climate change on UAE - Stockholm Environment Institute-US Center

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4. Quantitative <strong>climate</strong> impact assessment of water resources Observed water supply and demand data summarized in Sections 2 and 3 were used as the physical basis to develop a water resource planning model to broadly characterize future projections of water use and supply, calibrated with historic data. This model, constructed using the Water Evaluation and Planning (WEAP) platform, broadly represents the regional supply characteristics described in Section 2.1 (e.g. Regional fossil supplies in the West, including Liwa), Central (Abu Dhabi City), and East (Al Ain Oasis), limited renewable freshwater supplies in the east near Al Ain, and both existing and future desalinzation that supply both coastal and inland demands, as well as municipal waste water reclaimed and used again primarily for amenity (gardens and parks) uses. The water resource model explicitly captures total water demands of the municipal/ industrial (M&I) sectors based on estimates of population and per capita use, which together comprise domestic indoor uses such as bathing, toilet flushing, washing, and water for industrial production. This model simulates the observed growth in water demand by the domestic sector, with an increase in consumption of around 15% from 2002 to 2003 (e.g. 440 to 522 Million Cubic Meters, and the forestry sector from 510 to 607 Million Cubic Meters), and the small recorded reductions of 1% and 5% in the agriculture and amenity sectors, respectively. A smaller consumption in the agriculture sector is a result of a policy to reduce the area under irrigation in large state fodder farms; the 2002 irrigated area of 24,000 ha reduced to 17,000 ha in 2003. This WEAP model has the capability of including <strong>change</strong>s in cropped area and assumptions about irrigation and water use strategies, and thus the model should be capable of simulating the broad, observed water use patterns. Estimates of supplied water use for the years 2002, 2003, and 2005 were estimated at 3,200 MCM, 3,360 MCM, and 3,111 MCM respectively, and we apply the water resources model to simulate these uses, driven by both per capita use and <strong>climate</strong> driven irrigation demands. Outdoor water use was treated explicitly to account for the <strong>climate</strong> factors that drive irrigation demand, as higher temperatures, lower humidity and high wind speeds increase irrigation requirements of crops. These dynamics are included in order to estimate future irrigation demand under various <strong>climate</strong> <strong>change</strong> Scenarios. A crop water simulator based on United Nation Food and Agriculture (FAO) methods, was used to estimate monthly irrigation demand for the agricultural, forestry, and amenity sectors. The FAO method uses estimates of potential evapotranspiration and crop coefficients (Kc) to determine required irrigation requirements. In addition, we used estimates of acreage planted, irrigation efficiencies, and leaching requirements to derive estimates of monthly and annual irrigation demands that would closely match reported estimates. 4.1. The Water Evaluation and Planning (WEAP) model of Abu Dhabi Emirate The Water Evaluation and Planning (WEAP) model was used as the Decision Support System (DSS) for this study. WEAP is an integrated DSS platform designed to support water planning with consideration of both water supplies and multiple water demands characterized by spatially and temporally varying allocation priorities and supply preferences. Allocation priorities identify under conditions of scarce resources, which demands are supplied first before other competing demands. Supply Preferences identify the water source(s) that supply specific water demands. The WEAP representation of the Abu Dhabi Emirate water supplies and demands are presented in the figure below, with the inset Figure 4-1 showing the details of the model objects in and around Abu Dhabi, and will be used in the discussion below to describe some of WEAP’s functionality. WEAP employs a transparent set of model objects and procedures that can be used to analyze a full range of issues and uncertainties 102 Climate Change Impacts, Vulnerability & Adaptation
Table ‎4‐1. Irrigated Hectares (Ha) from GIS layers. Region Crop Ha E Forests (total) 88,749.92 E Amenity/Urban greening/ residential properties of palaces Al Ain (5814.39ha); Abu Dhabi (20,260ha) 26,074.29 (total) E Farms (total) 89,571.00 W Forests (total) 105,647.5421 W Amenity/Urban greening (total) 8580.59 W Hey/Fodder 2185.66 W Farms (total) 36,114.74 Impacts, Vulnerability & Adaptation for Water Resources in Abu Dhabi Figure ‎4‐1. A WEAP schematic of the Abu Dhabi Emirate. 103
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Acknowledgements The authors are de
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Foreword There are many levels at w
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Table of Contents (Part 2) Water Re
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9.2. Types of ecosystem models ....
