonsu
and Dakwadwom inherited the land or the houses they lived in.
56
Various reasons have been ascribed for use of wetland areas for building houses (Figure 3.6).
The commonest reasons were that wetland areas are cheap, close to other parts of the city and
are “no man’s land”. These are usually areas marked out in the landuse plans as natural areas
and not to be developed. However, the landowners later bypass the city authorities and sell
such areas at very low prices. The city authorities do not also actively protect or use such
areas therefore creating the impression that it is a no man’s land. For these reasons, the
wetland areas in Kumasi quickly develop into informal settlements harbouring squatters and
slum communities.
After staying in these environments for a while some residents relocate. Respondents have
different motivations to move out of their current home (Figure 3.7). Some respondents in
Aboabo and Ahensan love living in those suburbs and are not making any efforts to move out.
In all the suburbs, respondents over 75 % of the time, completely agree to move out if given
money or an alternative shelter elsewhere. Forcefully moving people out of these suburbs is
not popular. For all the suburbs, the flood water level is not a first priority to cause them to
move out.
57
Figu
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.5. R
espo
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d fo
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uctio
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ses
in th
e di
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asi
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58
Figu
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.6. R
easo
ns fo
r cho
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of w
etla
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for
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the
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economic activities"no mans's land"
close to amenitiesclose to familyin/close to city
it is cheapuse stream water
economic activities"no mans's land"
close to amenitiesclose to familyin/close to city
Aboa
boAh
ensa
nSp
etin
pom
Aton
suDa
kwad
wom
Kwad
aso
Esta
tes
Proportion of respondents in agreement with reason (%)
Subu
rbs
and
reas
ons
for c
hoice
of s
ubur
bs
59
Figu
re 3
.7. F
acto
rs o
r in
stru
men
ts t
hat w
ill m
otiv
ate
resi
dent
s of
the
vario
us f
lood
pro
ne c
omm
uniti
es t
o re
loca
te
0102030405060708090100
do nothing. I love it heregiven money to move
new land/plot elsewherewhen I make some money
when the floods get too muchwhen forced
I am already preparing to moveif provided an alternative shelter
do nothing. I love it heregiven money to move
new land/plot elsewherewhen I make some money
when the floods get too muchwhen forced
I am already preparing to moveif provided an alternative shelter
do nothing. I love it heregiven money to move
new land/plot elsewherewhen I make some money
when the floods get too muchwhen forced
I am already preparing to moveif provided an alternative shelter
do nothing. I love it heregiven money to move
new land/plot elsewherewhen I make some money
when the floods get too muchwhen forced
I am already preparing to moveif provided an alternative shelter
do nothing. I love it heregiven money to move
new land/plot elsewherewhen I make some money
when the floods get too muchwhen forced
I am already preparing to moveif provided an alternative shelter
do nothing. I love it heregiven money to move
new land/plot elsewherewhen I make some money
when the floods get too muchwhen forced
I am already preparing to moveif provided an alternative shelter
Aboa
boAh
ensa
nSp
etin
pom
Aton
suDa
kwad
wom
Kwad
aso
Esta
tes
proportion of respondents in agreement with reason (%)
subu
rbs
and
reas
ons
to m
ove
out
60
3.3.3 Community Efforts at Wetland Management in Kumasi Wetlands within the Kumasi Metropolis have been used for various purposes (Figure 3.8).
The commonest wetland uses are urban agriculture, grazing grounds, housing and as waste
disposal sites. In Aboabo, Atonsu, Dakwadwom and Kwadaso Estates, waste disposal was
commonest wetland use. The wetlands in Ahensan and Spetinpom were mainly used as
grazing grounds and for housing respectively. The only wetland area with significant
recreational use was that at Dakwadwom. Here, Friends of Rivers and Waterbodies had an
active educational programme on wetlands through the establishment of the Otumfuo
Children’s Park.
Even though these wetlands are not used sustainably, the associated communities believed
that they should be protected (Figure 3.9). Majority of respondents (59 %) were in favour of
protecting the wetland area. Only a few respondents (3 %) were indifferent to their protection.
There are various local laws, customs and beliefs that help in the protection and management
of wetlands. These are however, not being adhered to and respondents believe several factors
are responsible for this (Figure 3.10). Respondents in Aboabo and Ahensan did not believe
that political influence contributed to communities not managing the wetlands. Rather, it is
the lack of political will by stakeholders to protect the wetlands. In Spetinpom and Kwadaso
Estates, respondents were of the view that corruption and the lack of political will to enforce
the laws were the two important factors debilitating wetland management in Kumasi. In all
the suburbs, poverty was also viewed as a very strong factor (more than 50 % yes) accounting
for wetlands not being protected.
61
Figure 3.8. The predominant uses of wetlands in the various suburbs of Kumasi
Figure 3.9. Perception of wetland protection in Kumasi
62
Figu
re 3
.10.
Rea
sons
for t
he c
ontin
ual
dest
ruct
ion
of w
etla
nds
in t
he v
ario
us s
ubur
bs o
f Kum
asi
0102030405060708090100
political influence
changes in government
corruptionpoverty
lack of political will
cost of demolitionloss of cultural values
political influence
changes in governmentcorruption
poverty
lack of political willcost of demolition
loss of cultural values
political influencechanges in government
corruption
povertylack of political will
cost of demolition
loss of cultural valuespolitical influence
changes in government
corruptionpoverty
lack of political will
cost of demolitionloss of cultural values
political influence
changes in governmentcorruption
poverty
lack of political willcost of demolition
loss of cultural values
political influencechanges in government
corruption
povertylack of political will
cost of demolition
loss of cultural values
Aboa
boAh
ensa
nSp
etin
pom
Aton
suDa
kwad
wom
Kwad
aso
Esta
tes
Proportion of respondents in agreement with reason (%)
Subu
rbs
and
reas
ons
for c
ontin
ual d
estr
uctio
n of
wet
land
s
63
3.4 DISCUSSION Similar to the situation in most developing countries, urbanisation of Kumasi is characterised
by very high population growth and construction, merging up the city with the peri-urban
regions. This fast urban growth is however not matched with growth in infrastructure and
services, not even in the planned suburbs. The resource poor suburbs also harbour mostly
rural-urban migrants and the poorest of the population. In recent times, Kumasi has received
large influxes of rural youths from mostly northern Ghana to find menial jobs. A majority of
these low skilled migrants end up working in the informal sector as porters, petty traders,
seasonal labourers (Yeboah & Appiah-Yeboah, 2009). The porters and farmers identified in
this study are likely to be people of this origin. After a little training, most of these immigrants
pick up artisanal jobs like carpentry, masonry, barbers/hairdressers, tailoring/dressmaking etc.
Their economic conditions usually determine their choice of urban space and or housing.
The suburbs considered in this tudy have large immigrant populations and thus, not only
provide important basket of social networks for first time immigrants, but also as political
hotspots. For these reasons, residents from such suburbs have been able to vehemently resist
all efforts by the KMA to demolish their illegal structures. The relatively high population
density and communal spirit of these residents increase their collective bargaining power. In
these suburbs, the only ‘free’ areas are often the wetland areas. The immigrants therefore find
these areas convenient for erecting temporal dormitories with active assistance from old
residents. It is however, surprising that most people will continue to live in such structures or
their improved forms in the same locations after several years of living there and an improved
economic standing.
It is important to state that, majority of the wetland associated inhabitants are natives. These
natives continue to live in such neighbourhoods due to the strong historical, social and
economic ties developed over the years. For an immigrant also, early social networks and the
cost of accommodation might be determinants of their choice of such locations. It is not
surprising that these immigrants first live in makeshift shelters made of wood and may later
move to more permanent single room block structures. Aboabo, Ahensan and Dakwadwom
might be suburbs providing these initial favourable conditions to attract the high immigrant
squatter population. Ownership of such structures might be through a form of transfer of title
or a rental arrangement with the new tenant whilst the economically better off tenant moves
out. Due to the high the demand for these neighbourhoods by immigrants, landowners and
chiefs also then take advantage of these illegalities to lease out or sell the plots to these
64
tenants giving them title to the land. For any given environmental challenge, it is expected
that there is a tipping point at which an individual finds that particular environment unsuitable
for habitation. These suburbs however, are among the densest in Kumasi. The pull factors
motivating people to move in and to continue staying there are stronger than the dissuading
environmental pressures in these neighbourhoods.
According to the theory of the EKC, increased incomes or improved economic conditions
would lead to improvement in the environment or in this case, a desire for better housing
environment away from the annual floods. The findings of this study do not support this
theory either. Rather, improved economic conditions led to improved housing facilities in the
same environment. For example, wooden structures were converted to more permanent block
structures. This is still true even when flood water levels are increasing. A model is proposed
here to describe the relationship between the EKC and the decision to move or stay in these
flood prone suburbs in Kumasi (Figure 3.11). It shows that the initial trajectory of the EKC
curve realistically captures decision-making by poor resident in a flood prone suburb. In
beginning, the victim is only interested in making ends meet. However, at the critical income
threshold, the person starts to invest in improving his/her living space. The trajectory
therefore does not lead to a condition of zero environmental degradation, as would be
expected, but rather a tolerable level through participation in communal efforts like building
of foot bridges, network of walkways etc. In another dimension, this new poor resident
usually has almost 100 % tolerance to the floods. Such a person will only move when forced.
With increasing income, different motivations and needs come to the fore. Consequently,
flood tolerance never drops to 0 % in these communities. There are a few who are ready to
move out ‘when the water level increases’. But such a subjective target is never met and these
people continue to live there. The decision to move or stay in these suburbs is therefore an
abrupt one independent of the environmental and economic conditions.
Homeownership in Ghana is a cultural and societal requirement or an expectation as one
grows older; as having your house is a sign of success. This is aggravated by a national
housing deficit and a very poor mortgage system. Most people therefore acquire the land and
build their houses over several years. Land prices are very high in urban areas and the prices
reflect the quality of the potential houses and services and infrastructure availability in the
neighbourhood. Poor people therefore go for the cheapest available lands that are usually
wetland areas and therefore not part of the official city layout scheme. It is these cheap
65
Figure 3.11. A proposed model to describe the decision to move or stay in the flood prone suburbs of Kumasi
66
unapproved houses built in wetland areas that bear the full brunt of the annual floods. From
the list of pressures or initiatives in the model above, these flood prone inhabitants will rather be
moved more by external pressure than their own volition. The will to continue to stay or the
decreased personal initiative to move out of the wetland may be aggravated by the acquisition of
property rights through the purchase of such lands. According to Lant (1994), the core of the
conflict in wetland destruction is a question of property rights. However, does the owner of
the wetland have the right to alter that wetland for his or her own purposes? Does the public
have the right to the ecological functions and values of a private wetland? Do individual rights
acquired through the purchase of wetlands override national and local government laws? Does
the owner of a wetland have the right to alter it for private purposes at the public expense?
How can the externalities from such alterations be internalised? When can such an individual
right be revoked for the public good?
In demarcating the wetlands as natural areas, it is unfortunate that the KMA (through the
TCPD) does not make any effort at assigning and enforcing property rights to such areas. If
the city wishes to acquire property rights to such areas, it will have to pay a compensation (buy
the rights) to the landowner. By delineating these wetland areas as ‘Nature Reserves’ or ‘Parks’,
the TCPD gives de facto property rights to the public. This will imply that, the landowner has no
right to sell such lands. The land tenure system in Ghana, however, does not recognise such
de facto ownership. The proposals by Panayotou (1997) and Eppinka et al (2004) for more
secured property rights will not work in the Ghanaian context where wetlands delineated for
public good or environmental protection is not paid for. Most of the lands are privately owned
and therefore the city (public) does not automatically obtain rights to the wetlands because it
has been delineated as such. Whilst it may be expensive for the government to pay compensation
to designate these wetland areas as public lands, it is also widely known that government has
not been good managing existing public lands. Therefore, distribution of benefits and costs of
maintaining wetlands as advocated by Magnani (2001) may be a better option to management of
such spaces. The Otumfuo Children’s Park in Dakwadwom is an example which could be
replicated in other wetland areas. Names, uses and attributes should be assigned to the
wetlands and benefits and costs accrued be shared between the landowners and city
authorities for management of the wetland area. Hereafter, better enforcement and effective
environmental regulations will then be needed to maintain the wetland as such.
67
4 FLOODS AND ENVIRONMENTAL MANAGEMENT IN KUMASI, GHANA
4.1 INTRODUCTION Ghana is very much in tune with global environmental concerns. Over the years, it has signed
several conventions and protocols (see Table 4.1) in an effort to strengthen international
cooperation and linkages, and make the environment a better place for its citizenry. Also,
Ghana’s Constitution, Chapter six, Article 41 (k) enjoins the citizens to protect and safeguard
the environment (Government of Ghana, 1992). Apart from the articles in the Constitution,
there are specific laws and policies on the environment. Some of those that are of relevance to
wetlands include the Beaches Obstructions Act (1897), Rivers Act (1903), Town and Country
Planning Act (1945), Land Planning and Soil Conservation Act (1953), Volta River
Development Act (1961), Land Registry Act (1962), Lands Miscellaneous Provision Act
(1963), Ghana Water and Sewerage Corporation Act 310 (1965), Abandoned Property
(Disposal) Act (1974), Irrigation Development Authority Act (1977), Mercury Act (1989),
Small Scale Gold Mining Act (1989), Control and Prevention of Bush Fires Act (1990),
Towns Act (1992), Environmental Protection Agency Act 490 (1994), Lands Commission Act
483 (1994), National Development Planning Commission Act 479 (1994), Local Government
Act 462 (1994), Water Resources Commission Act 522 (1996), Environmental Assessment
Regulations LI 1652 (1999), Wetlands Management (RAMSAR sites) Regulations (1999),
Fisheries Act (2002) and Ghana Meteorological Agency Act (2004).
These laws and regulations have historically been applied to various contexts and use of
wetlands. However, the Environmental Protection Agency Act 490 (1994), Wetlands
Management Regulations (1999) and the Buffer Zone Policy are currently the most important
and of direct use in the protection and management of wetlands in Ghana. These laws and
policies were enacted based on the current Constitution of Ghana and have various institutions
mandated to regulate, direct and implement them. Ghana may be very sufficient in terms of
laws and policies. However, the human resources and institutional framework under which
the laws and policies are being implemented are equally important. This chapter therefore
assesses the laws and policies that apply to the environment in Ghana. Particular emphasis
will be placed on wetland management and floods and the stakeholders and institutional
framework under which they operate.
68
Table 4.1. Ghana’s international commitments to the environment
Convention/Protocol Date of Accession/ Ratification
� Convention on the Continental Shelf, Geneva, 1958 29 April, 1958
� Convention on Fishing and Conservation of the Living Resources of the Seas, Geneva, 1958
29 April,1958
� African Convention on the Conservation of Nature and Natural Resources, 1969
17 May, 1969
� Convention on International Trade in Endangered Species of Wild Fauna and Flora, Washington, 1973
14 November, 1975/ 12 February, 1976
� United Nations Convention on the Law of the Sea, Montego Bay, 1982.
10 December, 1982/ 7 June, 1983
� Convention on the Conservation of Migratory Species of Wild Animals, Bonn, 1979
19 January, 1988
� Convention on Wetlands of International Importance Especially as Waterfowl Habitat, Ramsar, 1971
22 February, 1988
� Convention for Cooperation in the Protection and Development of the Marine and Coastal Environment of the West and Central African Region, Abidjan,1981
20 July, 1989
� Protocol Concerning Cooperation in Combating Pollution in Cases of Emergency, Abidjan, 1981
20 July, 1989
� Vienna Convention for the Protection of the Ozone Layer, Vienna, 1985
24 July, 1989
� Montreal Protocol on Substances that Deplete the Ozone Layer, Montreal, 1987
24 July, 1989
� London Amendment to the Montreal Protocol on Substances that Deplete the Ozone Layer, London, 1990
24 July, 1992
� Convention on Biological Diversity, Rio de Janeiro, 1992 29 August, 1994
� United Nations Framework Convention on Climate Change, New York, 1992
6 September, 1994
� United Nations Convention to Combat Desertification in those Countries Experiencing Serious Drought and / or Desertification, Particularly in Africa, Paris, 1994
27 December, 1996
� Copenhagen Amendment to the Montreal Amendment on Substances that Deplete the Ozone Layer, Copenhagen, 1992
30 September, 2000
� Stockholm Convention on Persistent Organic Pollutants 30 May, 2003
� Montreal Amendment to the Montreal Protocol 8 August, 2005
� Beijing Amendment to the Montreal Protocol 8 August, 2005
69
4.2 ENVIRONMENTAL MANAGEMENT AND THE NATIONAL ENVIRONMENTAL ACTION PLAN
Traditionally, Ghana’s environmental challenges have been the depletion of her resources
through deforestation, desertification and soil degradation (Okley, 2004). Recently,
urbanisation and industrialisation have also come to the fore (UN-HABITAT, 2009). In
March 1988, the Government of Ghana initiated a major effort to manage these environmental
challenges. The exercise culminated in the preparation of a strategy and a National
Environmental Action Plan (NEAP), to define a set of policy actions, related investments, and
institutional strengthening activities to make Ghana's development strategy more
environmentally sustainable and to improve the surroundings, living conditions and the
quality of life for all generations of Ghanaians. The NEAP provided a framework for
interventions deemed necessary to safeguard the environment. For areas related to wetlands,
the policy actions included the establishment of the proposed Water Resources Commission;
adoption of the proposed Water Law; adoption of policy framework for extraction of water
for the different uses; integrated planning of river basins and the control of waste discharge
into water bodies; and establish watershed protection areas. Institutions and detailed working
documents to these objectives have all been produced.
The NEAP also includes a National Environmental Policy to provide the broad framework for
the implementation of the Action Plan. The policy aims at ensuring sound management of
resources and the environment and to avoid any exploitation of these resources in a manner
that might cause irreparable damage to the environment. The policy identified among others,
the following issues to be dealt with: population pressure, land ownership and tenure, landuse
planning, agricultural land use, water resources assessment, problems of water management,
water pollution, watershed protection, urbanisation and urban degradation.
4.2.1 The Environmental Protection Agency The Agency started as the Environmental Protection Council (EPC) in 1974 and was
responsible for all activities and efforts aimed at protecting and improving the quality of the
environment. The EPC functioned as an advisory body until 30th December 1994 when it was
transformed into an Agency by the Environmental Protection Agency (EPA) Act 490. By this
Act, the EPA became a corporate body mandated to implement the NEAP with powers to sue
and be sued. The EPA by law is therefore the leading public body for protecting and
improving the environment in Ghana. The objectives of the EPA, among others of interest to
this research, are to:
70
� mainstream the environment into the development process at the national, regional,
district and community levels;
� ensure that the implementation of environmental policy and planning are integrated
and consistent with the country’s desire for effective, long-term maintenance of
environmental quality; and
� guide development to prevent, reduce, and as far as possible, eliminate pollution and
actions that lower the quality of life.
It performs these with the following guiding principles, inter alios, partnerships, pollution
prevention and control, ecosystem management, environmental justice, environmental
education, compliance and enforcement. The EPA has power to issue environmental permits
and pollution abatement notices in order to control waste discharges and emissions and to
prevent or reduce noise pollution. It is supposed to provide standards and guidelines in
relation to air, water and other forms of environmental pollution. It also has authority to
ensure that developers of commercial entities comply with environmental impact assessments.
4.2.2 Water Resources Commission The major laws that guide the regulation and management of water resources in Ghana are
contained in the Water Resources Commission Act (Act 522 of 1996) and the Water Use
Regulations (L.I. 1692 of 2001). This Legislative Instrument categorises and prioritises water
uses in Ghana and spells out procedure for acquisition of water use permits. Water, like all
other natural resources in Ghana, falls within the provisions of Article 269 of Ghana's
Constitution, and is therefore vested in the President on behalf of and in trust for the people of
Ghana. There is no private ownership of water in Ghana, but that the President, or anyone so
authorised by the President, may grant rights for water use. The Water Resources Commission
was set up and given the powers by the President for the regulation and management of water
resources and for the coordination of policies in relation to them (Government of Ghana,
1996). The Commission is the focal point in fostering coordination and collaboration among
the various actors involved in the water resources sector.
The Commission’s management of water resources is underpinned by the National Water
Policy (Ministry of Water Resources, Works and Housing, 2007). The Policy recognises the
perceived abundance of water resources in Ghana. However, the production and utilisation of
water resources for consumptive and non-consumptive uses is not at optimal level and
therefore calls for an efficient and effective management of available water resources. The
Policy is based on principles of Integrated Water Resources Management (IWRM). In
71
particular, it encourages the sustainable exploitation, utilisation and management of water
resources to ensure full socio-economic benefits to the present and future generations, while
maintaining biodiversity and the quality of the environment.
Wetland ecosystems in Ghana constitute about 10 % of the country’s total land surface and
are grouped as marine/coastal, inland and man-made. Recognising the scale of distribution
and importance of wetlands, the Ministry of Lands and Forestry (1999b) integrated wetland
issues into the National Landuse Policy. The Policy recognises wetlands as environmental
conservation areas and precludes the following practices: physical draining of wetland water,
draining of streams and water courses feeding the wetlands, human settlements and their
related infrastructural developments in wetlands, disposal of solid waste and effluents in
wetlands and mining in wetlands. The Government of Ghana sees its role in wetlands
management as best performed through partnership and co-operation with local people,
governmental and non-governmental organisations, and the private sector.
Ghana became a signatory to the Ramsar Convention in 1988. A major obligation of
signatories to the Convention is the implementation of the principle of ‘wise use’ of their
wetland resources. Therefore, in consultation with stake-holders, the “Managing Ghana’s
Wetlands: A National Wetlands Conservation Strategy” document was prepared to promote
the participation of the local communities and other stakeholders in the sound management
and sustainable utilisation of Ghana’s wetlands and their resources (Ministry of Lands and
Forestry, 1999a). The document provides a national definition and distribution of wetlands, a
management strategy for wetlands and a policy framework for incorporating wetlands
management into the day-to-day activities of Government, organisations, traditional
authorities, communities and individuals. Accordingly, the Government of Ghana has overall
responsibility for perpetuating wetland areas, and also to administer a range of social,
economic and environmental programmes which impact on wetland management throughout
the country whilst local communities directly manage the "wise use" of wetland resources in
their localities.
