Modeling of Orchards Irrigation Demand Under Vulnerable ... · modeling software version 8.0, is...

Islamic University-Gaza

Deanship of Graduate Studies

Faculty of Science

Environment & Earth Science

زةـغ –الجامعة اإلسالمية

اـيـلـعـات الـدراسـعمادة ال

ــومـــلـــعــكــــلــــيــــة الــ

قسم البيئة و علوم األرض

Modeling of Orchards Irrigation Demand Under Vulnerable Climate

Change and the Sequencing Effect of Soil Salinization in Gaza Strip

By Ehab K. Ashour

Supervised By Dr. Husam Al-Najar

Islamic University – Engineering Faculty Environmental Engineering Department

In partial fulfillment of the requirement for degree of Master of Science in Environmental science / Environment management and monitoring

The Islamic University – Gaza – Palestine May, 2012

I

ABSTRACT

Gaza strip has an acute deficit in water both for domestic and agricultural use. This deficit is related to water quantity and quality. Agricultural sector is the main water consumer in the Gaza Strip with not less than 50% of the total groundwater extraction. Climate change has many effects on the hydrological cycle and thus, on water resources systems. Therefore; it is forecasted that the water deficit is likely to be exacerbated within the next years due to the consequence of the global warming and excessive use of irrigation water. This study aimed to analyze the potential impact of the temperature and precipitation change and water salinity on the agricultural water demand for the chosen orchards that covers around 83% of the orchards farms in Gaza Strip. To achieve this goal, CropWat modeling software version 8.0, is used to calculate the crop water requirement under different temperature and precipitation scenarios. Furthermore, a survey was conducted of random samples of farmers to evaluate their current irrigation practices and the impact of water quality on applied irrigation quantity as well as additional leaching requirements. The study results showed that there was increase in the minimum temperatures by +0.79 and +0.94 oC in the last two decades, and there was an increase in the maximum temperatures by +0.29 and +0.26 oC in the same period. The increased temperatures by +1oC or +2 oC caused an increase of the annual average evapo-transpiration by 0.13 and 0.16 leading to increase of irrigation requirements by 3.30% and 6.74%, respectively. Considering the increase of temperature +2oC, and decrease of precipitation by 10%, the irrigation requirements will be increased by 8.60%. In order to devoid the salinity effect, leaching requirements didn’t exceed 15% in case of EC value less than 2 ds/cm, while it begins to increase rabidly after the EC value passed 3 ds/cm in the moderately sensitive orchards like grape, citrus and guava, and steadily increase in the tolerant orchards like olives and palm. Generally, the impact of salinity increase on the irrigation requirements is much higher than the impact of climate change. Farmers used irrigation network applying irrigation quantities more than others whom using traditional channel system; this fact returns to the low cost of operating irrigation with network comparing to traditional channel method.

Keyword: Gaza Strip, Climate Change, Irrigation Requirements, Salinity and Leaching Fraction.

II

الدراسة ملخص

"في قطاع غزةنمذجة الطلب على مياه الري في ظل المتغيرات المناخية و تأثيرات تملح التربة ": عنوان الدراسة

و ينعكس ھذا العجز على لزراعي، أو للري اعجز حاد في المياه سواء لالستخدام المنزلي منقطاع غزة يعاني اع ـطـقـي الـف اهـوحيد للميـالتي ھي المصدر الو المياه الجوفية منياه التي من الممكن ضخھا ـمـكمية و نوعية ال

التي المياه الجوفيةإجمالي ٪ من 50بما ال يقل عن أن الزراعة ھي المستھلك الرئيسي للمياه في قطاع غزة كما ،، نظم الموارد المائية ، وبالتالي على على الدورة الھيدرولوجية كبيرةتأثيرات ا لھ يةالمناخ اتتغيرإن ال .يتم ضخھا

حرارة ات الالمقبلة وذلك نتيجة الرتفاع درجفي غضون السنوات اً متزايداً عجزتواجه من المتوقع أن و التي ً . واالستخدام المفرط لمياه الري رتفاع درجات الحرارة إبالتوازي مع داد زتأن المرجحملوحة المياه من أيضا

.الري بشكل كبيرعلى مياه الطلب ھذا ما سيزيد و التبخر، مستويات الرتفاع كنتيجة

مياه الري لري وملوحة المياه في الطلب على إلى تحليل اآلثار المحتملة للتغيرات المناخيةھذه الدراسة تھدف اتلتغيرلالعوامل الرئيسية أخرى ، و لھذا تم دراسة طبق على محاصيل تُ أشجار معينة كدراسة حالة يمكن أن

لتحقيق ھذا الھدفو و تأثير ذلك على الري ، ھطول األمطار ات فيتغيرالالحرارة و اتدرجتتمثل في و يةالمناخالتي تغطي حوالي لألشجار موضع الدراسة ولحساب االحتياجات المائية " CropWat" تم إستخدام برنامج النمذجة

، عالوة على ذلك. يةالمناخ اتتغيرإفتراضية للفي إطار سيناريوھات ، و ذلك ٪ من البساتين في قطاع غزة83، وتأثير نوعية المياه على الري الحالية ية من المزارعين لتقييم ممارساتأجريت دراسة استقصائية لعينات عشوائ

.، فضال عن متطلبات الترشيح اإلضافية تطبيقھاالتي يتم كمية الري

درجة مئوية 0.94+ إلى 0.79+ بمعدل ياالُدنأظھرت نتائج الدراسة أن ھناك زيادة في درجات الحرارة درجة مئوية خالل 0.26+ إلى 0.29+ھناك زيادة في درجات الحرارة القصوى كما أن ،العقدين الماضيين خالل

.نفس الفترة

2+أو 1+ات الحرارة زيادة درجف، التبخر مع ارتفاع درجات الحرارةمعدل زيادة CropWat أظھرت نتائجكما ، مما أدى إلى زيادة متطلبات الري على التوالي %0.16و % 0.13بمعدل سنوي يادة التبخر أدى لزمئوية درجة كان اإلرتفاع رتفاع درجات الحرارةاألسوأ الذي تم إفتراضه إل سيناريوال .على التوالي% 6.74و % 3.3بمعدل زيادة متطلبات الريى إلى ذي أداألمر ال ٪10بنسبة تناقص معدل ھطول األمطار و ، درجة مئوية 2+ بمعدل .٪8.60بنسبة

لكھربي اأن قيمة التوصيل ٪ في حال15لم تتجاوز أظھرت الدراسة أن الكميات اإلضافية الالزمة لغسيل التربة أن تتجاوز قيمة التوصيل بعد متسارع تبدأ في الزيادة بشكل أنھافي حين ، متر/ديسيسيمنز 2قل من لمياه الري ھي أ

و عند نفس درجة ، ة مثل الحمضيات والعنب والجوافةيالحساساألشجار معتدلة في متر/ديسيسيمنز 3 الكھربيالتوصيل الكھربي تزداد كميات الري اإلضافية بشكل معتدل في األشجار المقاومة للملوحة كما ھو الحال في أشجار

.يةالمناخ اتتغيرالي ھو أعلى بكثير من تأثير عموما، فإن تأثير زيادة الملوحة على متطلبات الر. الزيتون والنخيل

شبكة ري مون ستخدالذين يالمزارعين أنظھر الميداني أالمسح المزارعين التي تم جمعھا خالل تحليل بيانات، وھذا يعود إلى بالقنوات التقليدي الري نظاميعتمدون على ما زالوا ر من اآلخرين الذينبأكيقومون بالري بكميات

.للري بالقنواتمع الطريقة التقليدية عن طريق شبكات الري مقارنة تكلفة الريانخفاض

III

DDEEDDIICCAATTIIOONNSS

TToo tthhee ssppiirriitt ooff mmyy ffaatthheerr,,

TToo mmyy ssiinncceerree mmootthheerr ffoorr hheerr ccoonnttiinnuueess kkiinnddnneessss,,

TToo mmyy uunnccllee OOmmaarr AAsshhoouurr ffoorr hhiiss oouuttssttaannddiinngg ssuuppppoorrtt..

TToo mmyy wwiiffee wwhhoo aallwwaayyss ssuuppppoorrtteedd aanndd eennccoouurraaggeedd mmee

aatt aallll ssttaaggeess ooff oouurr mmaarrrriiaaggee;; aanndd

TToo mmyy bbeelloovveedd ssoonnss KKhhaalliidd aanndd ZZaaiinn,, bbeelloovveedd ddaauugghhtteerr

HHaayyaa wwhhoo hhaavvee bbeeeenn aa ggrreeaatt

ssoouurrccee ooff mmoottiivvaattiioonn aanndd iinnssppiirraattiioonn

IV

ACKNOWLEDGMENT

I would like to thank all those who have assisted, guided and

supported me in my studies leading to this thesis.

I would like to express my gratitude to my supervisors Dr.

Husam Al Najar for his support and valuable advises.

I would like to express my sincere appreciation to Eng. Nizar

Al Wheedy and Eng. Mohamad Amara from Ministry of

Agriculture whom showed unending cooperation and support,

extended appreciation to the Agricultural Union Works

Committee, particularly for Eng. Ra’aed Abu Jalal who provides

me with valuable data through the last agricultural census in

Gaza Strip.

Special thanks to Eng. Jamal Al-Dadah and Eng. Mahmoud

Abd Al-lateef from Palestinian Water Authority who always

provided me with valuable advises and references.

I am greatly indebted for Mr. Iyad Al-Faleet who assisted me

efficiently in the field survey, which would have been impossible

without his assistance.

Many thanks for Mr. Roger Shelton and Michael Odong from

the Economic Security Department in the International

Community of the Red Cross whom reviewed and corrected the

thesis language.

It is always impossible to personally thank everyone who has

facilitated successful completion of this study, to those of you who

I did not specifically named, I also give my thanks for moving me

towards my goal.

V

TABLE OF CONTENTS

ABSTRACT………………..........………………...………………………………………. I

ABSTRACT(ARABIC)……………………..…………………………………………… II

DEDICATIONS…………………………..…………………………………………….. III

ACKNOWLEDGMENT.………………….......…………………………………………IV

TABLE OF CONTENTS.……………..………………………………………………….V

LIST OF FIGURES.……………………..………………………………………..……VIII

LIST OF TABLES.………………………..………………………………..……………..X

LIST OF ANNEXES……………………..……………………...………………………..XI

LIST OF ABBREVIATIONS & ACRONYMS.………..………...…………………..XIII

Chapter 1: Introduction.……………………….……………..…………………………1

1.1 Preface.………………………………...………………………………………….1

1.2 Research Justifications.……………………………….……….…………………3

1.3 Objectives……..……………………….…………………………………………5

1.4 Structure of the Thesis……………………………..……………..………………6

Chapter 2: Literature Review…………..………………………………………………7

2.1 Climate Change Indicators….………….………………….………………………7

2.1.1 Temperature Trends……………..…..…………………………….…………7

2.1.2 Precipitation…………………..…….…………………………...……………8

2.2 Climate Change Impacts…………………………...….…………………………11

2.2.1 Climate Change Impacts on Water Resources……..………….……………11

2.2.2 Climate Change Impact on Agriculture and Food Security….….…….……12

2.3 Climate Change Projections………………………..…………….………………15

2.4 Climate Change Impacts in Gaza Strip…………………...….……..……………16

Chapter 3: Study Area…………………………...……………………………………19

3.1 Location………………..………………………..…………………..……………19

3.2 Soil and Topography……………………...………….…………….….…………20

3.3 Climate…………………………………….………………………..……………21

3.4 Water Sources……………………………………………………….……………25

3.4.1 Introduction……….………………………...………….……………………25

3.4.2 Water Resources Balance………………………...……………...…….….....25

3.4.3 Water Quality………………………………..….…………………………...27

VI

3.5 Agriculture in Palestinian Territories………….…………….……………………31

3.5.1 Introduction ……...……………………….……...….………………………31

3.5.2 Economic Contribution of the Agricultural Sector……….…..……..………31

Chapter 4: Methodology……………..…………….……………...……………………33

4.1 Introduction ……………………………….….………….………………………33

4.2 Methodology of the Study……..………………………...….……………………33

4.3 Study Framework………..…………………………………….….………………34

4.4 Study Area……...………..…………………………………….….………………36

4.5 CropWat Description and Concept...………………………….….………………36

4.5.1 Calculating reference evapotranspiration (ETo) ….……..……………...….…37

4.5.2 Calculating crop evapotrnspiration (ETc) ……………….….…………………38

4.5.3 Calculating crop water requirement (CWR) …………………………..………39

4.5.4 Calculating irrigation water requirements (IWR) …………………….….……40

4.5.5 Data required for CropWat…………………………….…….…………...……40

4.6 Salinity leaching factors…………………………………………………………..41

4.7 Orchards Selection……………...……………….……………...……...…………42

4.8 Data Used in the Study…………...…………………………….........……………43

4.8.1 Climatic Data…………………..……………….……………………………43

4.8.2 Crop data……………...………...……………………………………………44

4.8.3 Farmers data and survey analysis………..……………………………..……44

4.8.4 Soil Data…………………..……....…………………………………………49

4.9 Assumptions of Climate Change Scenarios………………………...….…………49

Chapter 5: Results and Discussion……………………………..…..….………………51

5.1 Introduction……………………………….……….………..…….………………51

5.2 Gaza Strip temperatures data analysis………………………..………….………51

5.3 Effect of irrigation water quality on irrigation water requirements……..….….…53

5.4 Evapotranspiration response to temperature and precipitation changes………….57

5.5 Impact of increasing temperature on crop water requirement……………...….. 58

5.5.1 Irrigation requirement per dunom …………………………………..………58

5.5.2 Irrigation requirement for total area of the studied orchards…………….….59

5.5.3 Impact of decreasing precipitation……………………...……….…………61

5.6 CropWat Irrigation Requirements, Leaching Requirements and Farmers Irrigation

Practices………………………………………..…….……………….……………...61

5.6.1 Olive Orchards………………………..…………….….………………………61

5.6.2 Palm Trees…………………………….……………..…………………………64

VII

5.6.3 Grape Farmers……………………..….……….….……………………………66

5.6.4 Citrus Farmers…………………………...…….…….…………………………67

5.6.5 Guava Farmers…………….……………………………………………………68

Chapter 6: Conclusion and Recommendation……………………..…………………70

6.1 Conclusion………………………………...………….….………………………70

6.1.1 Comprehensive………………………...….………….…………………………70

6.1.2 Study Outputs……………...………………..……….…………………………71

6.2 Recommendation………………........……….…….……………………………73

References…………….………..…………….………………………………………74

Annexes……………………………….……….….………………………….………82

VIII

LIST OF FIGURES

Figure 2.1 Average rainfall in mm in Gaza Strip (2000-2010) 10Figure 2.1 Average rainy days in Gaza Strip (1980-2010) 10Figure 2.3 Water stress map based on WaterGAP 11Figure 3.1 Regional setting of Gaza Strip and the neighboring countries 20Figure 3.2 The soil map of the Gaza Strip 23Figure 3.3 Topography of the Gaza Strip (Shaheen S., 2007) 23Figure 3.4 Rain station distribution in the Gaza Strip 24Figure 3.5 Average annual rainfall from 1974 -2004 (mm/year) 24Figure 3.6 Chloride Concentration for the year 2002 (Source: PWA, 2002) 29Figure 3.7 Chloride Concentration for the year 2007 (Source: CMWU,

March 2011) 29Figure 3.8 Chloride Concentration for the year 2010 (Source: CMWU,

2010) 30Figure 3.9 Predicted Chloride contour map (2020) (Source: PWA, 2011) 30Figure 3.10 Agricultural Sector contribution to the total Palestinian GDP

(2001-2010) (Source: PCBS, 2001-2010) 32Figure 4.1 Methodological framework of the study 35Figure 4.2 Reference (ETo), crop evapotranspiration under standard (ETc)

and nonstandard conditions (ETc adj). Source: FAO, 1998b 39Figure 5.1 Minimum and maximum temperature averages and trends for

three Decades in the Gaza Strip 52Figure 5.2 Ec level and Leaching Requirements Percentage Comparing to

CropWat Irrigation Requirements for Selected Orchards. 55Figure 5.3 Gaza Strip Olive Farms Irrigation Requirements & Leaching

Requirements for Different Levels of Ec 56Figure 5.4 Gaza Strip Palm Farms Irrigation Requirements & Leaching

Requirements for Different Levels of Ec 56Figure 5.5 Gaza Strip Grape Farms Irrigation Requirements & Leaching

Requirements for Different Levels of Ec 56Figure 5.6 Gaza Strip Citrus Farms Irrigation Requirements & Leaching

Requirements for Different Levels of Ec 57Figure 5.6 Gaza Strip Guava Farms Irrigation Requirements & Leaching

Requirements for Different Levels of Ec 57Figure 5.8 Applied irrigation quantities by the olive farmers for different

level of salinity, comparing to CropWat and leaching requirements 63

Figure 5.9 Irrigation method and average applied irrigation m3/year – olive farmers 64

Figure 5.10 Applied irrigation quantities by the palm farmers for different level of salinity, comparing to CropWat and leaching requirements 65

Figure 5.11 Irrigation method and average applied irrigation m3/year – palm farmers 66

Figure 5.12 Applied irrigation quantities by the grape farmers for different level of salinity, comparing to CropWat and leaching requirements 67

IX

Figure 5.13 Applied irrigation quantities by the citrus farmers for different level of salinity, comparing to CropWat and leaching requirements 68

Figure 5.14 Applied irrigation quantities by the guava farmers for different level of salinity, comparing to CropWat and leaching requirements 69

X

LIST OF TABLES

Table 4.1 Trees distribution in the Gaza Strip Governorates (PCBS and

MoA, 2010) 42Table 4.2 Monthly averages for the climatic parameters used for the study

(1995-2006) 43Table 4.3 Farmers number for selected orchards in different governorates

of the Gaza Strip (PCBS and MoA, 2010) 44Table 4.4 Distribution of the surveyed farmers of the selected orchards for

the research 46Table 4.5 Questioner form used for the farmers Survey 48Table 5.1 Minimum, maximum and averages temperatures for three

deceased of Gaza temperature records 53Table 5.2 Orchards tolerance and yield potential as influenced by irrigation

water salinity (ECw) or soil salinity (ECe) 54Table 5.3 Reference evapotranspiration (ETo) respond to the temperature

changes 58Table 5.4 Average irrigation requirements in cubic meter per dunom for the

studied orchards in Gaza Strip 59Table 5.5 Total irrigation requirements per MCM and percentage of

increase for total areas cultivated with the studied orchards in Gaza Strip 60

XI

LIST OF ANNEXES

Annex (1-A) Minimum temperature averages in Gaza Strip, 1976-2006 82Annex (1-B) Maximum temperature averages in Gaza Strip, 1976-2006 83Annex (1-C) Temperature averages in Gaza Strip, 1976-2006 84Annex (2-A) Irrigation requirements under different climate change

scenarios for the different orchards in different governorates of Gaza Strip - Olives, Gaza city 85

Annex (2-B) Irrigation requirements under different climate change scenarios for the different orchards in different governorates of Gaza Strip – Olives , Middle governorate 86

Annex (2-C) Irrigation requirements under different climate change scenarios for the different orchards in different governorates of Gaza Strip - Olives, Khan Younis governorate 87

Annex (2-D) Irrigation requirements under different climate change scenarios for the different orchards in different governorates of Gaza Strip - Palm, Middle governorate 88

Annex (2-E) Irrigation requirements under different climate change scenarios for the different orchards in different governorates of Gaza Strip - Palm, Khan Younis governorate 89

Annex (2-F) Irrigation requirements under different climate change scenarios for the different orchards in different governorates of Gaza Strip - Grape, Khan Younis governorate 90

Annex (2-G) Irrigation requirements under different climate change scenarios for the different orchards in different governorates of Gaza Strip - Citrus, Gaza city 91

Annex (2-H) Irrigation requirements under different climate change scenarios for the different orchards in different governorates of Gaza Strip - Citrus , Middle governorate 92

Annex (2-I) Irrigation requirements under different climate change scenarios for the different orchards in different governorates of Gaza Strip - Guava, Middle governorate 93

Annex (2-J) Irrigation requirements under different climate change scenarios for the different orchards in different governorates of Gaza Strip - Guava, Khan Younis governorate 94

Annex (3-A) Irrigation requirements respond to different salinity levels comparing to CropWat required irrigation under optimal salinity levels 95

Annex (3-B) Irrigation requirements respond to different salinity levels comparing to CropWat required irrigation under optimal salinity levels 96

Annex (3-C) Irrigation requirements respond to different salinity levels comparing to CropWat required irrigation under optimal salinity levels 97

Annex (3-D) Irrigation requirements respond to different salinity levels comparing to CropWat required irrigation under optimal salinity levels 98

XII

Annex (3-E) Irrigation requirements respond to different salinity levels comparing to CropWat required irrigation under optimal salinity level 99

Annex (4-A) CropWat results for the irrigation requirements of the studied trees in the different studied governorates of Gaza Strip. 100

Annex (4-B) CropWat results for the irrigation requirements of the studied trees in the different studied governorates of Gaza Strip. 101

Annex (4-C) CropWat results for the irrigation requirements of the studied trees in the different studied governorates of Gaza Strip. 102

Annex (5) Irrigation requirements in cubic meter per dunom for the studied orchards in the different governorates in Gaza Strip. 103

XIII

LIST OF ABBREVIATIONS & ACRONYMS

AMSL Above mean sea level

CWR Crop water requirement

dS/m deciSiemens per metre

EC Electrical Conductivity

ECe Average soil salinity tolerated by the crop

ECw Salinity of the applied irrigation water in dS/m. ET Evapotranspiration

ETo Reference evapotranspiration (mm day -1)

FAO Food and Agriculture Organization

GCMs General Circulation Models

GDP Gross domestic product

IPCC Intergovernmental Panel on Climate Change

IWR Irrigation water requirement

Kc Crop coefficient

LF Leaching fraction

LR Leaching requirement

MCM Million cubic meter

Mm3 Million cubic meter

MoA Ministry of Agriculture

mS/cm. milliSiemens (mS) per centimetre

MSL Mean sea level

NCEP National Centers for Environmental Prediction oC Celsius temperature scale

P Precipitation

PAPP Programme of Assistance to the Palestinian People

PCBS Palestinian Central Bureau of Statistics

PWA Palestinian Water Authority

R.H Relative humidity (%)

RCMs Regional Climate Models

T Temperature (°C)

Tmax Maximum temperature (°C)

Tmin Minimum temperature (°C)

UNDP United Nations Development Programme

WFP World Food Program

Chapter 1 Introduction

1

1. Chapter 1: Introduction

1.1 Preface:

Globally, agriculture is by far the largest water-use sector, accounting for about 70% of

all water withdrawn worldwide from rivers and aquifers for agricultural, domestic and

industrial purposes. In several developing countries, irrigation represents up to 95% of

all water withdrawn, and it plays a major role in food production and food security

(Max, 2009). In the arid and semiarid climates, irrigation is often essential to achieve

economically viable crop productions. Benefits from irrigation may be partially offset

by detrimental effects of rising water tables and soil salinization, inefficient water

delivery systems and poor on–farm irrigation techniques (Max, 2009).

In 2010, it was estimated that a proximately 86.67x106m3/y of water to Gaza Strip

supplied for domestic use, while the total water supplied for agriculture use was about

81 x106m3/y (PWA, 2012 and CMWU, 2011).

Gaza strip, like any other parts in the Middle East, has a distinct and serious deficit of

water. The problem in this area is more clear and serious, and it is related to the water

quantity and quality (Shomar, 2010; Qahman et al. 2009;and PWA, 2003).

Ground water is the only resource of water while agriculture is the main water

consumer in the Gaza Strip with more than 70% of the total groundwater extraction

(Lautze and Kirshen, 2009; and PWA, 2006). Ground water is the only re-source of

water, and many estimates of the annual groundwater recharge in the Gaza strip; it have

been mentioned in different references, all of these references agree on one fact, the

annual recharge is less than the extracted quantities for a long time ago. This is resulting

in a serious mining of the groundwater resources due to overexploitation and sea

intrusion if the current practice is continued. (Al-Khateib and Al-Najar, 2011; Qahman

et al. 2009; and PWA, 2003).

It is forecasted that the Palestinian territories are facing a severe water deficit likely to

be exacerbated within the next years due to the consequence of the global warming and

excessive use of irrigation water (Al-Najar, 2011). Farmers in the Gaza Strip use their

own experience to decide when to irrigate the crops. Flow measurement is rarely

installed in irrigation wells. The farmers use about 20 to 30% excess irrigation water

than required for the common cultivated crops (Al-Najar, 2011). Prudent planning


2

requires that a strong water resources research program be maintained, that decisions

about future water planning and management be flexible, and that the risks and benefits

of agricultural economy be incorporated into all long-term water planning (Al-Najar,

2011).

In particular, Gaza Strip is described as the most exploited place in the world where the

level of demand on resources exceeds the capacity of the environment (Gaza

Environmental profile, 1994). Apparently, increased temperatures lead to more

groundwater pumping to meet the escalating crop water demand.

Annual precipitation rates are deemed likely to fall in the eastern Mediterranean-

decreasing 10% by 2010 and 20% by 2050 - with an increased risk of summer droughts

(UNDP-PAPP, 2010).

