E Y F S I E I T A Côte d’Ivoire using the MOVE framework Y D E I C … · 2019. 9. 11. · E1 E2...
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1. Background Coupled with poor urban development, the increasing urban population of many Sub-Saharan African countries is subject to recurrent severe flooding episodes. In response to these flood events, while the focus is often put on slums and precarious urban settings, the social implications of these floods affect a variety of social classes.. Main objective: evaluates the social vulnerability of urban Côte d’Ivoire to flooding using the MOVE framework 2. Study site Cocody, a district of Abidjan, Côte d’Ivoire, known to have the country’s highest number of flood-impacted people. 3. Material and Methods Method for the Improvement of Vulnerability Assessment in Europe (MOVE Framework) Indicator selection Thanks to the organizers and sponsors of this event Fig.1. Localization of the study site Assessment of social vulnerability to flood in urban Côte d’Ivoire using the MOVE framework Fig. 4. Vulnerability map Table 1: list of selected indicators Fig. 3. The MOVE theoretical framework M.K.A Kablan*, K. Dongo, M. Coulibaly São Paulo School of Advanced Science on Climate Change: Scientific Basis, Adaptation, Vulnerability and Mitigation 3-15 July 2017, São Paulo (Brazil) SPSAS Climate Change ENVIRONMENT International ↔National↔ Subnational scale RISK Economic / social / environmental potential impact R I S K R E D U C T I O N P R E P A R E D N E S S D I S A S T E R M A N A G E M E N T P R E V E N T I O N M I T I G A T I O N T R A N S F E R Hazard intervention Vulnerability intervention Susceptibility reduction Exposure reduction Resilience improvement RISK GOVERNANCE Organization / planning / implementation Subnational ↔local scale Local scale Interactions COUPLING ADAPTATION EXPOSURE Temporal Spatial VULNERABILITY Social Physical LACK OF RESILIENCE Capacity to anticipate Capacity to cope Capacity to recover SUSCEPTIBILITY and FRAGILITY ENVIRONMENT R I S K M A N A G E M E N T SOCIETY HAZARDS Natural events / socio-natural events Ecological Social Institutional Cultural Economic Components N° Indicators Exposure E1 Population density (inhbts/km 2 ) E2 Elevation (m) E3 Vertical permeability (m/s2) E4 Flooded areas per sub-district (%) Susceptibility S1 Children under 5 (%) S2 Elderly above 65 (%) S3 Vegetation cover per sub-district (%) S4 Women (%) S5 Waste collection (number of day/week) S6 Unplanned waste deposits (number) Lack of Resilience LoR1 Literacy rate (%) LoR2 Number of people insured (%) LoR3 Unemployment rate (%) 4. Results E1 1 E2 0.05 1 E3 0.00 0.17 1 E4 0.22 −0.35 * 0.06 1 E 0.62 ** 0.42* 0.59 ** 0.45 ** 1 S1 −0.11 0.11 0.01 −0.46 ** −0.21 1 S2 −0.12 0.26 −0.36 * −0.30 −0.25 −0.06 1 S3 0.39 * −0.17 0.57 ** 0.02 0.39 * −0.03 −0.05 1 S4 0.04 0.22 0.29 −0.09 0.22 −0.17 0.07 0.17 1 S5 0.05 0.23 0.07 −0.28 0.03 0.34 * −0.13 0.09 −0.11 1 S 6 −0.05 −0.37 * 0.27 0.10 −0.02 0.09 −0.21 0.22 0.07 −0.05 1 S 0.15 0.10 0.36 * −0.40 * 0.10 0.65 ** −0.02 0.58 ** 0.08 0.70 ** 0.23 1 LoR1 −0.20 −0.47 ** 0.17 0.01 −0.24 0.05 −0.19 0.36 * −0.15 0.08 0.12 0.22 1 LoR 2 0.00 −0.09 0.30 −0.03 0.09 0.32 −0.22 0.45 ** −0.18 0.42 * 0.22 0.58 ** 0.43 * 1 LoR 3 0.08 0.12 −0.24 −0.22 −0.12 0.29 0.13 −0.12 −0.04 0.05 −0.03 0.12 −0.03 −0.19 1 LoR −0.06 −0.24 0.13 −0.13 −0.14 0.36 * −0.15 .37* −0.20 0.30 0.17 0.50 ** 0.76 ** 0.67 ** 0.42 * 1 V (sig) 0.52 ** 0.31 0.64 ** 0.08 0.75 ** 0.26 −0.19 0.66 ** 0.184 0.46 ** 0.17 0.72 ** 0.04 0.48 ** 0.01 0.29 1 0.00 0.07 0.00 0.66 0.00 0.13 0.28 0.00 0.30 0.01 0.34 0.00 0.80 0.00 0.95 0.10 E1 E2 E3 E4 E S1 S2 S3 S4 S5 S6 S LoR1 LoR2 LoR3 LoR V Table 2: Correlation of each component with the vulnerability Fig. 5. Flood related environmental issues 5. Conclusion - Several districts are flood vulnerability hot spot - Factors influencing vulnerability are differentiated - Communication tool and can serve for decision making - MOVE framework is a promising tool for vulnerability assessment in local context, Contact e-mail: [email protected] | Université Félix Houphouët-Boigny (UFHB)/ Young Scientist of the Integrated Research for Disaster Risk (IRDR) Fig.2. Flood consequences in Cocody
Transcript of E Y F S I E I T A Côte d’Ivoire using the MOVE framework Y D E I C … · 2019. 9. 11. · E1 E2...