Also, there is the Buffer Zone Policy for the protection, regeneration and maintenance of the
native or established vegetation in riparian buffer zones in Ghana (Water Resources
Commission, 2008). This policy is a further attempt at managing Ghana’s river basins in
accordance with the IWRM approach and to harmonize traditional and existing public
institutional standards on buffer zones in Ghana. The Policy adopts a 3-tier buffer zone as the
norm for effective erosion control and halting of water quality degradation caused by
72
nutrients, animal or human wastes, sediments and runoff. It however, gives provision for
variation of this optimum buffer “design” from the prescribed values to accommodate local
requirements. The buffer zones are also to be permanently reserved by legislative instruments
with the consent of local authorities and incorporated into the local landuse plans. Local
authorities must take steps to minimize the risk of conversion of buffer zones to uses
incompatible with sustainability of their functions and exclude exploitation or occupation
inimical to the purposes of designation of the areas as buffer zones. Government is also to
ensure that all designated riparian buffer zones along rivers, streams, and around lakes,
reservoirs or other surface water bodies are adequately vegetated and sustainably managed to
restore and maintain their ecological integrity. This is expected to provide socio-economic
benefits to local communities and in fulfilment of Ghana’s overall water, environment and
landuse policies, the MDGs and the Growth and Poverty Reduction Strategy (National
Development Planning Commission, 2005).
4.2.3 Lands Commission Ghana has basically two types of land ownership: state and private. State lands are lands
compulsorily acquired by the government through the invocation of the appropriate
legislation, vested in the President and held in trust by the State for the entire people of
Ghana. On the other hand, private lands in most parts of the country have communal, family
or individual ownership. Stool or skin lands are a feature of communal land ownership in
most Akan traditional groups in southern Ghana and in most traditional groups in northern
Ghana respectively. However, scattered all over Ghana are a number of traditional groups,
which do not recognize a stool or skin as symbolising private communal land ownership. Also
sandwiched between the public and private lands are vested lands, which are a form of split
ownership between the state and the traditional owners. Fundamentally, land ownership is
based on absolute allodial or permanent title from which all other lesser titles to, interests in,
or right over land derive. Normally, the allodial title is vested in a stool, skin, clan, family,
and in some cases, individuals.
Because of this diversity of land tenure regimes, the Lands Commission was established
under article 258 of the 1992 Constitution and came into being through the Lands
Commission Act (Act 483 and 767 of 1994 and 2008 respectively). The Commission is an
integration of the various land agencies for the efficient management of public lands and other
lands, advise and facilitation of good land delivery system in the country. The Commission’s
work is being guided by the National Land Policy. The National Land Policy, District
73
Assemblies Act 462 and the National Development Planning Systems Act 480 enjoin District
Assemblies in conjunction with land owners and the Lands Commission to prepare planning
schemes for all land uses to facilitate dispositions of land for development. In making these
planning schemes, the policy states that wetlands are environmental conservation areas and
the following uses considered incompatible with their ecosystem maintenance and natural
productivity are strictly prohibited: physical draining of wetland waters, damming of streams
and water courses feeding the wetlands, human settlements and their related infrastructural
development in wetlands, disposal of solid waste and effluents in wetlands and mining in
wetlands.
4.2.4 Local Government and Environmental Management For the purposes of local government, Ghana is divided into districts (Government of Ghana,
1993). The Local Government Act (Act 462 of 1993) makes the District Assembly the highest
political authority in any district with deliberative, legislative and executive powers. Among
others, the district assembly is responsible for the development, improvement and
management of human settlements and the environment in the district. The assemblies are
empowered to enact the appropriate bye-laws for planning and management of resources in
their geographical area. In accordance with the NEAP, the responsible committee for
environmental issues at the local level is the District Environmental Management Committee
(DEMC) of the district assembly. The number and composition of this committee varies from
district to district. In general, the DEMCs are made up of about 15 members. These include
the regional programme officer of the EPA, five assembly members (one as chair), at least
two of whom should be women, two representatives of environmental NGOs, officers from
decentralised institutions like the Department of Parks and Gardens, TCPD, Department of
Agriculture, Forest Services Division, District Health Directorate, the District Education
Service, Ghana Water Company or Community Water and Sanitation Division and National
Council on Women and Development. The EPA's Regional Programme Officers and their
staff are expected to provide support and assist with training of DEMCs and to act as a
conduit for dissemination of information from EPA to the districts. The DEMC enforces
environmental standards and regulations set by the EPA and other national regulatory
agencies within its jurisdiction.
74
4.3 WETLANDS, FLOOD PREVENTION AND MANAGEMENT
4.3.1 Stakeholders’ Capacity for Managing Wetlands and Floods The following stakeholders were identified to be involved in wetlands and or flood
management in Kumasi: KMA, HSD, TCPD, NADMO, Assemblyman, Chiefs and NGOs
(Friends of Rivers and Waterbodies).
There were varied perceptions about the responsibilities of stakeholders for the management
of wetlands (Figure 4.1). The commonest stakeholders mentioned were NADMO and the
KMA, especially, in Atonsu and Dakwadwom. Also, at all the study suburbs, chiefs and land
owners were rated high in the management of floods and wetlands. In Ahensan, respondents
completely agreed that the chiefs and landowners were responsible for the wetlands. In
Spetinpom, all the institutions listed as being responsible for managing wetlands and floods
were ranked relatively high by community members.
Apart from the Assemblyman, the other stakeholders were given the opportunity to assess
each other on wetlands protection and management and flood prevention and management.
The outcome of these assessments is presented in Table 4.2. Among the different
stakeholders, NADMO and the KMA were considered the most financially resourced to
manage floods and wetlands. NADMO however lacked the technical expertise at local levels.
The chiefs also lacked the technical and coordinating capacity in wetlands protection and
management and flood prevention even though they were considered very much respected
and could sometimes mobilise the financial resources.
Figure 4.1. Assessment of stakeholders’ responsibility for the management of floods and wetlands in Kumasi
75
4.3.1.1 Kumasi Metropolitan Assembly (KMA)
According to the Local Government Act (Act 462 of 1993), the KMA is the local authority of
the metropolis. This study revealed that decentralised structures for environmental
management in Kumasi are well in place. Flooding issues had been incorporated in the
Medium Term Development Plans of the Assembly (spanning 2006-2009). According to the
Assembly, the floods are caused by residential dwellings and other structures built in
waterways, dumping of refuse in gutters and drains and the inability of existing culverts to
receive large volumes of water whenever there is a heavy downpour. Some mitigating
strategies such as drain constructions or enlargement of existing ones, desilting or dredging of
streams, clearing of waterways (demolition of obstructing structures) and public education
were being carried out. Several houses along waterways have therefore been marked for
demolition. This was an on-going exercise in all the flood prone suburbs like Aboabo,
Ahensan, Anloga, Asafo, Asokwa, Atonsu, Breman, Daban and Oforikrom. According to the
KMA, plans were also in place to curb further building on waterways through strict
enforcement of the building regulations.
Respondents from the communities had varying perceptions about the demolition exercises
carried out by the KMA (Figure 4.2). Almost 50 % of the respondents in Aboabo and
Ahensan had houses in their neighbourhood marked for demolition and virtually none in
Dakwadwom. On the contrary, whilst there is a general support by respondents for demolition
in the other suburbs, no respondent in Aboabo supported it. Most support for demolition of
houses on waterways came from Atonsu.
4.3.1.2 Town and Country Planning Department (TCPD) The TCPD is a government agency responsible for planning and management of the orderly
development of human settlements; providing planning services to public authorities and
private developers and provision of layout plans to guide orderly development in Ghana. It
formulates goals and standards relating to the use and development of land in areas of rapid
urban growth. This Department is present in the Metropolis as one of the decentralised
government institutions. In performing these functions, the TCPD plays a key role in
delineating and protecting wetlands and waterbodies and the prevention of floods in built up
areas.
Apart from Spetinpom and Kwadaso Estates where the TCPD is recognised as responsible for
floods and wetland management, all the other suburbs virtually did not know the TCPD.
76
4.3.1.3 National Disaster Management Organisation (NADMO) NADMO is responsible for the coordination of the management of disasters and similar
emergencies. It ensures that the country is prepared to prevent disasters and manage them well
when they occur. It does this through training, education and awareness creation, coordinating
the activities of various stakeholders in the management of disasters and rehabilitates persons
affected by disasters. NADMO is very well decentralised to regional and district offices. Both
Regional and Metropolitan offices of NADMO are found within Kumasi.
Among all the institutions, NADMO is the most popular with the respondents as being
responsible for floods and wetlands management. This is especially so in Atonsu and
Dakwadwom where respondents virtually assigned all floods and wetlands management
responsibilities to NADMO.
Table 4.2. Stakeholder capacity assessment on wetlands and flood prevention and management in Kumasi
Stakeholder Capacity Rating (increasing from left to right) Comment
1 2 3 4
KMA
Personnel X The KMA knows what to do and how to do it. What is not available are the finances and logistics to carry out their plans. The KMA has other priorities and only reacts in times of flood.
Technical/logistics X Financing X Coordination X
NADMO
Personnel X NADMO has a budget that is usually increased in times of emergency. The organisation is however very politicised and lacks the qualified technical personnel.
Technical/logistics X Financing X Coordination X
TCPD
Personnel X This organisation is well staffed in Kumasi. They however do not coordinate with other stakeholders in their landuse planning mandate.
Technical/logistics X Financing X Coordination X
HSD
Personnel X This is very much an obscure organisation in function and visibility in the KMA. They are relatively under-resourced and much marginalised.
Technical/logistics X Financing X Coordination X
Chiefs
Personnel X They are very important in landuse decisions in Kumasi. Sale of land is a very big source of finance for this institution. Their decisions lack technical backing from the various experts.
Technical/logistics X Financing X Coordination X
NGO (Friends of Rivers and
Waterbodies)
Personnel X Has the personnel and capacity to coordinate wetland management issues. They are well known and resented in some of the suburbs of the KMA
Technical/logistics X Financing X Coordination X
Total and general assessment 7 3 4 10
Generally, the Metropolis has the technical capacity but does not coordinate its flood and wetland management efforts with the little logistical and financial resources available.
77
Figure 4.2. Spatial distribution of houses marked for demolition and attitude towards demolition of houses in waterways by the Kumasi Metropolitan Assembly
78
4.3.1.4 Hydrological Services Department (HSD) The HSD is responsible for assessing the country’s water resources (quantity, quality and
distribution in time and space), the potential for water related development, and the ability to
supply actual and foreseeable demand. The HSD also assesses the environmental, economic
and social impacts of existing and proposed water resources management practices, projects
and the adoption of sound policies and strategies. Above all, they assess the impacts of other
non-water sector activities such as urbanisation, waste management, forest harvesting etc. on
water resources thereby providing security for people and property against water–related
hazards such as floods, storm surges and droughts.
Among respondents, this is the most unknown stakeholder for the management of floods and
wetlands. The HSD and its functions are not known in Aboabo, Atonsu and Dakwadwom.
Like the other institutions, it was only in Spetinpom that the HSD was known and considered,
more than 50 % of the time, responsible for floods and wetlands management.
4.3.1.5 Chiefs and Assemblymen Chiefs or the chieftaincy institution is a traditional leadership arrangement which is
guaranteed in the Constitution of Ghana. The Constitution also recognizes customary law as a
source of law in Ghana and explicitly states that the management of stool lands are to be in
accordance with the relevant customary laws and usage. Majority of the land of the
Metropolis is customary or stool lands and customary law vests the powers in the appropriate
stool (chief) to manage such lands on behalf of and in trust for their people.
The assemblymen on the other hand, are a product of the local government system
representing decentralised decision making bodies at the community level. Officially, they
represent the community in the KMA. In most communities, the assemblymen work very
closely with the chiefs as community leaders to coordinate community development activities
and relief efforts in emergency situations.
Apart from Atonsu and Dakwadwom, the roles of chiefs in wetland and flood management
are very much recognised by all the stakeholders. Respondents in Ahensan and Spetinpom,
almost 100 % of the time, think chiefs are responsible for the management wetlands and
floods. The Assemblyman was rated higher than the chief in solving flood issues and the
provision of relief. The rating of an assemblyman in any community depends on the
dynamism and efforts the person puts in solving community problems. The assemblyman and
the chief will usually be the first line of contact for person(s) or institution(s) coming to the
79
community or bringing assistance in times of flood. Similarly they collaborate and mobilise
communal labour for various flood interventions.
4.3.1.6 Non-governmental organisations (Friends of Rivers and Waterbodies) Several non-governmental organisations (NGO) have interest in water and watershed
management in Ghana. One local NGO that has risen to prominence in the Kumasi Metropolis
is the Friends of Rivers and Waterbodies. The Friends of Rivers and Waterbodies is an
amalgam of volunteer scientists, businessmen, economists, opinion leaders and other
professionals as well as students. Volunteers are mobilised and empowered to execute tasks in
consonance with traditional and scientific values, to provide water and protect waterbodies
from pollution, siltation and abuse. A playground in Dakwadwom called Otumfuo Children’s
Park, was established by the Friends of Rivers and Waterbodies on one side of the wetland.
The NGO has also undertaken several wetland related activities in the community.
Respondents from Dakwadwom therefore rated NGOs high for management of floods and
wetlands. All the other suburbs rated the NGOs relatively low.
4.4 DISCUSSION In spite of the long list of institutions and environmental laws, Ghana’s urban environment is
one of the worst in the sub region. The urban environmental issues described above are
serious and damning to Kumasi and Ghana as a whole. According to the FAO (1985) few
sewage treatment plants existed in Ghana. Since this publication, the situation has rather
become worst because of the increase in urbanisation and little accompanying infrastructure
development (Brook & Dávila, 2000; Keraita et al., 2003; Fobil & Atuguba, 2004; UN-
HABITAT, 2009). Therefore, most of the raw domestic effluents are discharged directly into
water bodies. Information on the extent of pollution caused by domestic wastes on water
bodies exists only for the main rivers and reservoirs that serve as drinking water sources for
communities. This is well captured in a recent United Nations Human Settlements Programme
report that, Ghana’s environmental challenges and priorities are urban planning and
management, housing/urban development and the environment (UN-HABITAT, 2008b).
These environmental issues are the result of conflicts between human and environmental
interests due to urbanisation that has gone haywire. Also, the environmental framework based
on which one can evaluate these issues will be difficult to define because Ghana has no urban
policy. This discussion will therefore be compared to best practices elsewhere and an attempt
made at relating it to local conditions.
80
Appending signatures to conventions and treaties seem not to be a problem for Ghana
irrespective of the obligations and commitments required. This is because the translation of
the obligations of conventions into local laws and policies for implementation and
enforcement has not been followed through to the letter. The divide between policy and
implementation is evident in the contrast between the number of national and international
obligations and the unsanitary conditions and the increasing degradation of wetlands. For
example, Ghana ratified the Ramsar Convention in 1988, demonstrating her willingness and
commitment to reverse wetland loss and degradation. However, it took more than a decade
afterwards to fulfil the requirements of the Convention by recognising wetlands in the
National Land Policy (Ministry of Lands and Forestry, 1999b) and to develop a strategy for
management and sustainable utilisation of wetlands and their resources (Ministry of Lands
and Forestry, 1999a). Now, Ghana has to also fulfil the operational objectives of the Ramsar
Strategic Plan 2009-2015 which among others, required all parties to complete their national
inventories and have a web-based database; put in place a national wetland policy and
management plans founded on sound scientific research and identify priority sites for
restoration. Since becoming a member of this Convention, research on wetlands that could
help meet this operational objective has barely been conducted. Most wetland research has
been on the Volta and Densu Rivers because of their hydroelectric use and provision of
drinking water to Accra respectively.
Even though the environmental governance system is supposed to be decentralised according
to the Constitution and Local Government Acts, the extent of decentralisation is not the same
across the country. Whilst the older and richer districts have the various decentralised
government agencies, most of new or poor districts are still under the oversight of the regional
level agencies. There are, therefore, differences in availability of expertise and even
representation on the DEMC. For example, the EPA, TCPD, Forestry Service Division and
the Land Commission are not present in most districts in Ghana. These differences give multi-
dimensionality to the already complex problems associated with the urban environment. Also
prominent in most districts that are fortunate to have these agencies, e.g. the KMA, is the
conflict of interests among these agencies. For example, Forestry Service Division, EPA,
Department of Agriculture, District Directorate of Health Services, have overlapping
functions and sometimes try to outmanoeuvre each other into approving or disapproving some
environmental issues. This has been aggravated by high staff turnover, frequent changes in the
institutions' mandates, the complexity of the institutional framework and weak coordination.
81
The local government system practised in Ghana is very much in line with international best
practices of participatory governance and bottom-up approaches. Also, according to all the
laws and policies, environmental action in Ghana should be bottom-up. In the spirit of the
Constitution and policies of Ghana, the use of the term ‘Government’ at the local level on
environmental issues refer to the DEMC. This is because environmental protection and
management is a constitutional mandate of every citizen. This mandate is exercised through
local level environmental management and decision making through the DEMC. This is
expected to create ownership and empowerment for the sustainability of environmental
programmes by taking cognisance of local needs and aspirations (Okley, 2004). It is however,
unfortunate that the DEMCs are either non-existent or non-functional in most assemblies. At
the KMA, the EPA has overshadowed this Committee.
Unless land that has been acquired and protected for the public good, the system of land
ownership in Ghana does not augur well for the environment. Urban land value is always on
the ascendency. For example, wetland areas gain value due to urbanisation and improved
construction engineering feats. Like all other jurisdictions, there is market failure in the
environmental services of these wetlands. Wetland uses for residential and commercial
developments therefore often out-compete their use for environmental services as a landuse
priority. Urban wetland areas are therefore very popular sites for fuel stations in Kumasi and
other urban areas of Ghana. Rather than protecting, the EPA’s regulations for siting such
businesses promote the use and destruction of urban wetland areas. Also, most of the
institutions, especially, the DEMC, are non-functional when it comes to enforcing and
implementing the planning schemes for these urban areas.
The rate of urbanisation of Kumasi has overwhelmed the authorities. Settlements are
constructed with layouts from landowners before the TCPD develops or approve the chief’s
layout for the suburbs. In these instances, the wetlands are usually long destroyed by the time
these state institutions start to work. This is because the constitutional powers of governments
to protect the public welfare and the political acceptance of existing environmental
regulations are generally difficult to enforce (Lant, 1994). Albeit different geographical,
economic and social context, Sims & Schuetz (2009) showed that local regulations and
bylaws slowed wetland conversion to residential uses in Massachusetts. In the case of Kumasi
and Ghana at large, a strong DEMC and TCPD working in collaboration with the Chiefs and
other landowners could be a panacea to the wetland loss and environmental management.
82
From the described conditions of Kumasi, the future environment will largely consist of
human-dominated ecosystems, managed to varying degrees, and become harder and harder to
maintain in the poor suburbs. The victims of this looming crisis are both the state and the
persons at these wetland sites. Already plenty resources are spent yearly in supporting flood
victims in Kumasi. Also, the capacity rating of flood and wetland stakeholders has
implications on their level of responsiveness to the affected communities. With the limited
resources, there is the need to strengthen stakeholder collaboration and coordination.
Importantly, though NADMO has been providing relief items and materials to flood victims,
it is usually for immediate and short time relief. It is rather more important for these
stakeholders to focus on the reduction of socioeconomic vulnerability of community members
and the promotion of the culture of preparedness of both the authorities and community
members. This improves our collective resilience to floods.
From the information gathered, a general model for management of floods and wetlands
within the Kumasi Metropolis has been proposed in Figure 4.3. Whilst an integrated and
collaborative approach between stakeholders is advocated, the model takes cognisance of the
strengths and weaknesses of stakeholders in addressing the various flood management
elements. All these elements have to be treated with equal importance. What differ are the
scale and the dimensions of the issues. Based on the findings of this research, different levels
of emphases are proposed for the different dimensions or issues. The proposed order in
decreasing significance of the issues is: social, technical, institutional, environmental and
legal. With the limited financial resources available to the KMA, flood management within
the metropolis should focus on the social and technical elements to achieve better impacts.
The current level of economic development of Ghana is also a contributory factor to
ineffective implementation or non-enforcement of environmental laws. Most obviously, law
enforcement has financial implications and therefore will depend on the wealth of the country.
Developed countries may be more capable and willing to comply with their environmental
obligations than poorer countries because implementation places relatively less burden on the
national cake. On the other hand, if the cost of implementation is very low, or if
implementation produces a net economic gain, a country’s level of economic well-being may
not be very critical for its success. This is because, the decisive factor is the relationship
between the cost of implementation and the capacity of a country’s economy to absorb them.
83
Fi
gure
4.3
. A
con
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Dim
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Dim
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84
Apart from a nation’s economic situation, national environmental consciousness and
institutions are also very necessary for the protection and management of wetlands. Ghana
needs the birth of a green party. In many developed countries, rising environmental
consciousness has given birth to green parties (or the vice versa) that are revolutionising the
political landscape with green politics by putting environmental issues to the fore in national
policy debates. The challenge now lies as to whether it is the economy or the people that give
rise to green politics. If it is the economy, then Ghana needs to reach a certain level of
economic independence for businesses to go green and still survive the competition. The
Ghanaian economy and businesses are not yet there. If it is the people, there is the need for a
critical mass of people to have a level of dissatisfaction with the environment. That also,
Ghanaians are not yet there. The option left is for the developed countries to dictate the pace
towards a better urban environment through strings tied to bilateral and multilateral assistance
or introduction and enforcement of environment related trade barriers and conditionalities.
85
5 WETLAND ECOLOGY AND VEGETATION GEOGRAPHY IN THE KUMASI METROPOLIS
5.1 INTRODUCTION Human settlements, like other systems, are under constant change involving growth, decline,
aesthetic changes etc. depending on the age of the settlement, demographic trends, planning
and resources available. Urbanisation is currently the biggest change most developing country
settlements are undergoing (Bhattacharya, 2002). It is both a driver and outcome of economic,
political, cultural, social and physical processes. The ecological consequences of the
increasing built environment are pollution and landscape changes resulting in increased range
of spatial diversity from ‘biological deserts’ with paved or gravelled surfaces or manicured
monospecific lawns to biological hotspots like urban wetlands and abandoned industrial sites
and rail lines (Niemelä, 1999). This is because urbanisation and the associated environmental
stress lead to fragmentation of natural vegetation and changes in their structure and floristic
composition (Altobelli et al., 2007). Urbanisation also alters local climate and air quality
through increased concentrations of oxidants (O3, SO2), nutrients and chemicals (nitrates,
cations especially heavy metals), decreased net radiation and average wind speed, increased
cloudiness and precipitation and temperature (“heat island” effect). These changes imply that
urban sites cannot be directly compared with non-urban sites, any more than sites in different
climatic zones (Ehrenfeld, 2000). Therefore the wetlands of Kumasi were considered as
unique domains separate and different from the adjoining peri-urban or non-urban wetlands or
urban wetlands elsewhere in the country.
Most urban ecological research has focused on contributions of greenhouse gases and the heat
island effect (Hidalgo et al., 2008; Takebayashi & Moriyama, 2009). Urban wetlands on the
other hand, deliver a wide range of ecosystem services relating to climate change mitigation
and or adaptation, water catchments, buffer against flooding, soil purification, water and air or
act as carbon sinks and contribute to human well-being (Joosten & Clarke, 2002; Berkowitz et
al., 2003; Janssen et al., 2005; Nelson et al., 2009). Despite their ecological and
socioeconomic importance, urban wetlands have been understudied in the analysis of global
environmental change and flooding. Urban wetland areas are usually characterised by
vegetation patches of different sizes and nature, depending on the landuse options developed
by planners during the urbanisation process or patches left out in the landuse planning. The
vegetation is often affected by the hydroperiod or hydrologic changes and availability of
nutrients. Also, toxic materials in the runoff can interfere with biological processes of wetland
86
plants, resulting in impaired growth, mortality, and changes in plant communities. For
example, direct storm sewer inputs affect plant community structure and vegetation dynamics
(Ehrenfeld, 2000). Plants, as individuals or as communities, could therefore be valuable
indicators of water regime and other environmental conditions (Haslam, 2003).