The agriculture sector in the Palestinian territories is the most sensitive sector to

climatic hazards both current and future, this means that agricultural production will be

reduced for rain-fed agriculture, the price of vegetables, fruits, and other agriculture

products will rise as well, bringing about a further negative effect on marginalized

communities (UNDP-PAPP, 2010).

The rapid increase in urban population, land scarcity and the challenge of urban food

security has accelerated the phenomenon of urban agriculture on the account of water

resources in Gaza Strip, which is mostly ignored by planning institutions. The trend of

degradation of water resources will continue if serious plans are not prepared

considering the climate change in addition to policies and strategies towards efficient

water allocation (Al-Najar, 2007) .


3

1.2 Research Justifications:

Despite its small area (365 km2) and generally flat terrain, there are also significant

variations in the Gaza Strip’s temperate climate. The average seasonal rainfall is 522

mm in the northern Beit Lahia governorate and 225 mm in the southern Rafah

governorate (PWA, 2007).

The Gaza Strip experiences hot, dry summers and mild winters, there is already some

evidence that global warming is affecting the Gaza Strip; an analysis of daily

temperature data from 1976 to 1995 has shown an increase in mean temperature of

0.4oC, which reflects above all an upward trend in minimum temperature values (El-

Kadi, 2005). This finding is corroborated by Israeli research demonstrating that average

temperatures in the eastern Mediterranean have increased steadily over the last 100

years (Krichak et. al, 2007).

The present problems in the Palestinian territories that are related to water are many and

varied; as in the neighboring countries also with limited water resources; the last decade

have seen a variation in the amount of rainfall received, average rainfall for the Gaza

Strip during 2008-9 was 12% below the historic average, while it is more than 400 mm

during the year 2011-12 (MoA, 2012).

There are severe problems both with water quantity and quality in the Gaza Strip, which

relate above all to over-pumping of the Coastal Aquifer. The ‘sustainable limit’ of the

coastal aquifer has been estimated at 350 (MCM/year) of which the Gazan portion is

roughly 55 MCM/year (Yacoubi, 2008).

Total municipal water use in Gaza strip increased, from 57 MCM in year 2000 to 93.8

MCM in year 2010. This figure is reasonable and logical due to increase of population

(PWA, 2011), while agricultural water use and water use productivity are not always

available at country level. This is mainly due to the complexity of the assessment

methods and to the absence of direct measurement of water withdrawal for agriculture.

The water allocated for irrigation is never been measured, the farmers have not any

measurement devices on the wells to determine the abstracted amount for irrigation. In

the current farmers practice; citrus, olives, fruits and vegetables are irrigated with extra

or less amounts of water required for evapotranspiration due to absence of research in

this field (Al-Najar, 2007). According to the PWA, the approximate estimation of

irrigation water demand based on the quota allowed and the available irrigated lands in


4

the Gaza Strip is about 75-80 MCM/year in 2004 (PWA, 2004). They estimated the

same volume for the total water supplied for agriculture use in 2010 with about 81

MCM/y (PWA, 2011), with demonstrated a clear depression of water abstracted for

irrigation purposes taking into account the illegal abstraction from more than 4600

agricultural wells (2600 legal wells and more than 2000 illegal wells) distributed all

over Gaza Strip (PWA, 2004 and 2011).

The agricultural water consumption was roughly estimated from the available

cultivated areas multiplied by the irrigation water quota allowed for each crop allocated

officially by PWA and MoA. Mostly in Gaza Strip, the agricultural wells flow have not

been accurately measured, due to absence of well functioning water-meter or because it

was not installed absolutely. The seasonal crop water requirements showed that two

thirds of the total cultivated area is irrigated area (118,000 donam out of the total area

161,000 donams) (Afifi et al,. 2012 and PWA, 2011).

This means that the Gazan portion of the aquifer is already being over-drawn at nearly

three times its natural limit. furthermore salinity levels in the groundwater can rise as

high as 300-500 mg/l (as chloride) due to the over pumping which leads to seawater

intrusion (Al-Kateb and Al-Najar, 2011; Vengosh et al., 2005; Almasri, 2008).

The agro-economical sector in Palestine is one of the most sensitive to climate hazards,

both current and future. Agriculture has the highest sector usage for water in the

Palestinian territories (West Bank and Gaza Strip), consuming 155 MCM/yr, which is

66% of the water withdrawn by Palestinians (Lautze and Kirshen 2009). It is also an

economically significant sector accounting to about 10% of the Palestinian GDP, 20%

of exports and 15% of total employment (FAO 2009).

This is to imply that, there is an urgent need to address climatic changes on agricultural

livelihoods; climatic variables such as temperature and precipitation are essential inputs

to agricultural. Thus, it is important to assess the potential effect of climate change, not

only the direct effects of climate on crop yields and farm profit, but also the effects of

climate change on the effective water requirements and the availability of water for

agricultural irrigation (Schlenker et al, 2007).

Based on the previous mentioned facts, farmers in the Gaza Strip are facing challenges

to sustain and mitigate their future existence against the decreased water availability on


5

times where the increase in temperature required increase on water demand as a

quantitative factor, and groundwater salinization as qualitative factor.

The research is an attempt to explore and analyze the current irrigation water

consumption and the probable climate change impacts on irrigation requirements for the

main crops in Gaza Strip using CropWat model version 8 which is developed by Food

and Agriculture Organization. The research also will conclude general guidelines of

agricultural water management in Gaza Strip in light of climate change and prospective

drought conditions to face the future challenges in the agricultural sector in the Gaza

Strip.

1.3 Objectives:

The overall objective of the research is to study and assess the current irrigation

practices, and water used for certain orchards cultivated in the Gaza Strip, which cover

around 82% of orchards areas based on historical metrological data and water salinity.

Moreover, the irrigation water requirements for different predictable scenarios of

climate change in the future and the sequencing impact on soil salinity will be

highlighted.

The specific objectives are:

• To determine the current water use in irrigation of the main orchards cultivated

in the Gaza Strip

• To determine the proportion of crop evapotranspiration under different expected

climate change scenarios.

• To determine the crop water requirement for selected crops under different

expected scenarios of climate change.

• To determine the effects of leaching factors for different levels of salinity on the

irrigation water requirement.


6

1.4 Structure of the Thesis:

The basic structure of the thesis is organized in five chapters:

Chapter 1 Introduction, problem definition and objectives of the study.

Chapter 2 Summarizes the literature review along with a background information

related to climate change; observations from past century, projections for

the future and its potential impacts on agriculture water demand.

Chapter 3 Describing the study area geographically with briefing about its climate,

water resources and agriculture.

Chapter 4 Deals with the methodology used to achieve the objectives of the study.

Chapter 5 Explains the findings, results and discussion on irrigation requirements

and the impact of climate change in terms of temperature and

precipitation change and the potential impacts on agriculture water

demand.

Chapter 6 Concludes the results of the study and recommendations suggested.

References

Chapter 2 Literature Review

7

Chapter 2: Literature Review

This chapter reviews the literature related to the climate change indicators. And on the

other side reviews the climate changes impacts on water resources as well as

agricultural activities which will affect the food security.

2.1 Climate Change Indicators:

There are many indicators for the climate changes, but the most important parameters

which indicates the climatic changes are the temperature and precipitations. These two

factors will be highlighted in the following clauses.

2.1.1 Temperature Trends:

It is already known that during the 20th century there was an average increase in annual

mean temperature of between 1.5 to 4 oC for the region. Globally, the mean temperature

is expected to increase by an additional 1.8 to 4 oC by the end of the 21st century relative

to the 1980–1999 period (Bates et al. 2008; IPCC, 2007).

For Palestine, the temperature is expected to rise by 3.5–5 oC by 2071–2100 in

comparison to 1961–1990 (Alpert et al. 2008; Bar-Or 2008; Golan- Engleco and Bar-

Or 2008; IPCC, 2007). The full consequence of temperature and rainfall changes are

wide ranging and a variety of studies have described the possible impact of these

changes on nearly all aspects of environment and society (Bates et al., 2008).

Although the future effects of climate change in the Middle East are uncertain –

reflecting the relatively short time period covered by the existing record and a lack of

reliable data– substantial research has been conducted and some insights obtained.

Nearly most of the researches in the region confirms that climate change will have a

direct effect on regional water resources (Alpert 2004; Ben-Gai et al. 1998; Dayan and

Koch, 1999; Pe’er and Safriel, 2000). Temperature analyses by Saaroni et al. (2003)

for the period of 1948–2002 reported an increase of 0.013 oC per year for the months of

July and August and statistically significant warming trends were observed for the

decades of 1961–1970 and 1991– 2000 (Saaroni et al., 2003). For the period of 1964–

1994, Ben-Gai et al. (1994) observed an increase in both minimum and maximum

temperatures.


8

Furthermore, there has been an increase in the number of hot and cool days per year,

which implies an increase in temperature extremes (Saaroni et al., 2003). Between the

years 1948–1977, August was the hottest month of the year; however, since then July

has been observed to be the hottest month, a finding which implies the onset of earlier

summers (Saaroni et al., 2003).

2.1.2 Precipitation:

Interactions between the components of the hydrological cycle and the surface land

cover are complex and difficult to predict. Predictions of precipitation levels and

patterns using global climate models for the region were contradictory (Mariotti and

Struglia, 2002).

Confounding uncertainties in these models include variable estimates for long-term

changes to the hydrological cycle, uncertainties regarding future predictions of

greenhouse gas emissions and differing parameters for the hydrological and climate

model structures (Bates et al., 2008). These uncertainties are further exacerbated by the

coarse resolution of the global models, extrapolation issues from global to regional

scales and the spatial and temporal limitation of data sets. Several studies (Ben-Gai et

al. 1993; Otterman et al., 1990) have found evidence of increasing precipitation in the

south of historical Palestine. The Israel National Report on Climate Change surmised

that this increase is partially a result of land-use changes such as forestation,

modifications to agricultural practices, and grazing restrictions (Pe’er and Safriel,

2000). None of the studies cited above, however, are able to substantiate this trend as

being either of long- or short-term duration. Comparing the 1931–1961 with the 1962–

1990 records, Ben-Gai et al., (1998) reported that extreme weather events, both heavy

rains and droughts, have become more frequent. In terms of regional patterns, extreme

rain events are occurring more often in southern rather than northern historical Palestine

(Alpert and Ben-Zvi, 2001). While some studies found that precipitation increased in

the central and southern regions (e.g. Ben-Gai et al. 1993; Otterman et al., 1990), other

studies observed that there has been a decreasing trend in precipitation for the region as

a whole since the 1980s. A wetter than average year, 1991–1992, may be skewing the

figures pointing to increased rainfall (Albert and Ben-Zvi, 2001). Using a 5 year

average over Lake Tiberias, and excluding the wet year of 1991–1992, Albert and Ben-

Zvi (1991) identified a decreasing pattern in rainfall since 1987.


9

Based on global prediction by the IPCC (2007), a 10–30% decrease in annual

precipitation is expected by the second half of the 21st century for this region. Bates et

al., 2008 predicted an approximate 20% decrease in precipitation for the Mediterranean

region. Temporal climatic patterns are also likely to be affected, as changes in the

region’s climate are expected to produce a truncated but more intense winter rainfall

period followed by a longer, drier summer season, the consequences of which are

numerous. Using a high resolution model (Kitoh et al., 2008) simulated two future

climatic scenarios for the region; both scenarios yielded a decrease in future

precipitation. This decrease is predicted to occur mostly in the winter and spring

seasons, along with an increase in evaporation rates. Therefore, even in areas where

precipitation is predicted to increase under Kitoh model (Kitoh et al. 2008), such as the

Gulf Coast Region, water resources will likely not increase because of the increased

rates of evaporation. It is expected that the frequency of extreme (heavy) and variable

precipitation events are likely to increase as a result of climate change (Bates et al.,

2008), along with associated extreme events such as flooding, loss of human life and the

destruction of infrastructure. Extreme rainfall in a short winter season will decrease the

ability of water to infiltrate the soil and into the groundwater tables and also increase

topsoil erosion and exacerbate the process of desertification. Furthermore, rising

average temperatures will cause increasing rates of evapotranspiration, further limiting

groundwater infiltration.

Global changes are not linear in time, showing significant decadal variability, with a

relatively wet period from the 1950’s to the 1970’s, followed by a decline in

precipitation (IPCC, 2008).

For the Mediterranean Sea, precipitation variability has been investigated using gauge-

satellite merged products and atmospheric re-analyses (Mariotti and Struglia, 2002).

National Centers for Environmental Prediction “NCEP” re-analyses show that during

the last 50 years of the 20th century Mediterranean averaged winter precipitation has

decreased by about 20%, with the decrease mostly occurring during the period of the

late 1970s to early 1990s (MedCLIVAR, 2004).

In General, the analyses of Gaza rainfall shows similar rainfall characteristics and

drought conditions to those found in the Mediterranean area drought conditions from

1967 to late 1990s with short-term wet years (El-Kadi, 2001).


10

Recent data on average annual rainfall for the West Bank and Gaza Strip does indicates

a decline since 2002/3 at 354 mm. In 2007/8 the annual rainfall for the West Bank was

66% of the 25-year historical average; while at 262 mm in 2007/2008 the annual

average rainfall for the Gaza Strip was the lowest since 1999 with 73% of the 25-year

historical average (MoA, 2008).

Afifi, 2011, presented the significant decline in average rainfall quantities from 2000 to

2010; as well as the decline in the rainy days in the Gaza Strip within thirty years from

1980 to 2010. Figure 2.1 and 2.2 shows the declination of rainfall in the Gaza Strip, in

light of rainfall and rainy days of annual average

Figure 2.1: Average rainfall in mm in Gaza Strip (2000-2010)1, (Afifi, 2011)

Figure 2.2: Average rainy days in Gaza Strip (1980-2010), (Afifi, 2011)

The period is too short, of course to confidently attribute this recent fall-off in rainfall as

part of longer-term decline induced by climate change as opposed to ‘natural’ climate

variability. It is clear that, the expected changes in precipitation (and humidity) will

1 Source: Afifi, S. 2011: Climate Variability and changes – Gaza Strip, occupied Palestine Territories, UNEP, March, 2011.


11

affect groundwater sources. No previous studies have been carried out on this to date,

except the recent study for CLIMB project “Climate Induced Changes on the Hydrology

of Mediterranean Basin” which study the Gaza Strip case as a part of the Mediterranean

Basin. However, the impacts of changes in the climate on groundwater resources is

difficult to be estimated within a certainty (UNDP-PAPP, 2010).

2.2 Climate Change Impacts:

Climate change has a clear impact on the hydrological cycle and water resources.

Consequently, agricultural production cycle will be affected too, the following lines

presents the global impact of climate changes on water resources and agricultural

production.

2.2.1 Climate Change Impacts on Water Resources:

Water-stressed basins are located in northern Africa, the Mediterranean region, the

Middle East, the Near East, Southern Asia, Northern China, Australia, the USA,

Mexico, North-Eastern Brazil and the West coast of South America (Figure 2.3). The

estimates for the population living in such water-stressed basins range between 1.4

billion and 2.1 billion (IPCC, 2008).

Figure 2.3: Water stress map based on WaterGAP, (IPCC, 2008).


12

Climate warming observed over the past several decades is consistently associated with

changes in a number of components of the hydrological cycle and hydrological systems

such as changing precipitation patterns, intensity and extremes; widespread melting of

snow and ice; increasing atmospheric water vapor; increasing evaporation; and changes

in soil moisture and runoff. There is significant natural variability– on inter-annual to

decadal time-scales – in all components of the hydrological cycle, often masking long-

term trends (IPCC, 2008).

Climate change will lead to an intensification of the global hydrological cycle and is

likely to have major impacts on regional water resources, affecting both ground and

surface water supply for domestic and industrial uses, irrigation, in-stream ecosystems

and water-based recreation. Changes in the total amount of precipitation and in its

frequency and intensity directly affect the magnitude and timing of runoff and the

intensity of floods and droughts (IPCC, 2007).

There is still substantial uncertainty in trends of hydrological variables because of large

regional differences, and because of limitations in the spatial and temporal coverage of

monitoring networks (Huntington, 2006). At present, documenting inter-annual

variations and trends in precipitation over the oceans remains a challenge (IPCC, 2008).

Water use, in particular that for irrigation, generally increases with temperature and

decreases with precipitation. However, there is no evidence for a climate-related long-

term trend of water use in the past. This is due, in part, to the fact that water use is

mainly driven by non-climatic factors, and is also due to the poor quality of water-use

data in general, and of time-series data in particular (IPCC, 2007)

In water-stressed areas, people and ecosystems are particularly vulnerable to decreasing

and more variable precipitation due to climate change (IPCC, 2008).

2.2.2 Climate Change Impact on Agriculture and Food Security:

Water plays a crucial role in food production regionally and worldwide. On the one

hand, more than 80% of global agricultural land is rain-fed; in these regions, crop

productivity depends solely on sufficient precipitation to meet evaporative demand and

associated soil moisture distribution (FAO, 2003). Where these variables are limited by

climate, such as in arid and semi-arid regions in the tropics and subtropics, as well as in


13

Mediterranean-type regions in Europe, Australia and South America, agricultural

production is very vulnerable to climate change (FAO, 2003).

On the other hand, global food production depends on water not only in the form of

precipitation but also, and critically so, in the form of available water resources for

irrigation. Indeed, irrigated land, representing mere 18% of global agricultural land,

produces 1 billion tons of grain annually, or about half the world’s total supply; this is

because irrigated crops yield on average 2–3 times more than their rain-fed counterparts

(FAO, 2003).

Anthropogenic climate change does not only affect water resources but also water

demand. Future water and food security will depend, among other factors, on the impact

of climate change on water demand for irrigation (Döll, 2002).

If a region becomes drier and warmer, the decreased water availability will be

exacerbated by an increased water demand. The water use sector that will be influenced

most by climate change is irrigation. Irrigation is by far the largest use sector; today

about 67% of the current global water withdrawal and 87% of the consumptive water

use (withdrawal minus return flow) is for irrigation purposes (Shiklomanov, 1997).

Globally, irrigated agricultural land comprises less than one-fifth of the total cropped

area but produces about two-fifths of the world’s food. It is generally expected that

irrigated agriculture will have to be extended in the future in order to feed the world’s

growing population. However, it is not yet known whether there will be enough water

available for the necessary extension. One step towards evaluating how much water will

be needed for irrigation in the future is to quantify how climate change will affect

irrigation water requirements (Döll, 2002).

Climate change will affect agriculture through higher temperatures and more variable

rainfall, with substantial reductions in precipitation likely in the mid-latitudes where

agriculture is already precarious and often dependent on irrigation. Water resource

availability will be altered by changed rainfall patterns and increased rates of

evaporation. Rainfed farming will become more precarious in the mid and low latitudes

(FAO, 2011).

Climate change is projected to have significant impacts on conditions affecting global

agriculture, including temperature and precipitation. Agriculture is still directly


14

02dependent on climate, since heat, sunlight and water are the main drivers of crop

growth. While some aspects of climate change – such as longer growing seasons and

warmer temperatures may bring benefits – there will also be a range of adverse impacts,

including reduced water availability and more frequent extreme weather events. These

impacts may put agricultural activities, certainly at the level of individual land managers

and farm estates, at significant risk (AEA Energy & Environment 2007).

The productivity of agricultural, forestry and fisheries systems depends critically on the

temporal and spatial distribution of precipitation and evaporation, as well as, especially

for crops, on the availability of freshwater resources for irrigation (AEA Energy &

Environment 2007).

Where there has been limited high-resolution climate modeling for the eastern

Mediterranean region, increased warming is forecast this century, combined with

changes in rainfall amount and distribution. Some scientists have argued that climate

changes are already happening: analyses of precipitation and temperature data in the last

century reveal rising summer temperatures and a delay in the rainfall season, as well as

increasing inland aridity (Khatib et al., 2007).

Agricultural production in the Palestinian Territories has already been affected by recent

droughts and climate predictions suggest that these will become more pronounced over

time. Thus, a great challenge for the Palestinian Authority in the coming decades will be

the task of increasing food security (by domestic production and/or imports) in

conditions of increased water stress (Kafle and Bruins, 2009).

Production systems in marginal areas with respect to water face increased climatic

vulnerability and risk under climate change, due to factors that include, for instance,

degradation of land resources through soil erosion, over-extraction of groundwater and

associated salinization, and over-grazing of dry land (FAO, 2003).

By critically affecting crop productivity and food production, in addition to being a

necessity in food preparation processes, water plays a critical role in food security.

At the same time, during this century, climate change may further reduce water

availability for global food production, as a result of projected mean changes in

temperature and precipitation regimes, as well as due to projected increases in the

frequency of extreme events, such as droughts and flooding (Rosenzweig et al., 2002).


15

2.3 Climate Change Projections:

Climate varies naturally on all timescales from decades to millennia due to changes in

atmospheric and ocean circulation, solar output and volcanic activity. However, future

climate change will be dominated by human influences unless and until the composition

of the atmosphere is stabilized (Karas, 2010).

Stabilization of concentrations of carbon dioxide - a key greenhouse gas - requires cuts

in emissions of between 50 and 70%. Emissions of other gases would also have to be

reduced significantly – or even stopped completely – if atmospheric concentrations are

to be stabilized and the risk of climate change reduced (Karas, 2010).

The magnitude and rate of future climate change will depend on the amount of

greenhouse gases emitted, the sensitivity of climate to these gases, and the degree to

which the effects are modified by aerosol emissions. The IPCC present six scenarios of

future emissions, based on widely differing assumptions of future population and

economic growth, energy consumption, technological developments and land use.

These all show that atmospheric concentrations of greenhouse gases will continue to

rise throughout the 21st century unless there is concerted action to curb emissions

(Houghton and others, 1996).

If current trends in emissions of greenhouse gases continue, global temperatures are

expected to rise faster over the next century than over any time during the last 10,000

years. Significant uncertainties surround predictions of regional climate changes, but it

is likely that the Mediterranean region will also warm significantly (Karas, 2010).

The Mediterranean region is undergoing rapid local and global social and environmental

changes. All indicators point to an increase in environmental and water scarcity

problems with negative implications towards current and future sustainability. Water

management in Mediterranean countries is challenged these pressures and needs to

evolve to reach the target of increasing population with reliable access to freshwater

established by the Millennium Development Goals (Garrido, 2005).

The outlook for precipitation is much less certain, but most projections point to more

precipitation in winter and less in summer over the region as a whole. A common

feature of many projections is declining annual precipitation over much of the

Mediterranean region south of 40 or 45° N, with increases to the north of this. Even


16

areas receiving more precipitation may get drier than today due to increased evaporation

and changes in the seasonal distribution of rainfall and its intensity (Karas, 2010).

For the eastern Mediterranean, climate predictions have to contend with a lack of

scientific observations on regional atmospheric conditions and limited long-term

environmental data. There are also unresolved issues regarding the calibration of

Atmosphere – Ocean General Circulation Models (GCMs) and Regional Climate

Models (RCMs) in order to simulate conditions consistent with environmental processes

of particular importance to the Mediterranean region, such as the incorporation of dust

into the atmosphere and multiple sources of pollution (Wigley 1992: Mellouki and

Ravishankara 2007).

However, regional climate change simulations undertaken by different models have

delivered a surprisingly consistent account of climate change over the Mediterranean

(Giorgio and Lionello 2007). These forecasts give general scientific backing to the

Intergovernmental Panel on Climate Change (IPCC) projections for the region. In its

Fourth Assessment Report the IPCC predicts that, for the southern and eastern

Mediterranean, warming over the 21st century will be larger than global annual mean

warming – between 2.2 to 5.1ºC according to an optimistic emissions scenario (A1B).

In which rapid economic growth and technological change have reduced reliance on

fossil-intensive energy sources. Annual precipitation is deemed very likely to fall in the

eastern Mediterranean– decreasing 10% by 2020 and 20% by 2050 – with an increased

risk of summer drought.

However, the climate projections derived from high-resolution climate models applied

to the eastern Mediterranean region also differ in some key respects from the lower

resolution IPCC forecasts (Christensen et al. 2007).

2.4 Climate Change Impacts in Gaza Strip:

The agricultural sector is the Palestinian economic sector that is most sensitive to

climate hazards, both current and future. (Lautze and Kirshen 2009).

High climate vulnerability in the Gaza Strip is reflected clearly on the severe problems

both with water quantity and quality, which relate above all to over-pumping of the

Coastal Aquifer. The ‘sustainable limit’ of the Coastal Aquifer has been estimated at


17

350 MCM/year of which the Gazan portion is roughly 55 MCM/year (Yacoubi, 2008).

Total pumping within the Gaza Strip in 2006 was estimated at roughly 150 MCM/year

(distributed evenly between agricultural usage and domestic consumption). Not

accounting for return flows, this means that the Gazan portion of the aquifer is already

being over-drawn at nearly three times its natural limit. The lack of alternative water

sources contributes to water quality problems arising from seawater intrusion, the

infiltration of untreated or partially treated wastewater and ‘natural’ contamination from

Eocene salts migrating under the border from green line. Salinity levels in the

groundwater can rise as high as 300-500 mg/l as chloride (Vengosh et al. 2005;

Almasri, 2008).

The increasingly poor drinking water quality in the Gaza Strip necessitates the increased

purchase of desalinated water from private-sector neighborhood-level reverse osmosis

units, or the purchase of under-the-sink water filtration units, both of which contribute

to the ever-greater share of household income spent on basic services (PWA, 2008a &

2008b).