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APF AML CARA CO 2 CReSIS CSI DEM EG
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Table ‎1‐1. Climate Change and
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2. Sea-level Rise Impacts on Coasta
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differences in observed sea levels
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Sea Level Change (mm) 20 15 10 5 0
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Impacts, Vulnerability & Adaptation
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Gulf is that the shallower depth al
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ago when sea level was a few meters
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Scientists have every reason to bel
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amongst others. Sea level rise may
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Figure ‎4‐2. Data displaying ar
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processed SRTM topographic dataset
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water height of each tidal day obse
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Table ‎4‐3. UAE Coastal Cities.
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Figure ‎4-10: 1 meters above mean
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Figure ‎4-12: 3 meters above mean
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as well as parts of the Industrial
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Page 53 and 54: framework that has relevance to the
Page 55 and 56: to be estimated reliably and hence
Page 57 and 58: 6. Conclusions and recommendations
Page 59 and 60: 7. List of References ADEA (2006)
Page 61 and 62: Assessment Report of the Intergover
Page 63 and 64: 8. Glossary Adaptation: Adjustment
Page 65 and 66: To calculate areas inundated by lan
Page 67 and 68: Annex 1: Elevation Data Sensitivity
Page 69 and 70: Annex 2: Inundation maps 3. Urban V
Page 71 and 72: Figure A2-3 3 meters sea level rise
Page 73: Figure A2-6 1,3,9 meters sea level
Page 77 and 78: Page Figure 4‐6. WEAP estimates o
Page 79 and 80: in storage occurs in the Liwa lens
Page 81 and 82: Figure‎ 2‐1. Percentage of tota
Page 83 and 84: Total installed capacity equals 648
Page 85 and 86: Without demand management strategie
Page 87 and 88: Impacts, Vulnerability & Adaptation
Page 89 and 90: Figure 3-1 Global average temperatu
Page 91 and 92: The CO 2 storylines include both
Page 93 and 94: of topography on the region’s pre
Page 97 and 98: Temperature Change (degrees C) Temp
Page 99 and 100: neglected infrastructure, regional
Page 101: and magnitude of the ENSO (Haines e
Page 105 and 106: including estimates of population a
Page 107 and 108: 4.4. Representing Irrigation Demand
Page 109 and 110: Table 4-5. Comparison of Historical
Page 111 and 112: 4.6. Scenarios and Key Assumptions
Page 113 and 114: Avg. Monthly Air Temperature - MOR
Page 115 and 116: Table ‎4‐8. Summary of scenario
Page 117 and 118: 5. Results and Discussion The <stro
Page 119 and 120: total water demand estimate at abou
Page 121 and 122: for the Optimistic and Pessimistic
Page 123 and 124: eport of the IPCC holds out hope th
Page 125 and 126: Table 6-1. Adaptation options for w
Page 127 and 128: CIA, (1990), Middle East Area Oil a
Page 129 and 130: Figure A1‐2. Map of Abu Dhabi key
Page 131 and 132: Data Sources And Assumptions We rel
Page 133 and 134: Table A1-3. continued Liwa- Hammim
Page 135 and 136: Table A2-1. Summary of 36 emission
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Page 143 and 144: List of Tables Page Table 3-1: Majo
Page 145 and 146: 2. Potential risks to dryland ecosy
Page 147 and 148: 4. Major terrestrial ecosystems in
Page 149 and 150: Peninsula in the north to close to
Page 151 and 152: 5. Important flora in Abu Dhabi Abu
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over a one third of the known speci
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6. Fauna of the terrestrial ecosyst
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include the urban development and i
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(Arnell, 1999; Milly et al., 2005).
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camels and other large herbivores i
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8. Biodiversity, ecosystem threshol
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Alternatively, established shrublan
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e functionally deficient. We projec
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Adaptation can be planned or it can
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is based on a theoretical understan
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species to adapt to a changing <str
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that remediation steps begin soon t
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10 References Adler, PB, DA Raff, W
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Nordad, (2007), Climate Change Fact
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Annex 2: Expected effects of global
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Annex 4: Main drivers of ecosystem
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Sn Species Scientific name Family S
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Sn Species Scientific name Family S
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Name of species/sub-species Habitat
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Annex 8: Native species list of ter
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The cover picture represents a Brid
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