Reinelt et al. (1998) in a study on the impacts of urbanisation on palustrine wetlands found
that, changes in plant community composition may describe impact of pollution. In other
studies, it was found that contrary to that of Reinelt et al. (1998), vegetation types of different
floristic composition or vegetation cover or density are rather predetermined by
geomorphology, soil conditions, and water regime (Federal Interagency Committee for
Wetlands Delineation, 1989; Barrat-Segretain & Amoros, 1996; Coroi et al., 2004;
Hejcmanovā-Nežerková & Hejcman, 2006; Sorrell et al., 2007). On a large scale, factors such
as soil and climatic conditions may be the determining factors that control the distribution and
abundance of vegetation. However, on a small scale, while the soil and climatic conditions
may not be spatially varied, the vegetation may be very varied. These spatial differences in
species distribution are pronounced in the wetlands of Kumasi. This chapter therefore seeks to
identify the underlying factors that determine the wetland vegetation type and distribution in
Kumasi. Knowledge of the characteristic vegetation is useful in delineating wetland
boundaries and reduces incidence of conflicts associated with landuse planning and wetland
encroachments. This will be an input towards restoring Kumasi to its Garden City status.
5.2 METHODOLOGY
5.2.1 Reconnaissance Survey of Wetlands in Kumasi and Selection of Study Sites The wetlands in Kumasi were identified and delineated using the definition of Joosten &
Clarke (2002). Following a detailed study of drainage maps of Kumasi and use of aerial
photography, physical inspection and ground truthing of these drainage channels was done
using a handheld GPS. Detailed descriptions of landcover and landuse types were recorded
and photographs of salient features taken. The data collected was then be used to validate the
information gathered from the digitised drainage maps and aerial photography.
Based on the information from this survey, some of the major wetland sites of ecological,
landscape, economic and social interests were chosen for the study. Wetlands of ecological
interests included, but not limited to, areas with at least 50 m of wetland vegetation on both
sides of the water channel. Areas with economic and social activities directly affecting or
bordering the wetland (e.g. tie-dye industries, car wash, agriculture, settlement etc.) were
87
selected as sites of economic interests. These sites were selected for detailed socio-economic
studies as described in earlier chapters.
5.2.2 Ecological Survey of Wetlands in Kumasi The various wetlands of interest for this study were selected as described in section 3.2 above.
For each wetland area, e.g. along a stream X, three permanent transects A, B and C were
marked out not less than 50 m apart based on the ecological, landscape and surrounding
economic and social activities (Figure 5.1). The GPS coordinates of these transects were
noted to aid future identification of these sites if markers are removed. Within the permanent
transects detailed ecological studies were carried out at various sections of the transect (Coroi
et al., 2004; Barrat-Segretain & Amoros, 1996).
Figure 5.1. A schematic diagram of a sample study site along a stream X showing the transects and quadrat layout
5.2.2.1 Soil sampling A graduated soil corer of diameter 5.7 cm was used to take soil core samples to a depth of
30 cm (Driessen et al., 2001, Maltby & Barker, 2009) and within 10 m from the water
channel. Each sediment core was carefully studied and described. The sample was then put
into labelled sterile polythene bags and stored in ice chests for further laboratory analysis.
Also, as a proxy for testing soil consistency, the corer was pushed into the soil by hand at
these locations to estimate the resistance to penetration by measuring the total depth of
88
insertion. In the laboratory, a portion of the soil sample was taken and the texture determined
using the Bouyoucos hydrometer method of mechanical analysis (Beverwijk, 1967). The
textural classes were based on the US Department of Agriculture soil particle size ranges.
The total organic matter was estimated from these ice cooled samples using the loss on
ignition method. Each sample was first treated with excess of 10 % HCl to remove any
carbonates that might be present. The water was first removed by air drying in an oven for 24
hours at 70 °C. The dried sample was ground with an agate mortar and sieved through a
1000 µm sieve to homogenise it. A known weight was then placed into a preheated furnace at
500 °C for 2 hours. After ignition, 2-3 drops of (NH4)NO3 was added and the samples put
back into the furnace for 10 minutes in order to remove any unburned organic carbon. The
total organic carbon in each sample was the weight lost on ignition.
5.2.2.2 Stream sediments and physicochemical characteristics Along each permanent transect the presence or absence of water at the surface of each of the
sampling points was noted monthly. The total duration of surface water during the year was
used to assess the effects of wetland hydroperiod on vegetation dynamics.
In each stream, temperature (bottom), turbidity, conductivity, total dissolved solids, dissolved
oxygen and pH of the water were measured using a Hanna multiparameter water quality
portable meter (HI 9828) during the peak rainy season and dry season. Surface sediment
samples were also taken at a depth of 0-15 cm (U. S. Environmental Protection Agency,
1985) and quickly packed in air tight polythene bags to be analysed for various heavy and
trace metals. In the laboratory, samples were air dried in a vacuum oven at 70 ºC for 3-4 days
until constant weight and ground in an agate mortar for homogenisation. Approximately 0.2 g
of dried sample was extracted overnight with 2 ml concentrated nitric acid (HNO3) and
evaporated until near dryness and no nitrous vapours were released. After cooling, 5 ml of an
acid mixture made of concentrated acids HF:HClO4:HNO3 at 6:2:3 ratio was added. The
digestion continued until no coloured vapours were released. The atomic absorption
spectrophotometer (Varian SpectrAA-200FS) was used for the determination concentrations
of Lead (Pb) Mercury (Hg), Copper (Cu), Zinc (Zn), Cadmium (Cd), Chromium (Cr), Nickel
(Ni) and Arsenic (As) and photometric determination used for Phosphorus (P).
Assessment of contamination in the sediments This was done using three parameters: enrichment factor (EF), geo-accumulation index (Igeo),
and pollution load index (PLI).
89
a. Determination of heavy metal enrichment factor (EF)
Iron (Fe) was chosen as the element for normalisation of the enrichment because natural
sources vastly dominate its input in the environment (Schiff & Weisberg, 1999; Ghrefat &
Yusuf, 2006; Sekabira et al., 2010). To obtain the natural Fe concentration in the wetland
sediments of Kumasi, three sediment samples were taken from different locations in the
KNUST Botanical Gardens and pooled. The KNUST Botanical Gardens was chosen because
of its remoteness from known or suspected anthropogenic metal sources. World geochemical
background values in average shale as reported by Turekian & Wedepohl (1961) were used
for all the metals. The EF for each metal was computed as the relative abundance of species in
the sediment to that found in the Earth’s crust (Simex & Helz, 1981) with the formula:
EF = ��� (������)
��� (� ��ℎ′� �����)� Where X is concentration of the metal studied.
Six categories of enrichment were recognised: <1 background concentration, 1-2 depletion to
minimal enrichment, 2–5 moderate enrichment, 5–20 significant enrichment, 20–40 very high
enrichment and >40 extremely high enrichment (Duzgoren-Aydin et al., 2006; Harikumar et
al., 2010).
b. Determination of index of geoaccumulation (Igeo)
The Igeo values were calculated for the different metals using the formula of Müller (1969)
expressed as: Igeo = log2(Cn/1.5*Bn).
Where Cn is the measured concentration of element n in the sediment sample and Bn is the
geochemical background for the element n. The factor 1.5 is introduced to include possible
variation of the background values that are due to lithogenic variations. Müller (1969)
proposed seven sediment quality classes associated with the geoaccumulation index as given
in Table 5.1.
Table 5.1. Classes of the geoaccumulation index used to define sediment quality Igeo value Igeo Class Quality of sediment ≤ 0 0 Unpolluted 0-1 1 From unpolluted to moderately polluted 1-2 2 Moderately polluted 2-3 3 From moderately to strongly polluted 3-4 4 Strongly polluted 4-5 5 From strongly to extremely polluted ≥ 6 6 Extremely polluted
90
c. Determination of pollution load index (PLI)
The PLI is an indicator of site quality. For each metal, the contamination factor (CF) was first
determined using the formula, CF = metal concentration in sediments/background values of
the metal. The extent of pollution by trace metals was assessed using the PLI formula
developed by Tomlinson et al. (1980): PLI = (CF1 * CF2 *.....* CFn)1/n
Where CF = contamination factor and n= number of metals. PLI value >1 is polluted whereas
PLI value < 1 indicates no pollution.
5.2.2.3 Vegetation sampling To fulfil the requirements of the Ramsar Convention Secretariat (2005), the systematic
sampling approach described by Orloci (1978) was used. At each selected wetland site,
starting from the edge of the permanent water channel, 1 m x 1 m quadrats were marked along
each transect. Sampling was done at 10 m intervals. All herbaceous plants and shrubs in the
quadrats were identified to species level with their respective relative abundance and cover
recorded (see Appendix 2) using the Braun-Blanquet scale described in Table 5.2. Cover was
determined from estimates of vertical plant shoot-area projection as a percentage of quadrat
area (Wikum & Shanholtzer, 1978).
The plants were identified with the assistance of a technician and the use of vegetation
manuals by Akobundu & Agyakwa (1998), Cook (1996), Haflinger & Scholz (1980a, b),
Haflinger et al. (1982) and Terry (1983). Plants that could not be identified on the field were
collected and later identified in the laboratory. Around each wetland area, the various
anthropogenic activities up to 100 m from the water channel were noted.
Table 5.2. The Braun-Blanquet scale and the description of the values used for sampling of wetland species in Kumasi
Braun-Blanquet scale
Range of cover (%) Relative abundance Midpoint of over
range (%) 5 75-100 very common, usually single spp.
dominant 87.5
4 50-75 62.5
3 25-50 common, dominance is shared by 2 to 3 other species. 37.5
2 5-25 frequent, a species not sharing dominance but remains significant to the composition of the site
15.0
1 <5; numerous individuals occasional occurrence 2.5
+ <5; few individuals
rare, individuals infrequently seen, low count and crown cover 0.1
91
Sampling was done in June-July 2010 (peak rainy season) and December, 2010-January 2011
(peak dry season). The presence or absence of water on the surface at each sampling site was
noted. Variations in species composition were estimated using the importance value index for
all study sites using the following formulae:
i. density= ������ �� ������� ����! �!��"�#
ii. frequency= ������ �� �"�$� �% &'��' ������� � ������*�$!" %����� �� �"�$� �!��"�#
iii. dominance= *�$!" ��+�� �� ������� � ���! �!��"�#
iv. relative density= ,�%��$- �� ������� �*�$!" #�%��$- �� !"" ������� × 100
v. relative frequency= ���.��%�- +!"�� ��� ������� �*�$!" �� !"" ���.��%�- +!"��� ��� !"" ������� × 100
vi. Relative dominance= ,���%!%�� ��� ������� �*�$!" #���%!%�� ��� !"" ������� × 100
Therefore, importance value index = relative density + relative dominance + relative frequency.
5.2.3 Data Analysis Differences among sampling sites along each stream and sampling periods were found by
means of analysis of similarities (ANOSIM) test at α= 0.05. The various indices of diversity
(Shannon, species evenness and species richness) were used to assess the plant community of
each wetland. The non-metric multidimensional scaling (MDS), cluster analysis and principal
components analysis (PCA) were used to explain species richness/distribution patterns and
environmental parameters that influence/determine these patterns. The BIO-ENV procedure
was used to examine the extent to which the soil texture, physicochemical water parameters
and the total organic matter are related or explain (using the Spearman rank correlation
coefficient ρ) the distribution and type of vegetation in each wetland. The Pearson correlation
analysis was used to analyse and establish associations between heavy metals of wetland
sediments and other variables after the data was transformed and normalised. A PCA was
carried out on the correlation matrix to reduce the dimensionality of the problem and enable
an interpretation of the relationships between variables and sampling sites.
5.3 RESULTS
5.3.1 Anthropogenic Activities in the Wetland Areas of Kumasi The commonest anthropogenic activities identified within 100 m from either side of the
channel are houses, schools, churches, fuel/gas filling stations, farms, car washing bays and
repair shops (Figure 5.2, Photograph 1 and Appendix 3). Activities with the highest land
92
cover are housing and urban agriculture (vegetable farms). The wetlands along the Sisai River
from Family Chapel through Ahensan to Atonsu Sawmill (Sites A, B and E) have the highest
anthropogenic activities associated with them. The predominant anthropogenic activities at
these sites are houses, carpentry shops, car wash and repairs centres and waste disposal sites.
The car repair centres are usually a cluster of wooden shelters serving as garages which do
general repairs, engine oil change, vehicle body building and spraying. A lot of wastes from
these activities are washed directly into the water channel. Natural vegetation cover in these
sites is as low as 30 %.
All the sites have some vegetable farms associated with them. These are commonly small
plots of about 0.25 ha with carrots, cabbage, onions, green pepper and okro. The water from
the channel is used to irrigate the fields to provide an all year round cultivation. Fertilizers,
weedicides, insecticides and pesticides are used to increase yields and quality. The farming
activity at the wetland stretching from the Bekwai to Santasi roundabouts is on a relatively
large scale. Crops cultivated here include maize, oil palm, pawpaw, banana and plantain. Only
about 20 % of the 100 m buffer area is natural wetland vegetation. Houses, infrastructure and
public gardens or space occupy over 75 % of the total wetland area.
93
Figu
re 5
.2. L
andc
over
and
Lan
duse
act
iviti
es w
ithin
100
m fr
om t
he s
trea
m c
hann
el a
t the
diff
eren
t st
udy
site
s in
Kum
asi
94
5.3.2 Wetland Edaphic Characteristics, Heavy Metals and Stream Physicochemical Characteristics
The soils in Kumasi developed from two main primary materials (Obeng, 1971). The western and
north-eastern to south-eastern parts of the city have soils that developed from Cape Coast granites
to form the Kumasi-Asuansi/Nta-Ofin/Bomso-Asuansi compound associations (Figure 5.3). The
wetlands found around the KNUST Police Station (D), Faculty of Renewable Natural Resources
farms (C), High School junction (B), Kaase Guinness (H), the Family Chapel (E), Spetinpom (F)
and Bekwai roundabout (J) belong to this soil category. The soils stretching from the central to
south-western Kumasi developed from the lower Birimian phyllites, greywackes, schists and
gneisses primary materials. The soil groups from these primary materials form the Bekwai-
Nzima/Akumadan-Bekwai/Oda complex associations. The wetlands around Dakwadwom (K),
Family Chapel (E), Golden Tulip Hotel (G) and Atonsu Sawmill (A) belong to this soil category.
The site specific site edaphic conditions are described in Table 5.3. The upper layers of the soils
were generally dark brown and deeper layers were yellowish-reddish brown. Mottles were very
common in wetlands like Atonsu and Spetinpom wetlands. The texture types were mainly loamy
from forest ochrosols and lithosols. All the sites were waterlogged from a minimum 6 months to
being permanently waterlogged. The wetland at the KNUST Police Station had the highest organic
matter content of 34.5% and the whole length of the corer was easily inserted into the soil. At the
Atonsu, Spetinpom, Golden Tulip Hotel and Kaase Guinness wetlands, the corer could hardly
penetrate up to 20 cm and these sites also had comparatively higher proportion of sand and low
organic carbon.
There were spatial and temporal variations in physicochemical parameters measured (Table 5.4).
During the peak rainy season, all the study sites were weakly acidic with pH between 5.4 at Atonsu
to 6.4 at the Golden Tulip Hotel wetlands. The TDS and conductivity were the most varied in the
selected wetland sites. The conductivity of water was directly related to the TDS (conductivity ≈ 2
TDS) for all sites. The water at Atonsu and Kaase Guinness had relatively high TDS of 411 and
423 mg/l and salinity of 0.43 and 0.52 ‰ respectively. The water at the KNUST Police Station also
recorded the least salinity. The channel bottom water temperature, dissolved oxygen were less
varied between sites.
95
Figure 5.3. Soil map of the Kumasi showing study sites [sites are labelled in letters: Atonsu Sawmill (A), High school junction (B), FRNR farms (C), KNUST Police Station (D), Family Chapel (E), Spetinpom (F), Golden Tulip Hotel (G), Kaase Guinness (H), Bekwai roundabout (J) and Dakwadwom (K)] (Source: Obeng, 1971).
These observations were not different for some parameters for the dry season. The conductivity was
also approximately twice the TDS for all the wetlands. For this reason, only the TDS was used in
the subsequent analysis to eliminate the compounding effects of using both parameters. During the
dry season however, pH was generally alkaline with a range from an almost neutral 6.88 at the
KNUST Police Station to 10.6 at site the High School Junction. The biggest seasonal differences
were in dissolved oxygen concentration. For example, dissolved oxygen at sites Atonsu, High
96
School Junction, KNUST Police Station, Kaase Guinness, Bekwai roundabout and Dakwadwom
declined from 4.20, 5.50, 3.30, 4.90, 4.50 and 4.30 mg/l in the rainy season to 0.45, 2.05, 0.62, 0.16,
1.48 and 0.75 ml respectively in the dry season. The non-parametric Wilcoxon Test was used to
assess if there are any seasonal differences in the physicochemical parameters at the various
wetland sites (Appendix 4). The null hypothesis of no seasonal differences was rejected for pH and
dissolved oxygen (α=0.05, p-values = 0.005 and 0.009 respectively).
The concentrations of metals in the different wetland sites investigated are presented in Appendix 5.
Heavy metal concentrations were generally highest in Atonsu Sawmill, Family Chapel and the High
School Junction. The KNUST Police Station had relatively lowest concentrations in all heavy
metals except total phosphorus. The association between these metals and some of the measured
environmental parameters was assessed using the Pearson correlation coefficient (Figure 5.4 and
Appendix 6). The test showed a significantly positive correlation between Hg, Ni, Zn, pH and Pb.
Other clusters of significant correlations are clay, Cu and Cr; dissolved oxygen and salinity. The
percentage of silt in the soil was negatively correlated to pH and Cr; dissolved oxygen and salinity.
To reduce the dimensionality of variables that may be of significance in this study, a PCA was
carried out on the data (Figure 5.5 and Appendix 7). The first two principal components accounted
for 52.9 % of the variation. The major contributors to the first principal component axis are Pb, Zn,
Ni, Hg and pH and those to the second principal component axis are temperature, salinity, dissolved
oxygen and dissolved solids.
The extent of sediment contamination by these heavy metals was further evaluated using the EF,
Igeo and the PLI. All these indices were found to be significantly different between the seasons
(Appendices 8, 9 and 10). The FRNR farms and Spetinpom sediments that did not have significant
enrichment in any heavy metal in the rainy season whilst the KNUST Police Station had very high
enrichment in only phosphorus (Figure 5.6). The Family Chapel, Atonsu Sawmill and High School
Junction sediments had significant enrichment in all metals except cadmium. Sediments from
Family Chapel had very high enrichment of P and Pb and that from Atonsu Sawmill also has very
high enrichment of Pb. Heavy metal enrichment is higher for all sites in the dry season than the
rainy season (Figure 5.7). Very high enrichment was recorded at various study sites for P, Cu, As
and Pb.
According to the Igeo for both seasons (Figures 5.8 and 5.9), most heavy metals were accumulated in
sediments of Family Chapel, Atonsu Sawmill and High School Junction. In the rainy season (Figure
5.8), only Pb, Cu, P and Cr caused pollution class 4 (i.e. sites were strongly polluted by these
metals). In the dry season (Figure 5.9), these sites were extremely polluted by these metals. Extreme
97
pollution was reported of P and (or) Pb in the sediments of the wetlands at Atonsu Sawmill, High
School Junction, KNUST Police Station, Family Chapel and Dakwadwom.
The PLI was used for an overall assessment of the extent of pollution of each site from the
cumulative contributions of all the substances studied. By this criterion, all the sites considered in
this study are deemed polluted (Figure 5.10). Pollution levels in the dry season for all sites were
higher than that of the rainy season. The wetland sites in order of increasing levels of pollution are
FRNR farms, KNUST Police Station, Spetinpom, Dakwadwom, Golden Tulip Hotel, Bekwai
Roundabout, Kaase-Guinness, Family Chapel, Atonsu Saw Mill and the High School Junction.
Wetland being used as rubbish dump Cattle grazing in a wetland
House in a wetland Vegetable farm in a wetland
Photograph 1. Some uses of wetlands in the Kumasi Metropolis (Photograph taken by Author in 2011)
98
Tabl
e 5.
3. E
daph
ic c
hara
cter
istic
s of
wet
land
site
s sa
mpl
ed in
the
Kum
asi
Met
ropo
lis
Loc
atio
n of
w
etla
nd
Des
igna
ted
rese
arch
co
de
Des
crip
tion
of d
omin
ant s
oil f
orm
at 1
0 m
from
wat
er
chan
nel
Dep
th o
f in
sert
ion
of th
e co
rer
at 1
0 m
fr
om c
hann
el
Soil
text
ure
Org
anic
m
atte
r (%
) Sa
nd
(%)
Silt
(%)
Cla
y (%
)
Des
crip
tion
Ato
nsu
Saw
mill
A
Dee
p, b
row
n, m
ottle
d so
il un
derla
in b
y gl
eyed
cla
y. T
op
soil
is da
rk a
nd lo
ose.
Per
man
ently
wat
erlo
gged
28
19
40
41
C
lay
loam
19
.85
Hig
h sc
hool
ju
nctio
n B
Sh
allo
w s
oil u
nder
lain
by
hard
pan
(fer
ricre
te).
The
uppe
r lo
ose
soil
laye
r is
dark
bro
wn
and
low
er h
ard
laye
r is
brow
n w
ith r
ed b
ands
and
gle
yed
patc
hes.
Wat
erlo
gged
fo
r abo
ut 8
mon
ths
10
62
12
26
Sand
y cl
ay
loam
3.
84
FRN
R fa
rms
C
Shal
low
soi
l und
erla
in b
y ha
rdpa
n (f
erric
rete
). So
il is
mad
e up
of d
ark
and
red
porti
ons
with
gle
yed
patc
hes.
W
ater
logg
ed fo
r abo
ut 6
mon
ths
16
38
52
10
Loam
6.
09
KN
UST
pol
ice
stat
ion
D
Dee
p so
ft la
yer o
f org
anic
mat
ter,
loos
e da
rk b
row
n, li
ght
wei
ght a
nd p
erm
anen
tly w
ater
logg
ed w
ith d
eepe
r por
tions
co
ntai
ning
gle
yed
clay
.