Cultivated crops are also significantly reduced by decreases in water quality – primarily

the increased salinity of the groundwater, a higher variability in precipitation translates

into reduced yields for rain-fed agriculture. The predicted reductions in precipitation

will likely exacerbate groundwater salinity levels through reduced soil flushing and

groundwater recharge, while reductions in air moisture will likely increase the soil

water requirement of crops, or reduce fruit production. Finally, any sea level rise will

contaminate the coastal soil and increase the saline intrusion already experienced

throughout the Gaza Strip (UNDP-PAPP, 2010).

Increasing food imports from Egypt or other neighboring countries may eventually

enable Gazans to adapt in the long-term to its over-population and lack of natural

resources. Farmers may cope with the poor quality water through switching of crops.

Yet if, in a worst-case scenario, an increase in crop water requirements combines with a

further decrease in water quality. Such coping mechanisms may prove insufficient to

sustain the farmers’ livelihoods. With that threshold breached, a new set of

vulnerabilities may have to be faced, such as the prospects for alternative livelihoods in

an economy prevented from trading with the world. Once more, the social dimensions


18

of climate vulnerability are seen to be more determining than are the biophysical

dimensions (UNDP-PAPP, 2010).

Chapter 3 Study Area

19

Chapter 3: Study Area

3.1 Location:

Gaza Strip is the south-western part of Palestine which is on the south-eastern cost of

the Mediterranean Sea. The zone is located between longitudes 34°2’’ and 34°25’’ east

and latitudes 31°16’’ and 31°45’’ north. Its area is about 365 km2 with a length of 45

km and a width between 6 and 12 km. It is confined between the Mediterranean Sea in

the west, Egypt in the south and the occupied Palestine in 1948 in the east and the north

(Figure 3.1).

Gaza Strip is considered one of the denser places in the world where more than 1.7

million residents (PCBS, 2010). This population is concentrated in four cites, a few

villages, and eight refugee camps with a total built-up residential area of about 80 km2

varying with time due to the population growth (Khalaf et. al, 2007; Metcalf and Eddy,

2000). Geographically, the Strip divided to five main governorates; The Northen, Gaza,

Deir El-Balah, Khanyounis and Rafah as shown in figure 3.1.

From 1967 until 1994, the Gaza Strip was under Israeli occupation. According to the

Oslo agreement between Israeli and the Palestinian, the Gaza Strip has been under the

Palestinian Authority control since May, 1994. Now, the Gaza strip constitutes one

unity as the Israeli settlements were removed in 2005.

Gaza Strip has very limited natural resources especially in freshwater, where Gaza

costal aquifer is the only source of freshwater supply for municipal, agricultural, and

industrial uses (Qahman et al. 2009; PWA, 2009). Knowing that this source is in a

critical situation, it requires immediate efforts to improve the water situation in terms of

quality and quantity.


20

Figure 3.1: Regional setting of Gaza Strip and the neighboring countries.

3.2 Soil and Topography:

The soil in the Gaza Strip is composed mainly of three types, sands, clay and loess. The

sandy soil is found along the coastline extending from south to outside the northern

border of the Strip, at the form of sand dunes. The thickness of sand fluctuates from two

meters to about 50 meters due to the hilly shape of the dunes. Clay soil is found in the

north eastern part of the Gaza Strip. Loess soil is found around Wadis, where the

approximate thickness reaches about 25 to 30 m (Shomar, 2010, and Shaheen, 2007).

In the Gaza Strip, the main soil type originates from the dune sands. Dune sands are

overlying alluvial soils in a shallow layer creating ideal conditions for fruit plantations.

These dune sands have exceedingly low water holding capacity and very high water

permeability. In addition to the sandy soils, loess soils are also occurring in the Gaza

Strip. These soils owe their origin mainly to the dust storms of the desert.


21

The main soil constraint in the Gaza Strip is soil salinity (Dudeen B, 2007). Figure 3.2

shows the soil map of the Gaza Strip.

The topography of Gaza Strip is characterized by elongated ridges and depressions, dry

streambeds and shifting sand dunes. Land surface elevations range from mean sea level

(msl) to about 110 AMSL. There are three surface water features in Gaza Strip: Wadi

Gaza, Wadi Silka, and Wadi Halib (Qahman, 2004).

In the south, these features tend to be covered by sand dunes. The ridges and

depressions show considerable vertical relief, in some places up to 60 m. Surface

elevations of individual ridges range between 20 m and 90 m AMSL (Shaheen, 2007).

Figure 3.3 shows the topography of the Gaza Strip.

3.3 Climate:

Gaza Strip has a semi-arid climate. There are two well-defined seasons: the wet season

starting in October and extending through March and the dry season from April to

September. Peak months for rainfall are December and January.

The Gaza Strip is located in the transitional zone between the arid desert climate of the

Sinai Peninsula in Egypt and the temperate and semi-humid Mediterranean climate

along the coast. This fact could explain the sharp decrease in rainfall quantities of more

than 200 mm/year between Beit-Lahia in the north and Rafah in the South of Gaza Strip

(Qahman, 2004).

The average daily mean temperature ranges from 25°C in summer to 13°C in winter.

Average daily maximum temperatures range from 29°C to 17°C and minimum

temperatures from 21°C to 9°C in the summer and winter respectively. The daily

relative humidity fluctuates between 65% in the daytime and 85% at night in the

summer, and between 60% and 80% respectively in winter. The mean annual solar

radiation amounts to 2200 J/cm2/day (Qahman, 2004).

The rainfall data of the Gaza Strip is based on the data collected from 9 rain stations

(Figure 3.4 ). The average annual rainfall varies from 450 mm/yr in the north to 200

mm/yr in the south of the Gaza Strip (Figure 3.5).


22

Most of the rainfall occurs in the period from October to March, the rest of the year

being completely dry, precipitation patterns include thunderstorms and rain showers,

but only a few days of the wet months are rainy days (Qahman, 2004).

There is less aerial variation in evaporation than in rainfall in the Gaza Strip.

Evaporation measurements have clearly shown that the long term average open water

evaporation for the Gaza Strip is in the order of 1300 mm/yr. Maximum values in the

order of 140 mm/month are quoted for summer, while relatively low pan-evaporation

values of around 70 mm/month were measured during the months December to January

(PWA, 2000).


23

Figure 3.2: The soil map of the Gaza Strip (Palestinian Hydrology Group website, www.phg.org)

Figure 3.3: Topography of the Gaza Strip (Shaheen S., 2007).


24

Figure 3.4: Rain station distribution in the Gaza Strip (Al-Hallaq, A. 2008)

Figure 3.5: Average annual rainfall from 1974 -2004 (mm/year)

(PWA, 2007)


25

3.4 Water Resources:

3.4.1 Introduction:

The groundwater aquifer beneath Gaza Strip is limited in its area, while the natural

boundary of this aquifer reach Haifa in the North and goes to Sinai in Egypt in the

south, and it’s also bounded from Hebron in the East till the Meditation Sea in the west.

Due to Israeli occupation practices along the years, the Gaza ground aquifer becomes

limited in its fresh water storage because the natural recharge from East and North is

being trapped before reaching the green line of the Gaza Strip through drilling wells

adjust to the Eastern and Northern Gaza borders. In addition, the dams which are being

constructed along the upper stream of Wadi Gaza to stop the natural flow in the Wadi

towards Gaza Strip, in which make the entire Wadi’s in the Gaza Strip dry (CMWU,

2011).

The natural water resource in the coastal aquifer has been over abstracted and polluted

due to the increasing water demand that significantly exceeds the total water recharge of

the aquifer. The ground water system was controlled by subsequent parties in the last

decades, Egyptians, Israelis, share management between the Palestinians and Israelis

and finally the Palestinians. Over four thousands water wells are penetrating the shallow

aquifer of the Gaza Strip and pump more than its safe yield, which led to negative

impact on aquifer and consequently on quantity and quality of public water supply

(Hamdan, 2012).

3.4.2 Water Resources Balance:

Gaza’s water resources are essentially limited to that part of the coastal aquifer that

underlies its 365km2 area. The coastal aquifer is the only aquifer in the Gaza Strip. The

major source of renewable groundwater in the aquifer is rainfall, the total natural

recharge to the aquifer is estimated to be approximately 55-60 x106m3/y (PWA, 2012

and CMWU, 2011).

However, pumping over 50 years has significantly disturbed natural flow patterns, the

water balance of the Gaza coastal aquifer has been developed based on estimate of all

water inputs and outputs to the aquifer system. The Gaza coastal aquifer is a dynamic

system with continuously changing inflows and flows, the present net aquifer balance is

negative, that is resulted to a clear water deficit. Under defined average climatic


26

conditions and total abstraction and return flows, the net deficit is about 70x106m3/y in

2010 and will reach to about 180 x106m

3/y in 2035 if there is no management actions taken

mainly related to reuse and sea water desalination (PWA, 2012 and CMWU, 2011).

More water was pumped from the aquifer than was recovered by the aquifer. This over

extraction from the aquifer has resulted in drawdown of the groundwater with resulting

intrusion of seawater and up-coning the underlying saline water (PWA, 2012).

The only water source has been faced a deterioration in both quality and quantity for

many reasons, e.g. low rainfall rate, increased in the urban areas which led to a decrease

in the recharge quantity of the aquifer. Also increasing the population depleted the

groundwater aquifer and lead to seawater intrusion in some areas as a result in pressure

differences between the groundwater elevation and sea water level (CMWU, 2011).

This leads to an annual water deficit in the water resources of about 70 Mm3, which has

its impact on the supplied water quantities as well as their water quality due to sea water

intrusion and deep groundwater upcoming. The average annual rainfall gives a bulk

amount of water of about 114 Mm3 (PWA 2007), from which only 45 Mm3 infiltrate

naturally to the aquifer which forms only 40% of the total rainfall (Hamdan and

Muheisen 2003).

The water balance of the Gaza coastal aquifer has been developed based on an estimate

of all water inputs and outputs to the aquifer system (Al-Yaqubi, et al, 2007).

The deficit of 32 MCM / year between total input and output to Gaza aquifer, implying

the following adverse consequences:

A) Lowering of the groundwater table.

B) Reduction in availability of fresh groundwater.

C) Increased seawater intrusion and potential intrusion of deep brines.

The continuous depending on the groundwater as the only water resources will increase

the deficit and the aquifer will be worse by all means. Therefore new resources should

be considered to fulfill the present and future water needs (PWA, 2007).


27

3.4.3 Water Quality:

The previous hydrogeological studies showed clearly that the Gaza Coastal Aquifer has

been negatively affected by the intensive pumping. The water crisis is not limited only

to the deficit in quantity; where the groundwater quality is deteriorated and subject to

continuous increase in salinity due to over abstraction; as well as the pollution due to

the percolation of wastewater (PWA, 2007).

The groundwater quality is monitored through municipal wells and some agricultural

wells distributed all over the Gaza Strip. The agricultural monitoring wells are tested for

chloride and nitrate ions twice a year by the MOA, while the municipal wells are

monitored through selected cation’s and anion’s twice a year with the cooperation of

both MOH and CMWU. The groundwater quality varies from one place to another and

from one depth to another. The chloride ion concentration varies from less than

250mg/L in the sand dune areas and to about more than 10,000mg/L where the seawater

intrusion has occurred (CMWU, 2011).

Water quality in the Gaza Strip is clearly deteriorating, groundwater depletion impacted

on salinity increasing which become urgent problem in the strip, figure 3.6, 3.7, 3.8 and

3.9 show the current chloride concentration and the predicted increase by time (Al-

Khatib, 2009).

It became a clear fact that there is a critical environmental issue is related to the serious

water quality problems in the Gaza Strip. It is not rational saying that there is currently

no water shortage in the Gaza Strip (except in Rafah Governorate), water will become

increasingly more scarcer in the seen future (World Bank, 2009).

Up to end of 2007, PWA reported that there is no domestic water supply shortage in all

of the Gaza Strip Governorates except for Rafah governorate in terms of quantity, while

in term of quality more than 90% of the pumped water is far from the drinking water

standard and can be used only for domestic purposes (PWA, 2007).

Water quality in Gaza is rapidly deteriorating, and this can have an impact on

agricultural yields. The salinity of the water used for irrigation has increased

significantly in some parts of the Gaza Strip in recent years (World Bank, 2009).


28

Young fruit and olive saplings are less tolerant to brackish water and while mature

plants would have survived due to slow adaptation to rising salinity, and new crops may

not be able to develop (World Bank, 2009).


29

Figure 3.6: Chloride Concentration for the year 2002 (Source: PWA, 2002)

Figure 3.7: Chloride Concentration for the year 2007 (Source: CMWU, 2011)


30

Figure 3.8: Chloride Concentration for the year 2010

(Source: CMWU, 2010). Figure 3.9: Predicted Chloride contour map (2020)

(Source: PWA, 2011).


31

3.5 Agriculture in Palestinian Territories:

3.5.1 Introduction:

The Palestinian agricultural sector serve a population of about 3.8 million people in the

West Bank and Gaza Strip, providing both an economic and food resource to the

Palestinians (PCBS, MoA – 2011, Agriculture Census).

The type of agriculture practiced varies with region, but in general it can be divided into

two groups, plant production, both rain fed and irrigated, and livestock production

(MoA, 2010).

There are over 100 main crop types, and fruit trees are the most dominant group. Olive

production accounts for 81.1% of the area, and produces between 50,000 and 180,000

tons annually in a two-year production cycle. Citrus were the most important crop by

economic value, although they occupy around 13.1% of the tree area in the Gaza Strip,

citrus are also very water intensive crops and the production is concentrated mainly in

the Gaza Strip (PCBS, MoA – 2011, Agriculture Census).

3.5.2 Economic Contribution of the Agricultural Sector:

The agricultural sector is a vital sector in the Palestinian economy as it has

demonstrated to be one of the key sources of growth in the economic recovery that took

place from 2003-2005 (World Bank, 2009).

It is also an economically significant sector accounting for about 10% of the Palestinian

GDP, 20% of exports and 15% of total employment (FAO 2009: 12).

The Palestinian economy is highly susceptible to external shocks, political events and

the Israeli business cycle, including fluctuations in Israeli agricultural productivity. For

this reason, the Palestinian economy is extremely vulnerable (WFP, 2006). Prior to the

(2000), the agricultural sector contributed less than 10% to the GDP (PCBS, 1994-

2004).

Therefore, the contribution of the agricultural sector varies from one year to the other,

based on the activity of other economic sectors, and the accessibility of the Israeli job

market to Palestinian workers. Despite the reduction in the contribution of the

agricultural sector to the total Palestinian GDP in the period between 1997 and 2001, its


32

contribution has gradually increased since 2002. The total contribution value between

1995 and 2004 varied from its lowest value in 2002 with 387.1 US $ millions, to a

maximum of 487.5 US $ millions in 2004 (PCBS, 1994-2004).

On the other hand, the GDP for the years after 2004 showed a decrease in the

Agriculture contribution to the Palestinian GDP, reaching only 6.64%. (Figure 3.10)

(PCBS, 1994-2004).

This is not to imply that other sectors may not also be negatively affected by climate

variability and change; rather, that there is an urgent need to address climatic adaptive

capacity for those dependent on agricultural livelihoods.

Figure 3.10: Agricultural Sector contribution to the total Palestinian GDP (2001-2010) (Source: PCBS, 2001-2010)

Chapter 4 Methodology

33

Chapter 4: Methodology

4.1 Introduction:

In the study different processes were applied in three different governorates in Gaza

Strip to estimate the impacts of changing climatic parameters; temperature and

precipitation on the irrigation water requirement as the first factor affecting the

irrigation requirements, while the second factor was the salinity of applied water.

4.2 Methods of the Study:

1- Climatic data collection: metrological data for the governorates considered for

the research were collected and used to provide the baseline data. Second step

was to re-calculate the different orchards irrigation requirements under different

scenarios; including increasing temperature for different degrees and decreasing

precipitation with different percentage, in order to evaluate the changes in the

water requirement for the different trees.

2- CropWat modeling build-up: the study used the CropWat software model

version 8.0, CropWat 8.0 Windows, which is a program that the FAO uses since

(2004). The model will calculate the crop water requirement for the chosen

orchards which cover around 83% of the orchards farms in all entire Gaza Strip

(PCBS and MoA, 2010)2. The result of the model will simulate the expected

changes in agricultural water demand under different climate change scenarios.

3- Leaching factor calculations: another factor considered for the calculation of

irrigation water requirements, which is the water salinity, the leaching factor was

added to the irrigation requirements – as percentage of the irrigation

requirements – which maintain the productivity of the trees at 100% level.

4- On farm data collection: a survey for farmers in the study area were conducted.

The collected data about the farmers current irrigation practices are compared

with the calculated irrigation requirements plus the needed leaching quantities.

2 Unpublished data through the agriculture census partner: Union of Agricultural Works Committee “UAWC”.


34

4.3 Study Framework:

Figure 4.1 summarize the general framework of the study, which started with data

collections about the studied trees and the metrological data for Gaza Strip in the past

decades. On the other side, electrical conductivity were measured for irrigation water

used by sample of farmers within the study area. In addition, the current irrigation

practices were collected for the same sample of farmers.

The second step after collecting the data was processing this data and analyzing it to

calculate the averages of the climatic data, and the applied irrigation quantities by the

farmers, and calculating the leaching requirements depending on electrical conductivity

of the used water for irrigation.

The third step of the study was processing the metrological data through the CropWat

modeling to calculate the irrigation requirements for the studied trees within the study

area. Additionally, different predicted climate change scenarios were assumed, and the

changes in irrigation water requirements were calculated accordingly. The leaching

requirements for different level of salinity were added to the CropWat results to

formulate the total irrigation water requirements. Finally, the model outputs were

compared with the current irrigation practices.


35

P

T P Aver. P -5% P -10%

T Aver. Baseline Scenario Scenario 3 Scenario 6 T +1 Scenario 1 Scenario 4 Scenario 7 T +2 Scenario 2 Scenario 5 Scenario 8

T=Temperature P=Precipitation

Figure 4.1: Methodological framework of the study.

Data Collection

Processing of meteorological data Aver. of Tmax. & Tmin. Rainfall, R.H, Sunshine hours and Wind speed.

Processing

meteorological data for different

scenarios of climate change

CropWat model Calculation irrigation

requirements for different climate change scenarios

Farmers Irrigation Practices

% of farmer irrigation comparing to irrigation requirements

Water salinity EC

Metrological Data

Temperature Precipitation Relative

Humidity Sunshine Hours Wind Speed

Orchards Data

Length of growing season

Crop Coefficient Crop yield

response factor Root zone

Leaching fraction Calculation

ECw data ECe constant

factors for maintain 100% productivity

Processing farmers data and calculate

their irrigation quantities

comparing to the real requirements and need leaching

fraction

Compare the irrigation

requirements with current practices of

the farmers

Conclusion about current irrigation practices and future recommendations


36

4.4 Study Area:

The three governorates of the study were Gaza governorate, Deir Al-Balah governorate

and Khan Younis governorate; the reasons behind the choice of the mentioned

governorates were:

The research will study the irrigation requirements for certain crops which are

mainly cultivated in one or more of these governorates.

The other two governorates in the Gaza Strip (North governorate and Rafah

governorate “South of Gaza Strip”) were excluded because of the extreme

shortage in water in Rafah, while northern governorate didn’t have large

numbers of crops to be studied.

Since Gaza Strip has clear variation in the precipitation between the different

governorates, it was important to represent different precipitation rates for

different governorates; the excluded two governorates have the lowest and the

highest precipitation figures among the five Gaza Strip Governorates.

The chosen governorates have relatively homogenous soil texture which is

generally defined as medium soil. Most of the farmers changed the original soil

texture by adding more clay for the sandy dunes areas and vice versa.

4.5 CroPWat Description and Concept:

CropWat is a decision support system developed by the Land and Water Development

Division of FAO. It uses the FAO (1992) Penman-Monteith methods for calculating

reference crop evapotranspiration (FAO, 1998a). CropWat computer model was used in

the research to calculate reference evapotranspiration (ETo), crop water requirements

(CWR) as well as irrigation water requirements (IWR) for the different chosen orchards

types in the studying areas. The model support the development of recommendations for

improved irrigation practices, the planning of irrigation schedules under varying water

supply conditions, and the assessment of production under rain-fed conditions or deficit

irrigation.

The underlying sections simplify the calculation procedures used in the CropWat

software.


37

4.5.1 Calculating reference evapotranspiration (ETo):

The combination of two separate processes whereby water is lost on the one hand from

the soil surface by evaporation and on the other hand from the crop by transpiration is

referred by evapotranspiration (ET) (FAO, 1998b).

The evapotranspirration rate is normally expressed in millimeters (mm) per unit time.

The rate is expressed as the amount of water lost from a cropped surface in units of

water depth, the time unit can be an hour, day, month or even the entire growing period

or year.

The reference evapotranspiration (ETo) is defined as the evpotranspiration from a

reference surface of a reference crop. FAO defined the reference crop as a hypothetical

crop with an assumed height of 0.12m having the surface resistance of 70 sm−1 and

albedo of 0.23, closely resembling the evaporation of an extension surface of green

grass of uniform height which is actively growing and adequately watered.

Thus, ETo is a climatic parameter expressing the evaporation power of the atmosphere

and can be computed from meteorological data. CropWat uses the FAO Penman-

Monteith method to calculate ETo; the method was recommended as the standard

method for the definition and computation of the reference evapotranspiration, ETo as a

result of an expert consultation held in May 1990 and organized by the FAO.

The FAO Penman-Monteith equation to estimate ETo is:

)34.01(

)()(408.0

2

2273900

u

eeuGRET asTn

o

Where;

ETo Reference evapotranspiration [mm day-1]

Rn Net radiation at the crop surface [MJ m-2 day-1]

G Soil heat flux density [MJ m-2 day-1]

T Mean daily air temperature at 2 m height [°C]

2u Wind speed at 2 m height [m s-1]

se Saturation vapour pressure [kPa]

ae Actuel vapour pressure [kPa]


38

as ee Saturation vapour pressure deficit [kPa]

Δ Slope vapour pressure curve [kPa °C-1]

Psychrometric constant [kPa °C-1]

The equation uses standard climatologicale records of solar radiation (sunshine), air

temperature, humidity and wind speed. To ensure the integrity of computations, the

weather measurements should be made at 2 m (or converted to that height) above an

extensive surface of green grass, shading the ground and not short of water.

4.5.2 Calculating crop evapotrnspiration (ETc):

Crop evapotranspiration (ETc) refers to the evapotranspiration from excellently

managed, large, well-watered fields that achieve full production under the given

climatic conditions. Due to sub-optimal crop management and environmental

constraints that affect crop growth and limit evapotranspiration, ETc under non-standard

conditions generally requires a correction to obtain ETc adj (FAO, 1998b), (Figure 4.2).

For the purpose of this study ETc adj is not considered as we are interested in the impact

of climate change only; optimal management and environmental conditions should be

maintained. Crop evapotranspiration can be determined using the following equation:

occ ETKEt

Where;

ETo Rreference evapotranspiration,

Kc Crop coefficient.

At this stage, to calculate Kc using CropWat it is necessary to define the crop, select

cropping pattern, determine time of planting or sowing, rate of crop development stage

and growing period.


39

Figure 4.2: Reference (ETo), crop evapotranspiration under standard (ETc) and nonstandard conditions (ETc adj). Source: FAO, 1998b.

4.5.3 Calculating crop water requirement (CWR):

Under optimal management and environmental conditions crop evapotranspiration is

equal to the crop water requirements. In other words, the amount of water required to

compensate the evapotranspiration loss from the cropped field is defined as crop water

requirement.

Although the values for crop evapotranspiration and crop water requirement are

identical, crop water requirement refers to the amount of water that needs to be

supplied, while crop evapotranspiration refers to the amount of water that is lost through

evapotranspiration.


40

In CropWat, crop water requirement (CWR) is expressed as ETmax for maximum

potential evapotranspiration, and under optimal management and environmental

conditions.

4.5.4 Calculating irrigation water requirements (IWR):

The irrigation water requirement of a crop is the total amount of water that must be

supplied by irrigation to a disease free crop, growing in a large field with adequate soil

water and fertility, and achieving full production potential under the given growing

environment (FAO, 1998b).

The irrigation water requirement (IWR) basically represents the difference between the

crop water requirement and effective rain, where the effective rain is defined as the

portion of the rainfall that is effectively used by the crop after rain. The amount of

effective rainfall depends on the precipitation rate and soil moisture conditions.

4.5.5 Data required for CropWat:

For the CropWat to perform the procedures discussed earlier three types of data are

required:

Metrological data, including:

• Mean monthly maximum temperature (°C)

• Mean monthly minimum temperature(°C)

• Mean monthly relative humidity (%)

• Sunshine hours (hours)

• Wind speed (km/day)

• Precipitation (mm)

Crop data, including:

• Length of growing period of orchards

• Crops coefficient (Kc)

• Crops yield response factor (ky)

• Root zone (m)


41

4.6 Salinity Requirements:

Salinity leaching amount were calculated to the maximum level of leaching for each salinity level in order to maintain the orchards productivity at the highest level of 100%. The Non-computer Version of WATSUIT Model which developed by (Rhoades and

Merrill – 1976) were used to calculate the leaching factor and then the amount of

excessive water needed to minimize the salinity effects:

Where;

LR The minimum leaching requirement needed to control salts

within the tolerance (ECe) of the crop with ordinary surface methods of

irrigation.

