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Fig 1.

Proposed site of the study.

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Fig 2.

Schematic representation of water system of Abu Dhabi.

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Fig 3.

Schematic representation of dynamic model (ADWBM).

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Table 1.

Sample values and data source of key model parameters.

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Table 2.

Optimized values of parameters after calibration.

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Fig 4.

Comparison of simulated results and historical (actual) data.

(A) Residential. (B) Agricultural. (C) Commercial. (D) Municipal. (E) Forestry (F) Amenities.

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Table 3.

Statistical analysis of calibration performance.

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Fig 5.

Results of BL simulation.

(A) Supply from different supply sources and trend of GW reserve over years. (B) Water demand in all sectors under the BL simulation for 2020 (first bars), 2030 (second bars), and 2050 (third bars). (C) Increasing trend of water deficit over years for BL simulation.

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Fig 6.

Results of CS simulation.

(A) Supply from different supply sources and trend of GW reserve over years. (B) Water demand in all sectors under the CS for 2020 (first bars), 2030 (second bars), and 2050 (third bars).

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Table 4.

Reductions needed in demand sectors for CS for achieving a BWB.

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Fig 7.

Required reductions in consumption at drivers’ level for major demand sectors in the CS simulation.

(A) Target reduction in residential sector. (B) Target reduction in commercial sector. (C) Target reduction in irrigation sectors (Agricultural and Forestry).

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Fig 8.

Sensitivity analysis-effect of drivers on residential demand.

(A) For year 2020. (B) For year 2030. (C) For year 2050.

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