> 50
21
46
33
C
lay
loam
34
.50
Fam
ily C
hape
l E
Dee
p, g
rey,
mot
tled
soils
und
erla
in b
y gl
eyed
cla
y,
subj
ect t
o pe
rman
ent w
ater
logg
ed c
ondi
tions
. U
pper
laye
r is
loos
e an
d da
rk b
row
n.
22
46
38
16
Loam
5.
65
Spet
inpo
m
F Sh
allo
w g
rey
soils
und
erla
in b
y ha
rdpa
n fe
rric
rete
. M
ottli
ng i
s co
mm
on in
upp
er p
arts
exp
osed
to a
ir by
root
s of
pla
nts.
Wat
erlo
gged
for
abo
ut 6
mon
ths
10
42
30
28
Cla
y lo
am
14.0
3
Gol
den
Tulip
H
otel
G
R
ed w
ell d
rain
ed s
hallo
w s
oils
unde
rlain
by
hard
pan
ferr
icre
te w
ith c
lear
evi
denc
e of
per
iodi
c w
etne
ss a
nd
late
ral f
low
of w
ater
in th
e so
il pr
ofile
. Wat
erlo
gged
for
abou
t 6 m
onth
s
15
50
32
18
Loam
6.
23
Kaa
se G
uinn
ess
H
Dee
p, g
rey,
mot
tled
soils
und
erla
in b
y gl
eyed
cla
y,
subj
ect t
o pe
rman
ent w
ater
logg
ed c
ondi
tions
. W
ater
logg
ed fo
r abo
ut 7
mon
ths
17
48
30
22
Loam
7.
87
Bek
wai
ro
unda
bout
J
Shal
low
loos
e so
ils u
nder
lain
by
hard
pan
ferr
icre
te w
ith
clea
r evi
denc
e of
freq
uent
wat
erlo
ggin
g an
d la
tera
l flo
w
of w
ater
in th
e so
il pr
ofile
. Wat
erlo
gged
for
abo
ut 8
m
onth
s
20
47
32
21
Loam
5.
24
Dak
wad
wom
K
D
eep,
gre
y, m
ottle
d so
ils u
nder
lain
by
gley
ed c
lay,
su
bjec
t to
perm
anen
t wat
erlo
gged
con
ditio
ns.
Perm
anen
tly w
ater
logg
ed
39
33
31
36
Cla
y lo
am
6.17
Tabl
e 5.
4. P
hysi
coch
emic
al c
hara
cter
istic
s of
wat
er r
unni
ng t
hrou
gh t
he w
etla
nds
in K
umas
i
99
Loc
atio
n of
w
etla
nd
Des
igna
ted
rese
arch
co
de
Rai
ny s
easo
n (J
une)
D
ry s
easo
n (J
anua
ry)
pH
Tem
p (°
C)
Salin
ity
(ppt
) D
O
(mg/
l) T
DS
(mg/
l) C
ondu
ctiv
ity
(µS/
cm)
pH
Tem
p (°
C)
Salin
ity
(ppt
) D
O
(mg/
l) T
DS
(mg/
l) C
ondu
ctiv
ity
(µS/
cm)
Ato
nsu
Saw
mill
A
5.4
28.8
4 0.
43
4.2
411
822
8.6
30.3
1 0.
33
0.45
34
0 67
9
Hig
h Sc
hool
Ju
nctio
n B
6.
3 26
.14
0.10
5.
2 10
3 20
5 10
.6
26.9
8 0.
11
2.05
11
5 23
0
FRN
R fa
rms
C
6.3
25.6
8 0.
11
5.6
120
239
7.05
24
.36
0.08
3.
94
86
172
KN
UST
Pol
ice
Stat
ion
D
5.8
26.3
0 0.
10
3.2
110
220
6.88
26
.87
0.15
0.
62
164
340
Fam
ily C
hape
l E
5.9
27.8
8 0.
24
3.3
252
505
7.06
27
.36
0.25
4.
54
257
512
Spet
inpo
m
F 5.
9 27
.88
0.24
3.
3 25
2 50
5 7.
3 26
.88
0.13
3.
6 14
4 28
8
Gol
den
Tulip
Hot
el
G
6.4
27.0
4 0.
46
4.0
211
430
7.06
28
.02
0.25
0.
82
258
516
Kaa
se-G
uinn
ess
H
6.2
26.5
1 0.
52
4.9
423
805
8.32
31
.77
0.52
0.
16
537
1074
Bek
wai
roun
dabo
ut
J 6.
1 27
.12
0.26
4.
5 32
0 63
0 7.
47
38.1
3 0.
29
1.48
29
7 39
4
Dak
wad
wom
K
6.
0 26
.13
0.29
4.
3 30
5 61
0 7.
67
27.1
4 0.
29
0.75
29
8 59
7
100
Figu
re 5
.4.
A c
lust
er d
iagr
am o
f th
e co
rrel
atio
n m
atrix
of
the
vario
us e
nviro
nmen
tal
varia
bles
mea
sure
d in
the
diff
eren
t su
burb
s of
K
umas
i
101
Figu
re 5
.5.
A p
rinci
pal
com
pone
nts
anal
ysis
plo
t of
the
mea
sure
d en
viro
nmen
tal p
aram
eter
s (T
he v
ecto
r le
ngth
ref
lect
sth
e im
port
ance
of
the
varia
ble’
s co
ntrib
utio
n to
the
two
prin
cipa
l co
mpo
nent
s in
rel
atio
n to
all
poss
ible
axe
s an
d if
ave
ctor
touc
hes
the
circ
le, t
hen
none
of t
hat
varia
ble’
s ot
her
coef
ficie
nts
in t
he E
igen
vec
tors
will
diff
er f
rom
0)
102
Figu
re 5
.6. H
eavy
met
als
enric
hmen
t in
the
stre
am s
edim
ents
of t
he d
iffer
ent
subu
rbs
of K
umas
i in
the
rain
y se
ason
103
Fi
gure
5.7
. Hea
vy m
etal
s en
richm
ent
in th
e st
ream
sed
imen
ts o
f the
diff
eren
t su
burb
s of
Kum
asi i
n th
e dr
y se
ason
104
Figu
re 5
.8. H
eavy
met
als
accu
mul
atio
n in
the
stre
am s
edim
ents
of t
he d
iffer
ent
subu
rbs
of K
umas
i in
the
rain
y se
ason
105
Figu
re 5
.9. H
eavy
met
als
accu
mul
atio
n in
the
stre
am s
edim
ents
of t
he d
iffer
ent
subu
rbs
of K
umas
i in
the
dry
seas
on
106
Figu
re 5
.10.
Sea
sona
l diff
eren
ces
in p
ollu
tion
by m
etal
s in
the
stre
am s
edim
ents
of t
he d
iffer
ent
subu
rbs
of K
umas
i
107
5.3.3 Wetland Vegetation of Kumasi
5.3.3.1 Vegetation abundance and diversity in wetlands of Kumasi There were no seasonal differences (dry season and rainy season) in vegetation, so the data
were pooled and analysed according to the wetland areas sampled. In all, 112 species were
identified (Table 5.5). All the identified species are native vegetation of the forest region of
Ghana except Limnocharis flava and Ceratophyllum demersum which are exotic and invasive.
To assess the species’ individual contributions to the total wetland vegetation, the importance
value index was used. Using this index, species which have high relative dominance,
frequencies and densities in the various wetland areas have high importance value (see
Photographs 2, 3 and 4). The top five species with the highest importance values for each
wetland are marked in bold in Table 5.5. Some of the important species were Coix lacryma-
jobi (found at KNUST Police Station and Spetinpom), Paspalum vaginatum (Atonsu
Sawmill), Thalia geniculata (Atonsu Sawmill, High School Junction, FRNR farms, Family
Chapel and Kaase Guinness), Thelypteris palustris (KNUST Police Station) and Typha
australis (Atonsu Sawmill and Spetinpom). Most of these important species were found in
almost all the wetlands sampled, albeit with relatively low importance values at some sites.
Some species like Achyranthes aspera, Ipomoea carnea, and I. aquatica were found only at
one site each but with very high importance values. Paspalum vaginatum, Brachiaria deflexa,
Chromolaena odorata, Sporobolus pyramidalis and the Cyperaceae were ubiquitous and
formed the dominant species in at least 2 or more wetlands as manifested by their relatively
high total importance values. Species like Thelypteris palustris, Coix lacryma-jobi, Typha
australis, Lemna minor and Thalia geniculata each contributed relatively very high to the
total importance values but were present in few wetland areas whilst Bracharia lata,
Chromolaena odorata, Paspalum vaginatum and the Cyperaceae had relatively lower
importance values but contributed to total importance in all the wetlands sampled.
Different number of species were identified in the different wetlands sampled (Figure 5.11).
The FRNR farms had the highest number of species (86) and Spetinpom wetland with the
least number of species was. Comparing the various wetlands, the Shannon diversity and
species richness were very much varied than the species evenness. Overall, the Dakwadwom,
Golden Tulip Hotel and Bekwai roundabout wetlands had highest species richness and
Shannon diversity while Spetinpom was assessed to be poor in these indices (Figure 5.12).
Dakwadwom had the highest species richness and Shannon diversity of 6.09 and 3.53
respectively.
108
The longitudinal variability in species distribution from the water channel was also
investigated for each wetland area. In general, species richness and Shannon diversity
increased with increasing distance from the water channel (Figure 5.13). Sampling sites
between 30 and 40 m from the water channel were generally highest in species richness and
Shannon diversity. Except at Kaase Guinness, species evenness did not change much with
increasing distance from the water channel. This site has been channelised and there were no
plants growing in the water channel.
River channel at Family Chapel silted with vegetation and rubbish
Photograph 2. State of some of the wetlands in the Kumasi Metropolis (Photograph taken by Author in 2011)
109
Tabl
e 5.
5. S
peci
es i
dent
ified
in
the
diffe
rent
wet
land
s of
Kum
asi a
nd t
heir
impo
rtan
ce v
alue
s (T
op 5
impo
rtan
ce v
alue
spe
cies
for
eac
h si
te a
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Iden
tifie
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s
Sam
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Tota
l
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lue
Ato
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Saw
mill
H
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Scho
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Junc
tion
FRN
R fa
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KN
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Pol
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Stat
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Fam
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Chap
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Spet
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pom
Go
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Kaa
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Guin
ness
Bekw
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Dak
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Ach
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16.3
9.
9 0.
0 0.
0 0.
0 0.
0 0.
0 0.
0 0.
0 0.
0 26
.2
Aerv
a la
nata
0.
0 5.
9 5.
4 0.
0 0.
0 0.
0 0.
0 0.
0 0.
0 0.
0 11
.3
Aesc
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men
e cr
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0.0
0.0
2.0
2.2
0.0
0.0
0.0
0.0
2.1
3.5
9.8
Aden
ia lo
bata
0.
0 2.
9 4.
2 0.
0 4.
8 0.
0 2.
2 2.
8 0.
0 2.
9 19
.7
Ager
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con
yzoi
des
0.0
1.8
3.7
1.4
0.0
0.0
2.6
0.0
4.0
2.7
16.2
Alch
orne
a co
rdifo
lia
0.0
5.6
5.2
0.0
0.0
0.0
0.0
0.0
2.0
0.0
12.7
A
lcho
rnea
laxi
flora
0.
0 4.
3 6.
5 0.
0 0.
0 0.
0 0.
0 0.
0 0.
0 0.
0 10
.8
Alte
rnan
ther
a se
ssili
s 0.
0 1.
0 0.
0 0.
0 5.
5 6.
8 0.
0 0.
0 0.
0 1.
3 14
.6
Amar
anth
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2.3
2.1
2.0
1.3
5.8
1.6
4.7
0.0
3.0
1.4
24.2
A
mar
anth
us
spin
osus
1.
9 7.
6 2.
0 2.
5 8.
9 5.
8 4.
3 0.
0 3.
1 1.
0 37
.2
Andr
opog
on g
ayan
us
2.7
3.2
2.0
2.3
3.0
6.2
3.2
3.0
1.3
2.5
29.4
Aspi
lia a
frica
na
0.0
0.0
2.8
1.2
0.0
0.0
4.6
0.0
4.8
5.8
19.2
Asys
tasi
a gi
gant
ica
4.3
4.6
5.5
1.8
0.0
0.0
2.7
0.0
5.0
2.4
26.3
Ax
onop
us
com
pres
sus
3.9
3.5
0.0
0.0
6.0
0.0
0.0
0.0
0.0
0.0
13.3
Bam
busa
vul
gari
s 0.
0 0.
0 3.
8 0.
0 0.
0 0.
0 0.
0 0.
0 0.
0 0.
0 3.
8
Bide
ns p
ilosa
0.
0 1.
7 4.
4 1.
8 4.
4 0.
0 2.
8 3.
7 5.
6 3.
2 27
.6
Boer
havi
a di
ffusa
2.
5 3.
7 1.
9 0.
0 4.
6 0.
0 3.
7 3.
8 4.
8 3.
1 28
.0
Bra
chia
ria
lata
5.
4 5.
0 6.
6 7.
4 5.
4 5.
5 3.
5 3.
7 2.
7 9.
3 54
.5
Bra
chia
ria
defle
xa
18.2
0.
0 5.
2 7.
4 0.
0 0.
0 5.
9 6.
4 6.
5 11
.8
61.4
C
alop
ogon
ium
m
ucun
oide
s 6.
0 4.
5 3.
6 1.
2 4.
5 0.
0 6.
5 7.
0 5.
5 9.
2 48
.0
Cas
sia
mim
osoi
des
3.3
1.6
3.8
2.0
0.0
0.0
3.2
4.6
2.0
3.0
23.6
Cas
sia
occi
dent
alis
6.
5 5.
0 4.
2 0.
0 0.
0 0.
0 3.
0 1.
6 0.
0 0.
0 20
.3
110
Cas
sia
siam
ea
5.7
3.9
0.0
0.0
4.6
0.0
6.2
0.0
2.8
0.0
23.2
C
entr
osem
a pu
besc
ens
3.9
3.8
2.7
8.2
0.0
9.0
0.0
5.9
5.0
4.6
43.2
Cer
atop
hyllu
m
dem
ersu
m
1.0
0.0
0.0
3.8
0.0
0.0
0.0
0.0
0.0
0.0
4.9
Chr
omol
aena
od
orat
a 0.
0 6.
9 7.
1 0.
0 6.
8 9.
0 12
.2
10.9
13
.7
9.0
75.5
Cle
ome
rutid
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rma
3.3
2.0
2.3
2.5
0.0
0.0
4.0
0.0
4.4
2.8
21.3
C
oix
lacr
yma-
jobi
0.
0 0.
0 0.
0 13
.6
15.3
24
.1
0.0
0.0
0.0
0.0
53.0
Col
ocas
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cule
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6.
1 2.
8 0.
0 0.
0 4.
0 5.
1 1.
9 0.
0 2.
4 1.
9 24
.2
Com
bret
um h
ispi
dum
0.
0 0.
0 3.
8 0.
0 0.
0 1.
4 0.
0 0.
0 0.
0 0.
0 5.
3 C
omm
elin
a be
ngha
lens
is
0.0
4.6
3.9
4.0
3.7
0.0
4.0
5.6
6.7
5.1
37.6
Com
mel
ina
erec
ta
0.0
0.0
0.0
0.0
0.0
0.0
2.7
0.0
2.3
13.5
18
.5
Com
mel
ina
sene
gale
nsis
0.
0 0.
0 5.
3 0.
0 0.
0 0.
0 0.
0 0.
0 0.
0 0.
0 5.
3
Cuc
umis
sativ
us
0.0
2.8
2.3
0.0
2.2
0.0
2.0
1.2
0.9
0.9
12.3
Cym
bopo
gon
citr
atus
0.
0 0.
0 2.
2 1.
0 0.
0 0.
0 1.
7 0.
0 2.
1 1.
7 8.
7
Cyn
odon
dac
tylo
n 11
.6
2.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
13.8
Cyp
erus
alte
rnifo
lius
3.1
2.0
2.7
6.3
0.0
3.6
4.3
4.2
5.6
4.1
36.0
C
yper
us c
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s 2.
1 2.
9 3.
0 0.
0 0.
0 0.
0 6.
6 5.
9 6.
8 4.
6 31
.7
Cyp
erus
esc
ulen
tus
3.2
3.1
5.4
7.9
8.2
3.0
7.8
6.0
4.6
5.5
54.7
C
yper
us
long
ibra
ctea
tus
2.1
1.6
1.7
4.1
4.9
5.0
7.8
6.8
4.2
1.8
40.0
Cyp
erus
rotu
ndus
3.
9 2.
8 4.
1 4.
5 4.
4 0.
0 5.
6 5.
3 2.
0 5.
8 38
.2
Cyp
erus
stri
gosu
s 5.
0 0.
0 1.
7 4.
7 0.
0 0.
0 4.
6 4.
8 3.
4 5.
5 29
.8
Des
mod
ium
ad
scen
dens
0.
0 8.
0 3.
1 0.
0 0.
0 0.
0 3.
1 1.
8 4.
0 2.
2 22
.2
Echi
noch
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colo
num
2.5
1.2
0 0
0 0
0 0
1.8
0 5.
5 Ec
hino
chlo
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flora
5.
9 3.
1 2.
2 9.
2 0.
0 0.
0 5.
4 3.
2 4.
5 0.
0 33
.6
Eclip
ta a
lba
0.0
0.0
2.7
8.4
0.0
0.0
3.0
2.0
2.4
2.1
20.6
E
leus
ine
indi
ca
6.3
5.7
2.4
4.7
10.5
0.
0 4.
1 7.
1 3.
6 3.
1 47
.5
111
Euph
orbi
a he
tero
phyl
la
0.0
0.0
2.7
1.3
5.1
8.8
4.5
4.7
5.5
5.7
38.1
Fleu
rya
aest
uans
3.
4 2.
7 3.
1 1.
4 4.
4 0.
0 2.
3 4.
3 3.
9 3.
1 28
.7
Glin
us o
ppos
itifo
lius
0.0
0.0
2.0
3.3
0.0
0.0
0.0
0.0
0.0
0.0
5.3
Gom
phre
na
celo
sioi
des
3.4
3.6
1.0
1.1
0.0
0.0
3.7
0.0
2.1
0.0
15.0
Hel
iotr
opiu
m
indi
cum
6.
1 9.
3 0.
8 0.
0 0.
0 0.
0 0.
0 0.
0 0.
0 0.
0 16
.2
Hyd
role
a gl
abra
0.
0 0.
0 0.
0 7.
7 0.
0 0.
0 0.
0 0.
0 0.
0 0.
0 7.
7
Hyp
arrh
enia
rufa
3.
6 3.
3 2.
4 2.
5 2.
7 4.
1 3.
1 4.
2 3.
1 2.
3 31
.2
Impe
rata
cyl
indr
ica
3.1
3.7
3.4
7.0
6.0
3.7
2.2
2.8
2.2
6.2
40.4
Ip
omoe
a aq
uatic
a 0.
0 0.
0 0.
0 14
.0
0.0
0.0
0.0
0.0
0.0
0.0
14.0
Ip
omoe
a as
arifo
lia
5.4
4.6
0.0
0.0
8.0
9.8
0.0
7.0
0.0
2.4
37.2
Ipom
oea
cair
ica
0.0
1.0
2.9
0.0
0.0
0.0
5.1
3.8
4.3
5.4
22.4
Ip
omoe
a ca
rnea
0.
0 13
.7
2.6
0.0
0.0
0.0
0.0
0.0
0.0
0.0
16.2
Ipom
oea
invo
lucr
ata
0.0
2.3
2.7
5.3
5.8
6.7
7.0
4.6
4.0
3.6
41.7
Ip
omoe
a m
auri
tiana
0.
0 3.
6 0.
9 1.
2 2.
3 0.
0 2.
3 2.
4 7.
3 4.
0 24
.0
Ipom
oea
subl
obat
a 0.
0 0.
0 0.
0 0.
0 0.
0 0.
0 4.
9 5.
1 5.
3 3.
3 18
.7
Just
icia
flav
a 0.
0 0.
0 3.
3 1.
4 3.
9 0.
0 3.
3 2.
5 3.
0 3.
1 20
.5
Lem
na m
inor
16
.9
0.0
0.0
7.6
4.4
0.0
0.0
0.0
0.0
0.0
28.9
Le
ptoc
hloa
ca
erul
esce
ns
3.5
2.8
3.7
3.5
0.0
0.0
4.4
5.4
3.5
5.0
31.8
Lim
noch
aris
flav
a 1.
7 3.
0 1.
8 6.
3 0.
0 0.
0 0.
0 0.
0 0.
0 0.
0 12
.7
Ludw
igia
aby
ssin
ica
3.0
1.9
2.9
3.2
4.6
6.3
4.7
5.0
3.1
3.5
38.0
Ludw
igia
dec
urre
ns
0.0
0.0
0.0
15.9
0.
0 6.
0 0.
0 0.
0 0.
0 5.
3 27
.2
Luffa
cyl
indr
ica
2.3
0.0
1.9
0.0
0.0
3.7
2.5
4.9
3.9
2.4
21.7
M
alva
stru
m
coro
man
delia
num
0.
0 3.
5 4.
3 2.
9 0.
0 0.
0 5.
0 4.
4 3.
7 3.
6 27
.4
Mel
anth
era
scan
dens
0.
0 0.
0 3.
1 5.
1 0.
0 5.
5 4.
7 3.
9 5.
2 2.
8 30
.3
Mill
ettia
zenk
eri
1.2
1.4
3.1
2.9
2.7
5.0
5.3
2.9
5.3
2.0
31.7
M
imos
a pi
gra
0.0
0.0
6.9
1.0
0.0
0.0
0.0
0.0
0.0
5.0
12.8
Mom
ordi
ca c
hara
ntia
3.
1 3.
1 2.
9 0.
7 2.
3 4.
4 4.
5 6.
8 2.
4 3.
6 33
.7
112
Nep
tuni
a ol
erac
ea
1.7
2.3
3.1
0.0
3.3
3.3
2.7
3.1
2.2
0.0
21.6
Nym
phae
a lo
tus
0.0
0.0
0.0
3.4
0.0
0.0
0.0
0.0
0.0
0.0
3.4
Oci
mum
bas
ilicu
m
2.8
4.2
2.3
0.0
2.3
5.5
2.4
3.2
1.9
2.3
26.9
O
lden
land
ia
cory
mbo
sa
0.0
0.0
3.6
4.7
0.0
0.0
0.0
1.5
1.8
3.2
15.0
Oxa
lis c
orni
cula
ta
0.0
0.0
2.7
0.0
2.8
2.5
3.8
4.9
2.9
3.4
23.1
Palis
ota
hirs
uta
0.0
0.0
2.9
0.0
0.0
4.0
0.0
3.3
2.7
0.0
12.8
Pa
nicu
m
dich
otom
iflor
um
0.0
0.0
5.8
2.6
8.6
7.9
4.1
6.2
5.7
6.2
47.1
Pani
cum
max
imum
3.
6 4.
8 3.
3 3.