ECw Salinity of the applied irrigation water in dS/m 3.

ECe Average soil salinity tolerated by the crop4.

And The total annual depth of water that needs to be applied to meet both the crop

demand and leaching requirement can be estimated from equation:

LR

ETAW

1

Where;

AW Depth of applied water (mm/year)

ET Total annual crop water demand (mm/year)

LR Leaching requirement expressed as a fraction (leaching fraction)5

3 deciSiemens per meter (dS/m) = milliSiemens per cm (mS/cm) times by 1000 equals microSiemens per cm (uS/cm) = Electrical Conductivity units (EC's), Example 1.5 dS/m = 1.5 mS/cm = 1500 uS/cm = 1500 EC

4 ECe = EC of saturated soil extraction where the appropriate acceptable yield is obtained as a constant values, it is recommended that the ECe for water in the moderate to high salinity range (>1.5 dS/m), it might be better to use the ECe value for maximum yield potential (100 percent) since salinity control is critical to obtaining good yields (FAO website, salinity problems). 5 In many texts, the Terms ‘leaching fraction (LF)’ and ‘leaching requirement (LR)’ are used interchangeably. They both refer to that portion of the irrigation which should pass through the root zone

we

w

ECEC

ECLR

)(5


42

4.7 Orchards Selection:

The research considered the main orchards kinds in the Gaza Strip. Among around

twenty main types of orchards in the Gaza Strip; there are only 6 types occupying 83%

of the total trees in all of Gaza Strip. While the selected orchards present 83% of the

trees in Gaza Strip, olive trees alone has the greatest percentage with 45.6% of the trees

in Gaza Strip. Table 4.1 summarize the different trees numbers in the Gaza Strip

Governorates, the shaded cells presents the selected trees for the study.

Table 4.1: Trees distribution in the Gaza Strip Governorates (PCBS and MoA,

2010)6.

NNoo. TTrreeeess

Area per Dunom (1,000 m2) % of trees

North Gaza Gov.

Gaza Gov.

Deir AlBalah

Gov.

Khan Younis Gov.

Rafah Gov.

Total

1 Olive 728 5,150 9,000 9,346 3,500 27,724 45.6

2 Palm 333 520 2,400 1,800 400 5,453 9.0

3 Grape 111 3,808 760 140 440 5,259 8.6

4 Orange “Valencia” 441 880 2,500 53 380 4,254 7.0

5 Lemon 1038 1830 255 528 229 3,880 6.4

6 Guava 167 105 370 2,980 220 3,842 6.3

7 Clementine “Makhal” 296 670 190 885 234 2,275 3.7

8 Peach 127 265 30 459 130 1,011 1.7

9 Apple 200 102 63 467 60 892 1.5

10 Fig 131 420 140 150 50 891 1.5

11 Navel Orange 360 205 5 222 28 820 1.3

12 Almond 0 62 100 145 510 817 1.3

13 Local Clementine 564 85 25 0 10 684 1.1

14 Orange “Shamoti” 409 220 10 34 0 673 1.1

15 Pomegranate 15 210 20 145 0 390 0.6

16 Others 7.5 14 60 0 300 381.5 0.6

17 Cactus 189 70 0 0 110 369 0.6

18 Apricot 78 175 30 20 20 323 0.5

19 Mango 18 130 0 140 10 298 0.5

20 Grapefruit 37 140 80 22 14 293 0.5

21 Orange “French” 31 70 8 0 0 109 0.2

Total No. of trees 5,409 15,131 16,046 17,536 6,655 60,837 100

to control salts at a specific level. While LF indicates that the value be expressed as a fraction, LR can be expressed either as a fraction or percentage of irrigation water. 6 Unpublished data through the agriculture census partner: Union of Agricultural Works Committee “UAWC”.


43

4.8 Data Used in the Study:

4.8.1 Climatic Data:

Precipitation, temperature, humidity, wind speed and solar radiation monthly records

were taken from the Ministry of Agriculture. Records were available with different

periods for each parameter as the following:

Maximum and minimum temperatures records were available for 31 years from

1976 to 2006, but what used for the CropWat software was only for 17 years from

1990 to 2006 which has higher reliability.

Relative humidity data were available for 12 years, from 1995 to 2006.

Wind speed data were available for 12 years, from 1995 to 2006.

Sunshine duration records were available for 17 years from 1990 to 2006.

Rainfall records were available for 36 years from 1973 to 2009 with missing data

in the first years, the used data only was for the last 20 years from 1990 to 2009

which has more accuracy comparing with the previous years.

The rainfall data were calculated only for the studied governorates which are Gaza

governorate, Deir Al-Balah governorate and Khan Younis governorate. Table 4.2

illustrate the monthly averages for the climatic parameters used for the study.

Table 4.2: Monthly averages for the climatic parameters used for the study (1995-2006)

Climate Data

Month

Rainfall mm Max. Aver. Temp

Min. Aver. Temp

Aver. Wind speed

(KM/Day)

Relative Humidity

1995 - 2006

Sunshine Hour / Day

Gaza Middle

Area

Khan

Younis

January 112.9 94.6 77.7 17.90 10.76 282.9 65.1 4.81 February 75.5 63.8 53.5 18.06 11.13 276.3 67.2 6.09 March 29.8 33.0 33.2 19.62 12.82 257.7 67.0 7.51 April 8.0 6.7 6.7 22.55 16.10 250.8 66.6 8.42 May 1.5 0.6 0.8 24.48 19.01 230.9 72.1 9.77 June 0.0 0.0 0.0 27.04 21.57 235.4 73.6 9.87 July 0.0 0.0 0.0 29.39 23.80 230.3 74.4 10.65 August 0.0 0.0 0.0 29.96 24.38 238.6 72.2 11.53 September 0.0 0.0 0.0 28.80 22.99 249.4 68.4 9.68 October 23.5 18.5 14.5 26.50 20.22 257.2 67.0 8.35 November 44.5 47.7 37.3 23.28 16.28 256.0 62.7 6.24 December 90.5 82.1 67.4 19.54 12.57 259.5 58.9 4.07 Total 386.27 347.00 291.07 - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Average - - - - - - - - - - - - - - - 23.91 17.64 252.08 67.94 8.08


44

These climate records were used as the entry data for the CropWat in order to

calculate evapotranspiration and water requirement for the selected orchards.

4.8.2 Crop data:

Crops considered in this study are the permanent orchards; which represent 83% of the

orchards farming area of Gaza Strip, the selected trees were olives, palm, grapes,

citruses and guava. Data about the number of orchards cultivated in the Gaza Strip

referred to the Agriculture Census 2010 given by Palestinian Central Bureau of

Statistics “PCBS”, additional detailed data about the distribution of different orchards

between Gaza governorates were obtained from the Ministry of Agriculture and the

Union of Agricultural Work Committees “UAWC”.

The Table 4.2 illustrated the different trees numbers in the Gaza Strip Governorates, the

crops parameters were taken from the FAO, 1998b.

4.8.3 Farmers data and survey analysis:

Farmers data for the selected orchards to be considered in the study were obtained

through Union of Agricultural Work Committees “UAWC.” whom participated in the

agriculture census 2010 given by “PCBS”.

The following Table 4.3 summarizes number of farmers for each selected orchards in

the potential governorates in the Gaza Strip.

Table 4.3: Farmers number for selected orchards in different governorates of the

Gaza Strip (PCBS and MoA, 2010)

Orchards

Governorate

Olive Palm Grape

Citruses

“Valencia &

Lemon”

Guava Total

Gaza 1,608 205 378 803 116 3,110

Deir Al-Balah 942 155 145 309 48 1,599

Khan Younis 1656 551 55 720 266 3,248

Total 4,206 911 578 1832 430 7,957

% % 52.86 % 11.45 % 7.26 % 23.02 % 5.40 % 100


45

To define the number of farmers to be surveyed; the following equations were used to

calculate the number of potential sample farmers (Glenn, 1992):

2

22

D

Zn

Where;

n Sample size

Z Tabulated value of the standard normal distribution (For 99% is 2.58,

For 95% is 1.96 and For 90% is 1.65), for the calculation the confidence

level was 95% which set the value of “Z” equal to “1.96”.

Standard deviation, which calculated through (start) sample of 10 farmers

before setting the final number of sample farmers.

D Maximum error, in the sample calculation 5% as a margin of error could

be accepted.

While the previous equation calculated the sample size regardless of the population

number; which is the total number of farmers cultivating the potential orchards in the

potential governorates, the next equation used to finite the population correction

(Glenn, 1992):

N

nn

n)1(

1 0

0

Where “n” is the sample size and “N” is the population size – total farmers number in

the three governorate.

Example for sample size calculation:

First step was to calculate the sample size regardless the population size:

2

22

D

Zn

=

2

22

)05.0(

)32.0()96.1( =

0025.0

1024.08416.3 X = 157.352

Second step was to finite the population correction:

N

nn

n)1(

1 0

0

=

7957

)135.157(1

35.157

=

020.1

35.157 = 154.32

Third step was to calculate the sample size for each farmer/tree type depend on its

percentage comparing to the all population size as it is presented in Table 4.3.

Olive sample size = 0.52.86 X 154.32 = 82


46

The following Table .4 summarizes number of framers to be surveyed according to the

above equations, calculating the number of the farmers cultivating certain orchards was

according the percentage of each orchards type among the total orchards farms in the

different governorates in the Gaza Strip.

Table 4.4: Distribution of the surveyed farmers of the selected orchards

for the research

Orchards Olive Palm Grape Citruses Guava Total

Sample No. 82 18 11 35 8 154

With respect to the above Table, more than 200 farmers were interviewed and “187”

valid questionnaire were filled in. The used questionnaire contained different data about

the farmer, but the final goal of the questions was to estimate the irrigation quantity

applied by the farmers. The data of the questionnaire form were processed in excel sheet

in order to integrate it with recommended irrigation requirements from the MoA and

with the outputs of the CropWat results for each orchards type.

The following remarks explain the way of processing the data resulted by the

questioner form presented in Table 4.5

1- The white cells were directly filled during meeting with the farmers.

2- The Electrical Conductivity “ECw” for the source of water used for irrigation

were measured in the field using portable equipments (HACH – HQ 40d field

case).

3- The gray cells were either inserted numbers like rows number 39 and 41, while

the other gray rows were calculated as the following:

1. Row No 22: Dividing No of the month days “30” by the irrigation frequency

time, (30 days / answer of question No 22)

2. Row No 29: Dividing No of total irrigation hours by the area of the

cultivated part of the farm, (Average irrigation per hour for the total farm –

question No 28 / Orchards farm area - question No 8)

3. Row No 34: Multiplying number of irrigation duration per hours or cubic

meter – question No 24 or 26 X Pump flow – question No 16.

4. Row No 35: Dividing the irrigation volume each time for the total area per

m3 by the area of the cultivated part of the farm, (irrigation volume each


47

time for the total area per m3 – question No 34 / Orchards farm area -

question No 8).

5. Row No 36: Multiplying the monthly irrigation volume for the total area per

m3 – question No 34 X the frequency of irrigation per month - question No

22.

6. Row No 37: Multiplying the Irrigation volume each time for the one dunom

per m3 – question No 35 X the frequency of irrigation per month - question

No 22.

7. Row No 38: : Multiplying the monthly irrigation volume for one dunom per

m3 – question No 37 X six months as an average irrigation period.

8. Row No 40: Dividing the irrigation volume for six months for one dunom

per m3 – question No 38 by the average irrigation seasonal requirements

"m3" per dunom including excessive leaching volume by Ministry of

Agriculture "MoA".

9. Row No 42 & 43: leaching fraction factor calculated as it is explained in the

clause No (3.3 Salinity leaching factors).

10. Row No 44: The percentage between the recommended irrigation seasonal

requirements "m3" per dunom including excessive leaching volume and the

real quantity applied by the farmer.


48

Table 4.5: Questioner form used for the farmers Survey No Farmer Name 1 Mobile No 2 Education Illiterate primary School High school University 3 Land location 4 Governorate North Gaza Middle area Khan Yonis Rafah 5 Land tenure Taboo Saba'a Awqaf Entry Govermental 6 Soil texture (1)Sandy (2)Sandy clay (3)Clay (4)Light clay & limestone 7 Total land area 8 Orchards farm area 9 Trees variety(s)

10 Trees age 11 No. of trees per donum 12 Irrigation source Own well Shared well Buy 13 Well depth (m) 14 Pump technique Traditional Vertical Submersible 15 Pump capacity (HP) 16 Pump flow (Qm/H) 17 Pump outlet (Inch) 18 Pump motor Electrical Diesel 19 Water meter availability Yes No 20 Irrigation method Dripper Sprinklers Open Tube channels

21 Irrigation frequency Each 3 days

Each 7 days

Each 10 days

Each 15 days

determine

22 Frequency of irrigation per month 23 Irrigation quantity per m3 / total farm 24 Irrigation duration per Hour 25 Irrigation costs per m3 or Hour 26 Average irrigation per m3 / total farm 27 Average irrigation per m3 / Donum 28 Average irrigation per H / total farm 29 Average irrigation per H / Donum

30 The irrigation adequacy from the farmer standpoint

Quite enough

To a certain

degree Not enough

31 If irrigation is inadequate, what is the required increase percentage?

32 Suitability of water quality for irrigation from the farmer standpoint

Quite Good

To a certain

degree Salty

33 Irrigation water EC measurement

34 Irrigation volume each time for the total area per m3

35 Irrigation volume each time for the one dunom per m3

36 Monthly irrigation volume for the total area per m3

37 Monthly irrigation volume for one dunom per m3

38 Irrigation volume for eight months for one dunom per m3

39

Average irrigation seasonal requirements "m3" per dunom including excessive leaching volume by Ministry of Agriculture "MoA"

40 Irrigation adequacy percentage comparing to MoA recommendation

41 Average irrigation seasonal requirements "m3" per dunom according to CropWat results

42 Leaching fraction factor

43 Recommended irrigation seasonal requirements "m3" per dunom including excessive leaching volume

44 Irrigation adequacy percentage comparing to CropWat results & Leaching requirements


49

4.8.4 Soil Data:

Based on the CroWat soil classifications (FAO, 1998b); the Gaza Strip soil were

considered as medium soil, anyway; soil texture doesn’t have significant effects on the

irrigation requirements calculated by the modeling software, while it is the main factor

for the irrigation scheduling calculation.

4.9 Assumptions of Climate Change Scenarios:

Different climate change scenarios were applied for the study area, and for each

expected scenario, reference evapotranspiratio (ETo), crop water requirement (CWR)

and irrigation water requirement (IWR) were calculated.

The scenarios were formulated based on changing Temperature (T) and precipitation

(P); the other metrological data, soil data and crop data were kept without any changes.

The assumed scenarios for the climate change used in the study are:

1. Temperature change: increasing temperature for 1 and 2 oC while keeping

precipitation static was the first assumption; as the trends of temperature changes

discussed in Chapter 2; increase in temperature is highly expected during the

current century in the Mediterranean basin countries as well as the Palestinian

territories, the temperature increase scenarios was as follows:

Temperature

CropWat outputs T T + 1 T + 2

Reference evapotranspiratio (ETo) - - - - - - - - - - - - - - - - - - - - - - - -

Crop water requirement (CWR) - - - - - - - - - - - - - - - - - - - - - - - -

Irrigation water requirement (IWR) - - - - - - - - - - - - - - - - - - - - - - - -

2. Precipitation change: as discussed in Chapter 2, despite that there is no clear

liner trend for the precipitation change, it is predicted to have a decrease in

precipitation in the Mediterranean basin countries, and this prediction was

harmonized with the precipitation records in the Gaza Strip.

Therefore, and since that increasing in precipitation to a certain level in the Gaza Strip

are likely desirable; the decrease in precipitation scenarios only were considered. The

low precipitation scenarios was as follows:


50

precipitation

CropWat outputs P P – 5% P – 10%

Reference evapotranspiratio (ETo) - - - - - - - - - - - - - - - - - - - - - - - -

Crop water requirement (CWR) - - - - - - - - - - - - - - - - - - - - - - - -

Irrigation water requirement (IWR) - - - - - - - - - - - - - - - - - - - - - - - -

3. The combination of the changing in temperature and precipitation resulted in

different scenarios Described in the following matrix:

P

T P Aver. P -5% P -10%

T Aver. Baseline Scenario Scenario 3 Scenario 6

T +1 Scenario 1 Scenario 4 Scenario 7

T +2 Scenario 2 Scenario 5 Scenario 8

For each scenarios in this matrix, metrological data of the temperature and precipitation

were proceeded by the CropWat model, consequently these scenarios were applied nine

times for each orchards types; to calculate reference evapotranspiration (ETo), crop

water requirement (CWR) and irrigation water requirement (IWR).

Chapter 5 Results and Discussion

51

Chapter 5: Results and Discussion

5.1 Introduction:

Changes in climatic parameters cause direct effect on the agricultural water demand; the

study calculated the irrigation requirements for five types of orchards in the Gaza Strip

which cover 83% of the orchards farms in the entire area of the Gaza Strip. The

irrigation requirements calculated by using the CropWat modeling software, and

different metrological data were processed by the CropWat to calculate the irrigation

requirements.

Additional assumption for changing climatic parameters had been studied, temperatures

and precipitations factors are the most important climatic factors affecting the irrigation

requirements, consequently different scenarios of increasing temperatures and

decreasing precipitation were processed using the same modeling software to measure

the potential effect of changes in the two factors on evapotranspiration rates, and

subsequently the additional amount of irrigation water that may be needed to overcome

the increase in evapotranspiration. The increase in temperature will adversely affect the

soil quality such as increase of salt accumulation due to the increase of evaporation and

evapotranspiration rates. Decrease of rainfall rates will affect the amount of leached salt

to the deep soil layers. Temperature increase and the decrease of rainfall rate will have

cumulative adverse effect on soil quality which will affect the productivity and increase

the required irrigation water for leaching of the salts.

5.2 Gaza Strip temperatures data analysis:

Gaza Strip temperature records in the three decades between 1976 to 2006 showed a

trend towards raising temperatures in both the minimum and maximum averages, this

increase was clearer in the minimum temperature averages more than the maximum

temperature averages.

The linear trend of both minimum and maximum averages of the three interval time was

calculated, where the equation of the average minimum temperatures for the three

decades from 1976 to 2006 is:

y = 0.8645x + 15.018 .


52

And the equation of the average maximum temperatures is:

y = 0.2756x + 23.087

The diagram in figure 5.1 illustrate the averages minimum and maximum temperatures

and its linear trends.

Figure 5.1: Minimum and maximum temperature averages and trends for three Decades – 1976 to 2006 – in the Gaza Strip

As it is shown in Table 5.1; Gaza Strip temperatures analysis between 1976 to 2006

showed a trend to raise. The second decade between 1986 to 1995 comparing to the first

decade between 1976 to 1985, the average temperatures showed an increase by 0.79 ,

0.29 and 0.72 for the minimum, maximum and averages temperatures respectively. The

third decade between 1966 to 2006 comparing to the second decade between 1986 to

1995, the average temperatures showed increase by 0.94 , 0.26 and 0.86 for the

minimum, maximum and averages temperatures respectively.

Overall, temperatures increase of Gaza Strip within the past thirty years was clear by

around 1.73 degree in the average minimum temperatures, and around 0.55 degree in

the average maximum temperatures, and around 1.587 degree in the average

temperatures of the Gaza Strip.

These results are consistent and intersect with previous studies for temperature

mentioned in chapter “2” paragraph No. 2.1.1

Linear Linear

15.9116.70

17.64

23.36 23.65 23.91


53

Table 5.1: Minimum, maximum and averages temperatures for three

deceased of Gaza temperature records

No Year Minimum

temperature averages Maximum

temperature averages Temperature averages

1 1976 15.44 24.04 19.74 2 1977 15.77 23.39 19.58 3 1978 15.89 23.18 19.53 4 1979 16.57 23.81 20.19 5 1980 15.69 23.16 19.42 6 1981 15.89 23.22 19.55 7 1982 15.87 22.99 19.43 8 1983 15.48 22.49 19.11 9 1984 15.92 23.45 19.69

10 1985 16.55 23.84 20.20 AVE 15.91 23.36 19.64 STDEV 0.38 0.46 0.34 Change - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 1 1986 16.54 23.56 20.05 2 1987 16.40 23.59 19.99 3 1988 16.74 23.57 20.16 4 1989 16.34 23.31 19.82 5 1990 16.83 23.73 20.29 6 1991 16.84 23.62 20.23 7 1992 16.42 23.09 19.75 8 1993 16.55 23.82 20.19 9 1994 17.19 24.07 20.63

10 1995 17.13 24.13 20.63 AVE 16.70 23.65 20.36

STDEV 0.30 0.32 0.43 Difference ± + 0.79 + 0.29 + 0.72 1 1996 17.26 24.12 20.69 2 1997 16.73 23.72 20.24 3 1998 17.65 24.73 21.16 4 1999 17.55 24.24 21.10 5 2000 17.18 23.49 20.57 6 2001 18.99 24.04 21.09 7 2002 17.95 23.75 21.16 8 2003 17.61 23.87 21.00 9 2004 17.55 23.67 23.67

10 2005 17.68 23.56 20.98 11 2006 17.83 24.01 21.21

AVE 17.64 23.91 21.22 STDEV 0.56 0.37 0.92

Difference ± + 0.94 + 0.26 + 0.86 ∑ Difference ± + 1.73 + 0.55 + 1.58

5.3 Effect of irrigation water quality on irrigation water requirements:

Since salinity control is crucial to obtaining good yields when irrigating with water

specified as moderate to high salinity range (>1.5 dS/m), which is the case in the most

areas in the Gaza Strip, it is recommended to use the EC value for maximum yield

potential (100 percent) when calculating the leaching fraction to be added for the

irrigation requirements (FAO website, salinity problems). Table 5.2 shows the studied


54

orchards tolerance and yield potential as influenced by irrigation water salinity (ECw) or

soil salinity (ECe)7. To maintain the highest productivity level at 100%; the ECw should

not exceed 2.5, 2.7, 1, 1.1 and 1.7 dS/cm for the olive, palm, grape, citrus and guava

respectively.

Table 5.2: Orchards tolerance and yield potential as influenced by irrigation water

salinity (ECw) or soil salinity (ECe) 8.

Potential Yield Orchards Type

100% 90% 75% 50% 0%

Maximum9 ECe ECw ECe ECw ECe ECw ECe ECw ECe ECw

dS/mOlive 3.75 2.5 6.3 4.2 10.2 6.8 16.8 11.2 28.5 19 Palm 4 2.7 6.8 4.5 11 7.3 18 12 32 21 Grape 1.5 1 2.5 1.7 4.1 2.7 6.7 4.5 12 7.9 Citruses 1.7 1.1 2.3 1.6 3.3 2.2 4.8 3.2 8 5.3 Guava 2.5 1.7 3.8 2.6 6 4 9.4 6.3 16 11

After calculating the irrigation requirements for the studied orchards using the CropWat

modeling software, the leaching requirements for different level of salinity had been

calculated to maintain productivity at the level of maximum yield potential (100

percent).

Increasing in EC values caused a significant increase in irrigation water requirements.

The excess of irrigation water requirements was higher in the sensitive and the

moderately sensitive orchards, while the increased irrigation water requirements was

lower for the tolerant and the moderately tolerant orchards. As shown in Table 5.4 most

of the orchards tolerate the soil extract electrical conductivity (EC) 2 dS/cm, showing an

increase in irrigation requirements for olive, Palm and Guava by 12%, 11% and 15%

respectively. At EC 3 dS/cm sever increase in irrigation requirements is shown for grape

and citrus which estimated to be 36% and 55% respectively. The feasibility of

cultivating grape and citrus at higher EC values is not acceptable due to a high increase

7 ECe means average root zone salinity as measured by electrical conductivity of the saturation extract of the soil, reported in deciSiemens per metre (dS/m) at 25°C. ECw means electrical conductivity of the irrigation water in deciSiemens per metre (dS/m). The relationship between soil salinity and water salinity (ECe = 1.5 ECw) assumes a 15–20 percent leaching fraction and a 40-30-20-10 percent water use pattern for the upper to lower quarters of the root zone. 8 Source: FAO website, salinity problems. 9 The zero yield potential or maximum ECe indicates the theoretical soil salinity (ECe) at which crop growth ceases.


55

in water requirements by more than 200%. Other orchards showing acceptable increase

in water requirements which accounted for 47%, 43% and 67% at 6 ds/cm for olives,

Palm and Guava, respectively.

Figure 5.2 presents the percentage of required irrigation requirements for the different

orchards under different levels of EC values comparing to CropWat required irrigation

under optimal salinity levels.

Figure 5.2: Ec level and Leaching Requirements Percentage Comparing to

CropWat Irrigation Requirements for Selected Orchards.

Figures 5.3, 5.4, 5.5, 5.6 and 5.7 presents the increase percentage of irrigation water

requirements per MCM for the total areas cultivated with different orchards under

different levels of EC comparing to CropWat irrigation under optimal salinity levels.