1. BackgroundCoupled with poor urban development, the increasing urban population of many Sub-Saharan
African countries is subject to recurrent severe flooding episodes. In response to these flood
events, while the focus is often put on slums and precarious urban settings, the social
implications of these floods affect a variety of social classes..
Main objective: evaluates the social vulnerability of urban Côte d’Ivoire to flooding using
the MOVE framework
2. Study site
Cocody, a district of Abidjan, Côte d’Ivoire, known to have the country’s highest number offlood-impacted people.
3. Material and MethodsMethod for the Improvement of Vulnerability Assessment in Europe (MOVE Framework)
Indicator selection
Thanks to the organizers and sponsors of this event
Fig.1. Localization of the study site
Assessment of social vulnerability to flood in urban Côte d’Ivoire using the MOVE framework
Fig. 4. Vulnerability map
Table 1: list of selected indicators
Fig. 3. The MOVE theoretical framework
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Components N° Indicators
Exposure
E1 Population density (inhbts/km2)E2 Elevation (m)E3 Vertical permeability (m/s2)E4 Flooded areas per sub-district (%)
Susceptibility
S1 Children under 5 (%)S2 Elderly above 65 (%)S3 Vegetation cover per sub-district (%)S4 Women (%)S5 Waste collection (number of day/week)S6 Unplanned waste deposits (number)
Lack of Resilience
LoR1 Literacy rate (%)LoR2 Number of people insured (%)LoR3 Unemployment rate (%)
4. Results
E1 1E2 0.05 1E3 0.00 0.17 1E4 0.22 −0.35 * 0.06 1E 0.62 ** 0.42* 0.59 ** 0.45 ** 1
S1 −0.11 0.11 0.01 −0.46 ** −0.21 1S2 −0.12 0.26 −0.36 * −0.30 −0.25 −0.06 1S3 0.39 * −0.17 0.57 ** 0.02 0.39 * −0.03 −0.05 1S4 0.04 0.22 0.29 −0.09 0.22 −0.17 0.07 0.17 1S5 0.05 0.23 0.07 −0.28 0.03 0.34 * −0.13 0.09 −0.11 1S 6 −0.05 −0.37 * 0.27 0.10 −0.02 0.09 −0.21 0.22 0.07 −0.05 1S 0.15 0.10 0.36 * −0.40 * 0.10 0.65 ** −0.02 0.58 ** 0.08 0.70 ** 0.23 1
LoR1 −0.20 −0.47 ** 0.17 0.01 −0.24 0.05 −0.19 0.36 * −0.15 0.08 0.12 0.22 1LoR 2 0.00 −0.09 0.30 −0.03 0.09 0.32 −0.22 0.45 ** −0.18 0.42 * 0.22 0.58 ** 0.43 * 1LoR 3 0.08 0.12 −0.24 −0.22 −0.12 0.29 0.13 −0.12 −0.04 0.05 −0.03 0.12 −0.03 −0.19 1LoR −0.06 −0.24 0.13 −0.13 −0.14 0.36 * −0.15 .37* −0.20 0.30 0.17 0.50 ** 0.76 ** 0.67 ** 0.42 * 1
V(sig)
0.52 ** 0.31 0.64 ** 0.08 0.75 ** 0.26 −0.19 0.66 ** 0.184 0.46 ** 0.17 0.72 ** 0.04 0.48 ** 0.01 0.29 10.00 0.07 0.00 0.66 0.00 0.13 0.28 0.00 0.30 0.01 0.34 0.00 0.80 0.00 0.95 0.10E1 E2 E3 E4 E S1 S2 S3 S4 S5 S6 S LoR1 LoR2 LoR3 LoR V
Table 2: Correlation of each component with the vulnerability
Fig. 5. Flood related environmental issues
5. Conclusion
- Several districts are flood vulnerability hot spot
- Factors influencing vulnerability are differentiated
- Communication tool and can serve for decisionmaking
- MOVE framework is a promising tool forvulnerability assessment in local context,
Contact e-mail: [email protected] | Université Félix Houphouët-Boigny (UFHB)/ Young Scientist of the Integrated Research for Disaster Risk (IRDR)
Fig.2. Flood consequences in Cocody
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