7 8.
9 9.
2 5.
7 6.
1 2.
5 5.
4 53
.2
Pasp
alum
vag
inat
um
14.9
7.
9 6.
9 10
.3
14.9
14
.7
3.8
5.0
4.9
5.9
89.2
Pent
odon
pen
tand
rus
0.0
0.0
0.0
6.6
0.0
0.0
0.0
0.0
0.0
0.0
6.6
Phyl
lant
hus a
mar
us
3.9
6.0
3.4
5.2
4.9
0.0
4.8
5.4
3.7
2.7
39.9
Phys
alis
ang
ulat
a 2.
2 4.
0 3.
9 6.
4 4.
2 5.
1 5.
3 5.
0 4.
4 3.
7 44
.2
Pith
ecel
lobi
um d
ulce
0.
0 4.
6 0.
0 0.
0 0.
0 0.
0 0.
0 0.
0 0.
0 0.
0 4.
6 Po
lygo
num
la
nige
rum
4.
4 6.
7 0.
0 0.
0 0.
0 5.
4 0.
0 0.
0 0.
0 0.
0 16
.4
Poly
gonu
m
salic
ifoliu
m
0.0
0.0
0.0
4.6
0.0
0.0
0.0
0.0
0.0
0.0
4.6
Rhy
ncho
spor
a co
rym
bosa
6.
6 0.
0 3.
9 0.
0 0.
0 9.
0 7.
3 13
.2
8.4
6.7
55.1
Rici
nus c
omm
unis
4.
1 5.
0 2.
9 0.
0 6.
0 0.
0 0.
0 0.
0 0.
0 0.
0 18
.0
Rot
tboe
llia
coch
inch
inen
sis
0.0
0.0
9.6
0.0
4.5
8.2
11.5
6.
1 9.
4 9.
3 58
.5
Schr
anki
a le
ptoc
arpu
s 0.
0 0.
0 3.
2 0.
0 0.
0 0.
0 0.
0 0.
0 3.
4 6.
8 13
.4
Scir
pus c
uben
sis
1.2
1.8
3.2
0 0
0 0
0 0
1 7.
2 Se
tari
a ba
rbat
a 0.
0 0.
0 2.
6 0.
0 3.
7 5.
9 4.
4 2.
7 6.
8 2.
6 28
.7
Seta
ria
palli
de-fu
sca
5.2
0.0
2.3
0.0
3.8
4.3
2.7
2.7
2.2
2.0
25.4
Sida
acu
ta
2.0
2.9
2.2
3.0
2.8
3.5
3.6
3.6
2.3
1.0
26.8
Sida
gar
ckea
na
2.9
3.2
2.4
0.0
5.1
3.1
4.0
4.1
2.4
2.8
30.0
Sola
num
nig
rum
3.
3 3.
4 1.
4 0.
0 2.
8 0.
0 0.
0 1.
5 3.
4 0.
0 15
.8
Sola
num
torv
um
0.0
4.3
0.0
0.0
3.1
0.0
0.0
0.0
0.0
0.0
7.3
113
Sorg
hum
ar
undi
nace
um
4.6
0.0
3.1
0.0
5.7
5.9
5.3
5.9
6.4
2.5
39.4
Spig
elia
ant
helm
ia
0.0
2.2
1.8
0.0
1.4
3.0
3.4
1.7
2.2
1.9
17.6
Sp
orob
olus
py
ram
idal
is
15.0
4.
9 4.
7 8.
0 5.
3 9.
9 3.
8 3.
3 6.
3 6.
6 67
.7
Syne
drel
la n
odifl
ora
1.1
0.0
2.0
1.0
3.9
4.9
4.4
4.0
3.2
4.1
28.7
Talin
um tr
iang
ular
e 2.
3 1.
3 2.
1 1.
3 4.
0 4.
1 1.
3 4.
3 2.
2 2.
4 25
.3
Thal
ia g
enic
ulat
a 20
.4
16.3
20
.9
0.0
20.6
0.
0 0.
0 19
.1
0.0
0.0
97.2
Th
elyp
teri
s pal
ustr
is
0.0
0.0
2.5
27.4
0.
0 0.
0 0.
0 0.
0 0.
0 0.
0 29
.9
Tria
nthe
ma
port
ulac
astr
um
2.2
2.0
1.4
0.0
2.6
0.0
1.8
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13.8
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lis
0.0
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0 0.
0 0.
0 24
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7 0.
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8 26
.0
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onia
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9.9
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onia
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0 0.
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7 6.
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tal n
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76
11
2
114
Thelypteris palustris Ipomoea carnea
Luffa cylindrica Achyranthes aspera
Thalia geniculata Coix lacryma-jobi
Photograph 3. Some high importance value wetland species in the Kumasi Metropolis (Photographs taken by Author in 2011)
115
Centrocema pubescens Typha australis
Urena lobata Cyperus alternifolius
Ipomoea aquatica Lemna minor
Photograph 4. More high importance value wetland species in the Kumasi Metropolis (Photographs taken by Author in 2011)
116
Figure 5.11. Number of species identified at the various wetland sites in Kumasi
Figure 5.12. Species richness, evenness and Shannon diversity at the study sitesin Kumasi
117
Figu
re 5
.13.
Spe
cies
div
ersi
ty in
dice
s wi
th r
espe
ct to
dis
tanc
e fr
om t
he w
ater
cha
nnel
at t
he d
iffer
ent
sam
plin
g si
tes
in K
umas
i
118
5.3.3.2 Determinants of wetland vegetation distribution in Kumasi An analysis of similarities (ANOSIM) was carried out to assess the differences or similarities
in species within and between wetlands. There were significant differences in species
composition among the wetland sites with regards to the presence or absence of surface water
at the sampling sites (Figure 5.14a). Also, species changed with increasing distance from the
water channel (Figure 5.14b). The sites could therefore be separated hydrologically and the
distribution of the species also varied according to distance from the water channel (Global
R= 0.24 and 0.37 respectively, at 1 %).
The species found from the water channel up to 10 m away were significantly different from
those found from 30 m and beyond. Typical species in these two categories were Ipomoea
aquatica, Thalia geniculata, Nymphaea lotus, Typha australis, Ipomoea asarifolia, I.
aquatica, I. carnea, Alchornea cordifolia, Thelypteris palustris, Coix lacryma-jobi, Ludwigia
decurrens, Centrocema pubescens, Limnocharis flava, Hydrolea glabra in the water channel
up to 10 m and Cynodon dactylon, Desmodium adscendens, Eleusine indica, Aspilia africana,
Vernonia cinerea, Hyparrhenia rufa, Synedrella nodiflora, Trianthema portulacastrum,
Setaria pallide-fusca, Malvastrum coromandelianum, Ipomoea sublobata, Euphorbia
heterophylla, Oxalis corniculata, Paspalum vaginatum, Eleusine indica, Sporobolus
pyramidalis, Brachiaria deflexa, B. lata, Cyperus longibracteatus, C. esculentus C.
alternifolius from 30 m and beyond. All the species found within the 10 m distance from the
water channel were also found in sampling sites that had water on the surface irrespective of
the distance. Species found about 20 m from the water channel were not significantly different
from those beyond this distance. Cyperus spp were present in various clusters in the different
sampling sites and independent of distance from the water channel or the presence or absence
of surface water.
Having found the sites to be significantly different from each other, a hierarchical cluster
analysis was used to group the sites at the different levels of similarity using the vegetation
data. The clustering was done according to the two environmental factors: presence or
absence of surface water and distance from the main water channel. The sites showed 5
distinct clusters at 28 % similarity (Figure 5.15a and b). Inspecting the two subfigures, the
sites showed a high tendency to cluster according to the presence or absence of surface water
(Figure 5.15a open triangles separate from closed triangles). The clusters were, however, not
distinct when the distance from the water channel was used as a factor for distinguishing the
119
Figure 5.14. Analysis of similarities of the community composition among wetland sites in Kumasi according to (a) presence or absence of surface water and (b) distance from the water channel
120
sampling sites (Figure 5.15b distances symbols show no consistent order). In an attempt to
find underlying reasons for the observed clustering, multidimensional scaling (MDS) was
used. The resultant MDS plot with a stress of 0.17 is shown in Figure 5.16. Apart from site
H2 which in both the hierarchical cluster and MDS plot looked like an outlier, all the other
sites stick together similar to the clusters above according to the hydrological conditions of
presence or absence of surface water. The sites were also further distinguished by their
measured environmental parameters using the MDS (Figure 5.17) and PCA (Figure 5.18). The
MDS shows that the wetlands at Family Chapel, Golden Tulip Hotel, Bekwai roundabout and
Dakwadwom are quiet similar to each other than to the others. From the PCA plots, wetlands
at Family Chapel, Golden Tulip Hotel, Bekwai roundabout and Dakwadwom were different
from the other the wetland sites in the measured environmental parameters. A total variability
of 68.1% is attributed to the PC1 and PC2 (45.7 and 22.4 % respectively). Vectors with the
strongest contributions to the first two axes mentioned above are the percentage organic
carbon, sand, soil consistency, pH, temperature, TDS and salinity.
The assumption from the objective is that the suite of measured environmental parameters are
responsible for structuring the spatial distribution of vegetation or the vice versa such that, an
ordination based on the data would always group sites the same way. In order to match biotic
to environmental patterns, the vectors with the strongest contributions to the first two axes in
the PCA are considered in the BIO-ENV procedure. The combination of variables that best
explained the distribution of the vegetation is percentage organic carbon, sand, temperature
and salinity (in decreasing order of magnitude). Looking at the measures of these important
variables in the various sites, the wetland at the KNUST Police Station has the highest amount
of organic carbon, the lowest salinity, and comparatively low values for percentage sand and
temperature. A further hierarchical step by step analysis of these best results identified
percentage of organic carbon in the soil to be the strongest abiotic factor influencing
vegetation distribution in the studied wetlands.
121
Figure 5.15. A hierarchical cluster of the community composition among wetland sites in Kumasi according to (a) presence or absence of surface water and (b) distance from the water channel (all samples standardised by totals and square root transformed)
122
Figure 5.16. A non-metric multidimensional scaling plot of the community composition among wetland sites in Kumasi using the presence or absence of surface water as a factor (All samples standardised by totals and square root transformed)
Figure 5.17. A non-metric multidimensional scaling plot of the wetland sites in Kumasi using the measured environmental parameters
123
5.4 DISCUSSION A review of literature on soils of Kumasi shows that they are generally forest ochrosols and
lithosols (Obeng, 1971; Adjei-Gyapong & Asiamah, 2000). These soils may belong to the
nitisols and acrisols in the World Reference Base for Soil Resources (Driessen et al., 2001).
Although a detailed soil analysis was not undertaken to enable wetland specific soil
classification, Adjei-Gyapong & Asiamah (2000) states that soils bordering most of the rivers
and network of streams in Ghana are either recent alluvial deposits or presently influenced by
Figure 5.18. A principal components analysis plot of the sampled wetland sites in Kumasi superimposed with vector plots (circle and lines) of the measured environmental parameters. The vector length reflects the importance of the variable’s contribution to the two principal components in relation to all possible axes and if a vector touches the circle, then none of that variable’s other coefficients in the Eigenvectors will differ from 0
124
the floods of these drainage channels and therefore classified as alluvial soils. These alluvial
soils may accumulate autochthonous materials from dying vegetation during the dry seasons
when there is reduced flow and erosive power leading to deposition of organic material at
some wetlands. According to the Driessen et al. (2001), histosols have soil material with more
than 20 % organic matter by weight. Following this definition, soils of Atonsu Sawmill and
KNUST Police Station may be considered histosols. The relatively higher percentage of
organic carbon in wetlands of Atonsu Sawmill and KNUST Police Station could be due to the
low levels pH, salinity/conductivity and dissolved oxygen which all favoured net
deposition/accumulation of organic material.
The pH and dissolved oxygen were also significantly different between the seasons. These
conditions may have caused a decrease in biotic activity in the sites and decreased
decomposition of organic matter. An initial condition of a silty-clay soil might have facilitated
the anoxic conditions leading to the accumulation of organic material. The major
anthropogenic activity in these study sites that could have affected the soil conditions is
agriculture. However, the samples were taken from points that were not under cultivation, at
least not in the recent past. The depth of penetration of the corer was closely related to the soil
textural conditions. It is therefore difficult to isolate soil influence on plant species
distribution and hence accumulation of organic material. Root penetrability and anchorage are
dependent on soil consistency and very important for plant growth (Kim, 2006). The direct
relationship between the TDS and conductivity may be due to the type and amount of
inorganic and ionized substances in the water. The quantities of these substances may be such
that their contribution to conductivity and TDS for all the sites is similar. This direct
relationship also exists with salinity. The range of values for the salinity also shows that all
the study sites are freshwater environments.
By all indices used, Kumasi is said to be polluted by the heavy metals assessed in this study.
This pollution also varies with the seasons. The seasonal differences in sediment
contamination by heavy metals could also be related to the variations in dissolved oxygen and
pH. This is because, heavy metals concentration in sediments depends not only on their inputs
but also upon the ability of the environment to retain the metals. Some factors that determine
heavy metal retention are the textural characteristics, organic matter contents, mineralogical
composition and properties of the adsorbed compounds and depositional environment of the
sediments (Chakravarty & Patgiri, 2009). The seasonal variation in dissolved oxygen and pH
could therefore explain the positive correlation between Hg, Ni, Zn, Pb with pH and Cu and
125
Cr with dissolved oxygen and the respective strong seasonal differences in concentrations of
these metals. These physicochemical conditions might be necessary for the high retention or
adsorption of these metals in the sediments. The significantly positive correlation between
these metals also demonstrates possible co-contamination from similar sources: auto
mechanic shops (car spray and mechanic shops), car wash centres, pesticides and herbicides
from vegetable farms, wood preservatives from waste wood and saw dust from the carpentry
shops, waste from tie-dye industries and vehicle emissions.
If these metals presumably had the same sources, then differences in Igeo, EF and CF values
may be due to the difference in the magnitude of input for each metal in the sediment and/or
difference in the removal or retention rates of each metal from the sediment. This may be
particularly significant due to soil differences and the rainy season when erosion washes away
precipitated and adsorbed metals. Also, the changes in physicochemical conditions could lead
to destabilisation of the adsorbed complexes leading to the measured lower concentrations in
the rainy seasons. In general, when dissolved metals from natural or anthropogenic sources
come in contact with saline water they quickly adsorb to particulate matter and are removed
from the water column to bottom sediments (Schropp & Windom, 1988). This could explain
the high metal concentrations in the sediments at Atonsu Sawmill which has relatively higher
salinity. The Kaase Guinness wetland has been modified to a storm drain and the high
salinity, even though might have increased adsorption, did not reflect in high metal
concentration in the sediment because the concrete bottom of the water channel.
Conversely, no correlations were noted between Cd, P and As with the other heavy metals
suggesting that contamination of these substances in Kumasi might be from different sources
or had a different depositional nature. Cd concentrations were generally low in all sites. This
might be from natural sources such as weathering rather than anthropogenic (Sekabira et al.,
2010). The KNUST Police Station had conditions to potentially contain high concentrations
of heavy metals: fine-grained inorganic particles of clay and natural organic substances which
could have facilitated adsorption, chelation, complex formation or direct precipitation (Gibbs,
1977). Except for P, the low levels of other metals at this site could be due to the absence of
anthropogenic activities that would have introduced such substances. The phosphorus could
be from fertilizers washed from the surrounding agricultural activities and domestic
wastewater.
Trace amounts of heavy metals are always present in fresh waters from terrigenous sources
through weathering of rocks generally at relatively low concentrations. In recent times, due to
126
the combined effects of industrialisation/transport and urbanisation, heavy metal pollution of
aquatic ecosystems is becoming a potential global problem. Ghana is fast developing along
these lines, but like other developing countries, lacks mechanisms and tools to detect and
monitor water quality. Whilst none of these water sources is being directly used for human
consumption, the measured concentrations are so high that it could easily reach humans
through the food chain. For example, these wetlands are used as grazing grounds for livestock
and it will be very necessary to check the concentrations of these metals in the surrounding
vegetation and animals grazing in such wetlands. The Ghana EPA has effluent quality
guidelines for discharges into natural waterbodies. The car wash and repair garages do not
follow these guidelines. Even with the maximum permissible levels for release of effluents
given by the Ghana EPA, heavy metals have the tendency to accumulate in sediments and will
still pollute streams as detected in Kumasi.
Typical of tropical environments, the study sites had very diverse vegetation as expressed by
the Shannon diversity and species richness (Burslem et al., 2005). However, it is difficult to
attribute these levels as a standard for describing wetlands in Kumasi because of the various
forms of disturbances that may be specific to different areas. The inverted U-shaped pattern of
species richness and Shannon diversity might be due to fewer plants adapted to the extremes
and the 30 or 40 m zone providing a more ideal intermediate environment for most species.
The intermediate disturbance hypothesis may hold true for these study sites and thus explain
the pattern of species richness and Shannon diversity (Dial & Roughgarden, 1988).
Even with this inverted U-shaped pattern, species distribution followed specific longitudinal
environmental gradients like flooded conditions (presence or absence of water on the surface).
That is, some of the species are facultative whilst others obligate wetland species. The
presence or absence of water on the surface may have caused the within wetland differences
in species composition and distribution. Since the landscape is not completely flat, it is usual
to find small high ground quadrat plot areas within a wetland that are not flooded and hence
have different species cover. It is worthy to state that, even though no two quadrat plots can
be exactly the same, the edaphic differences may not be so sharp between the quadrat plots to
produce distinct differences in species along the distances that were considered for this study.
Even though this study did not investigate obligate and facultative wetland species, the
association of important value species to flooded sites defines the very unique niches that
characterise such species in the environment. The sites of obligate high importance value
species could be delineated to define the wetland microcosms for each study site.
127
The most popular definitions of wetlands have the key words hydrological conditions and
vegetation adapted to the flooded conditions (Keddy, 2000; Maltby & Barker, 2009). Even
though the cluster analysis shows that the presence or absence of surface water best grouped
species (vegetation distribution), the species found under the different hydrologic conditions
were different for the different wetland sites. What then causes these differences in species
among wetlands in Kumasi? That is, per the definition of wetlands, places with similar
hydrologic conditions in the same area should have similar vegetation. Therefore, other
environmental conditions might be contributing to the species distribution because, the much
used definitions of Keddy (2000) and Maltby & Barker (2009) are not adequate in describing
small scale heterogeneity in the species distribution in Kumasi. The findings of this research
confirm the difficulty to delineate wetlands from a landscape (Mitsch & Gosselink, 1993;
Keddy, 2000; Haslam, 2003; Maltby & Barker, 2009). A wetland is a transition zone between
aquatic and terrestrial environments. The limits and characteristics of this environment may
therefore not be defined by only the hydrological characteristics.
Apart from hydrology, several studies show that wetland geomorphology, substratum,
chemistry, adjacent terrestrial system, grazing, anthropogenic influences and individual plant
tolerance or response to the stresses of flood and drought are significant (Harper et al., 1995;
Barrat-Segretain et al., 1998; Owen, 1999; Casanova & Brock, 2000; Fortney et al., 2004;
Maltby & Barker, 2009; Miller & Fujii, 2010). By virtue of the percentage organic carbon and
other important physiochemical parameters identified by the BIO-ENV procedure, the
wetland at KNUST Police Station can be described as a peatland (Joosten & Clarke, 2002).
The peatland conditions might also have been the defining conditions for the growth and
establishment of Thelypteris palustris not only because of its dominance there but that was the
only site in which this species occurred. Other important species that also occurred in this site
were Coix lacryma-jobi, Hydrolea glabra, Ipomoea aquatica, Ludwigia decurrens,
Centrosema pubescens and Pentodon pentandrus. These species could also be said to be well
adapted to peatland conditions. These wetlands being in urban settings, urbanisation could
also have created perturbation gradients that affect aquatic plant species (Ot’ahel’ová et al.,
2007). The landuse change due to urbanisation could have resulted in alterations in the
hydrology, autochthonous and allochthonous inputs and water chemistry of wetland areas
leading to changes in the local plant communities (Owen, 1999).
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6 CLIMATE, LANDUSE CHANGES AND FLOODING IN THE KUMASI METROPOLIS
6.1 INTRODUCTION Floods are part of the ecosystem and a natural hydrological feature of most river systems.
They provide benefits to humans through maintenance of ecosystem functioning such as
sediment and nutrient inputs to renew soil fertility in floodplains and floodwaters to fish
spawning and breeding sites (Avakyan & Polyushkin, 1989; Brinson, 1993; Casanova, 2000).
However, this important natural phenomenon causes disasters because human settlements are
getting increasingly closer to the floodplains or river channels such that communities are more
vulnerable and unprepared for these floods. Recent floods in most areas are therefore
preventable or anthropogenically induced and on a spatial and temporal increase (IPCC, 2007;
Millennium Ecosystem Assessment, 2005). On the average, 140 million people are affected
by floods each year, more than all other natural or technological disasters put together and in
addition to human lives, floods cost more than $244 billion damage from 1990 to 1999, the
most expensive of any single class of natural hazard (Millennium Ecosystem Assessment,
2005; IFRC, 2010).
Naturally, climate is dynamic. However, the world has experienced more anthropogenic
induced climate changes over the last 100 years. Observed changes include more frequent and
extreme weather events increasing the risk of flooding especially in urban areas (IPCC, 2007;
IFRC, 2010). The extent to which urban centres are vulnerable to changes in climate is
influenced by a variety of factors. However, this vulnerability could be mediated through
social and economic interventions and the ability of stakeholders and institutions to address
the challenges. Research shows that West Africa is among the most vulnerable regions to
climate change worldwide (Niasse et al., 2004; Millennium Ecosystem Assessment, 2005;
IPCC, 2007). Kumasi has experienced both landuse changes and floods in recent years. The
relationship between these floods and the landuse changes, climate variability or change has
not been investigated. This chapter therefore seeks to identify climate and landuse changes of
Kumasi and assess their influences on the current incidents of floods in some parts of the city.
The adaptations by the vulnerable suburbs to these annual floods are studied.
129
6.2 METHODOLOGY
6.2.1 Rainfall and Flood Data Collection and Analysis Monthly mean rainfall data on Kumasi from 1961 to 2010 were collected from the
Meteorological Services Department, Accra, Ghana. Basic descriptive statistics were used to
evaluate the rainfall data. The Mann–Kendall test (ZMK) was also used to determine the trends
in annual and monthly rainfall and trends in rainy days (Rodrigo et al., 2001; Modarres & da
Silva, 2007; Batisani & Yarnal, 2010). When testing either increasing or decreasing
monotonic trends at a p significance level, the null hypothesis is rejected for absolute values
of Z > Z1-p/2, obtained from standard cumulative distribution tables as 1.96. The standard
significance levels of p = 0.05 is applied. Positive values of ZMK indicate increasing trends
while negative ZMK indicate decreasing trends. The slope of the linear trend (as change per
year) was estimated with the nonparametric Sen’s method Q (Gilbert, 1987). The relationship
between total monthly and annual rainfall and number of rainy days (R≥1 mm/day) and heavy
rainfall events (R≥31 mm/day derived from an estimate of the 95th percentile of the rainfall
events of 1963 [chosen at random among first 3 years of Kumasi’s rainfall data]) was assessed
using correlation. This was to assess if Kumasi’s rainfall is explained more by the total
number of days with rain or by individual heavy rainfall events.