56

Figure 5.3: Gaza Strip Olive Farms Irrigation Requirements & Leaching Requirements for Different Levels of EC

Figure 5.4: Gaza Strip Palm Farms Irrigation Requirements & Leaching Requirements for Different Levels of EC

Figure 5.5: Gaza Strip Grape Farms Irrigation Requirements & Leaching Requirements for Different Levels of EC


57

Figure 5.6: Gaza Strip Citrus Farms Irrigation Requirements & Leaching Requirements for Different Levels of EC

Figure 5.7: Gaza Strip Guava Farms Irrigation Requirements & Leaching Requirements for Different Levels of EC

5.4 Evapotranspiration response to temperature and precipitation changes:

Reference evapotranspiration (ETo) reacting with temperature changes either increasing

or decreasing; and precipitation change has no effect on ETo.

Normally the evapotranspiration was increased with the increased temperatures;

therefore the irrigation requirements were increased to cover the raise in the

evapotranspiration value.

ETo of the studied orchards are listed in Table 5.3 for the different climatic scenarios;

current situation, increase in temperature by one degree, increase in temperature by two

degrees.


58

Table 5.3: Reference evapotranspiration (ETo) respond to the temperature

changes10

P Scenarios P Ave. P Ave. P Ave.

T Scenarios T Ave. T + 1 T + 2

Month ETo / mm/day ETo / mm/day ETo / mm/day

January 2.44 2.53 2.63

February 2.66 2.76 2.86

March 3.29 3.4 3.52

April 4.15 4.28 4.41

May 4.57 4.71 4.85

June 5.04 5.19 5.33

July 5.48 5.64 5.79

August 5.59 5.75 5.91

September 4.97 5.11 5.26

October 4.06 4.19 4.32

November 3.17 3.28 3.38

December 2.69 2.78 2.88

Average 4.01 4.13 4.26

5.5 Impact of increasing temperature on crop water requirement:

5.5.1 Irrigation requirement per dunom:

CropWat results for the different assumed and expect climate change presents a clear

relationship between irrigation water requirements and temperature variations. Increase

in temperature caused significant increase in the irrigation water requirements for the

studied orchards.

Table 5.4 presents the irrigation requirements in cubic meter per dunom for the studied

orchards. The table illustrate the CropWat model results for irrigation requirements

under the real historical climatic data as indicated in the first column used average

temperature and average precipitation, whilst the other columns presents the irrigation

requirements under the different assumed climatic changes; current situation, increase in

temperature by one degree, increase in temperature by two degrees, increase in

temperature by one degree associated with a decrease in rainfall by 5% and 10% and

increase in temperature by 2 degrees associated with rainfall reduction by 5% and 10%.

10 Precipitation changes has no effect on ETo


59

Table 5.4: Average irrigation requirements in cubic meter per dunom for the

studied orchards in Gaza Strip

TTrreeeess

Irrigation Requirements per (1,000 m2)

T Ave. T + 1 T + 2 T Ave. T + 1 T + 2 T Ave. T + 1 T + 2

P Ave. P Ave. P Ave. P – 5% P – 5% P – 10% P – 10% P – 10% P – 10%

Olive 543 544 547 559 561 565 577 579 582

Palm 1022 1060 1100 1033 1071 1111 1055 1093 1133

Grape 584 606 627 590 611 633 602 623 645

Citruses 656 676 699 658 681 704 670 693 717

Guava 1036 1071 1106 1041 1075 1110 1049 1084 1118

Detailed data about the irrigation requirements for each orchards in the different studied

governorate are listed in the annex No.(5).

5.5.2 Irrigation requirement for total area of the studied orchards:

Generally, an increase of temperature by +1 °C and +2 °C comparing to the current

temperature average degree; caused an average increase of 3.28% and 6.68% in the crop

water requirement respectively when the precipitation factor was neutralized.

As shown in Table 5.5, the current irrigation requirement for orchards in the studied

area is estimated by 32.99 MCM. Considering the reduction of rainfall by 5%, and 10%;

the estimated amount for the irrigation requirement will be 33.16 MCM and 33.56,

respectively, while the irrigation requirement is estimated by 34.08, 34.27 and 34.68

MCM when there is a one degree temperature increase, a one degree temperature

increase jointly with 5% reduction in rainfall and a one degree temperature increase

jointly with 10% reduction in rainfall, respectively. The most extreme scenario

considered the increase of 2 degrees temperature associated with 5% and 10% reduction

in rainfall, the estimated irrigation requirements will be 35.22, 35.42 and 35.83 MCM,

respectively.

The impacts of temperature increase on irrigation water requirement for all the studied

orchards were calculated in the different governorates in the Gaza Strip where these

orchards are cultivated, Table 5.5 illustrates the changes in the irrigation water

requirements for the different studded orchards.


60

Table 5.5: Total irrigation requirements per MCM and percentage of increase for

total areas cultivated with the studied orchards in Gaza Strip

NNoo.. TTrreeeess Area (1,000

m2)

Irrigation Requirements for Total Cultivated Area per Million Cubic Meter

P Ave. P – 5% P – 10% P Ave. P – 5% P – 10% P Ave. P – 5% P – 10%

T Ave. T Ave. T Ave. T + 1 T + 1 T + 1 T + 2 T + 2 T + 2

1 Olive 27,724 15.04 15.07 15.17 15.51 15.55 15.65 16.00 16.05 16.14

2 Palm 5,453 5.57 5.63 5.75 5.78 5.84 5.96 6.00 6.06 6.18

3 Grape 5,259 3.07 3.10 3.17 3.19 3.21 3.28 3.30 3.33 3.39

4 Citruses 8,134 5.33 5.35 5.45 5.49 5.54 5.63 5.68 5.73 5.83

5 Guava 3,842 3.98 4.00 4.03 4.11 4.13 4.16 4.25 4.26 4.29

Total 50,412 32.99 33.16 33.56 34.08 34.27 34.68 35.22 35.42 35.83

Irrigation needed increase MCM 0.00 0.16 0.57 1.09 1.28 1.69 2.22 2.43 2.84

% of needed irrigation increase 0.00 0.49 1.73 3.30 3.87 5.12 6.74 7.37 8.60


61

5.5.3 Impact of decreasing precipitation:

As mentioned in clause No (2.1.2); there is an average predictable decrease in

precipitation by 20% within the coming decades, therefore the impact of decreases in

precipitation by only 5% and 10% were considered as a possible decrease in the next

few years.

The average response of irrigation requirements to the precipitation decrease by 5% and

10% was by an average of 0.45% and 1.73% respectively.

5.6 CropWat Irrigation Requirements, Leaching Requirements and

Farmers Irrigation Practices:

More than 185 farmers cultivating orchards were surveyed in the study area, the main

aim of the farmers' survey was to measure the EC of the used irrigation water, and to

estimate the applied irrigation quantities. Unfortunately, farmers in the surveyed area

have never measured the used quantities of irrigated water. Flow meters were not

installed on the irrigation wells. Therefore data is collected about the pump capacity and

irrigation scheduling applied by the farmers to calculate the irrigation water quantity

that they have been using for irrigating their orchards.

For each orchard types, farmers were categorized depending on the EC of the used

irrigation water, then the average irrigation quantities applied by each farmers group

were calculated. The processed data of applied irrigation quantities were integrated with

the recommended result of CropWat for each orchards type in addition to the

recommended leaching requirements to maintain the orchards productivity at the highest

level.

5.6.1 Olive Orchards:

The recommended irrigation quantities for the olive orchards depending on the

CropWat results was 543 m3/year. There was no real significant differences between the

three studied governorates in the Gaza Strip. Most of the surveyed farmers applied more

than the recommended amount of irrigation water including the leaching requirements

depending on their salinity levels.


62

Despite that olive orchards are known as tolerant trees, but still it is required to add a

certain amount of leaching water in order to maintain the trees productivity. Generally,

most of the olive orchards farmers applied more than the recommended amount of

irrigation water including the required leaching quantities. The farmers who irrigate

with water of EC values less than 5 are in coincidence with the model results. High

water use in comparison to the model results is noticed for farmer having irrigation

water with EC higher the 5 dS/cm, the increase is account for 30% as shown in figure

5.8.

Ministry of agriculture has different figures for the olive irrigation requirements depend

on the olive trees variety and the irrigation type. The maximum recommended irrigation

requirement by MoA is 470 m3/year. Additionally, they used constant percentage for the

soil leaching factor which is plus 25%, accordingly the irrigation requirement of olive

trees became 588 m3/year.11 The recommended irrigation requirements by the MoA is

less than the result of the CropWat modeling, and while leaching requirements were

fixed as constant value by MoA; the leaching requirements were calculated for different

levels of salinity in the study.

The figure 5.8 presents the average applied irrigation quantities by the olive farmers,

and the recommended CropWat required irrigation quantities in addition to the required

leaching amount.

11 Source of information: Personal meetings with MoA, water and soil department.


63

Figure 5.8: Applied irrigation quantities by the olive farmers for different level of salinity, comparing to CropWat and leaching requirements

Throughout the olive orchards farmers' survey, it was noticeable that the farmers using

an irrigation network12 applying higher quantity of irrigation water comparing to the

farmers using a flooding irrigation method whether it is old traditional channels or 2-3

inches pipes flooding the trees basins.

As shown in figure 5.9, the irrigation systems significantly affected the used amount of

irrigation water. The irrigation by networks and traditional open channels account for

890 and 763 m3/dunum/year, respectively

There were mainly two reasons behind such trends of farmer behavior, the first reason is

due to unneeded workers for irrigation with irrigation network techniques while they are

needed for flooding irrigation techniques. The second reasons is the low costs of

operating the small size submersible pumps which have a limited flow; but sufficient to

be distributed through irrigation networks, while huge vertical pumps with high flow are

needed to meet the flooding irrigation techniques requirements, such pump operation

costs is high.

12 Usually it was not high uniformity system such as dripper, it could be considered as a piping conveying system.


64

Figure 5.9: Irrigation method and average applied irrigation m3/year – olive farmers

It is worthily to be mentioned that the recommended irrigation requirements by MoA

for olive trees are less when the irrigation methodology is by drip irrigation. They

considers the irrigation efficiency is higher in this case and consequently the applied

water should be less. This theoretical assumption by MoA is contradicting the real

practices by farmers as founded on the ground.

5.6.2 Palm Orchards:

The recommended irrigation quantities for the palm trees depending on the CropWat

results was 1040 and 1079 m3/year in the Dair Al-Balah and Khan Younis governorates

respectively. As shown in figure 5.10 most of the surveyed farmers applied excessive

amount of water by an average of 77% when the applied irrigation quantities compared

to the CropWat results, and by an average of 26% when the applied irrigation quantities

compared to the CropWat including the leaching amount.

889.5 762.6


65

Figure 5.10: Applied irrigation quantities by the palm farmers for different level of salinity, comparing to CropWat and leaching requirements

Ministry of agriculture recommended irrigation requirements for palm trees is 714

m3/year. The constant percentage for the soil leaching factor which is plus 25%,

accordingly the irrigation requirement of palm trees became 892 m3/year.13 These

figures are less than the result of the CropWat modeling as well as the needed excessive

water amount for different levels of salinity as presented in the previous figure 5.10.

Similar to olive orchards, it was clear that farmers using irrigation network applying

more quantities of irrigation water comparing to those farmers using flooding irrigation

method. As shown in figure 5.11 the used amount for irrigation networks and traditional

channels is accounted for 2,049 and 1,309 m3/dunum/per, respectively. According to

farmers the yield of both systems is nearly the same.

Irrigation network for palm trees was usually linked to other vegetables irrigation

networks, this phenomena was clear in west of Khan Younis governorate.



66

Figure 5.11: Irrigation method and average applied irrigation m3/year – palm farmers

5.6.3 Grape Orchards:

Generally, grapes are cultivated in two areas in the Gaza Strip, the first one is the

southern west of Gaza city at Al-Shekh Ejlein area where farmers didn’t used to irrigate

the grape frequently especially for the old trees, and exceptionally they irrigate it

between one to three times in February up to April depending on the rain season.

Consequently grapes in Gaza city governorate is considered as rain-fed grape, and its

irrigation requirements were neglected.

The second area in the Gaza Strip where grapes are cultivated widely is the eastern area

of Khan Younis governorate, the grapes in this area are extensively irrigated despite the

extreme shortage of water access in the area.

The recommended irrigation quantities for the grapes in Khan Younis governorate

depending on the CropWat results was 584 m3/year,

As shown in figure 5.12 most of the surveyed farmers applied excessive amount of

water by an average of 344% when the applied irrigation quantities compared to the

CropWat results, and by an average of 186% when the applied irrigation quantities

compared to the CropWat and the required leaching amount.

2049 1309


67

Figure 5.12: Applied irrigation quantities by the grape farmers for different level

of salinity, comparing to CropWat and leaching requirements

Ministry of agriculture recommended irrigation requirements for grapes is 520 m3/year.

The constant percentage for the soil leaching factor which is plus 25%, accordingly the

irrigation requirement of grapes became 670 m3/year.14 These figures are higher than

the result of the CropWat modeling, while it is clearly less than the needed excessive


5.6.4 Citrus Orchards:

Citrus groups are mainly cultivated in the Dair Al-Balah, Gaza and north Gaza

governorates. The average recommended irrigation quantities for the citruses in Gaza

and Dair Al-Balah governorates depending on the CropWat results was 657 m3/year.

Figure 5.13 shows that most of the surveyed farmers applied an excessive amount of

water by an average of 184% when the applied irrigation quantities compared to the

CropWat results, while it is less than the CropWat and the required leaching amount

when the EC of irrigation water more than 3 dS/m.



68

Also, figure 5.13 illustrates the extreme significant increase in the leaching

requirements when the EC value passed 3 dS/m which is the point causing 50%

reduction in citrus productivity.

Figure 5.13: Applied irrigation quantities by the citrus farmers for different level of salinity, comparing to CropWat and leaching requirements

Ministry of agriculture recommended irrigation requirements for citrus is 516 m3/year.


irrigation requirement of citrus trees became 644 m3/year.15 These figures are lower

than the result of the CropWat modeling, and it is clearly less than the needed excessive


5.6.5 Guava Orchards:

Guava orchards are mainly cultivated in the Dair Al-Balah and Khan Yuonis

governorates. The average recommended irrigation quantities for the Guava trees

depending on the CropWat results was 1,040 m3/year.

Most of the surveyed farmers as shown in figure 5.14 applied excessive amount of

water by an average of 292% compared to the CropWat results, while the excessive



69

amount reduced to 133% when the applied irrigation quantities are compared to the

CropWat and the required leaching amount.

Particularly; most of the farmers in the west of Khan Yuonis governorate applied huge

excessive amounts of irrigation water, they tripled the required irrigation for the guava

trees including the leaching requirements.

Figure 5.14: Applied irrigation quantities by the guava farmers for different level of salinity, comparing to CropWat and leaching requirements

Ministry of agriculture recommended irrigation requirements for guava is 913 m3/year.


irrigation requirement of citrus trees became 1142 m3/year.16 These figures are close

the result of the CropWat modeling, and it is clearly less than the needed excessive

water amount when the Ec of the water is higher than 3 dS/m as shown in figure 5.14.


Chapter 6 Conclusion and Recommendations

70

Chapter 6: Conclusion and Recommendations

6.1 Conclusion:

6.1.1 Comprehensive:

Agriculture is a human activity that is intimately associated with climate; it is well

known that the broad patterns of agricultural growth over long time scales can be

explained by a combination of climatic, ecological and economic factors.

The major concern in the understanding of the impacts of climate change is the extent to

which agriculture will be affected.

The issue is particularly important for the Mediterranean countries, where water

availability and sustainable irrigation development pose a growing problem under

today’s climatic conditions and entropic pressure. Thus, in the medium and long terms,

climate change is an additional challenge that agriculture has to face in meeting national

food requirements.

Climate change has many effects on the hydrological cycle and thus, on water resources

systems. Impact of global warming on crop water requirements plays a role of

paramount importance in assessing irrigation needs.

Uncertainties as to how the climate will change and how irrigation systems will have to

adapt to these changes are issues that water authorities are compelled to address.

In view of these uncertainties, planners and designers need guidance as to when the

prospect of climate change should be embodied and factored into the planning and

design process.

The challenge is to identify short-term strategies to cope with long-term uncertainties;

and the question is not what is the best course for a project over the next fifty years or

more, but rather, what is the best direction for the next few years, knowing that a

prudent hedging strategy will allow time to learn and change course.

The planning and design process needs to be sufficiently flexible to incorporate

consideration of and responses to many possible climate impacts.


71

6.1.2 Study Outputs:

The results presented in the study are for certain crops, it provides a preliminary idea

about the potential impact of climate change on agricultural water demand, taking into

consideration that these results present the impact on six different trees only, which

means that the deficit in agricultural water demand will become greater when

considering the impact of climate change on all the irrigated agriculture.

The study highlighted different points:

1- The study indicated the changes of Gaza Strip temperatures, as a factor of the

climate changes in the Gaza Strip, where it showed the increase in the

minimum temperatures by +0.79 and +0.94 oC in the last two decades, and the

increase in the maximum temperatures by +0.29 and +0.26 oC in the same

period.

2- Calculating the irrigation requirements for certain orchards under the current

climate conditions, as well as different scenarios of temperature increase and

precipitation decrease, and

3- Calculating the effects of different levels of water salinity on irrigation

requirements.

Throughout the study; the different irrigation requirements according to CropWat

results, leaching fraction calculation and current farmers practices were illustrated in a

comparable structure.

The study focused on the irrigation requirements responds to the changes of the climate

variables, in addition it is showed relation between the irrigation requirements and the

water salinity for the studied orchards.

The CropWat results showed that evapotranspiration is reacting with temperature

changes only; either increasing or decreasing, precipitations changes has no effect on

ETo.

Normally the evapotranspiration was increased with the increased temperatures;

increasing of +1oC or +2 oC caused an increase of the annual average evapotranspiration

by 0.13 and 0.16 , therefore the irrigation requirements were increased with an average

of 3.30% and 6.74% for the total cultivated area of the studied orchards. This increase


72

percentage could be translated to 1.09 and 2.22 MCM respectively to cover the

irrigation demand of the cultivated area with the studied orchards only.

In the worse scenario of increasing temperatures +2 oC, and decreasing precipitation by

10%, the irrigation requirements will be increased by 8.60% which represent 2.84 MCM

for the same area of the studied orchards.

Regarding salinity impact, the leaching requirements were calculated for the studied

orchards, whereas the leaching requirements didn’t exceed 15% in case of EC value is

less than 2 ds/cm. While the leaching requirements begin to increase rabidly after the

EC value passed 3 ds/cm in the moderately sensitive orchards like grape, citrus and

guava, and it will increase steadily in the tolerant orchards like olives and palm.

Anyway, the impact of salinity increase on the irrigation requirements is much higher

than the impact of climate change, unfortunately water and soil salinity are likely to be

increased in parallel with the temperatures increasing as a result of rising

evapotranspiration, consequently irrigation demand will be increased dramatically.

Additional subjects were presented in the study related to estimate the effects of

irrigation techniques used by farmers on the irrigation quantities, the results were

traumatic and illogic in the beginning, farmers used irrigation network regardless of its

system using irrigation quantities more than others whom using traditional channel

system. The explanation behind this unexpected data were related to the low cost of

operating irrigation with network; it needs less workers and smaller submersible pumps

to guarantee sufficient flow to be distributed through the irrigation network, while huge

vertical pumps with high flow are needed to meet the flooding irrigation techniques

requirements, such pumps operational costs are high.


73

6.2 Recommendation

The following points are concluding the recommended measures to be taken into

consideration:

1- Technical level and decision-makers need to systematically review planning

principles, design criteria, operating rules, contingency plans and water

management policies.

2- Planning and design process for water resource systems and coping with uncertain

climate and hydrologic events, and potentially irrigation requirements should

consider the following points:

Climate change should be recognized as a major planning issue,

Predicting the impacts of climate change on the irrigated area,

Formulation of alternative plans, and evaluation of the alternatives, would be

based on the most likely conditions expected to exist in the future with and

without the plan.

Comparing the alternatives and selecting a recommended development plan.

3- Support programs for predictions of future irrigation water requirement for

agriculture in Gaza Strip; considering the effects of climate change and water

salinity to cover the whole agricultural areas and crops.

4- Enhance the development of using other water sources for irrigation, non-

conventional water source should be considered as one of the most feasible

solutions in the seen future.

5- Capacity building and training should focus firstly on increasing the awareness on

the value of water; and the right of future generations to the natural resources

including water, after developing this sense, technical training about saving water

strategies and techniques could be continued.

6- Reducing water pumping for irrigation will never be achieved without applying

restrictive rules preventing digging or using unlicensed wells and installing water-

meters for the agricultural wells to determine its acceptable monthly flow according

to size of irrigated area.

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Annexes

82

Annex (1-A): Minimum temperature averages in Gaza Strip, 1976-2006.

No. Year JAN FEB MAR APR MAY JUN JUL AUG SEB OCT NOV DEC Year Ave 1 1976 9.03 8.27 11.07 14.84 16.80 18.36 21.24 21.20 19.44 18.93 15.06 11.06 15.44 2 1977 9.05 11.30 10.61 13.92 17.14 19.67 22.05 22.81 20.98 17.71 14.16 9.84 15.77 3 1978 9.09 10.79 12.13 14.11 17.35 19.79 22.56 21.03 20.59 19.21 12.81 11.21 15.89 4 1979 10.03 11.18 12.88 15.34 16.58 20.77 21.88 21.84 21.57 19.28 17.01 10.42 16.57 5 1980 8.77 9.68 11.18 14.48 16.22 19.32 21.68 22.15 20.06 18.12 15.12 11.50 15.69 6 1981 8.36 10.06 11.75 13.93 16.37 19.42 22.31 22.17 21.37 19.06 14.19 11.75 15.89 7 1982 10.12 9.34 10.86 15.75 17.05 19.47 21.68 22.54 21.16 19.25 12.87 10.31 15.87 8 1983 7.60 8.67 10.18 12.88 16.74 20.23 21.98 22.72 20.89 17.56 15.16 11.20 15.48 9 1984 10.07 10.06 12.86 13.85 17.40 19.44 21.56 21.29 20.88 18.86 14.87 9.86 15.92 10 1985 11.36 9.93 11.25 14.81 18.19 20.60 21.45 23.79 21.58 17.67 15.97 12.01 16.55

AVE 9.35 9.93 11.48 14.39 16.99 19.71 21.84 22.15 20.85 18.56 14.72 10.92 15.91 STDEV 1.07 1.00 0.91 0.83 0.58 0.70 0.40 0.86 0.68 0.71 1.29 0.77 0.38

1 1986 10.38 11.18 13.08 16.64 16.26 20.65 22.17 22.63 23.17 19.40 13.11 9.85 16.54 2 1987 10.22 11.41 10.44 13.95 15.83 19.80 22.65 23.71 22.09 18.83 14.91 12.97 16.40 3 1988 10.66 10.52 11.97 14.41 18.65 21.16 23.83 23.78 22.38 18.77 13.20 11.56 16.74 4 1989 8.17 8.77 11.92 15.41 18.32 20.47 22.63 23.16 21.78 18.61 15.65 11.17 16.34 5 1990 10.19 9.91 11.47 14.84 17.16 20.28 22.62 22.80 22.02 20.15 17.21 13.31 16.83 6 1991 9.85 11.10 13.76 16.09 17.84 20.42 22.43 23.04 21.70 20.05 15.46 10.31 16.84 7 1992 8.54 8.49 10.88 14.20 16.99 20.27 22.17 23.41 21.86 23.93 15.77 10.51 16.42 8 1993 8.59 8.24 11.36 14.83 17.43 20.69 22.35 23.48 22.01 20.83 15.41 13.35 16.55 9 1994 11.85 10.94 12.06 16.17 17.98 20.92 22.75 23.06 23.46 22.30 14.97 9.82 17.19 10 1995 9.81 10.47 12.63 13.80 17.38 21.36 23.14 23.73 22.77 19.22 14.14 17.13

AVE 9.82 10.10 11.96 15.03 17.38 20.60 22.68 23.28 22.32 20.21 14.98 11.43 16.70 STDEV 1.12 1.19 1.00 1.00 0.88 0.46 0.50 0.40 0.61 1.73 1.24 1.45 0.30

1 1996 10.54 12.03 12.44 14.25 18.66 20.72 23.92 23.50 22.80 19.18 16.42 12.70 17.26 2 1997 11.40 9.04 10.83 13.78 17.84 21.18 23.51 23.14 21.59 19.50 16.30 12.71 16.73 3 1998 10.30 11.39 11.89 15.80 18.58 21.59 23.20 25.01 23.58 20.53 17.48 12.51 17.65 4 1999 10.73 11.16 13.10 15.10 18.63 21.76 23.67 24.35 23.03 20.50 16.44 12.18 17.55 5 2000 9.79 10.00 11.55 15.89 17.84 21.70 24.57 24.53 22.87 19.17 15.70 12.62 17.18 6 2001 10.83 10.83 14.79 23.41 24.66 21.62 23.16 24.45 23.34 20.36 15.60 14.78 18.99 7 2002 9.52 12.22 13.97 15.63 18.06 21.72 24.49 24.94 23.16 21.29 17.27 13.09 17.95 8 2003 11.94 10.39 11.75 15.35 20.14 22.04 23.85 24.62 22.54 20.24 16.62 11.86 17.61 9 2004 10.83 11.32 13.92 15.59 18.03 20.97 23.81 24.01 22.92 21.15 16.89 11.17 17.55 10 2005 11.14 11.34 13.28 15.72 18.13 21.72 23.78 25.11 23.24 19.96 15.17 13.60 17.68 11 2006 11.32 12.72 13.49 16.62 18.53 22.23 23.79 24.55 23.81 20.59 15.20 11.06 17.83

AVE 10.76 11.13 12.82 16.10 19.01 21.57 23.80 24.38 22.99 20.22 16.28 12.57 17.64 STDEV 0.71 1.05 1.22 2.55 1.98 0.45 0.44 0.62 0.59 0.71 0.79 1.05 0.56

Annexes

83

Annex (1-B): Maximum temperature averages in Gaza Strip, 1976-2006.

No. Year JAN FEB MAR APR MAY JUN JUL AUG SEB OCT NOV DEC Year Ave 1 1976 18.44 17.04 19.63 23.89 25.30 27.06 29.12 29.54 27.93 27.17 23.68 19.61 24.04 2 1977 16.43 18.92 18.44 22.32 24.49 27.16 28.75 29.57 28.20 25.20 23.14 18.01 23.39 3 1978 17.07 18.58 19.79 22.21 23.80 26.60 28.49 27.90 27.52 26.23 21.30 18.65 23.18 4 1979 17.65 19.72 20.03 23.84 23.18 27.49 28.42 28.84 27.74 26.71 24.15 17.98 23.81 5 1980 16.59 16.58 19.55 23.20 23.87 25.63 28.29 28.97 27.45 25.65 23.13 18.98 23.16 6 1981 16.48 17.35 19.44 21.57 23.95 26.49 28.35 28.40 28.03 26.66 21.86 20.14 23.22 7 1982 17.91 16.24 17.91 22.94 23.71 26.22 27.79 28.82 28.29 27.01 21.07 17.94 22.99 8 1983 14.85 15.53 17.65 20.16 23.94 26.66 28.56 28.59 27.88 24.05 19.51 22.49 9 1984 17.36 18.56 20.09 21.99 24.99 26.29 27.83 28.14 27.96 26.33 23.08 18.78 23.45 10 1985 19.78 17.99 19.01 22.31 25.41 26.99 27.89 29.30 28.01 25.62 24.21 19.61 23.84

AVE 17.26 17.65 19.16 22.44 24.26 26.66 28.35 28.81 27.90 26.29 22.97 18.92 23.36 STDEV 1.33 1.32 0.87 1.11 0.75 0.54 0.42 0.57 0.27 0.68 1.17 0.79 0.46

1 1986 18.72 18.95 19.94 23.47 23.05 27.09 28.48 28.97 28.72 25.66 21.38 18.29 23.56 2 1987 18.27 19.55 17.97 20.85 24.22 26.41 28.92 29.88 28.74 25.64 22.99 19.58 23.59 3 1988 17.78 17.66 18.98 21.52 25.08 27.12 29.56 29.65 28.39 26.24 21.79 19.08 23.57 4 1989 15.34 17.19 18.85 23.25 24.29 26.55 28.32 29.09 28.27 25.85 23.71 18.95 23.31 5 1990 17.38 17.52 19.04 22.13 23.14 26.34 28.56 28.96 27.92 27.08 24.54 22.16 23.73 6 1991 17.94 18.43 20.36 23.48 24.03 26.26 28.03 28.77 27.89 27.06 23.34 17.88 23.62 7 1992 15.94 15.41 18.38 21.58 23.33 26.65 28.50 29.93 29.11 26.99 23.84 17.47 23.09 8 1993 16.51 16.67 19.44 23.38 24.15 27.86 28.89 29.34 28.46 28.01 22.71 20.48 23.82 9 1994 18.88 18.48 18.26 23.89 25.00 27.00 28.88 29.57 29.88 29.43 22.29 17.33 24.07 10 1995 17.34 17.44 19.48 21.41 23.76 28.54 29.75 30.25 29.13 26.13 22.19 24.13

AVE 17.41 17.73 19.07 22.50 24.01 26.98 28.79 29.44 28.65 26.81 22.88 19.02 23.65 STDEV 1.17 1.19 0.76 1.11 0.71 0.73 0.54 0.49 0.61 1.20 0.99 1.56 0.32

1 1996 17.67 18.72 19.66 21.19 25.43 27.11 29.47 29.89 29.19 26.84 23.53 20.73 24.12 2 1997 18.88 16.77 18.06 22.14 24.01 27.50 29.66 29.02 28.29 26.48 24.04 19.77 23.72 3 1998 18.00 18.39 19.64 24.75 24.78 27.12 29.55 31.90 30.03 27.58 24.25 20.80 24.73 4 1999 18.15 18.07 20.24 21.18 24.74 27.71 29.87 30.38 29.36 27.08 23.91 20.23 24.24 5 2000 16.66 17.14 17.56 22.93 23.82 27.54 30.06 29.98 28.66 25.55 22.98 18.96 23.49 6 2001 18.35 18.21 21.45 23.41 24.66 26.66 28.87 29.91 28.74 26.55 22.82 18.89 24.04 7 2002 15.93 18.34 20.91 21.84 23.12 27.02 29.65 29.96 28.56 26.10 24.14 19.39 23.75 8 2003 19.13 17.10 17.62 22.90 26.35 27.27 29.35 29.75 28.34 26.20 22.95 19.46 23.87 9 2004 17.71 18.95 20.20 21.49 24.91 25.94 28.93 29.24 27.99 26.69 23.31 18.72 23.67 10 2005 18.66 17.62 19.88 22.58 23.51 26.16 28.70 29.40 28.83 25.64 22.11 19.59 23.56 11 2006 17.79 19.30 20.59 23.65 23.92 27.39 29.23 30.15 28.84 26.80 22.04 18.42 24.01

AVE 17.90 18.06 19.62 22.55 24.48 27.04 29.39 29.96 28.80 26.50 23.28 19.54 23.91 STDEV 0.94 0.81 1.32 1.12 0.92 0.57 0.43 0.76 0.57 0.60 0.78 0.79 0.37

Annexes

84

Annex (1-C): Temperature averages in Gaza Strip, 1976-2006.

No. Year JAN FEB MAR APR MAY JUN JUL AUG SEB OCT NOV DEC Year Ave 1 1976 13.74 12.66 15.35 19.37 21.05 22.71 25.18 25.37 23.69 23.05 19.37 15.34 19.74 2 1977 12.74 15.11 14.53 18.12 20.81 23.42 25.40 26.19 24.59 21.45 18.65 13.92 19.58 3 1978 13.08 14.68 15.96 18.16 20.57 23.20 25.53 24.46 24.06 22.72 17.06 14.93 19.53 4 1979 13.84 15.45 16.46 19.59 19.88 24.13 25.15 25.34 24.66 23.00 20.58 14.20 20.19 5 1980 12.68 13.13 15.37 18.84 20.04 22.47 24.90 25.56 23.76 21.89 19.13 15.24 19.42 6 1981 12.42 13.71 15.59 17.75 20.16 22.95 25.33 25.28 24.70 22.75 18.02 15.95 19.55 7 1982 14.01 12.79 14.38 19.34 20.38 22.85 24.74 25.68 24.73 23.13 16.97 14.12 19.43 8 1983 11.23 12.10 13.92 16.52 20.34 23.45 25.27 25.65 24.38 21.49 19.61 15.35 19.11 9 1984 13.72 14.36 16.48 17.92 21.20 22.87 24.69 24.72 24.42 22.60 18.98 14.32 19.69 10 1985 15.57 13.96 15.13 18.56 21.80 23.79 24.67 26.55 24.80 21.64 20.09 15.81 20.20

AVE 13.30 13.79 15.32 18.42 20.62 23.18 25.09 25.48 24.38 22.37 18.84 14.92 19.64 STDEV 1.16 1.12 0.86 0.93 0.59 0.52 0.31 0.62 0.41 0.68 1.20 0.73 0.34

1 1986 14.55 15.07 16.51 20.06 19.66 23.87 25.33 25.80 25.95 22.53 17.25 14.07 20.05 2 1987 14.24 15.48 14.20 17.40 20.03 23.10 25.79 26.80 25.42 22.23 18.95 16.28 19.99 3 1988 14.22 14.09 15.59 17.97 21.87 24.10 26.69 26.72 25.39 22.50 17.49 15.32 20.16 4 1989 11.75 12.98 15.38 19.33 21.30 23.51 25.48 26.13 25.02 22.23 19.68 15.06 19.82 5 1990 13.79 13.71 15.25 18.49 20.15 23.31 25.59 25.88 24.97 23.61 20.97 17.74 20.29 6 1991 13.89 14.76 17.06 19.79 20.93 23.34 25.23 25.90 24.80 23.55 19.40 14.10 20.23 7 1992 12.24 11.95 14.63 17.89 20.16 23.46 25.34 26.67 25.48 25.46 19.80 13.92 19.75 8 1993 12.55 12.45 15.40 19.10 20.79 24.28 25.62 26.41 25.24 24.42 19.06 16.91 20.19 9 1994 15.37 14.71 15.16 20.03 21.49 23.96 25.81 26.31 26.67 25.87 18.63 13.58 20.63 10 1995 13.57 13.95 16.06 17.61 20.57 24.95 26.45 26.99 25.95 22.67 18.17 13.58 20.63

AVE 13.66 13.77 15.51 18.76 21.00 23.93 25.95 26.55 25.61 23.79 19.67 15.44 20.36 STDEV 1.17 1.16 0.75 0.94 0.61 0.53 0.59 0.72 0.77 1.18 0.90 1.57 0.43

1 1996 14.10 15.37 16.05 17.72 22.05 23.91 26.69 26.70 26.00 23.01 19.98 16.72 20.69 2 1997 14.93 12.91 14.46 17.97 21.11 24.23 26.60 26.20 24.96 23.01 20.19 16.26 20.24 3 1998 14.37 14.85 15.62 19.70 21.48 24.33 26.70 28.33 27.01 24.07 20.87 16.60 21.16 4 1999 14.59 14.69 16.94 18.44 21.99 24.77 26.95 27.66 26.68 24.09 20.20 16.19 21.10 5 2000 13.01 13.78 14.79 19.47 21.15 24.96 27.34 27.55 26.10 22.94 19.90 15.81 20.57 6 2001 14.67 14.52 18.13 19.86 21.75 24.84 26.42 27.71 26.23 23.98 19.46 15.57 21.09 7 2002 12.85 15.67 17.56 18.86 20.92 24.70 27.41 27.84 26.45 24.25 21.06 16.31 21.16 8 2003 15.62 13.89 15.04 19.25 23.19 25.06 26.94 27.54 25.91 23.74 20.20 15.65 21.00 9 2004 17.71 18.95 20.20 21.49 24.91 25.94 28.93 29.24 27.99 26.69 23.31 18.72 23.67 10 2005 14.90 14.65 16.83 19.10 21.25 24.37 26.79 27.73 26.66 23.40 19.16 16.92 20.98 11 2006 14.72 16.24 17.13 20.10 21.71 25.25 26.88 27.79 26.84 24.01 18.91 14.98 21.21

AVE 14.68 15.05 16.61 19.27 21.96 24.76 27.06 27.66 26.44 23.93 20.29 16.34 21.22 STDEV 1.30 1.59 1.68 1.06 1.16 0.56 0.69 0.78 0.76 1.04 1.19 0.97 0.92 Mon. Ave 13.17 13.40 14.83 17.58 19.73 22.39 24.29 24.92 23.91 21.84 18.21 14.57 19.06

Annexes

85

Annex (2-A): Irrigation requirements under different climate change scenarios for the different orchards in different governorates of Gaza Strip. Olives, Gaza city

Aver Temp Aver 1990-2006 Aver Temp Aver 1990-2006 Aver Temp Aver 1990-2006 Rainfall Aver Aver Rainfall - 5% Aver Rainfall - 10% Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req.

coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec Mar 1.65 5.47 56.6 27.2 29.5 Mar 1.65 5.47 56.6 27.2 29.5 Mar 1.65 5.47 56.6 24.6 32 Apr 1.68 6.86 68.6 7.6 61.1 Apr 1.68 6.86 68.6 7.6 61.1 Apr 1.68 6.86 68.6 6.9 61.8 May 1.77 8.06 83.4 1.5 81.8 May 1.77 8.06 83.4 1.5 81.8 May 1.77 8.06 83.4 1.4 82 Jun 1.8 9.07 90.7 0.1 90.6 Jun 1.8 9.07 90.7 0.1 90.6 Jun 1.8 9.07 90.7 0.1 90.6 Jul 1.8 9.8 101.3 0 101.3 Jul 1.8 9.8 101.3 0 101.3 Jul 1.8 9.8 101.3 0 101.3 Aug 1.8 9.91 102.3 0 102.3 Aug 1.8 9.91 102.3 0 102.3 Aug 1.8 9.91 102.3 0 102.3 Sep 1.8 8.88 77.6 0.1 77.5 Sep 1.8 8.88 77.6 0.1 77.5 Sep 1.8 8.88 77.6 0.1 77.5 Total 580.5 36.5 544.1 Total 580.5 36.5 544.1 Total 580.5 33.1 547.5 Aver Temp + 1 Aver Temp + 1 Aver Temp + 1 Rainfall Aver Aver Rainfall - 5% Aver Rainfall - 10% Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec Mar 1.65 5.65 58.6 28.5 30.2 Mar 1.65 5.65 58.6 27.2 31.5 Mar 1.65 5.65 58.6 24.6 34 Apr 1.68 7.08 70.8 8 62.9 Apr 1.68 7.08 70.8 7.6 63.2 Apr 1.68 7.08 70.8 6.9 64 May 1.77 8.3 85.9 1.6 84.4 May 1.77 8.3 85.9 1.5 84.4 May 1.77 8.3 85.9 1.4 84.5 Jun 1.8 9.33 93.3 0.1 93.2 Jun 1.8 9.33 93.3 0.1 93.2 Jun 1.8 9.33 93.3 0.1 93.1 Jul 1.8 10.07 104.2 0 104.2 Jul 1.8 10.07 104.2 0 104.2 Jul 1.8 10.07 104.2 0 104.2 Aug 1.8 10.2 105.3 0 105.3 Aug 1.8 10.2 105.3 0 105.3 Aug 1.8 10.2 105.3 0 105.3 Sep 1.8 9.14 79.9 0.1 79.8 Sep 1.8 9.14 79.9 0.1 79.8 Sep 1.8 9.14 79.9 0.1 79.8 Total 598 38.3 560 Total 598 36.5 561.6 Total 598 33.1 564.9 Aver Temp + 2 Aver Temp + 2 Aver Temp + 2 Rainfall Aver Aver Rainfall - 5% Aver Rainfall - 10% Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec Mar 1.65 5.85 60.6 28.5 32.1 Mar 1.65 5.85 60.6 27.2 33.5 Mar 1.65 5.85 60.6 24.6 36 Apr 1.68 7.3 73 8 65.1 Apr 1.68 7.3 73 7.6 65.5 Apr 1.68 7.3 73 6.9 66.1 May 1.77 8.54 88.4 1.6 86.8 May 1.77 8.54 88.4 1.5 86.9 May 1.77 8.54 88.4 1.4 87.1 Jun 1.8 9.59 95.9 0.1 95.8 Jun 1.8 9.59 95.9 0.1 95.8 Jun 1.8 9.59 95.9 0.1 95.8 Jul 1.8 10.36 107.1 0 107.1 Jul 1.8 10.36 107.1 0 107.1 Jul 1.8 10.36 107.1 0 107.1 Aug 1.8 10.49 108.3 0 108.3 Aug 1.8 10.49 108.3 0 108.3 Aug 1.8 10.49 108.3 0 108.3 Sep 1.8 9.42 82.3 0.1 82.2 Sep 1.8 9.42 82.3 0.1 82.2 Sep 1.8 9.42 82.3 0.1 82.2 Total 615.6 38.3 577.4 Total 615.6 36.5 579.3 Total 615.6 33.1 582.6

Annexes

86

Annex (2-B): Irrigation requirements under different climate change scenarios for the different orchards in different governorates of Gaza Strip. Olives, Middle governorate


coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec Mar 1.65 5.47 56.6 31.3 25.4 Mar 1.65 5.47 56.6 29.9 26.6 Mar 1.65 5.47 56.6 27 29.8 Apr 1.68 6.86 68.6 6.8 61.9 Apr 1.68 6.86 68.6 6.4 62.3 Apr 1.68 6.86 68.6 5.6 63 May 1.77 8.06 83.4 0.7 82.7 May 1.77 8.06 83.4 0.7 82.7 May 1.77 8.06 83.4 0.6 82.8 Jun 1.8 9.07 90.7 0.1 90.7 Jun 1.8 9.07 90.7 0.1 90.7 Jun 1.8 9.07 90.7 0.1 90.7 Jul 1.8 9.8 101.3 0 101.3 Jul 1.8 9.8 101.3 0 101.3 Jul 1.8 9.8 101.3 0 101.3 Aug 1.8 9.91 102.3 0 102.3 Aug 1.8 9.91 102.3 0 102.3 Aug 1.8 9.91 102.3 0 102.3 Sep 1.8 8.88 77.6 0.1 77.5 Sep 1.8 8.88 77.6 0.1 77.5 Sep 1.8 8.88 77.6 0.1 77.5 Total 580.5 39 541.8 Total 580.5 37.2 543.4 Total 580.5 33.4 547.4 Aver Temp + 1 Aver Temp + 1 Aver Temp + 1 Rainfall Aver Aver Rainfall - 5% Aver Rainfall - 10% Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec Mar 1.65 5.65 58.6 31.3 27.3 Mar 1.65 5.65 58.6 29.9 28.6 Mar 1.65 5.65 58.6 27 31.7 Apr 1.68 7.08 70.8 6.8 64.2 Apr 1.68 7.08 70.8 6.4 64.4 Apr 1.68 7.08 70.8 5.6 65.2 May 1.77 8.3 85.9 0.7 85.2 May 1.77 8.3 85.9 0.7 85.2 May 1.77 8.3 85.9 0.6 85.3 Jun 1.8 9.33 93.3 0.1 93.2 Jun 1.8 9.33 93.3 0.1 93.2 Jun 1.8 9.33 93.3 0.1 93.2 Jul 1.8 10.07 104.2 0 104.2 Jul 1.8 10.07 104.2 0 104.2 Jul 1.8 10.07 104.2 0 104.2 Aug 1.8 10.2 105.3 0 105.3 Aug 1.8 10.2 105.3 0 105.3 Aug 1.8 10.2 105.3 0 105.3 Sep 1.8 9.14 79.9 0.1 79.8 Sep 1.8 9.14 79.9 0.1 79.8 Sep 1.8 9.14 79.9 0.1 79.8 Total 598 39 559.2 Total 598 37.2 560.7 Total 598 33.4 564.7 Aver Temp + 2 Aver Temp + 2 Aver Temp + 2 Rainfall Aver Aver Rainfall - 5% Aver Rainfall - 10% Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec Mar 1.65 5.85 60.6 31.3 29.3 Mar 1.65 5.85 60.6 29.9 30.6 Mar 1.65 5.85 60.6 27 33.6 Apr 1.68 7.3 73 6.8 66.4 Apr 1.68 7.3 73 6.4 66.7 Apr 1.68 7.3 73 5.6 67.3 May 1.77 8.54 88.4 0.7 87.8 May 1.77 8.54 88.4 0.7 87.7 May 1.77 8.54 88.4 0.6 87.8 Jun 1.8 9.59 95.9 0.1 95.9 Jun 1.8 9.59 95.9 0.1 95.9 Jun 1.8 9.59 95.9 0.1 95.9 Jul 1.8 10.36 107.1 0 107.1 Jul 1.8 10.36 107.1 0 107.1 Jul 1.8 10.36 107.1 0 107.1 Aug 1.8 10.49 108.3 0 108.3 Aug 1.8 10.49 108.3 0 108.3 Aug 1.8 10.49 108.3 0 108.3 Sep 1.8 9.42 82.3 0.1 82.2 Sep 1.8 9.42 82.3 0.1 82.3 Sep 1.8 9.42 82.3 0.1 82.2 Total 615.6 39 577 Total 615.6 37.2 578.6 Total 615.6 33.4 582.2

Annexes

87

Annex (2-C): Irrigation requirements under different climate change scenarios for the different orchards in different governorates of Gaza Strip. Olives, Khan Younis governorate


coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec Mar 1.65 5.47 56.6 31.3 25.3 Mar 1.65 5.47 56.6 30 26.8 Mar 1.65 5.47 56.6 27 29.6 Apr 1.68 6.86 68.6 6.8 61.8 Apr 1.68 6.86 68.6 6.5 62.2 Apr 1.68 6.86 68.6 5.9 62.9 May 1.77 8.06 83.4 0.9 82.6 May 1.77 8.06 83.4 0.7 82.6 May 1.77 8.06 83.4 0.9 82.6 Jun 1.8 9.07 90.7 0.1 90.6 Jun 1.8 9.07 90.7 0.1 90.6 Jun 1.8 9.07 90.7 0.1 90.6 Jul 1.8 9.8 101.3 0 101.3 Jul 1.8 9.8 101.3 0 101.3 Jul 1.8 9.8 101.3 0 101.3 Aug 1.8 9.91 102.3 0 102.3 Aug 1.8 9.91 102.3 0 102.3 Aug 1.8 9.91 102.3 0 102.3 Sep 1.8 8.88 77.6 0.1 77.5 Sep 1.8 8.88 77.6 0.1 77.5 Sep 1.8 8.88 77.6 0.1 77.5 Total 580.5 39.2 541.4 Total 580.5 37.4 543.3 Total 580.5 34 546.8 Aver Temp + 1 Aver Temp + 1 Aver Temp + 1 Rainfall Aver Aver Rainfall - 5% Aver Rainfall - 10% Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec Mar 1.65 5.65 58.6 31.3 27.2 Mar 1.65 5.65 58.6 30 28.7 Mar 1.65 5.65 58.6 27 31.5 Apr 1.68 7.08 70.8 6.8 64.1 Apr 1.68 7.08 70.8 6.5 64.3 Apr 1.68 7.08 70.8 5.9 65.1 May 1.77 8.3 85.9 0.9 85.1 May 1.77 8.3 85.9 0.7 85.1 May 1.77 8.3 85.9 0.9 85 Jun 1.8 9.33 93.3 0.1 93.2 Jun 1.8 9.33 93.3 0.1 93.2 Jun 1.8 9.33 93.3 0.1 93.2 Jul 1.8 10.07 104.2 0 104.2 Jul 1.8 10.07 104.2 0 104.2 Jul 1.8 10.07 104.2 0 104.2 Aug 1.8 10.2 105.3 0 105.3 Aug 1.8 10.2 105.3 0 105.3 Aug 1.8 10.2 105.3 0 105.3 Sep 1.8 9.14 79.9 0.1 79.8 Sep 1.8 9.14 79.9 0.1 79.8 Sep 1.8 9.14 79.9 0.1 79.8 Total 598 39.2 558.9 Total 598 37.4 560.6 Total 598 34 564.1 Aver Temp + 2 Aver Temp + 2 Aver Temp + 2 Rainfall Aver Aver Rainfall - 5% Aver Rainfall - 10% Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec Mar 1.65 5.85 60.6 31.3 29.3 Mar 1.65 5.85 60.6 30 30.7 Mar 1.65 5.85 60.6 27 33.6 Apr 1.68 7.3 73 6.8 66.2 Apr 1.68 7.3 73 6.5 66.6 Apr 1.68 7.3 73 5.9 67.3 May 1.77 8.54 88.4 0.9 87.6 May 1.77 8.54 88.4 0.7 87.7 May 1.77 8.54 88.4 0.9 87.6 Jun 1.8 9.59 95.9 0.1 95.8 Jun 1.8 9.59 95.9 0.1 95.9 Jun 1.8 9.59 95.9 0.1 95.9 Jul 1.8 10.36 107.1 0 107.1 Jul 1.8 10.36 107.1 0 107.1 Jul 1.8 10.36 107.1 0 107.1 Aug 1.8 10.49 108.3 0 108.3 Aug 1.8 10.49 108.3 0 108.3 Aug 1.8 10.49 108.3 0 108.3 Sep 1.8 9.42 82.3 0.1 82.2 Sep 1.8 9.42 82.3 0.1 82.2 Sep 1.8 9.42 82.3 0.1 82.3 Total 615.6 39.2 576.5 Total 615.6 37.4 578.5 Total 615.6 34 582.1

Annexes

88

Annex (2-D): Irrigation requirements under different climate change scenarios for the different orchards in different governorates of Gaza Strip. Palm, Middle governorate


coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec Jan 2.71 6.81 66 69.5 6 Jan 2.71 6.81 66 66.6 7.7 Jan 2.71 6.81 66 60.9 11.6 Feb 2.7 7.74 72.3 48.8 23.5 Feb 2.7 7.74 72.3 46.5 25.7 Feb 2.7 7.74 72.3 42.2 30.1 Mar 2.7 9.66 99.8 22.4 77.3 Mar 2.7 9.66 99.8 21.4 78.4 Mar 2.7 9.66 99.8 19.2 80.5 Apr 2.7 11.58 115.8 3.1 112.8 Apr 2.7 11.58 115.8 2.9 113 Apr 2.7 11.58 115.8 2.5 113.3 May 2.69 12.75 131.7 0.1 131.7 May 2.69 12.75 131.7 0.1 131.7 May 2.69 12.75 131.7 0.1 131.7 Jun 2.62 13.61 136.1 0 136.1 Jun 2.62 13.61 136.1 0 136.1 Jun 2.62 13.61 136.1 0 136.1 Jul 2.61 14.34 148.2 0 148.2 Jul 2.61 14.34 148.2 0 148.2 Jul 2.61 14.34 148.2 0 148.2 Aug 2.61 13.98 144.5 0 144.5 Aug 2.61 13.98 144.5 0 144.5 Aug 2.61 13.98 144.5 0 144.5 Sep 2.61 12.12 121.2 3.9 117.3 Sep 2.61 12.12 121.2 3.7 117.5 Sep 2.61 12.12 121.2 3.3 117.9