The data on flooding in Kumasi was obtained from the Ashanti Regional Office of the
National Disaster Management Organisation (NADMO). Extra data on the frequency and
duration of floods and extent of damage due to flooding was gathered through focus group
discussions, interviews and questionnaires administered to the affected communities in
Kumasi as described in Section 3.2.2. During the field visits and administration of
questionnaires and interviews, effort was made to identify and understand practices in dealing
with floods. This involved looking out for, noting and recording of behaviours, adaptations,
practices and activities related to flooding and life in slum or informal environments.
6.2.2 Assessment of Urbanisation of Kumasi Urbanisation was assessed by determining the landcover change of Kumasi. Landsat images
of Kumasi (at path 194, row 055) were collected from the landsat website www.landsat.org.
In order to minimise problems related to vegetation phenology, only images acquired during
the dry season were used. These images were captured on 11th January, 1986 and 13th
January, 2007.
130
Various image enhancement and classification techniques were performed to help with the
identification of the landcover types and changes using Leica Geosystems Erdas Imagine 9.2.
A hybrid of supervised and unsupervised classification techniques was performed on the
satellite images. The method was evaluated for accuracy using field verified landmarks with a
GPS. For each study site, the spatio-temporal changes in vegetation cover were estimated.
The final results of the classified image data and change thematic layer were further processed
into maps in ARC-GIS 9.3 environment.
6.3 RESULTS
6.3.1 Rainfall Patterns and Trends in Kumasi
6.3.1.1 Rainfall pattern in Kumasi The annual rainfall pattern of Kumasi is weakly bimodal (Figure 6.1). The first and major
rainy season starts from a relatively dry period in January with an average rainfall of 18.9 mm
and peaks in June with an average of 211.7 mm. The second starts from August with an
average rainfall of 87.7 mm and peaks at an average of 168.9 mm in September and drops to
an average of 23 mm in December. The average annual rainfall of Kumasi was 1372.5 mm
(Figure 6.2). Even though the highest average rainfall occurred in June, the highest monthly
total rainfall ever recorded was 534.5 mm in September, 2007 and the lowest and highest
annual rainfalls were 891.3 and 2345.1 mm in 1982 and 1968 respectively.
The descriptive statistics of the rainfall of Kumasi from 1961 to 2010 is presented in Table
6.1. Within these 50 years, there were 15 January months and 6 December months without
rainfall. All the other months always had rainfall. The months with the highest variability in
rainfall distribution were those between April and October. The rainfall distribution for these
months was also characterised by relatively high coefficients of variation and mostly positive
values for skewness and kurtosis. The rainfall distribution for August and September was
significantly peaked over the normal distribution (kurtosis of 6.98 and 5.50 respectively). All
the monthly rainfall distributions had positive skew values. That is, several extreme rainfall
values lie to the right of the mean. Skewness for August was the highest (2.06).
131
Figure 6.1. Average monthly rainfall pattern of Kumasi from 1961 to 2010
year
1960 1970 1980 1990 2000 2010
Ann
unal
rain
fall
(mm
)
800
1000
1200
1400
1600
1800
2000
2200
2400
2600
Figure 6.2. Historical annual rainfall pattern of Kumasi from 1961 to 2010
0
50
100
150
200
250
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
Aver
age
rain
fall
(mm
)
month
1372.5
132
Table 6.1. Descriptive statistics of monthly rainfall pattern of Kumasi from 1961 to 2010
Variable Minimum Maximum Mean Std. Deviation Variance Skewness Kurtosis Mann–
Kendall Z Sen’s
slope Q January 0 111 18.92 25.85 668.05 1.52 1.97 0.00 0.000 February 1 135 55.75 40.03 1602.44 0.43 -0.92 -1.31 -0.546 March 36 310 119.12 53.61 2874.49 1.21 2.31 -2.44 -1.200 April 45 311 146.32 64.54 4165.61 0.80 0.03 0.90 0.631 May 46 307 174.79 63.93 4086.88 0.43 -0.56 -1.15 -0.715 June 41 377 211.73 83.00 6889.14 0.26 -0.66 -0.47 -0.490 July 18 446 146.62 98.14 9630.74 1.10 1.20 -0.74 -0.562 August 7 400 87.70 69.71 4859.20 2.06 6.98 0.49 0.304 September 15 535 168.89 87.10 7586.15 1.80 5.50 0.00 -0.004 October 43 336 156.12 63.55 4038.46 0.77 0.73 -0.50 -0.378 November 3 213 62.38 47.33 2240.15 1.20 1.24 -2.90 -1.145 December 0 116 26.40 26.60 707.48 1.37 1.81 -0.26 -0.025
6.3.1.2 Rainfall trends in Kumasi From the results of the nonparametric Mann-Kendall (Z) and Sen’s slope (Q) methods, it was
not possible to generalise either an increasing or a decreasing trend for the given set of data
(Figures 6.3 to 6.15.). Rainfall for January and September showed no changes (Z=0, Q=0).
Rainfall in April and August were increasing whilst that for February, May, June, July,
October and December was decreasing. In both instances above, the trends were not
significant. Only rainfall for March and November had decreased significantly over the period
(Z= -2.44, Q= -1.20 and Z=-2.90, Q= -1.15 respectively at α=0.05). That is, the average
rainfall for these two months was decreasing at 1.20 and 1.15 mm per year respectively. The
annual total rainfall was also decreasing although not significant (Z= -0.89, Q= -0.59).
133
-20
0
20
40
60
80
100
120
1960 1970 1980 1990 2000 2010
tota
l rai
nfal
l (m
m),
Jan
Year
Data
Sen's estimate
95 % conf. min
95 % conf. max
Residual
-100
-50
0
50
100
150
1960 1970 1980 1990 2000 2010
tota
l rai
nfal
l (m
m),
Feb
Year
Data
Sen's estimate
95 % conf. min
95 % conf. max
Residual
Z= 0.00 Q= 0.00
Z= -1.31 Q= -0.55
Figure 6.3. Trends in rainfall of Kumasi for the months of January from 1960 to 2010
Figure 6.4. Trends in rainfall of Kumasi for the months of February from 1960 to 2010
134
-100
-50
0
50
100
150
200
250
300
350
1960 1970 1980 1990 2000 2010
tota
l rai
nfal
l (m
m),
Mar
Year
Data
Sen's estimate
95 % conf. min
95 % conf. max
Residual
-150
-100
-50
0
50
100
150
200
250
300
350
1960 1970 1980 1990 2000 2010
tota
l rai
nfal
l (m
m),
Apr
Year
Data
Sen's estimate
95 % conf. min
95 % conf. max
Residual
Z= 0.90 Q= 0.63
Figure 6.5. Trends in rainfall of Kumasi for the months of March from 1960 to 2010
Figure 6.6. Trends in rainfall of Kumasi for the months of April from 1960 to 2010
Z= -2.44* Q= -1.20
135
-150
-100
-50
0
50
100
150
200
250
300
350
1960 1970 1980 1990 2000 2010
tota
l rai
nfal
l (m
m),
May
Year
Data
Sen's estimate
95 % conf. min
95 % conf. max
Residual
-200
-100
0
100
200
300
400
500
1960 1970 1980 1990 2000 2010
tota
l rai
nfal
l (m
m),
Jun
Year
Data
Sen's estimate
95 % conf. min
95 % conf. max
Residual
0
Z= -0.47 Q= -0.49
Figure 6.7. Trends in rainfall of Kumasi for the months of May from 1960 to 2010
Figure 6.8. Trends in rainfall of Kumasi for the months of June from 1960 to 2010
Z= -1.15 Q= -0.72
136
-200
-100
0
100
200
300
400
500
1960 1970 1980 1990 2000 2010
tota
l rai
nfal
l (m
m),
Jul
Year
Data
Sen's estimate
95 % conf. min
95 % conf. max
Residual
-100
0
100
200
300
400
500
1960 1970 1980 1990 2000 2010
tota
l rai
nfal
l (m
m),
Aug
Year
Data
Sen's estimate
95 % conf. min
95 % conf. max
Residual
Figure 6.9. Trends in rainfall of Kumasi for the months of July from 1960 to 2010
Figure 6.10. Trends in rainfall of Kumasi for the months of August from 1960 to 2010
Z= 0.49 Q= 0.30
Z= -0.74 Q= -056
137
-200
-100
0
100
200
300
400
500
600
1960 1970 1980 1990 2000 2010
tota
l rai
nfal
l (m
m),
Sept
Year
Data
Sen's estimate
95 % conf. min
95 % conf. max
Residual
-150
-100
-50
0
50
100
150
200
250
300
350
400
1960 1970 1980 1990 2000 2010
tota
l rai
nfal
l (m
m),
Oct
Year
Data
Sen's estimate
95 % conf. min
95 % conf. max
Residual
Z= -0.50 Q= -0.38
Figure 6.11. Trends in rainfall of Kumasi for the months of September from 1960 to 2010
Figure 6.12. Trends in rainfall of Kumasi for the months of October from 1960 to 2010
Z= 0.00 Q= 0.00
138
-100
-50
0
50
100
150
200
250
1960 1970 1980 1990 2000 2010
tota
l rai
nfal
l (m
m),
Nov
Year
Data
Sen's estimate
95 % conf. min
95 % conf. max
Residual
-40
-20
0
20
40
60
80
100
120
140
1960 1970 1980 1990 2000 2010
tota
l rai
nfal
l (m
m),
Dec
Year
Data
Sen's estimate
95 % conf. min
95 % conf. max
Residual
Z= -2.90** Q= -1.15
Figure 6.13. Trends in rainfall of Kumasi for the months of November from 1960 to 2010
Figure 6.14. Trends in rainfall of Kumasi for the months of December from 1960 to 2010
Z= -0.26 Q= -0.03
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6.3.2 Floods in Kumasi
6.3.2.1 Scope and frequency of floods in Kumasi The first rainy peak of the year (May, June and July) has always been associated with floods
in some parts of Kumasi. For the purposes of this study, the definition of flood events by
NADMO as occasions when water from e.g. rainfall events covered temporarily land outside
the limits of the river banks, which is not normally covered, is adopted. Table 6.2 is an extract
of rainfall events that have been reported to have caused floods and documented by the
NADMO Office in Kumasi for June 2009. Except for the flood that occurred on 9th June,
2009, all others occurred during/after heavy rainfall events (R≥31 mm/day). None of the
antecedent rainfall events was heavy. June and July were the months with the most reported
incidence of floods. The flood experience of the residents from the suburbs that are being
studied is shown in Figure 6.16. All respondents in Aboabo and Ahensan had had their homes
flooded before. In the other suburbs, depending on the distance of a house to the water
channel and length of stay of the respondent in the suburb, he/she might have experienced
floods or not. In general, residents who have lived longer than 10 years in the various suburbs
claim the floods are a recent phenomenon.
The relationship between rainy days, heavy rainfall events and the total monthly rainfall was
assessed by correlation. The rainfall of Kumasi was observed to be influenced by both number
-1000
-500
0
500
1000
1500
2000
2500
1960 1970 1980 1990 2000 2010
tota
l ann
ual r
ainf
all (
mm
)
Year
Data
Sen's estimate
95 % conf. min
95 % conf. max
Residual
Z= -0.89 Q= -2.34
Figure 6.15. Trends in total annual rainfall of Kumasi from 1960 to 2010
140
of rainy days and heavy rainfall events (Figure 6.17). However, total monthly rainfall was
found to be explained more by heavy rainfall events than the number of rainy days in the
month (85 % and 72 % of variance in common between heavy rainfall events and rainy days
with total rainfall respectively). A trend analysis of heavy rainfall events is presented in
Figure 6.18. Annual heavy rainfall events are increasing in trend, although not significant (Z=
0.45, Q=0.00). The heavy rainfall trends for the two flood prone months of June and July are
varied. Whilst the heavy rainfall events are decreasing for June (Z= -0.78, Q= 0.00), that for
July is increasing (Z= 0.91, Q= 0.00).
Table 6.2. Rainfall events and reported floods in some suburbs of Kumasi in 2009
Figure 6.16. Respondents’ flood experience in the various suburbs of Kumasi
Flood conditions Antecedent conditions Flood date Amount of
rainfall (mm) Flood location Date of last
rainfall Amount of rainfall (mm)
09/06/2009 27.8 Aboabo, Anloga, Oforikrom, Ahensan,
Kwadaso Estates, Dakwadwom, Sisaso,
Atonsu
08/06/2009 3.1 11/06/2009 60.4 10/06/2009 0.1 15/06/2009 43.3 13/06/2009 19.1 26/06/2009 90.3 25/06/2009 17.3 04/07/2009 53.4 03/07/2009 12.8 09/07/2009 72.7 08/07/2009 27.6
141
Figure 6.17. Relationship between different rainfall events and total monthly rainfall for Kumasi from 1961 to 2010
R2=0.72
R2=0.85
142
-10
-5
0
5
10
15
20
25
1960 1970 1980 1990 2000 2010
tota
l hea
vy r
ainf
all e
vent
s in
the
year
Year
DataSen's estimate95 % conf. min95 % conf. maxResidual
-4
-2
0
2
4
6
8
10
1960 1970 1980 1990 2000 2010heav
y ra
infa
ll ev
ents
in Ju
ne
Year
DataSen's estimate95 % conf. min95 % conf. maxResidual
-3
-2
-1
0
1
2
3
4
5
6
7
1960 1970 1980 1990 2000 2010heav
y ra
infa
ll ev
ents
in Ju
ly
Year
DataSen's estimate95 % conf. min95 % conf. maxResidual
Figure 6.18. Trends in heavy rainfall events in Kumasi from 1961 to 2010
Z= 0.45 Q= 0.00
Z= -0.78 Q= 0.00
Z= -0.13 Q= 0.00
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6.3.2.2 Adaptations to floods in Kumasi All the suburbs considered have experienced floods at one time or the other. The location of
respondents’ houses influenced their estimation of the number of days the flood waters take to
recede in the suburbs (Figure 6.19). The predominant number of days the people live under flood
conditions was more than 20 days in a year for all the suburbs. For some suburbs like Ahensan,
Atonsu and Dakwadwom, it took more than one month for the water to recede. The estimation
of the loss was usually astronomical and varied depending on the interest and capacity of the
person or institution making the estimate. These losses have however been increasing year
after year.
Several coping strategies have been identified in the various suburbs (Figure 6.20). Each
strategy is used in combination with the others. The most popular strategies are fetching or
pumping out of flood waters and the creation of channels to facilitate the flow of the water.
Respondents who do nothing in these flood situations (about 25% of the time) are usually the
very young and the aged. Respondents of Kwadaso Estates and Spetinpom have relatively
higher educational backgrounds and, almost 75% of the time, more likely to complain to city
authorities.
There are also individual and community adaptations to floods (Figure 6.21). The action a
resident took depended on previous experiences of flood and length of stay within the community. Most new rent paying tenants of these suburbs do not to know that the houses are
flood prone. The first time experience of flood is usually that of shock and annoyance at the
non-disclosure that the house is flood prone. Coping strategies of such persons to the flood are
usually egocentric e.g. victims attempt to retrieve their rent (rent is usually paid 2 to 5 years in
advance); move valuables and or relocate till the conditions improve; seal vents or build
embankments around apartment (Photographs 5,6,7 and 8), complete relocation of property; and
to complain to the city authorities. Most of these individual efforts often result in conflicts
between the person and the landlord or neighbours. Some of the conflict issues were
disagreements on the direction of a new drainage channel created by the individual;
perception of individual not participating in communal efforts; or perception of the individual
being proud. Residents who have lived in these suburbs for a while respond differently to the
floods: they are more accommodating of the landlords and employ more communal adaptations to
the floods e.g. participation in the construction of new drainage channels; (re)dredging of streams;
landlords build embankments around houses; construction of networks of raised walkways to
the various houses or compounds.
144
Figu
re 6
.19.
Rec
essi
on t
ime
of w
ater
at
the
vario
us fl
ood
pron
e su
burb
s of
Kum
asi
Figu
re 6
.20.
Ada
ptat
ions
of
resi
dent
s to
flo
ods
in t
he v
ario
us
subu
rbs
of K
umas
i
Suburb is flooded
individual
� Move residence to new location � Retrieve their rent � Relocate till water subsides � Complain to authorities � Fetch/pump water out of room or
house � Seal water ways and build
embankments around room or house
community
� Things will improve here � God will take care of things. It will
not always be bad � Construct bigger drainage channels
in the neighbourhood � Dredge river/stream channel � Build higher embankments around
house � Do nothing
� Moved out or started to behave like an old resident
� Moved out or started to behave like an old resident
� Construct drainage channels in the neighbourhood
� Dredge river/stream channel � Build embankments around house � Build houses on stilts � Improve on our houses � Do nothing
� Move things to higher grounds � Construct drainage channels in the
neighbourhood � Dredge river/stream channel � Build embankments e.g. with sand
bags or ridges � Fetch/pump water out of room or
house � raised walkways of block and wood � Do nothing
First year (Y)
Next year (Y+1)
Subsequent years (Y+1+2+…n)
New resident Old resident and homeowners
Figure 6.21. Flood response model of new and old residents of flood prone suburbs ofKumasi
conflict
146
In most of these flood prone suburbs, the chiefs and assemblymen harness local labour and
capacity into building walkways, footbridges, drains etc. The public institutions usually
provide some assistance in times of flood. NADMO may provide relief items depending on
the availability of funds and number of people who have been affected. This is also the time
that the KMA and NADMO mostly carry out their public education on floods. The major
flood management strategy of the KMA is the engineering approach. For example, a storm
drain is being constructed on the Aboabo River spanning through Anloga, Asokwa and
Ahensan to Atonsu. In other places, the KMA does desilting, dredging and removal of
structures within the waterways to improve flow of the water.
6.3.3 Landcover Change in Kumasi Landcover change was used as a proxy to assess urbanisation of Kumasi. To do this, it was
assumed that there are two possible landcover types: the land is either covered with vegetation
or built-up and bare areas. The landcover change from vegetated to built-up and bare areas is
shown in Figure 6.22. In 1986, the land area currently under the jurisdiction of the KMA was
about 80 % covered by vegetation. The remaining land area was either built up or bare e.g.
public spaces, construction sites, roads, newly cleared farmlands etc. Land areas adjacent
streams were largely vegetated (Schmidt, 2005; KMA, 2006). The major vegetated
continuums in 1986 were in the eastern and the southern corridors stretching from Asokore
Mampong to Deduako and the north western corridors from Ohwim to Tanoso. Typical built-
up or bare areas were Central Kumasi stretching towards Suame, Airport, Atonsu, Santasi and
Kwadaso. Built-up or bare areas beyond these suburbs were settlements located along the
major routes leading out of Kumasi. By 2007, the vegetated areas within the KMA had
reduced from 80 % to 50 %. The remaining major vegetation patches were at KNUST,
Dakwadwom, Nyankyereniase and the south eastern land area beyond Emena. Vegetation
cover along stream banks had also reduced. That is, the bare and built-up areas had been
growing at about 1.9 % per annum between 1986 and 2007.
147
Figure 6.22. Landcover changes within the jurisdiction of the Kumasi Metropolitan Assembly between 1986 and 2007
148
Photograph 5. House being built on stilts in a flood prone suburb in the Kumasi Metropolis (Photograph taken by Author in 2011)
Photograph 6. Raised walkways in the compound of a flood prone house in the Kumasi Metropolis (Photograph taken by Author in 2011)
149
Photograph 7. Embankment built around a flood prone house in the Kumasi Metropolis (Photograph taken by Author in 2011)
Photograph 8. Embankment built around the main door to an apartment in a flood prone suburb of the Kumasi Metropolis (Photograph taken by Author in 2011)
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6.4 DISCUSSION The seasonal rainfall cycle of Ghana shows a progressive shift from an all-year-round or two
distinct rainy seasons from the coast to a single rainy season in the north. The results for
Kumasi located around latitude 6°N show two distinct rainy seasons with a lower second
peak. This is because the rainfall in Kumasi is dependent on convection following the
movements of the ITCZ as the dominant mechanism producing rain (Barbé et al., 2002). After
September, the ITCZ is receding and there is less penetration of moisture laden winds to
cause rainfall, hence the weaker second peak. The high variations in rainfall of the rainy
seasons may be due to inconsistencies in quantity and temporal distribution in the rainfall as
shown by the skewness and kurtosis of the rainfall data. Positive skew values mean that the
larger proportions of the rainfall for those months are a result of extreme rainfall events
(Barbé et al., 2002; Modarres & da Silva, 2007; Batisani & Yarnal, 2010). The statistical
results for July, August and September which are the peaks of the rainy season and floods in
Kumasi are therefore not surprising and therefore due to heavy rainfall events as proven by
the correlation analysis. Even though this analysis did not consider time between rainfall
events, the antecedent conditions, as in date of last rainfall event, could have affected the
probability of occurrence and duration of floods.
Apart from January and September, all months experienced a change in rainfall, albeit, most
of them not significant. March and November are the only months with significant decrease in
rainfall at a rate of 1.2 and 1.15 mm/annum respectively. According to Ghana’s Initial
National Communication to the IPCC in 2000, Ghana’s annual rainfall was found to have
decreased by 20% in the past 30 years (Ghana Environmental Protection Agency, 2001). Even
though total rainfall for Kumasi may be decreasing (albeit, not significant), the change is less
than the national figure reported by the EPA. However small it is, this change in can modify
some elements of the water cycle in Kumasi: the frequency and intensity of precipitation,
evapotranspiration, soil moisture, groundwater recharge and runoff (Fedeski & Gwilliam,
2007; Ramsar Convention Secretariat, 2008). Due to the relatively short period of the
available data (50 years), it is difficult to draw conclusions on trends which may only end up
being natural variability in rainfall. Because of this shortfall in the data, these results may
therefore have to be validated by other climate models to draw stronger conclusions on
climate change and rainfall trends in Kumasi.
The rate of growth of bare and built up areas in Kumasi could be a proxy measure of the rate
of urbanisation. The built-up and bare areas within the KMA have been growing at a rate of
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1.9 % per annum in the past two decades. The total population of Kumasi more than doubled
within this period. The associated anthropogenic removal of vegetation and soil compaction,
e.g. for housing and road constructions resulting from this growth, could decrease infiltration
of rainwater and increase overland flow to cause the recent floods. It is now known that the
most widespread serious potential impact of climate change on human settlements is flooding
(Dazé, 2007; Fedeski & Gwilliam, 2007; IPCC, 2007; Wilby, 2007; International Recovery
Platform, 2009; McClean, 2010). However, from the results obtained, flooding as being
experienced in Kumasi is may not be the result of climate change in June and July but wrong
urban spatial planning and management. The growth of Kumasi is not accompanied by
development of sustainable urban drainage systems and waste management systems with
enough system capacity or sophistication to avoid being overwhelmed by the increased
overland flow. These are aggravated by multiple stresses and low adaptive capacities arising
from endemic poverty and weak institutions (United Nations Inter-Agency Secretariat of the
International Strategy for Disaster Reduction, 2005; Satterthwaite, 2003, 2008).