Oct 2.61 9.78 101.1 26.1 75 Oct 2.61 9.78 101.1 24.9 76.2 Oct 2.61 9.78 101.1 22.5 78.6 Nov 2.66 7.99 79.9 53.7 26 Nov 2.66 7.99 79.9 51.3 28.4 Nov 2.66 7.99 79.9 46.7 33.2 Dec 2.73 7.12 73.6 76.7 0.8 Dec 2.73 7.12 73.6 73.4 2.8 Dec 2.73 7.12 73.6 67.2 6.9 Jan 0.91 2.22 4.4 5.7 4.4 Jan 0.91 2.22 4.4 5.4 4.4 Jan 0.91 2.22 4.4 5 4.4 Total 1290.9 309.8 1004 Total 1290.9 309.8 1015 Total 1290.9 309.8 1037 Aver Temp + 1 Aver Temp + 1 Aver Temp + 1 Rainfall Aver Aver Rainfall - 5% Aver Rainfall - 10% Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec Jan 2.71 7.06 68.3 69.5 7.6 Jan 2.71 7.06 68.3 66.6 9.7 Jan 2.71 7.06 68.3 60.9 13.5 Feb 2.7 8.03 74.9 48.8 26.1 Feb 2.7 8.03 74.9 46.5 28.4 Feb 2.7 8.03 74.9 42.2 32.7 Mar 2.7 9.98 103.1 22.4 80.7 Mar 2.7 9.98 103.1 21.4 81.7 Mar 2.7 9.98 103.1 19.2 83.8 Apr 2.7 11.94 119.4 3.1 116.4 Apr 2.7 11.94 119.4 2.9 116.6 Apr 2.7 11.94 119.4 2.5 116.9 May 2.69 13.12 135.6 0.1 135.5 May 2.69 13.12 135.6 0.1 135.5 May 2.69 13.12 135.6 0.1 135.5 Jun 2.62 13.98 139.8 0 139.8 Jun 2.62 13.98 139.8 0 139.8 Jun 2.62 13.98 139.8 0 139.8 Jul 2.61 14.73 152.2 0 152.2 Jul 2.61 14.73 152.2 0 152.2 Jul 2.61 14.73 152.2 0 152.2 Aug 2.61 14.37 148.5 0 148.5 Aug 2.61 14.37 148.5 0 148.5 Aug 2.61 14.37 148.5 0 148.5 Sep 2.61 12.47 124.7 3.9 120.7 Sep 2.61 12.47 124.7 3.7 121 Sep 2.61 12.47 124.7 3.3 121.4 Oct 2.61 10.08 104.2 26.1 78.1 Oct 2.61 10.08 104.2 24.9 79.3 Oct 2.61 10.08 104.2 22.5 81.7 Nov 2.65 8.24 82.4 53.7 28.7 Nov 2.65 8.24 82.4 51.3 31 Nov 2.65 8.24 82.4 46.7 35.7 Dec 2.73 7.37 76.1 76.7 2.4 Dec 2.73 7.37 76.1 73.4 4.6 Dec 2.73 7.37 76.1 67.2 8.9 Jan 0.91 2.3 4.6 5.7 4.6 Jan 0.91 2.3 4.6 5.4 4.6 Jan 0.91 2.3 4.6 5 4.6 Total 1290.9 309.8 1041 Total 1290.9 309.8 1053 Total 1290.9 309.8 1075 Aver Temp + 2 Aver Temp + 2 Aver Temp + 2 Rainfall Aver Aver Rainfall - 5% Aver Rainfall - 10% Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec Jan 2.71 7.32 70.9 69.5 9.7 Jan 2.71 7.32 70.9 66.6 11.7 Jan 2.71 7.32 70.9 60.9 15.6 Feb 2.7 8.31 77.6 48.8 28.8 Feb 2.7 8.31 77.6 46.5 31 Feb 2.7 8.31 77.6 42.2 35.4 Mar 2.7 10.31 106.5 22.4 84.1 Mar 2.7 10.31 106.5 21.4 85.1 Mar 2.7 10.31 106.5 19.2 87.2 Apr 2.7 12.3 123 3.1 120.2 Apr 2.7 12.3 123 2.9 120.3 Apr 2.7 12.3 123 2.5 120.6 May 2.69 13.51 139.6 0.1 139.5 May 2.69 13.51 139.6 0.1 139.5 May 2.69 13.51 139.6 0.1 139.5 Jun 2.61 14.36 143.6 0 143.6 Jun 2.61 14.36 143.6 0 143.6 Jun 2.61 14.36 143.6 0 143.6 Jul 2.58 15.12 156.2 0 156.2 Jul 2.58 15.12 156.2 0 156.2 Jul 2.58 15.12 156.2 0 156.2 Aug 2.58 14.76 152.5 0 152.5 Aug 2.58 14.76 152.5 0 152.5 Aug 2.58 14.76 152.5 0 152.5 Sep 2.58 12.82 128.2 3.9 124.4 Sep 2.58 12.82 128.2 3.7 124.5 Sep 2.58 12.82 128.2 3.3 124.9 Oct 2.58 10.38 107.3 26.1 81.2 Oct 2.58 10.38 107.3 24.9 82.4 Oct 2.58 10.38 107.3 22.5 84.9 Nov 2.64 8.5 85 53.7 31.4 Nov 2.64 8.5 85 51.3 33.6 Nov 2.64 8.5 85 46.7 38.4 Dec 2.73 7.61 78.6 76.7 4.1 Dec 2.73 7.61 78.6 73.4 6.3 Dec 2.73 7.61 78.6 67.2 11.4 Jan 0.91 2.39 4.8 5.7 4.8 Jan 0.91 2.39 4.8 5.4 4.8 Jan 0.91 2.39 4.8 5 4.8 Total 1290.9 309.8 1081 Total 1290.9 309.8 1092 Total 1290.9 309.8 1115

Annexes

89

Annex (2-E): Irrigation requirements under different climate change scenarios for the different orchards in different governorates of Gaza Strip. Palm, Khan Younis governorate


coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec Jan 2.71 6.81 66 58.9 12.8 Jan 2.71 6.81 66 56.3 14.5 Jan 2.71 6.81 66 51.3 18 Feb 2.7 7.74 72.3 43.2 29.1 Feb 2.7 7.74 72.3 41.3 31.1 Feb 2.7 7.74 72.3 37.4 35 Mar 2.7 9.66 99.8 23.1 76.7 Mar 2.7 9.66 99.8 22.1 77.7 Mar 2.7 9.66 99.8 19.9 79.9 Apr 2.7 11.58 115.8 3.2 112.7 Apr 2.7 11.58 115.8 3 112.9 Apr 2.7 11.58 115.8 2.8 113.2 May 2.69 12.75 131.7 0.2 131.5 May 2.69 12.75 131.7 0.1 131.6 May 2.69 12.75 131.7 0.3 131.6 Jun 2.62 13.61 136.1 0 136.1 Jun 2.62 13.61 136.1 0 136.1 Jun 2.62 13.61 136.1 0 136.1 Jul 2.61 14.34 148.2 0 148.2 Jul 2.61 14.34 148.2 0 148.2 Jul 2.61 14.34 148.2 0 148.2 Aug 2.61 13.98 144.5 0 144.5 Aug 2.61 13.98 144.5 0 144.5 Aug 2.61 13.98 144.5 0 144.5 Sep 2.61 12.12 121.2 3 118.1 Sep 2.61 12.12 121.2 2.9 118.3 Sep 2.61 12.12 121.2 2.6 118.6

Oct 2.61 9.78 101.1 20.5 80.5 Oct 2.61 9.78 101.1 19.6 81.5 Oct 2.61 9.78 101.1 17.7 83.5 Nov 2.66 7.99 79.9 43.7 36.1 Nov 2.66 7.99 79.9 41.9 37.9 Nov 2.66 7.99 79.9 37.8 41.9 Dec 2.73 7.12 73.6 64.9 8.6 Dec 2.73 7.12 73.6 62.1 11.5 Dec 2.73 7.12 73.6 56.6 16.9 Jan 0.91 2.22 4.4 4.8 4.4 Jan 0.91 2.22 4.4 4.6 4.4 Jan 0.91 2.22 4.4 4.2 4.4 Total 1290.9 191.5 1039 Total 1290.9 191.5 1050 Total 1290.9 191.5 1072 Aver Temp + 1 Aver Temp + 1 Aver Temp + 1 Rainfall Aver Aver Rainfall - 5% Aver Rainfall - 10% Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec Jan 2.71 7.06 68.3 58.9 14.8 Jan 2.71 7.06 68.3 56.3 16.6 Jan 2.71 7.06 68.3 51.3 20 Feb 2.7 8.03 74.9 43.2 31.8 Feb 2.7 8.03 74.9 41.3 33.6 Feb 2.7 8.03 74.9 37.4 37.6 Mar 2.7 9.98 103.1 23.1 80.1 Mar 2.7 9.98 103.1 22.1 81 Mar 2.7 9.98 103.1 19.9 83.2 Apr 2.7 11.94 119.4 3.2 116.3 Apr 2.7 11.94 119.4 3 116.5 Apr 2.7 11.94 119.4 2.8 116.8 May 2.69 13.12 135.6 0.2 135.4 May 2.69 13.12 135.6 0.1 135.5 May 2.69 13.12 135.6 0.3 135.4 Jun 2.62 13.98 139.8 0 139.8 Jun 2.62 13.98 139.8 0 139.8 Jun 2.62 13.98 139.8 0 139.8 Jul 2.61 14.73 152.2 0 152.2 Jul 2.61 14.73 152.2 0 152.2 Jul 2.61 14.73 152.2 0 152.2 Aug 2.61 14.37 148.5 0 148.5 Aug 2.61 14.37 148.5 0 148.5 Aug 2.61 14.37 148.5 0 148.5 Sep 2.61 12.47 124.7 3 121.5 Sep 2.61 12.47 124.7 2.9 121.7 Sep 2.61 12.47 124.7 2.6 122.1 Oct 2.61 10.08 104.2 20.5 83.6 Oct 2.61 10.08 104.2 19.6 84.6 Oct 2.61 10.08 104.2 17.7 86.5 Nov 2.65 8.24 82.4 43.7 38.6 Nov 2.65 8.24 82.4 41.9 40.5 Nov 2.65 8.24 82.4 37.8 44.5 Dec 2.73 7.37 76.1 64.9 11.3 Dec 2.73 7.37 76.1 62.1 14 Dec 2.73 7.37 76.1 56.6 19.6 Jan 0.91 2.3 4.6 4.8 4.6 Jan 0.91 2.3 4.6 4.6 4.6 Jan 0.91 2.3 4.6 4.2 4.6 Total 1290.9 309.8 1079 Total 1290.9 309.8 1089 Total 1290.9 309.8 1111 Aver Temp + 2 Aver Temp + 2 Aver Temp + 2 Rainfall Aver Aver Rainfall - 5% Aver Rainfall - 10% Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec Jan 2.71 7.32 70.9 58.9 16.8 Jan 2.71 7.32 70.9 56.3 18.6 Jan 2.71 7.32 70.9 51.3 22 Feb 2.7 8.31 77.6 43.2 34.4 Feb 2.7 8.31 77.6 41.3 36.3 Feb 2.7 8.31 77.6 37.4 40.3 Mar 2.7 10.31 106.5 23.1 83.4 Mar 2.7 10.31 106.5 22.1 84.4 Mar 2.7 10.31 106.5 19.9 86.7 Apr 2.7 12.3 123 3.2 120 Apr 2.7 12.3 123 3 120.1 Apr 2.7 12.3 123 2.8 120.4 May 2.69 13.51 139.6 0.2 139.4 May 2.69 13.51 139.6 0.1 139.4 May 2.69 13.51 139.6 0.3 139.4 Jun 2.61 14.36 143.6 0 143.6 Jun 2.61 14.36 143.6 0 143.6 Jun 2.61 14.36 143.6 0 143.6 Jul 2.58 15.12 156.2 0 156.2 Jul 2.58 15.12 156.2 0 156.2 Jul 2.58 15.12 156.2 0 156.2 Aug 2.58 14.76 152.5 0 152.5 Aug 2.58 14.76 152.5 0 152.5 Aug 2.58 14.76 152.5 0 152.5 Sep 2.58 12.82 128.2 3 125.2 Sep 2.58 12.82 128.2 2.9 125.3 Sep 2.58 12.82 128.2 2.6 125.6 Oct 2.58 10.38 107.3 20.5 86.8 Oct 2.58 10.38 107.3 19.6 87.8 Oct 2.58 10.38 107.3 17.7 89.6 Nov 2.64 8.5 85 43.7 41.3 Nov 2.64 8.5 85 41.9 43.2 Nov 2.64 8.5 85 37.8 47.1 Dec 2.73 7.61 78.6 64.9 13.8 Dec 2.73 7.61 78.6 62.1 16.6 Dec 2.73 7.61 78.6 56.6 22.1 Jan 0.91 2.39 4.8 4.8 4.8 Jan 0.91 2.39 4.8 4.6 4.8 Jan 0.91 2.39 4.8 4.2 4.8 Total 1290.9 309.8 1118 Total 1290.9 309.8 1129 Total 1290.9 309.8 1150

Annexes

90

Annex (2-F): Irrigation requirements under different climate change scenarios for the different orchards in different governorates of Gaza Strip. Grape, Khan Younis governorate


coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec Feb 0.9 2.98 30.9 31.3 0 Feb 0.9 2.98 30.9 30 0 Feb 0.9 2.98 30.9 27 0 Mar 0.9 3.69 36.9 6.8 3.9 Mar 0.9 3.69 36.9 6.5 4.2 Mar 0.9 3.69 36.9 5.9 5.6 Apr 0.9 4.12 42.6 0.9 30.2 Apr 0.9 4.12 42.6 0.7 30.4 Apr 0.9 4.12 42.6 0.9 31.1 May 0.9 4.54 45.4 0.1 41.8 May 0.9 4.54 45.4 0.1 41.9 May 0.9 4.54 45.4 0.1 41.8 Jun 1.38 7.53 78.4 0 45.3 Jun 1.38 7.53 78.4 0 45.3 Jun 1.38 7.53 78.4 0 45.3 Jul 2.25 12.39 128.3 0 78.4 Jul 2.25 12.39 128.3 0 78.4 Jul 2.25 12.39 128.3 0 78.4 Aug 2.43 11.97 119.7 0.1 128.3 Aug 2.43 11.97 119.7 0.1 128.3 Aug 2.43 11.97 119.7 0.1 128.3 Sep 2.43 9.85 101.6 14.1 119.6 Sep 2.43 9.85 101.6 13.5 119.6 Sep 2.43 9.85 101.6 12.2 119.6

Oct 2.43 7.8 78 35.2 87.3 Oct 2.43 7.8 78 33.8 88.2 Oct 2.43 7.8 78 30.3 89.3 Nov 2.39 6.48 66.8 60.1 42.9 Nov 2.39 6.48 66.8 57.4 44.4 Nov 2.39 6.48 66.8 52.4 47.7 Dec 1.73 4.32 44.4 67.9 6.7 Dec 1.73 4.32 44.4 65 9.4 Dec 1.73 4.32 44.4 59.2 14.6 Jan 0 0 0 0 0 Jan 0 0 0 0 0 Jan 0 0 0 0 0 Total 1290.9 309.8 584 Total 1290.9 309.8 590 Total 1290.9 309.8 602 Aver Temp + 1 Aver Temp + 1 Aver Temp + 1 Rainfall Aver Aver Rainfall - 5% Aver Rainfall - 10% Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec Feb 0.9 3.33 34.4 23.1 0 Feb 0.9 3.33 34.4 22.1 0 Feb 0.9 3.33 34.4 19.9 0 Mar 0.9 3.98 39.8 3.2 11.9 Mar 0.9 3.98 39.8 3 12.4 Mar 0.9 3.98 39.8 2.8 14.5 Apr 0.9 4.38 45.3 0.2 36.7 Apr 0.9 4.38 45.3 0.1 36.8 Apr 0.9 4.38 45.3 0.3 37.1 May 0.96 5.11 51.1 0 45.1 May 0.96 5.11 51.1 0 45.1 May 0.96 5.11 51.1 0 45 Jun 1.69 9.61 99.3 0 51.1 Jun 1.69 9.61 99.3 0 51.1 Jun 1.69 9.61 99.3 0 51.1 Jul 2.39 13.2 136.5 0 99.3 Jul 2.39 13.2 136.5 0 99.3 Jul 2.39 13.2 136.5 0 99.3 Aug 2.43 11.64 116.4 3 136.5 Aug 2.43 11.64 116.4 2.9 136.5 Aug 2.43 11.64 116.4 2.6 136.5 Sep 2.43 9.41 97.2 20.5 113.4 Sep 2.43 9.41 97.2 19.6 113.5 Sep 2.43 9.41 97.2 17.7 113.8 Oct 2.43 7.54 75.4 43.7 76.8 Oct 2.43 7.54 75.4 41.9 77.8 Oct 2.43 7.54 75.4 37.8 79.5 Nov 2.25 6.09 63 64.9 31.7 Nov 2.25 6.09 63 62.1 33.6 Nov 2.25 6.09 63 56.6 37.5 Dec 1.06 2.71 28.3 45.3 3 Dec 1.06 2.71 28.3 43.3 4.9 Dec 1.06 2.71 28.3 39.5 8.5 Jan 0 0 819.9 265.6 0 Jan 0 0 819.9 253.8 0 Jan 0 0 819.9 230.4 0 Total 1290.9 309.8 606 Total 1290.9 309.8 611 Total 1290.9 309.8 623 Aver Temp + 2 Aver Temp + 2 Aver Temp + 2 Rainfall Aver Aver Rainfall - 5% Aver Rainfall - 10% Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec Feb 0.9 3.44 35.5 23.1 0 Feb 0.9 3.44 35.5 22.1 0 Feb 0.9 3.44 35.5 19.9 0 Mar 0.9 4.1 41 3.2 12.6 Mar 0.9 4.1 41 3 13.4 Mar 0.9 4.1 41 2.8 15.7 Apr 0.9 4.51 46.6 0.2 37.9 Apr 0.9 4.51 46.6 0.1 38 Apr 0.9 4.51 46.6 0.3 38.3 May 0.96 5.26 52.6 0 46.4 May 0.96 5.26 52.6 0 46.4 May 0.96 5.26 52.6 0 46.4 Jun 1.69 9.88 102.1 0 52.6 Jun 1.69 9.88 102.1 0 52.6 Jun 1.69 9.88 102.1 0 52.6 Jul 2.39 13.57 140.3 0 102.1 Jul 2.39 13.57 140.3 0 102.1 Jul 2.39 13.57 140.3 0 102.1 Aug 2.43 11.98 119.8 3 140.3 Aug 2.43 11.98 119.8 2.9 140.3 Aug 2.43 11.98 119.8 2.6 140.3 Sep 2.43 9.69 100.2 20.5 116.7 Sep 2.43 9.69 100.2 19.6 116.9 Sep 2.43 9.69 100.2 17.7 117.1 Oct 2.43 7.79 77.9 43.7 79.7 Oct 2.43 7.79 77.9 41.9 80.7 Oct 2.43 7.79 77.9 37.8 82.5 Nov 2.25 6.29 65 64.9 34.2 Nov 2.25 6.29 65 62.1 36 Nov 2.25 6.29 65 56.6 40 Dec 1.06 2.81 29.4 45.3 4.6 Dec 1.06 2.81 29.4 43.3 6.4 Dec 1.06 2.81 29.4 39.5 10 Jan 0 0 844.5 265.6 0 Jan 0 0 844.5 253.8 0 Jan 0 0 844.5 230.4 0 Total 1290.9 309.8 627 Total 1290.9 309.8 633 Total 1290.9 309.8 645

Annexes

91

Annex (2-G): Irrigation requirements under different climate change scenarios for the different orchards in different governorates of Gaza Strip. Citrus, Gaza city


coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec Feb 2.1 6.96 72.1 27.2 0 Feb 2.1 6.96 72.1 27.2 0 Feb 2.1 6.96 72.1 24.6 0.2 Mar 2.04 8.36 83.6 7.6 45 Mar 2.04 8.36 83.6 7.6 45 Mar 2.04 8.36 83.6 6.9 47.6 Apr 1.91 8.76 90.6 1.5 75.9 Apr 1.91 8.76 90.6 1.5 75.9 Apr 1.91 8.76 90.6 1.4 76.7 May 1.79 9 90 0.1 89.1 May 1.79 9 90 0.1 89.1 May 1.79 9 90 0.1 89.2 Jun 1.74 9.41 97.3 0 89.9 Jun 1.74 9.41 97.3 0 89.9 Jun 1.74 9.41 97.3 0 89.8 Jul 1.74 9.52 98.3 0 97.3 Jul 1.74 9.52 98.3 0 97.3 Jul 1.74 9.52 98.3 0 97.3 Aug 1.74 8.53 85.3 0.1 98.3 Aug 1.74 8.53 85.3 0.1 98.3 Aug 1.74 8.53 85.3 0.1 98.3 Sep 1.76 7.11 73.4 21.5 85.1 Sep 1.76 7.11 73.4 21.5 85.1 Sep 1.76 7.11 73.4 19.4 85.1

Oct 2.01 6.44 64.4 39.6 51.8 Oct 2.01 6.44 64.4 39.6 51.8 Oct 2.01 6.44 64.4 35.8 54 Nov 2.01 5.43 56 74.1 24.9 Nov 2.01 5.43 56 74.1 24.9 Nov 2.01 5.43 56 67.8 28.6 Dec 2.01 4.99 51.6 88.7 0 Dec 2.01 4.99 51.6 88.7 0 Dec 2.01 4.99 51.6 81.5 0 Jan 0 0 0 0 0 Jan 0 0 0 0 0 Jan 0 0 0 0 0 Total 1290.9 309.8 657 Total 1290.9 309.8 657 Total 1290.9 309.8 667 Aver Temp + 1 Aver Temp + 1 Aver Temp + 1 Rainfall Aver Aver Rainfall - 5% Aver Rainfall - 10% Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec Feb 2.09 7.74 80 19.9 9.2 Feb 2.09 7.74 80 18.9 9.8 Feb 2.09 7.74 80 17.1 11.7 Mar 2 8.84 88.4 4.6 60.2 Mar 2 8.84 88.4 4.3 61.1 Mar 2 8.84 88.4 3.9 62.9 Apr 1.87 9.11 94.1 0.6 83.8 Apr 1.87 9.11 94.1 0.6 83.9 Apr 1.87 9.11 94.1 0.6 84.4 May 1.74 9.34 93.4 0 93.5 May 1.74 9.34 93.4 0 93.5 May 1.74 9.34 93.4 0 93.5 Jun 1.71 9.78 101.1 0 93.4 Jun 1.71 9.78 101.1 0 93.4 Jun 1.71 9.78 101.1 0 93.4 Jul 1.71 9.54 98.6 0 101.1 Jul 1.71 9.54 98.6 0 101.1 Jul 1.71 9.54 98.6 0 101.1 Aug 1.71 8.28 82.8 5.2 98.6 Aug 1.71 8.28 82.8 5 98.6 Aug 1.71 8.28 82.8 4.5 98.6 Sep 1.84 7.13 73.6 28.6 77.6 Sep 1.84 7.13 73.6 27.3 77.9 Sep 1.84 7.13 73.6 24.6 78.3 Oct 2.01 6.21 62.1 52.7 45 Oct 2.01 6.21 62.1 50.4 46.3 Oct 2.01 6.21 62.1 45.8 49 Nov 2.01 5.39 55.7 85.2 12.4 Nov 2.01 5.39 55.7 81.8 13.6 Nov 2.01 5.39 55.7 75 16.3 Dec 1.34 3.43 36 61.9 0 Dec 1.34 3.43 36 59.5 0 Dec 1.34 3.43 36 54.7 0 Jan 0 0 943 338.1 0 Jan 0 0 943 323.8 0 Jan 0 0 943 295.3 0 Total 1290.9 309.8 675 Total 1290.9 309.8 679 Total 1290.9 309.8 689 Aver Temp + 2 Aver Temp + 2 Aver Temp + 2 Rainfall Aver Aver Rainfall - 5% Aver Rainfall - 10% Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec Feb 2.09 7.99 82.6 19.9 9.9 Feb 2.09 7.99 82.6 18.9 10.5 Feb 2.09 7.99 82.6 17.1 13.4 Mar 2 9.11 91.1 4.6 62.8 Mar 2 9.11 91.1 4.3 63.8 Mar 2 9.11 91.1 3.9 65.6 Apr 1.87 9.36 96.7 0.6 86.5 Apr 1.87 9.36 96.7 0.6 86.6 Apr 1.87 9.36 96.7 0.6 87.1 May 1.74 9.59 95.9 0 96 May 1.74 9.59 95.9 0 96 May 1.74 9.59 95.9 0 96.1 Jun 1.71 10.05 103.8 0 95.9 Jun 1.71 10.05 103.8 0 95.9 Jun 1.71 10.05 103.8 0 95.9 Jul 1.71 9.8 101.2 0 103.8 Jul 1.71 9.8 101.2 0 103.8 Jul 1.71 9.8 101.2 0 103.8 Aug 1.71 8.52 85.2 5.2 101.2 Aug 1.71 8.52 85.2 5 101.2 Aug 1.71 8.52 85.2 4.5 101.2 Sep 1.84 7.34 75.8 28.6 80 Sep 1.84 7.34 75.8 27.3 80.1 Sep 1.84 7.34 75.8 24.6 80.7 Oct 2.01 6.42 64.2 52.7 47.2 Oct 2.01 6.42 64.2 50.4 48.5 Oct 2.01 6.42 64.2 45.8 51.2 Nov 2.01 5.58 57.7 85.2 13.6 Nov 2.01 5.58 57.7 81.8 15 Nov 2.01 5.58 57.7 75 18.4 Dec 1.34 3.55 37.3 61.9 0 Dec 1.34 3.55 37.3 59.5 0 Dec 1.34 3.55 37.3 54.7 0 Jan 0 0 971.1 338.1 0 Jan 0 0 971.1 323.8 0 Jan 0 0 971.1 295.3 0 Total 1290.9 309.8 697 Total 1290.9 309.8 701 Total 1290.9 309.8 713

Annexes

92

Annex (2-H): Irrigation requirements under different climate change scenarios for the different orchards in different governorates of Gaza Strip. Citrus, Middle governorate


coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec Feb 2.1 6.96 72.1 31.3 0 Feb 2.1 6.96 72.1 29.9 0.8 Feb 2.1 6.96 72.1 27 4 Mar 2.04 8.36 83.6 6.8 40.9 Mar 2.04 8.36 83.6 6.4 42.1 Mar 2.04 8.36 83.6 5.6 45.2 Apr 1.91 8.76 90.6 0.7 76.9 Apr 1.91 8.76 90.6 0.7 77.2 Apr 1.91 8.76 90.6 0.6 77.9 May 1.79 9 90 0.1 89.8 May 1.79 9 90 0.1 89.8 May 1.79 9 90 0.1 90 Jun 1.74 9.41 97.3 0 89.9 Jun 1.74 9.41 97.3 0 89.9 Jun 1.74 9.41 97.3 0 89.9 Jul 1.74 9.52 98.3 0 97.3 Jul 1.74 9.52 98.3 0 97.3 Jul 1.74 9.52 98.3 0 97.3 Aug 1.74 8.53 85.3 0.1 98.3 Aug 1.74 8.53 85.3 0.1 98.3 Aug 1.74 8.53 85.3 0.1 98.3 Sep 1.76 7.11 73.4 18.1 85.1 Sep 1.76 7.11 73.4 17.2 85.2 Sep 1.76 7.11 73.4 15.5 85.1

Oct 2.01 6.44 64.4 44.2 55.3 Oct 2.01 6.44 64.4 42.2 56.1 Oct 2.01 6.44 64.4 38.3 57.8 Nov 2.01 5.43 56 71.2 20.3 Nov 2.01 5.43 56 68.2 22.2 Nov 2.01 5.43 56 62.3 26.2 Dec 2.01 4.99 51.6 80.3 0 Dec 2.01 4.99 51.6 76.8 0 Dec 2.01 4.99 51.6 70.4 0.4 Jan 0 0 0 0 0 Jan 0 0 0 0 0 Jan 0 0 0 0 0 Total 1290.9 309.8 654 Total 1290.9 309.8 659 Total 1290.9 309.8 672 Aver Temp + 1 Aver Temp + 1 Aver Temp + 1 Rainfall Aver Aver Rainfall - 5% Aver Rainfall - 10% Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec Feb 2.09 7.74 80 22.4 9.5 Feb 2.09 7.74 80 21.4 11.7 Feb 2.09 7.74 80 19.2 16.1 Mar 2 8.84 88.4 3.1 57.6 Mar 2 8.84 88.4 2.9 58.5 Mar 2 8.84 88.4 2.5 60.7 Apr 1.87 9.11 94.1 0.1 85.3 Apr 1.87 9.11 94.1 0.1 85.4 Apr 1.87 9.11 94.1 0.1 85.9 May 1.74 9.34 93.4 0 94.1 May 1.74 9.34 93.4 0 94.1 May 1.74 9.34 93.4 0 94.1 Jun 1.71 9.78 101.1 0 93.4 Jun 1.71 9.78 101.1 0 93.4 Jun 1.71 9.78 101.1 0 93.4 Jul 1.71 9.54 98.6 0 101.1 Jul 1.71 9.54 98.6 0 101.1 Jul 1.71 9.54 98.6 0 101.1 Aug 1.71 8.28 82.8 3.9 98.6 Aug 1.71 8.28 82.8 3.7 98.6 Aug 1.71 8.28 82.8 3.3 98.6 Sep 1.84 7.13 73.6 26.1 79 Sep 1.84 7.13 73.6 24.9 79.2 Sep 1.84 7.13 73.6 22.5 79.5 Oct 2.01 6.21 62.1 53.7 47.5 Oct 2.01 6.21 62.1 51.3 48.7 Oct 2.01 6.21 62.1 46.7 51.1 Nov 2.01 5.39 55.7 76.7 10.2 Nov 2.01 5.39 55.7 73.4 11.6 Nov 2.01 5.39 55.7 67.2 15.7 Dec 1.34 3.43 36 53.5 0 Dec 1.34 3.43 36 51.2 0 Dec 1.34 3.43 36 46.9 0 Jan 0 0 943 309.8 0 Jan 0 0 943 296.3 0 Jan 0 0 943 269.4 0 Total 1290.9 309.8 676 Total 1290.9 309.8 682 Total 1290.9 309.8 696 Aver Temp + 2 Aver Temp + 2 Aver Temp + 2 Rainfall Aver Aver Rainfall - 5% Aver Rainfall - 10% Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec Feb 2.09 7.99 82.6 22.4 11.6 Feb 2.09 7.99 82.6 21.4 13.8 Feb 2.09 7.99 82.6 19.2 18.2 Mar 2 9.11 91.1 3.1 60.2 Mar 2 9.11 91.1 2.9 61.2 Mar 2 9.11 91.1 2.5 63.3 Apr 1.87 9.36 96.7 0.1 88 Apr 1.87 9.36 96.7 0.1 88.1 Apr 1.87 9.36 96.7 0.1 88.5 May 1.74 9.59 95.9 0 96.6 May 1.74 9.59 95.9 0 96.6 May 1.74 9.59 95.9 0 96.6 Jun 1.71 10.05 103.8 0 95.9 Jun 1.71 10.05 103.8 0 95.9 Jun 1.71 10.05 103.8 0 95.9 Jul 1.71 9.8 101.2 0 103.8 Jul 1.71 9.8 101.2 0 103.8 Jul 1.71 9.8 101.2 0 103.8 Aug 1.71 8.52 85.2 3.9 101.2 Aug 1.71 8.52 85.2 3.7 101.2 Aug 1.71 8.52 85.2 3.3 101.2 Sep 1.84 7.34 75.8 26.1 81.2 Sep 1.84 7.34 75.8 24.9 81.5 Sep 1.84 7.34 75.8 22.5 81.9 Oct 2.01 6.42 64.2 53.7 49.6 Oct 2.01 6.42 64.2 51.3 50.8 Oct 2.01 6.42 64.2 46.7 53.2 Nov 2.01 5.58 57.7 76.7 11.5 Nov 2.01 5.58 57.7 73.4 13 Nov 2.01 5.58 57.7 67.2 17.6 Dec 1.34 3.55 37.3 53.5 0 Dec 1.34 3.55 37.3 51.2 0 Dec 1.34 3.55 37.3 46.9 0 Jan 0 0 971.1 309.8 0 Jan 0 0 971.1 296.3 0 Jan 0 0 971.1 269.4 0 Total 1290.9 309.8 700 Total 1290.9 309.8 706 Total 1290.9 309.8 720

Annexes

93

Annex (2-I): Irrigation requirements under different climate change scenarios for the different orchards in different governorates of Gaza Strip. Guava, Middle governorate


coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec Feb 3.3 10.94 113.4 31.3 25.8 Feb 3.3 10.94 113.4 29.9 28.3 Feb 3.3 10.94 113.4 27 33.3 Mar 3.3 13.53 135.3 6.8 82 Mar 3.3 13.53 135.3 6.4 83.3 Mar 3.3 13.53 135.3 5.6 86.3 Apr 3.3 15.11 156.3 0.7 128.6 Apr 3.3 15.11 156.3 0.7 129 Apr 3.3 15.11 156.3 0.6 129.6 May 3.3 16.63 166.3 0.1 155.6 May 3.3 16.63 166.3 0.1 155.6 May 3.3 16.63 166.3 0.1 155.7 Jun 3.3 17.97 185.8 0 166.3 Jun 3.3 17.97 185.8 0 166.3 Jun 3.3 17.97 185.8 0 166.3 Jul 3.3 18.18 187.7 0 185.8 Jul 3.3 18.18 187.7 0 185.8 Jul 3.3 18.18 187.7 0 185.8 Aug 3.3 11.15 100.6 0 187.7 Aug 3.3 11.15 100.6 0 187.7 Aug 3.3 11.15 100.6 0 187.7 Sep 2.2 11.15 100.6 0 100.6 Sep 2.2 11.15 100.6 0 100.6 Sep 2.2 11.15 100.6 0 100.6 Total 1290.9 309.8 1032 Total 1290.9 309.8 1037 Total 1290.9 309.8 1045 Aver Temp + 1 Aver Temp + 1 Aver Temp + 1 Rainfall Aver Aver Rainfall - 5% Aver Rainfall - 10% Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec Feb 3.3 11.32 117.2 31.3 28.8 Feb 3.3 11.32 117.2 29.9 31.3 Feb 3.3 11.32 117.2 27 36.4 Mar 3.3 13.97 139.7 6.8 86 Mar 3.3 13.97 139.7 6.4 87.3 Mar 3.3 13.97 139.7 5.6 90.2 Apr 3.3 15.56 160.9 0.7 132.9 Apr 3.3 15.56 160.9 0.7 133.2 Apr 3.3 15.56 160.9 0.6 134 May 3.3 17.11 171.1 0.1 160.3 May 3.3 17.11 171.1 0.1 160.3 May 3.3 17.11 171.1 0.1 160.4 Jun 3.3 18.48 191.1 0 171 Jun 3.3 18.48 191.1 0 171 Jun 3.3 18.48 191.1 0 171.1 Jul 3.3 18.69 193 0 191.1 Jul 3.3 18.69 193 0 191.1 Jul 3.3 18.69 193 0 191.1 Aug 3.3 11.48 103.6 0 193 Aug 3.3 11.48 103.6 0 193 Aug 3.3 11.48 103.6 0 193 Sep 2.2 11.48 103.6 0 103.6 Sep 2.2 11.48 103.6 0 103.6 Sep 2.2 11.48 103.6 0 103.6 Total 1290.9 309.8 1067 Total 1290.9 309.8 1071 Total 1290.9 309.8 1080 Aver Temp + 2 Aver Temp + 2 Aver Temp + 2 Rainfall Aver Aver Rainfall - 5% Aver Rainfall - 10% Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec Feb 3.3 11.7 121.2 31.3 31.9 Feb 3.3 11.7 121.2 29.9 34.5 Feb 3.3 11.7 121.2 27 39.5 Mar 3.3 14.41 144.1 6.8 89.8 Mar 3.3 14.41 144.1 6.4 91.3 Mar 3.3 14.41 144.1 5.6 94.2 Apr 3.3 16.03 165.8 0.7 137.3 Apr 3.3 16.03 165.8 0.7 137.6 Apr 3.3 16.03 165.8 0.6 138.2 May 3.3 17.6 176 0.1 165.1 May 3.3 17.6 176 0.1 165.1 May 3.3 17.6 176 0.1 165.2 Jun 3.3 18.99 196.3 0 175.9 Jun 3.3 18.99 196.3 0 175.9 Jun 3.3 18.99 196.3 0 175.9 Jul 3.3 19.22 198.5 0 196.3 Jul 3.3 19.22 198.5 0 196.3 Jul 3.3 19.22 198.5 0 196.3 Aug 3.3 11.81 106.5 0 198.5 Aug 3.3 11.81 106.5 0 198.5 Aug 3.3 11.81 106.5 0 198.5 Sep 2.2 11.81 106.5 0 106.5 Sep 2.2 11.81 106.5 0 106.5 Sep 2.2 11.81 106.5 0 106.5 Total 1290.9 309.8 1101 Total 1290.9 309.8 1106 Total 1290.9 309.8 1114

Annexes

94

Annex (2-J): Irrigation requirements under different climate change scenarios for the different orchards in different governorates of Gaza Strip. Guava, Khan Younis governorate


coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec Feb 3.3 10.94 113.4 31.3 34 Feb 3.3 10.94 113.4 30 36.2 Feb 3.3 10.94 113.4 27 40.6 Mar 3.3 13.53 135.3 6.8 81.9 Mar 3.3 13.53 135.3 6.5 83.4 Mar 3.3 13.53 135.3 5.9 86.3 Apr 3.3 15.11 156.3 0.9 128.6 Apr 3.3 15.11 156.3 0.7 128.8 Apr 3.3 15.11 156.3 0.9 129.5 May 3.3 16.63 166.3 0.1 155.4 May 3.3 16.63 166.3 0.1 155.5 May 3.3 16.63 166.3 0.1 155.5 Jun 3.3 17.97 185.8 0 166.3 Jun 3.3 17.97 185.8 0 166.3 Jun 3.3 17.97 185.8 0 166.3 Jul 3.3 18.18 187.7 0 185.8 Jul 3.3 18.18 187.7 0 185.8 Jul 3.3 18.18 187.7 0 185.8 Aug 3.3 11.15 100.6 0 187.7 Aug 3.3 11.15 100.6 0 187.7 Aug 3.3 11.15 100.6 0 187.7 Sep 2.2 11.15 100.6 0 100.6 Sep 2.2 11.15 100.6 0 100.6 Sep 2.2 11.15 100.6 0 100.6 1290.9 309.8 1040 1290.9 309.8 1044 1290.9 309.8 1052 Aver Temp + 1 Aver Temp + 1 Aver Temp + 1 Rainfall Aver Aver Rainfall - 5% Aver Rainfall - 10% Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec Feb 3.3 11.32 117.2 31.3 37 Feb 3.3 11.32 117.2 30 39.2 Feb 3.3 11.32 117.2 27 43.6 Mar 3.3 13.97 139.7 6.8 85.9 Mar 3.3 13.97 139.7 6.5 87.2 Mar 3.3 13.97 139.7 5.9 90.2 Apr 3.3 15.56 160.9 0.9 132.9 Apr 3.3 15.56 160.9 0.7 133.2 Apr 3.3 15.56 160.9 0.9 133.8 May 3.3 17.11 171.1 0.1 160.2 May 3.3 17.11 171.1 0.1 160.2 May 3.3 17.11 171.1 0.1 160.2 Jun 3.3 18.48 191.1 0 171 Jun 3.3 18.48 191.1 0 171 Jun 3.3 18.48 191.1 0 171 Jul 3.3 18.69 193 0 191.1 Jul 3.3 18.69 193 0 191.1 Jul 3.3 18.69 193 0 191.1 Aug 3.3 11.48 103.6 0 193 Aug 3.3 11.48 103.6 0 193 Aug 3.3 11.48 103.6 0 193 Sep 2.2 11.48 103.6 0 103.6 Sep 2.2 11.48 103.6 0 103.6 Sep 2.2 11.48 103.6 0 103.6 1290.9 309.8 1075 1290.9 309.8 1079 1290.9 309.8 1087 Aver Temp + 2 Aver Temp + 2 Aver Temp + 2 Rainfall Aver Aver Rainfall - 5% Aver Rainfall - 10% Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. Month Kc ETc ETc Eff rain Irr. Req. coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec coeff mm/day mm/dec mm/dec mm/dec Feb 3.3 11.7 121.2 31.3 40.2 Feb 3.3 11.7 121.2 30 42.3 Feb 3.3 11.7 121.2 27 46.7 Mar 3.3 14.41 144.1 6.8 89.9 Mar 3.3 14.41 144.1 6.5 91.2 Mar 3.3 14.41 144.1 5.9 94.2 Apr 3.3 16.03 165.8 0.9 137.3 Apr 3.3 16.03 165.8 0.7 137.5 Apr 3.3 16.03 165.8 0.9 138.2 May 3.3 17.6 176 0.1 164.9 May 3.3 17.6 176 0.1 164.9 May 3.3 17.6 176 0.1 165 Jun 3.3 18.99 196.3 0 175.9 Jun 3.3 18.99 196.3 0 175.9 Jun 3.3 18.99 196.3 0 175.9 Jul 3.3 19.22 198.5 0 196.3 Jul 3.3 19.22 198.5 0 196.3 Jul 3.3 19.22 198.5 0 196.3 Aug 3.3 11.81 106.5 0 198.5 Aug 3.3 11.81 106.5 0 198.5 Aug 3.3 11.81 106.5 0 198.5 Sep 2.2 11.81 106.5 0 106.5 Sep 2.2 11.81 106.5 0 106.5 Sep 2.2 11.81 106.5 0 106.5 1290.9 309.8 1110 1290.9 309.8 1113 1290.9 309.8 1121

Annexes

95

Annex (3-A): Irrigation requirements respond to different salinity levels comparing to CropWat required irrigation under optimal salinity levels.

Olive

EECC lleevveell Area (1,000 m2)


P Ave. P – 5% P – 10% P Ave. P – 5% P – 10% P Ave. P – 10% P – 10% % of additional I R related to

EC rise T Ave. T Ave. T Ave. T + 1 T + 1 T + 1 T + 2 T + 2 T + 2

CropWat I. R 27,724 15.04 15.07 15.17 15.51 15.55 15.65 16.00 16.05 16.14 1-2 16.85 16.88 16.99 17.37 17.42 17.53 17.92 17.97 18.08 12% <2 -3 17.90 17.94 18.06 18.45 18.51 18.63 19.04 19.10 19.21 19% <3 -4 19.10 19.14 19.27 19.70 19.75 19.88 20.31 20.38 20.50 27% <4 -5 20.45 20.50 20.64 21.09 21.15 21.29 21.75 21.82 21.96 36%

<5 22.11 22.16 22.30 22.80 22.86 23.01 23.51 23.59 23.73 47%

Gaza Strip Olive Farms irrigation Requirements & Leaching Fraction for Different Level of EC

Annexes

96

Annex (3-B): Irrigation requirements respond to different salinity levels comparing to CropWat required irrigation under optimal salinity levels.

Palm





CropWat I. R 5,453 5.57 5.63 5.75 5.78 5.84 5.96 6.00 6.06 6.18

1-2 6.18 6.25 6.38 6.42 6.48 6.62 6.66 6.72 6.85 11% 2-3 6.57 6.64 6.79 6.82 6.89 7.03 7.07 7.15 7.29 18% 3-4 6.96 7.04 7.19 7.23 7.30 7.45 7.49 7.57 7.72 25% 4-5 7.41 7.49 7.65 7.69 7.77 7.93 7.97 8.06 8.21 33%

<5 7.97 8.05 8.22 8.27 8.35 8.52 8.57 8.66 8.83 43%

Gaza Strip Palm Farms irrigation Requirements & Leaching Fraction for Different Level of EC

Annexes

97

Annex (3-C): Irrigation requirements respond to different salinity levels comparing to CropWat required irrigation under optimal salinity levels.

Grape





CropWat I. R 5,259 3.07 3.10 3.17 3.19 3.21 3.28 3.30 3.33 3.39

>1 3.53 3.57 3.64 3.66 3.70 3.77 3.79 3.83 3.90 15% 1-2 4.18 4.22 4.31 4.33 4.37 4.46 4.48 4.53 4.61 36% 2-3 5.13 5.18 5.29 5.32 5.37 5.47 5.51 5.56 5.66 67% 3-4 6.57 6.64 6.78 6.82 6.88 7.01 7.06 7.12 7.26 114% 4-5 9.21 9.31 9.50 9.56 9.64 9.83 9.89 9.99 10.18 200%

Gaza Strip Grape Farms irrigation Requirements & Leaching Fraction for Different Level of EC

Annexes

98

Annex (3-D): Irrigation requirements respond to different salinity levels comparing to CropWat required irrigation under optimal salinity levels.

Citrus



P Ave. P – 5% P – 10% P Ave. P – 5% P – 10% P Ave. P – 10% P – 10% % of additional I R related to EC

rise T Ave. T Ave. T Ave. T + 1 T + 1 T + 1 T + 2 T + 2 T + 2

CropWat I. R 8,134 5.33 5.35 5.45 5.49 5.54 5.63 5.68 5.73 5.83

2-3 8.26 8.30 8.44 8.52 8.58 8.73 8.81 8.88 9.03 55% 3-4 10.08 10.12 10.29 10.38 10.46 10.65 10.74 10.82 11.01 89% 4-5 12.96 13.01 13.23 13.35 13.45 13.69 13.81 13.91 14.16 143%

<5 18.13 18.20 18.52 18.68 18.82 19.15 19.32 19.47 19.82 240%

Gaza Strip Citrus Farms irrigation Requirements & Leaching Fraction for Different Level of EC

Annexes

99

Annex (3-E): Irrigation requirements respond to different salinity levels comparing to CropWat required irrigation under optimal salinity levels.

Guava



P Ave. P – 5% P – 10% P Ave. P – 5% P – 10% P Ave. P – 10% P – 10% % of additional I R related to EC

rise T Ave. T Ave. T Ave. T + 1 T + 1 T + 1 T + 2 T + 2 T + 2

CropWat I. R 3,842 3.98 4.00 4.03 4.11 4.13 4.16 4.25 4.26 4.29

>1 4.26 4.28 4.31 4.40 4.42 4.45 4.54 4.56 4.59 7% 1-2 4.58 4.60 4.63 4.73 4.75 4.79 4.88 4.90 4.94 15% 2-3 4.98 5.00 5.04 5.14 5.16 5.20 5.31 5.33 5.37 25% 3-4 5.41 5.44 5.48 5.60 5.62 5.66 5.78 5.80 5.84 36% 4-5 5.97 6.00 6.04 6.17 6.20 6.24 6.37 6.40 6.44 50%

<5 6.65 6.68 6.73 6.87 6.90 6.95 7.09 7.12 7.17 67%

Gaza Strip Guava Farms irrigation Requirements & Leaching Fraction for Different Level of EC

Annexes

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Annex (4-A): CropWat results for the irrigation requirements of the studied trees in the different studied governorates of Gaza Strip.

Figure 5.9: Olive trees irrigation requirements in Gaza governorate.

Figure 5.10: Olive trees irrigation requirements in Dair Al-Balah governorate.

Figure 5.11: Olive trees irrigation requirements in Khan Younis governorate.

Figure 5.12: Palm trees irrigation requirements in Dair Al-Balah governorate.

Annexes

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Annex (4-B): CropWat results for the irrigation requirements of the studied trees in the different studied governorates of Gaza Strip.

Figure 5.13: Palm trees irrigation requirements in Khan Younis governorate. Figure 5.14: Grape trees irrigation requirements in Khan Younis governorate.

Figure 5.15: Citrus trees irrigation requirements in Gaza governorate. Figure 5.16: Citrus trees irrigation requirements in Dair Al-Balah governorate.

Annexes

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Annex (4-C): CropWat results for the irrigation requirements of the studied trees in the different studied governorates of Gaza Strip.

Figure 5.17: Guava trees irrigation requirements in Dair Al-Balah governorate. Figure 5.18: Guava trees irrigation requirements in Khan Younis governorate.

Annexes

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Annex (5): Irrigation requirements in cubic meter per dunom for the studied orchards in the different governorates in Gaza Strip.

TTrreeeess

Irrigation requirements per (1,000 m2)

T Ave. T + 1 T + 2 T Ave. T + 1 T + 2 T Ave. T + 1 T + 2

P Ave.

P Ave.

P Ave.

P – 5%

P – 5%

P – 10%

P – 10%

P – 10%

P – 10%

Olive, Gaza 544 544 548 560 562 565 577 579 583

Olive, Middle 542 543 547 559 561 565 577 579 582

Olive, K Y 541 543 547 559 561 564 577 579 582

Palm, Middle 1004 1041 1081 1015 1053 1092 1037 1075 1115

Palm, K Y 1039 1079 1118 1050 1089 1129 1072 1111 1150

Grape 584 606 627 590 611 633 602 623 645

Citrus Valencia &Lemon, Gaza 657 675 697 657 679 701 667 689 713

Citrus Valencia &Lemon, Middle 654 676 700 659 682 706 672 696 720

Guava, Middle 1032 1067 1101 1037 1071 1106 1045 1080 1114

Guava, K Y 1040 1075 1110 1044 1079 1113 1052 1087 1121

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