Even though the floods occurred during or after heavy rainfall events, the relatively long time
it takes for the flood waters to recede may indicate that not all the floods are flash floods or
due to heavy rainfall events. These suburbs are sited on lands, hitherto, considered as
wetlands. This is evidenced by the prevalence and dominance of vegetation adapted to
growing in wetlands (see section 5.3.3). The experiences of these flood prone neighbourhoods
are, therefore, consequences of the spread of physical urban developments into wetlands.
Surface compaction due to urbanisation may increase overland flow and produce flash floods
as described by Griggs & Paris (1982) and the United Nations Inter-Agency Secretariat of the
International Strategy for Disaster Reduction (2005). However, the rising of the water table
during the rainy season (peaking in June) creates a network of effluent streams in large parts
of these suburbs. The heavy rainfall events recorded each year trigger the flow and duration of
these effluent streams. Effluent streams, rather than flash floods, best explain the delay of the
flood waters in drying out from the neighbourhoods. Also, the dense networks of raised
walkways and drainage channels could only be an adaptation to effluent stream flows rather
than flash floods. From the above arguments, these events in those neighbourhoods should not
be considered as floods contrary to the KMA’s definition of floods. This is because, even
though the areas are inundated, the water is very much expected.
It is widely reported that a large and growing number of people are at high risk of adverse
ecosystem changes because of the worsening trend of human suffering and economic losses
152
from floods (ActionAid International, 2006; Fedeski & Gwilliam, 2007; IPCC, 2007; Nelson
et al., 2009). The ecosystem change as a result of the unmanaged urbanisation of Kumasi may
increase the losses to floods. The scale of the risk, extent of vulnerability and losses from
these flood events is much influenced and increased by the poor quality of housing and
infrastructure in Kumasi, the lack of planning and enforcement of wetland management plans
and the low level of preparedness among the city’s population and key emergency services.
The flood prone suburbs have relatively higher human population and densities (Ghana
Statistical Service, 2005) and higher demand for wetland services per person, therefore,
making the human and ecological impacts of flooding more serious.
Also, these flood prone suburbs are predominantly inhabited by the urban poor and new rural-
urban immigrants. Even though there is no spatial poverty profile of the residents of Kumasi,
the physical location and characteristics of the poor are undeniably obvious in the housing
landscape: an agglomeration of dilapidated structures without social infrastructure and
amenities. It is however surprising that estimated economic losses from the floods keep rising
year after year irrespective of the scale of the floods. Because the type and quality of houses
identified in these suburbs are among the worst in the city, these reported increases in losses
may be due to improvement in the economic conditions of these slum residents leading to
increase in acquisition of precious and capital goods and services which may easily be
destroyed by the floods. However, after living in such environments for several years, the
residents adapt very much and losses are supposed to be very minimal except for some off-
season large scale flash floods. Also, there is usually the perception and anticipation of help or
a craving for public sympathy by these victims and therefore the tendency to exaggerate their
losses. Either way it is difficult to independently verify these claims or accurately estimate the
value of properties destroyed by floods in Kumasi.
In recent years, the notion of adaptation has become a significant component of climate
change literature and international negotiations on climate (Niasse et al., 2004; World
Meteorological Organisation, 2006; Intergovernmental Panel on Climate Change, 2007;
Ireland, 2010). However, small scale adaptations by individuals and communities in informal
settlements have not been given attention. What is reported in this study are individual and
communal coping strategies rather than proactive and concerted efforts by city authorities at
managing floods. After several years of stay, residents might have developed strong economic
and social ties in the community and are therefore more reluctant to move out than the new
community entrants. The choice to remain therefore transcends the push effect of annual
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floods. A key consideration in the adaptation debate should therefore be on the small scale
adaptation efforts and coping strategies of residents of mostly informal settlements who are
most hit by floods. In addition, most of the flood victims have problematic relationships with
the KMA because their houses have either been marked for demolition or they have no
building permits. Yet the KMA is to act with all stakeholders to reduce these risks. In the light
of the increasing urbanisation, the actions of the KMA must be to increase its efforts at not
only re-engineering the city but also dialogue and enforcement of spatial plans and building
regulations to reduce the proliferation of these informal settlements and preserve the
demarcated buffer zones of streams within its jurisdiction.
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7 GENERAL DISCUSSION, CONCLUSIONS AND RECOMMENDATIONS
7.1 GENERAL DISCUSSION The state of the urban environment in Ghana is undeniably unacceptable. On the one hand,
chiefs, landowners and local government agencies do not coordinate their efforts in spatial
planning, and on the other, urban residents are overwhelmed with their own waste. The result
is that waste is disposed of in any available “free” space, mostly wetlands. Urban wetland
communities therefore bear the full brunt of filth and floods. Cleanliness may be deemed a
virtue. However, this virtue needs to be reinforced and promoted through conscious efforts by
all stakeholders. Whilst residents of Kumasi may be consciously interested in maintaining a
clean environment, it behoves the responsible stakeholders to provide the much needed public
services to enable residents carry out this civic responsibility. Waste disposal in streams and
wetland areas could therefore be a thing of the past if the appropriate spatial planning and
waste management approaches are implemented.
The consequences of urbanisation in developed and developing countries have been very
much described. The KMA does not have to make all the mistakes that have been described or
experienced by other cities elsewhere. There is still a window of opportunity for the KMA to
avert this doom by harnessing the interest of the current King of Ashanti (Asantehene),
Otumfuo Osei Tutu II, in its environmental management agenda. The Asantehene is very
much interested in saving waterbodies. Because of the land tenure system and the authority
the Asantehene wields in Kumasi, efforts to reverse the dire wetland situation could be made
easy. The clearing of waterways through the demolition of houses has been vehemently
resisted in most areas. Political interferences into these activities have sometimes made the
situation more complicated. However, the involvement of the Asantehene in these activities
could provide the much needed impetus that the KMA needs in carrying out their corrective
environmental management and Garden City agenda.
The recent experiences of urban Kumasi make restoration to its former Garden City status not
only desirable, but necessary. More and more people are experiencing floods and the results
of this research show that, total annual rainfall of Kumasi is more from heavy rainfall events
than rainy days. If this trend continues, the city has two options to curb the incidence of flash
floods: (i) either adopt the engineering approach by increasing and expanding the drainage
systems or (ii) improve the conditions of the wetlands to play its natural role of absorbing and
155
slowing down the storm waters. Whilst none of these options will single-handedly solve the
problem, the economics of these options favour the latter. Urban storm drainage systems are
expensive to construct and maintain. Improving wetland areas will not only curb the incidence
of floods but is also an ecologically sound approach for a city that is growing and increasingly
producing more pollutants.
This research has shown that the wetlands of Kumasi are a rich store of plant biodiversity. It
is surprising that, a city that is undergoing such a rapid landcover change still has wetland
patches that have maintained plant diversity comparable to undisturbed environments. That is,
despite the pollution, encroachment and fragmentation of the wetlands, good fragments
worthy of protection still exists. Whilst most of the wetlands have relatively high diversity
indices, the importance value indices show that they are predominantly vegetated by 1-3
species. There seems to be a form of vegetation specialisation based on the soil and water
regime of each wetland. Conservation objectives for these wetlands should therefore be for
their ecological services rather than their store of biodiversity. For example carbon
sequestration should be the conservation objective for the wetlands at the KNUST Police
Station and Atonsu Sawmill; aesthetic values for Golden Tulip Hotel, Bekwai roundabout,
Dakwadwom, Atonsu Sawmill; and FRNR Farms; and flood mitigation objectives for those at
KNUST Police Station, Kaase Guinness. The diverse ecological potentials of these wetlands
should be harnessed for sustainable urban environment of Kumasi. The success of the new
Garden City of Kumasi will depend on how this rich diversity is integrated into the spatial
planning efforts. Whilst the presence of heat island effect has not yet been determined in
Kumasi, the increasing use of air conditioners, vehicles and the reduction in vegetation cover
make it plausible. When these urban green spaces and streams are improved, they could
mitigate the heat island effect and also provide places for relaxation to escape from the
pressures of the city.
Poverty and vulnerability have always been used together in literature on slums and informal
settlements. Even though these suburbs generally house the poor of Kumasi and are exposed
to the annual floods, they cannot necessarily be described as vulnerable. Most of these
residents have accepted the annual flooding as the status quo. Whilst anyone can be
vulnerable to non-seasonal flash flood events, the prevalent form of inundation in these
suburbs is due to effluent streams from the annual rise in the water table. This type of
inundation by its nature and frequency is very much expected. The inhabitants may therefore
be frequently exposed to floods but cannot be described as vulnerable because they expect it
156
and prepare for it. This may explain their reluctance to relocate. Poverty (expressed by their
inability to afford the relatively high rental charges at other suburbs) may be the determinant
in the initial choice to settle in that location. However, these residents soon tap into other
forms of human capital (social, experiential, cultural, spiritual capitals) to reduce their
vulnerability to the floods. These forms of capital need time to mature, improve and increase
in value. Any efforts by the city authorities to relocate these wetland inhabitants should
therefore involve the early identification and removal of factors that provide resilience to
floods. These may, however, be deeply rooted in the social fabric and, therefore, difficult to
remove by the time the inertia ridden city authorities decide to take action.
This study also shows that human environmental behaviour and choices are very fluid and
unpredictable. Different people have different tolerance levels which are related to their
individual value judgements. The Ghanaian society is still very much communal. Even in
urban settings, people easily build relations in their neighbourhood. These bonds are
Ghanaian social values that influence highly the outcomes and decision making processes of
these urban residents. The trajectory of the EKC would apply in very individualistic societies
where persons, or at most the household, take decisions independent of the influence of their
neighbours. Where this independence is lost, the trajectories of flood tolerance or
environmental pollution with increasing wealth deviates from what has been proven by Dinda
(2004), Stern (2004) and Mills & Waite (2009). What is observed is that, after staying in these
communities for a while, income gradually loses its power as a major decision making factor
in residential choices.
Kumasi is growing faster than the inhabitants and planning authorities can cope with. Most
inhabitants are still dependent on agriculture, natural resources and fresh foodstuff. With
increasing urbanisation, these are drawn from increasingly distant environments to satisfy
these inhabitants. The distance from which goods are acquired and to which waste can be sent
is directly related to the spatial developmental stage of the city. Distances and costs to dispose
of wastes are increasing for both the residents and waste management companies. The
distance is also a function of energy (or financial resources). The more the availability of
energy, the further these wastes could be transported or better processed into less harmful
forms. Because of the high costs of managing wastes, streams serve as sources of “free
energy” to transport the waste when it rains. Disposal of waste in wetlands and streams may
therefore be an adaptation by urban residents to reduce this energy function in their lives.
157
These are conscious decisions residents take considering the cost of floods and aesthetic
values of the environment being lost through such waste disposal methods.
Furthermore, the placing of waste containers in wetlands by the KMA could also be a
reinforcing factor to the wrongful use of these wetlands as dump sites. The KMA sees these
wetlands as the remaining islands of free public spaces for these purposes in an already
unplanned and overdeveloped neighbourhood. In most of these poor suburbs, there is a high
default rate of fee payment for collection or disposal of waste. Therefore, domestic waste is
secretly deposited in the immediate surroundings of these containers. These are all washed into
the surrounding streams choking them and increasing the siltation rates. These shallow rivers
therefore easily overflow their banks during the heavy rain events flooding the neighbouring
low lying areas. Therefore, whilst the KMA is working in one dimension to reduce the
incidence of floods by removing structures along the waterways, they should also to be blamed,
in part, for increasing the incidence of floods by siting waste bins in wetland areas.
7.2 CONCLUSIONS This study sought to contribute knowledge on the state of wetlands, incidence of flooding and
stakeholder needs for the management of wetlands in Kumasi, Ghana. Data was collected in
the chosen study sites and suburbs from January, 2010 to December 2011. After various
analyses, the following conclusions were drawn in answer to the research questions and
hypotheses that were set for the study:
� All the wetlands are riverine and associated with Rivers Suatem, Subin, Aboabo, Sisai
and Wiwi which flow through the jurisdiction of the KMA. The size and quality of these
wetlands are being decreased through adjacent anthropogenic activities.
� Whilst there are some species common to all the wetlands, each wetland is unique in
species composition. In each wetland, vegetation distribution followed a hydrological
gradient. That is, the degree of soil water saturation was found to be the main determinant
of species composition for each site (within wetland differences). However, no one
obligate wetland species could be used to characterise all wetlands in Kumasi.
� The percentage organic carbon was the strongest factor that explained the observed
spatial heterogeneity of wetland vegetation in Kumasi (between wetland differences).
Whilst there were seasonal differences in water conditions (pH and dissolved oxygen),
there was no seasonal change in the vegetation. The wetland vegetation species diversity
158
was not found to be influenced by adjacent landuse but by the hydrology and edaphic
conditions of the wetland.
� The hydrology and edaphic conditions at the KNUST Police Station make the wetland
have the highest amount of carbon sequestered among the wetlands investigated. Typical
species at the KNUST Police Station are Thelypteris palustris, Coix lacryma-jobi,
Hydrolea glabra, Ipomoea aquatica, Ludwigia decurrens, Centrosema pubescens and
Pentodon pentandrus.
� All the wetlands were found to be polluted by the heavy metals investigated. The
heavy metals Hg, Ni, Zn, and Pb probably come from the same source whilst Cu and Cr
from another. Major anthropogenic activities that could be the sources of these heavy metals
are the auto mechanic shops (car spray and repair shops), car wash centres, pesticides and
herbicides from vegetable farms, wood preservatives from waste wood and saw dust from
the carpentry shops, wastes from tie-dye industries and vehicle emissions.
� The total annual rainfall is decreasing but not significant. Only rainfall for March and
November is significantly decreasing over the period considered (Z= -2.44, Q= -1.20 and
Z=-2.90, Q= -1.15 respectively at α=0.05). Annual heavy rainfall events are also decreasing
in trend, although not significant. The analyses show that total monthly rainfall of Kumasi is
explained more by heavy rainfall events than by the number of rainy days in the month.
However, there is no significant change in trends of heavy rainfall events for the two
flood prone months (June and July). Floods in Kumasi are therefore not attributable to
changes in climate.
� There are two types of floods that affect the wetland communities studied: flash floods
and ‘effluent stream floods’. The flash floods arise from overland flow due to heavy
rainfall events. The effluent stream floods are due to a rise in the water table during the
peak rainy season of June-July causing a relatively longer surface inundation from
groundwater.
� The built-up and bare areas within the KMA have been growing at a rate of 1.9 % per
annum between 1986 and 2007. This landcover change leads to increase in surface runoff
because of reduced infiltration, decrease in concentration time and time to peak discharge
and consequently increase in peak discharge. This is the major cause of the increased
flash floods in Kumasi.
159
� There was no relationship between number of years of stay in an area and presence or
absence of floods (r = -0.135). The inhabitants are adapted to life in these flood prone
neighbourhoods. Adaptations include: dredging of streams, erection of embankments
around houses, move property to higher grounds, build a network of raised walkways and
building houses on stilts. With these adaptations, residents plan to move out only when
they are provided with an alternative house elsewhere. These are adaptations rather to the
long lasting seasonal effluent floods than to flash floods.
� The behaviour of the flood prone residents does not follow the EKC trajectory. Even
when incomes of these residents increase, they do not move out, not even when they are
forced. The social and experiential capitals developed by staying in these suburbs far
outweigh the financial or economic losses due to the floods. The opportunity cost of
moving out is therefore too high for these flood prone residents to bear. The duration of
stay in a flood prone environment rather than income, is the stronger determinant in the
decision making process of a resident to stay or relocate. Increased income will flatten the
curve but will not bring flood tolerance to 0.
� The stakeholders contacted for this study considered wetlands important and should be
protected. The stakeholders most important for the management of floods and wetlands are
chiefs and the KMA. The responsible authorities should manage wetlands and floods
through the enforcement of landuse plans, demolition of houses on waterways and setting
up public parks. The social, institutional and technical dimensions of flood and wetland
management will achieve better outcomes for all the stakeholders.
7.3 RECOMMENDATIONS Based on the findings of this research, the following actions are recommended:
� The KMA should use the presence of effluent streams and the identified typical
wetland important vegetation species for each wetland as defining factors to delineate the
wetland boundaries. This exercise should particularly target the relatively large stretches
of wetlands at the KNSUT Police Station, FRNR farms, Atonsu, Family Chapel,
Dakwadwom, Spetinpom and Golden Tulip Hotel. After delineating the wetland boundaries,
all structures within the wetlands should be demolished. These recovered wetlands should
be given special names and revegetated to recover their natural system functions. In
doing this, the KMA should liaise with the Asantehene (King of Ashanti) to solicit his
support to reduce opposition.
160
� The wetlands at the KNUST Police Station and Atonsu should be protected for their
peat storage value. These sites could be further assessed for their potential to earn carbon
credits for the city in the on-going climate change mitigation schemes. For example, the
opportunities in the Reducing Emissions from Deforestation and forest Degradation
(REDD+) programme being advocated by the United Nations could be tapped to facilitate
the achievement of the Garden City status. This will also pave the way for Kumasi to
meet the demands of the Millennium Cities Initiative and the Convention on Biological
Diversity’s Global Partnership on Cities and Biodiversity.
� Relevant academic institutions and faculty should develop and actively focus their
research on urban ecology. The research should include the use of vegetation for urban
waste water treatment, wetland vegetation for storm water management and carbon
sequestration. Site specific rainfall input should be studied to assess the wetland
hydrodynamics and its influence on temporal variation in vegetation. Also, scientific
input from this research and others should be the backbone for the management of the
delineated wetland areas to conserve biodiversity and provide ideal environments for
human relaxation.
� The KMA should endeavour not to site waste containers in wetlands to reduce the
direct introduction of waste into stream channels. Where it is necessary to do so, a wall
should be built around such a facility to contain any overflows. Also, waste collection in
these poor neighbourhoods should be free so that residents are encouraged to use the
designated dump sites. Anthropogenic activities around the wetlands should also be
regulated to reduce the direct anthropogenic destruction and pollution of these habitats. In
particular, car wash and repair shops should either be relocated or their waste be managed
so that it is not directly introduced into the wetlands.
� Considering the limited financial resources available to the KMA, an engineering
based urban drainage system is not feasible. The approach to managing floods in Kumasi
should be a combination of the reconstruction of the wetlands as described above and social
interventions. The social flood management elements in each suburb should be identified
and prioritised for action to increase resilience and reduce the scope and incidence of
floods. In this regard, the KMA and NADMO need to recognise and give the needed
support to chiefs and assemblymen of these neighbourhoods and relevant NGOs who are
better placed to achieve these objectives.
161
� The DEMC of the KMA should be strengthened to carry out their objectives and
mandate. The powers vested in this Committee and its apolitical nature will make their
actions more acceptable to the people. When operational, the DEMC should collaborate
with the chiefs and assemblymen of the flood prone suburbs in enforcing community
based flood and wetland management plans.
162
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9 APPENDICES Appendix 1. Survey instrument used for the wetland associated communities in Kumasi
Questionnaire number…………………………Area………………………………...............
Type of house..............................................................Date…………………………………
INTRODUCTION
The researcher is a student of the University of Bremen, Germany working on urban wetland ecology and flooding in Kumasi. The information you provide will be treated as confidential and will be used for academic purposes only. Thank you for your time and cooperation.
1.1 Do you own the house you live in yes [ ] no [ ]
1.2 How did you get access to this land? Family inheritance [ ] Chief [ ] Bought from
another person [ ] Squatter [ ] Not applicable [ ]
1.3 For how long have you been living in the area? Below 5years [ ] 5-10 years [ ]
10-15 years [ ] 15-20 years [ ] more than 20 years [ ]
Please rank the following options according the criterion below:
0= no change/no influence/no contribution/nothing, 1=… 2= … 3=… 4=… in increasing
order to 5=highest increase/most influential/most contribution.
1.4 What do you do for a living?
Job types 0 1 2 3 4 5 1. Trading 2. Farming 3. Artisan (e.g. car fitting/Saw milling/carpentry etc.) 4. Tie-dye manufacturing
5. Oil extracting (palm oil/palm kernel oil etc.)
6. Formal sector job 7. Nothing/unemployed/dependant
Other, please specify 1.5 What are the predominant economic activities in this area?
Activity/use of land at time of moving in 0 1 2 3 4 5 1. Agriculture (vegetables, animals, etc.) 2. Tie-dye industries 3. Hunting 4. Fishing 5. Car washing bays
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6. Car fitting/spraying shops 7. Carpentry/sawmill 8. Trading
Other (specify) 1.6 What was the previous use of this wetland to the people of this area?
……………...................................................................................................................................
1.7 What is/are the current uses of this stream/wetland to the people of this area?
Uses 0 1 2 3 4 5 1. Agricultural purposes 2. Tie-dye industries 3.Waste disposal 4. Car washing bays 5. Car fitting shops 6. Carpentry 7. Water supply 8. Fishing
9. Rangeland/forage area for cows sheep and goats
10. Recreation/tourism Other, please state
1.8 What are the major landuse activities around the wetland (100 m from water channel)?
Activities 0 1 2 3 4 5 1. Agriculture (vegetables, animals, etc.) 2. Tie-dye industries
3. Waste disposal 4. Car washing bays
5. Car fitting shops
6. Carpentry 7. Rangeland/forage area 8. Recreation/tourism 9. Housing/construction
Other, please specify 1.9 What have been the effects of these activities (1.8 above) on the environment/wetland?
Changes 0 1 2 3 4 5 1. Channel width (size of the river) 2. Water depth 3. Number and type of living organisms (e.g. fish, plants animals)
4. Storm flow (amount of water in the river/channel immediately after rainfall)
5. Suitability of water for domestic/industrial purposes
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Other, please specify 2.0 What changes have you observed in the wetland vegetation since you first settled?
Changes 0 1 2 3 4 5 1. Plant species diversity 2. Number of woody plants (e.g. trees) 3. Number of herbaceous plants (e.g. grasses) 4. Distribution of plants 5. Density of plants 6. Plant cover 7. Loss of some species 8. Presence of new species
Other, please specify 2.1 Buildings in wetland areas are major problems in Kumasi. Strongly agree [ ] Agree [ ]
Disagree [ ] Not sure [ ]
2.2 What are some of the effects building on wetland areas have on our environment?
Effects 0 1 2 3 4 5 1. Nothing 2. Causes flooding 3. Makes the environment dirty 4. No place to dump wastes anymore 5. Does not make the city beautiful
Other, please specify 2.3 Why do you think people build in wetland areas?
Reasons 0 1 2 3 4 5 1. Wetland areas are cheap 2. Close to amenities 3. Direct use of the water for domestic purposes 4. Close to family 5. Do their economic activities 6. It is “no man’s land”
Other, please specify 2.4 Have you experienced flood in this area? Yes [ ] No [ ]
2.5 If yes, how many times in a year do you experience floods? Once [ ] Twice [ ] Thrice [ ]
more than thrice [ ]
2.6. Which month(s) of the year do you experience the
floods?………………………………………
182
2.7. How long do the floodwaters take to recede? Less than 5 days in a year [ ] less than 10
days in a year [ ] less than 15 days in a year [ ] less than 20 days in a year [ ] less than 25
days in a year [ ] About a month in a year [ ]
2.8. How do you assess the frequency of the floods compared to 10 years ago?
Less frequent [ ] More frequent [ ]
2.9 How do you deal with floods as an individual and community? (mark I or C or both)
Activities 0 1 2 3 4 5 1. Do nothing 2. Fetch/pump water out of flooded areas 3. Move out till water subsides 4. Create channels for easy flow of water 5. Dredge stream 6. Build embankments along stream 7. Complain to authorities
Others, please specify 3.0 Have you ever been educated on the usefulness of a wetland? Yes [ ] no [ ]
If yes, give the name(s) of the organisation(s)
…………………………………………………………………………………………………
3.1 Has there been any attempt by an organisation to move you from this site? yes [ ] no [ ]
If yes, name of organisation……………………………………………………………………
3.2 What will make you move out of this place?
Motivation/reason 0 1 2 3 4 5 1. Nothing, I love it here 2. Given money to move 3. New land/plot somewhere 4. When I make some money 5. When the water gets too much 6. When we are forced 7. I am already preparing to move 8. If I am provided alternative shelter
Other, please specify 4.0 Do you think the wetland should be protected? yes [ ] no [ ]
4.1 How are you and your community protecting this wetland?
Activities 0 1 2 3 4 5 1. We are doing nothing 2. Stop waste disposal on wetland 3. Stop building too close to wetland 4. Create channels for easy flow of water 5. Dredge stream
183
6. Build embankments along stream 7. Stop all economic activities on wetland 8. Complain to authorities
Others, please specify 4.2 Have houses in this neighbourhood ever been marked for demolition because of the
wetland? Yes [ ] No [ ]
If yes, when less than 2 yrs age [ ] 2-5 yrs ago [ ] 5-10 yrs ago [ ]
more than 10 yrs [ ]
4.3 Has any demolition been carried out in this area? Yes [ ] No [ ]
4.4 Do you support the demolition along water ways? Yes [ ] No [ ]
4.5 Who are responsible for the management of the wetlands in Kumasi?
Agencies/institutions 0 1 2 3 4 5 1. KMA 2. Hydrological Services Department 3. Town and Country Planning Department 4. The community and Assemblyman 5. NGOs (e.g. IWMI, Friends of Rivers and
Waterbodies)
6. NADMO 7. The chief/land owners
Others, please specify 4.6 Are there any on-going management practices to protect the wetland? Yes [ ] No [ ]
4.7. What factors affect the implementation of wetland policies and management plans?
Factors 0 1 2 3 4 5 1. Political influence 2. Changes in government 3. Corruption 4. Poverty levels 5. Lack of political will 6. Cost of demolition 7. Cultural values
Other, please specify 4.8 Do you know any of the laws regarding building or sitting of infrastructure in wetland
areas? Yes [ ] No [ ] If yes what is it
Background Information
5.1 Age: below 20yrs [ ] 20-30yrs [ ] 30-40yrs [ ]
40-50yrs [ ] 50-60yrs [ ] above 60yrs [ ]
5.2 Sex: Male [ ] Female [ ]
184
5.3 Education: Primary [ ] Middle School/JHS [ ] Secondary/SHS [ ]
Post-secondary/Tertiary [ ] No formal education [ ] Other [ ]
5.4 Occupation: …………………Household size:..............................................................
185
Appendix 2. Survey instrument used for wetland associated NGOs and government agencies in Kumasi
Date………………………………. INTRODUCTION The researcher is a student of the Kwame Nkrumah University of Science and Technology
working on urban wetlands in Kumasi. The information you provide will be treated as
confidential and will be used only for academic purposes. Thank you for your time and
cooperation.
1. In your opinion; what has been the overall change in the state of the wetland?
2. What are the tasks of inspectors/ officers- in- charge of developments on wetland areas?
3. How often do developers who flout the regulations come to your notice?
4. What punitive measures are there for such offenders?
5. Are these punitive measures effective?
6. How can the effectiveness be improved?
7. Are prospective (building) developers aware of these regulations/rules?
8. How often does your outfit organise educative seminars for people living on wetlands?
9. What medium do you use for such educative forum?
10. Are there any risks/dangers your inspectors/ officers face in visiting development sites in
wetland (e.g. from land guards, mob attack, etc)?
11. Under what circumstances can a building on wetlands be pulled down?
12. Are there maps/demarcations showing wetland areas?
13. What major constraints affect the implementation of wetlands management plan?
14. How do non-economic variables other than per capita income, such as the features of the
political system, and some cultural values, affect the implementation of wetland policies
and management plan?
186
App
endi
x 3.
Fie
ld d
ata
shee
t use
d fo
r wet
land
veg
etat
ion
and
ecol
ogic
al s
tudi
es in
Kum
asi
spec
ies
Dis
tanc
e fr
om w
ater
cha
nnel
Rem
ark/
com
men
t wa
ter
chan
nel
10m
20
m
30m
40
m
≥50m
# co
ver
# co
ver
# co
ver
# co
ver
# co
ver
# co
ver
187
App
endi
x 4.
Stu
dy s
ites
and
anth
ropo
geni
c ac
tiviti
es w
ithin
100
m f
rom
the
wat
er c
hann
el [
min
imum
buf
fer
dist
ance
set
by
Min
istr
y of
La
nds
and
Nat
ural
Res
ourc
es (W
ater
Res
ourc
es C
omm
issi
on, 2
008)
]
Act
ivity
/ la
ndus
e
Ato
nsu
Sawm
ill
A
Hig
h Sc
hool
Ju
nctio
n
B
FRN
R
farm
s
C
KN
UST
Polic
e St
atio
n
D
Fam
ily
Cha
pel
E
Spet
inpo
m
F
Gol
den
Tulip
Hot
el
G
Kaa
se-
Gui
nnes
s H
Bek
wai
roun
dabo
ut
J
Dak
wodj
om
K
# %
la
nd
cove
r #
%
land
co
ver
# %
la
nd
cove
r #
% la
nd
cove
r #
%
land
co
ver
# %
la
nd
cove
r #
%
land
co
ver
# %
la
nd
cove
r #
%
land
co
ver
# %
land
co
ver
Hou
sing
74
34
52
35
1
0 19
6
65
50
45
55
45
20
37
30
152
55
30
20
Farm
ing
2 0
3 5
9 2
15
2 7
10
11
5 12
12
3
15
41
20
3 5
Nat
ural
ve
geta
tion
50
45
98
91
30
30
65
50
0 20
70
Was
te d
ispo
sal
3 10
4
5 0
0 3
0 7
5 2
3 2
0 1
0 2
0 2
0 Sc
hool
s 0
0 1
0 0
0 1
1 1
2 1
1 0
0 2
1 3
0 0
0 C
hurc
h 0
0 5
0 0
0 1
0 7
1 0
1 2
0 4
1 3
0 2
0 M
osqu
e 1
0 0
0 0
0 0
0 0
0 0
1 0
0 0
0 0
0 0
0 C
arpe
ntry
/saw
m
ills
2 5
15
1 0
0 0
0 9
0 0
0 0
0 0
0 0
0 6
0 C
ar w
ashi
ng
bay
2 0
5 0
0 0
0 0
1 0
1 0
2 0
2 0
12
1 0
0 C
ar r
epai
rs
2 0
22
5 0
0 0
0 15
2
0 0
0 0
22
2 12
0
6 2
Roa
d
2 0
5 0
1 0
6 0
6 0
2 0
6 2
3 0
6 2
2 0
Gas
/fuel
fill
ing
stat
ion
0 0
1 0
0 0
0 0
2 0
3 1
2 1
3 1
3 0
0 0
Mar
ket
1
1 2
2 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 K
iosk
s
4 0
6 2
0 0
2 0
0 0
0 2
3 0
12
0 17
0
9 0
Oil
extr
actio
n 0
0 0
0 0
0 0
0 15
0
0 0
0 0
0 0
0 0
6 0
Tie-
Dye
in
dust
ry
0 0
1 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
Play
grou
nd
0 0
1 0
0 0
0 0
0 0
0 1
0 0
0 0
0 2
1 3
Fish
pro
cess
ing
1 0
2 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
22
0 To
tal
94
100
125
100
11
100
47
100
135
100
65
100
74
100
89
100
251
100
89
100
App
endi
x 5.
A W
ilcox
on S
igne
d R
anks
Tes
t co
mpa
rison
of
the
seas
onal
diff
eren
ces
in p
hysi
coch
emic
al p
aram
eter
s of
the
wet
land
s in
K
umas
i
188
N
Mea
n
Ran
k Su
m o
f R
anks
Te
st S
tatis
tics
Z A
sym
p. S
ig. (
2-ta
iled)
ra
iny_
pH -
dry
_pH
N
egat
ive
Rank
s 10
a 5.
50
55.0
0 -2
.803
0.
005
Posi
tive
Rank
s 0b
.00
.00
Ties
0c
Tota
l 10
ra
iny_
Tem
p - d
ry_T
emp
Neg
ativ
e Ra
nks
7d 5.
86
41.0
0 -1
.376
Base
d on
po
sitiv
e ra
nks
0.16
9 Po
sitiv
e Ra
nks
3e 4.
67
14.0
0 Ti
es
0f
To
tal
10
Rai
ny_S
al -
dry
_Sal
N
egat
ive
Rank
s 5g
3.30
16
.50
-.211
Base
d on
ne
gativ
e ra
nks
0.83
3 Po
sitiv
e Ra
nks
3h 6.
50
19.5
0 Ti
es
2i
To
tal
10
Rai
ny_D
O -
dry
_DO
N
egat
ive
Rank
s 1j
2.00
2.
00
-2.5
99
Base
d on
ne
gativ
e ra
nks
0.00
9 Po
sitiv
e Ra
nks
9k 5.
89
53.0
0 Ti
es
0l
To
tal
10
rain
y_TD
S - d
ry_T
DS
Neg
ativ
e Ra
nks
5m
5.40
27
.00
-.051
Base
d on
ne
gativ
e ra
nks
0.95
9 Po
sitiv
e Ra
nks
5n 5.
60
28.0
0 Ti
es
0o
To
tal
10
189
App
endi
x 6.
Met
al c
once
ntra
tion
(mg/
kg)
in s
edim
ents
of t
he d
iffer
ent
stud
y si
tes
in K
umas
i
stud
y si
tes
Ato
nsu
Sawm
ill
Hig
h Sc
hool
Ju
nctio n
FRN
R
farm
s
KN
UST
Po
lice
Stat
ion
Fam
ily
Cha
pel
Spet
inpo m
Gol
den
Tulip
H
otel
Kaa
se
Gui
nnes s
Bek
wai
roun
dabo
u t
Dak
wadw
o m
rain
y se
ason
17
/06/
2010
Ars
enic
138.
6 11
7.5
22.5
17
5.8
44.0
37
.2
54.7
25
.2
45.0
24
.5
Cop
per
652.
5 51
3.2
152.
1 72
.6
621.
3 18
4.2
584.
5 24
5.2
445.
8 12
5.2
Lead
42
5.3
189.
2 35
.8
45.3
45
2.1
49.5
65
.2
75.3
12
2.0
87.5
Zi
nc
842.
6 75
2.5
154.
2 15
2.2
825.
2 15
2.0
242.
2 23
9.0
234.
2 54
1.2
Chr
omiu
m
542.
2 45
2.2
142.
3 14
5.3
1078
.3
142.
8 22
1.5
236.
5 18
9.5
425.
3 C
adm
ium
0.9
0.6
1.0
0.6
1.0
0.6
0.5
0.6
0.6
0.8
Nick
el 44
3.8
479.
2 14
5.2
109.
2 54
2.2
105.
2 17
9.2
102.
7 10
7.2
102.
2 M
ercu
ry
2.1
2.5
0.9
0.7
0.6
0.8
0.8
0.8
0.8
0.8
Phos
phor
us
7785
.2
3022
.2
2230
.5
1889
7.5
1520
2.5
1745
.2
4421
.9
5232
.2
4523
.2
2202
.0
dry
seas
on
14/0
1/20
10
Ars
enic
48.6
18
5.7
25.1
85
.2
200.
1 47
.2
295.
4 27
7.2
189.
1 31
.3
Cop
per
652.
5 62
4.6
214.
2 12
7.4
1052
.1
984.
2 49
7.2
589.
2 38
9.5
323.
2 Le
ad
425.
3 48
9.2
38.5
47
.6
612.
9 84
.9
86.2
40
5.4
342.
4 33
2.1
Zinc
15
42.6
12
52.5
17
7.2
242.
2 10
41.2
42
7.5
327.
6 55
7.2
534.
2 58
2.1
Chr
omiu
m
542.
2 75
2.2
152.
8 32
4.2
532.
9 15
42.9
32
4.9
723.
1 28
7.5
325.
1 C
adm
ium
0.8
1.0
1.3
0.6
0.8
1.0
1.0
0.8
0.9
1.3
Nick
el 84
3.8
779.
2 10
7.6
104.
9 64
2.2
112.
7 12
4.2
148.
2 18
5.2
134.
2 M
ercu
ry
2.5
3.7
0.8
1.0
2.1
0.8
0.8
1.0
0.8
0.8
Phos
phor
us
1778
5.2
1902
2.2
1185
2.3
2252
1.2
1612
5.2
1252
1.3
1689
5.0
1121
4.4
1252
3.2
1754
2.4
190
App
endi
x 7.
Pea
rson
cor
rela
tion
mat
rix o
f he
avy
met
als
and
othe
r m
easu
red
envi
ronm
enta
l var
iabl
es (
sign
ifica
nt r
elat
ions
hips
sho
wn in
bo
ld)
Ars
eni
c C
oppe
r Le
ad
Zinc
C
hrom
ium
C
adm
ium
N
icke
l M
ercu
ry
Phos
phor
us
pH
Tem
pera
ture
Sa
linity
D
isso
lve
d O
2 D
isso
lve
d so
lids
sa
nd
silt
cl
ay
Ars
enic
Cop
per
0.28
7
Lead
0.
358
0.53
8
Zinc
0.
127
0.59
2 0.
852
Chr
omiu
m
0.05
3 0.
743
0.18
8 0.
330
Cad
miu
m
-0.3
98
-0.0
03
-0.1
16
-0.1
27
-0.1
42
Nic
kel
0.12
1 0.
510
0.73
6 0.
939
0.19
6 -0
.155
Mer
cury
0.
141
0.42
6 0.
654
0.86
7 0.
257
-0.1
64
0.95
2
Phos
phor
us
-0.0
66
-0.2
54
0.02
7 0.
255
-0.1
65
-0.3
32
0.33
5 0.
416
pH
0.16
7 0.
243
0.56
7 0.
691
0.33
0 0.
032
0.64
7 0.
775
0.16
5
Tem
pera
ture
0.
438
0.06
8 0.
406
0.20
4 -0
.041
-0
.305
0.
043
-0.0
88
-0.3
05
0.09
0
Sali
nity
0.
441
0.20
3 0.
533
0.29
2 0.
015
-0.3
09
0.05
7 -0
.101
-0
.201
0.
042
0.63
2
Dis
solv
ed
O2
-0.2
22
0.35
2 -0
.092
-0
.067
0.
148
0.38
1 0.
108
0.11
3 -0
.259
-0
.207
-0
.401
-0
.666
Dis
solv
ed
soli
ds
0.43
4 0.
202
0.51
7 0.
279
0.03
2 -0
.325
0.
042
-0.1
15
-0.2
03
0.03
2 0.
628
0.99
9 -0
.672
sand
0.
733
0.15
5 0.
382
0.09
9 -0
.147
0.
179
0.15
6 0.
238
-0.2
23
0.36
2 0.
187
0.07
8 0.
136
0.05
8
silt
-0
.401
-0
.427
-0
.465
-0
.460
-0
.536
-0
.129
-0
.349
-0
.502
-0
.082
-0
.774
-0
.136
-0
.009
0.
046
-0.0
01
-0.5
28
clay
-0
.415
0.
198
0.01
7 0.
270
0.60
7 -0
.131
0.
064
0.07
5 0.
304
0.18
6 0.
015
0.07
3 -0
.289
0.
090
-0.6
77
-0.2
46
191
App
endi
x 8.
Prin
cipa
l C
ompo
nent
Ana
lysi
s of
env
ironm
enta
l va
riabl
es a
nd h
eavy
met
als
asse
ssed
in th
e we
tland
s of
Kum
asi
Eige
nval
ues
PC E
igenv
alue
s %
Var
iatio
n C
um. %
Var
iatio
n 1
5
.52
32.4
32.
4 2
3
.48
20.5
52.
9 3
2
.52
14.8
67.
7 4
1
.93
11.3
79.
1 5
1
.3
7.7
86.
8 Ei
genv
ecto
rs
(Coe
ffici
ents
in
the
linea
r co
mbi
natio
ns o
f var
iables
mak
ing u
p PC
's)
Var
iable
PC
1
PC
2
PC
3
PC
4
PC
5 A
rsen
ic 0.
197
-0
.257
0.31
3
0.05
9
-0.2
14
Cop
per
0.27
3
0.09
8
0.04
8
-0.4
42
0.21
7 Le
ad
0.37
8
-0.0
65
0.
062
0.
028
0.
239
Zinc
0.
387
0.
105
-0
.113
0.06
6
0.23
8 C
hrom
ium
0.
188
0.
143
-0
.178
-0.5
10
-0.2
09
Cad
mium
-0
.100
0.19
7
0.23
6
-0.1
91
-0.0
09
Nick
el 0.
344
0.
194
-0
.031
0.19
1
0.30
9 M
ercu
ry
0.33
7
0.26
1
-0.0
07
0.
231
0.
099
Phos
phor
us
0.05
6
0.15
3
-0.2
89
0.
498
-0
.146
pH
0.
326
0.
151
0.
017
0.
116
-0
.318
Te
mpe
ratu
re
0.15
2
-0.3
73
0.
026
-0
.066
0.
007
Salin
ity
0.18
2
-0.4
50
-0
.093
-0.0
73
0.12
2 D
issol
ved
O2
-0.0
76
0.
355
0.
282
-0
.231
0.
324
Diss
olve
d so
lids
0.17
7
-0.4
52
-0
.105
-0.0
82
0.11
5 sa
nd
0.15
6
-0.0
54
0
.553
0.09
4
-0.2
10
silt
-0.2
90
-0
.124
-0.1
20
0.
122
0.
543
clay
0.07
8
0.08
3
-0.5
39
-0
.233
-0
.224
App
endi
x 9.
Com
paris
on o
f m
eans
of
heav
y m
etal
enr
ichm
ent
fact
ors
for
rain
y an
d dr
y se
ason
in K
umas
i N
orm
ality
Tes
t: Fa
iled
(P <
0.0
50)
Test
exec
utio
n en
ded
by u
ser r
eque
st, R
ank
Sum
Tes
t beg
un
Man
n-W
hitn
ey
Ran
k Su
m T
est
Gro
up
N
Mis
sing
M
edia
n
25
%
7
5 %
EF
rain
y se
ason
90
0
3.24
1 1.
968
6.74
2
EF d
ry s
easo
n 90
0
5.99
4 2.
842
16.0
63
M
ann-
Whi
tney
U S
tatis
tic=
2694
.000
T
= 67
89.0
00
n(s
mal
l)= 9
0 n
(big
)= 9
0 (P
= <
0.00
1)
The
diffe
renc
e in
the
med
ian
valu
es b
etw
een
the t
wo
grou
ps is
gre
ater
than
wou
ld
be e
xpec
ted
by ch
ance
; the
re is
a s
tatis
tical
ly s
igni
fican
t diff
eren
ce (P
= <
0.00
1)
193
App
endi
x 10
. C
ompa
rison
of
m
eans
of
he
avy
met
al
geoa
ccum
ulat
ion
indi
ces
for
rain
y an
d dr
y se
ason
in K
umas
i N
orm
ality
Tes
t: Fa
iled
(P <
0.0
50)
Test
exec
utio
n en
ded
by u
ser r
eque
st, R
ank
Sum
Tes
t beg
un
Man
n-W
hitn
ey
Ran
k Su
m T
est
Gro
up
N
Mis
sing
M
edia
n
25
%
75 %
geoa
ccum
ulat
ion
rain
y se
ason
90
0
1.05
0 0.
330
2.10
7
geoa
ccum
ulat
ion
dry
seas
on
90
0 1.
937
0.86
1 3.
359
M
ann-
Whi
tney
U S
tatis
tic=
2694
.000
T
= 67
89.0
00
n(s
mal
l)= 9
0 n
(big
)= 9
0 (P
= <
0.00
1)
The
diffe
renc
e in
the
med
ian
valu
es b
etw
een
the t
wo
grou
ps is
gre
ater
than
wou
ld
be e
xpec
ted
by ch
ance
; the
re is
a s
tatis
tical
ly s
igni
fican
t diff
eren
ce (P
= <
0.00
1)
194
App
endi
x 11
. C
ompa
rison
of
mea
ns o
f Po
llutio
n Lo
ad I
ndic
es
for
the
diffe
rent
site
s in
the
rain
y an
d dr
y se
ason
in K
umas
i N
orm
ality
Tes
t: Pa
ssed
(P
= 0
.051
) Eq
ual
Var
ianc
e Te
st:
Pass
ed
(P =
0.3
74)
Gro
up N
ame
N
M
issi
ng
Mea
n St
d D
ev
SEM
PLI r
ainy
s
10
0 4.
082
2.19
9 0.
695
PL
I dry
sea
10
0
6.84
1 3.
062
0.96
8
Diff
eren
ce
-2.7
59
t = -2
.314
with
18
degr
ees o
f fre
edom
. (P
= 0.
033)
95
per
cent
conf
iden
ce in
terv
al fo
r diff
eren
ce o
f mea
ns: -
5.26
4 to
-0.2
54
The
diffe
renc
e in
the
mea
n va
lues
of t
he tw
o gr
oups
is g
reat
er th
an w
ould
be
expe
cted
by
chan
ce; t
here
is a
sta
tistic
ally
sig
nific
ant d
iffer
ence
bet
wee
n th
e inp
ut
grou
ps (P
= 0
.033
). Po
wer
of p
erfo
rmed
tes
t with
alp
ha =
0.0
50:
0.49
8
i