الفهرس 
IntroductionOnly 14 pages are availabe for public view
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Abstract
The North Western Coast Zone (NWCZ) is one of the most promising areas for development, so that, strategic plans should be established. Since rainfall is the main fresh water source in that area, it is important to check its spatial and temporal distributions, which are highly required for hydrologic applications. In this research, three climate models with resolution of 50×50 km called “EC-EARTH13, CNRM-CM514, and GFDL-ESM2M15” have been compared and corrected with 25 years measured historical rainfall data of five gauging stations. To test the performance of the regional models (REGs) against the historical rainfall data, some quantitative statistics have been used such as Nash-Sutcliffe efficiency (NSE), percent bias (PBIAS), the ratio of the root mean square error to the standard deviation of measured data (RSR), probability density function (PDF), precipitation concentration index (PCI), and the cumulative distribution function (CDF). The results revealed that EC-EARTH13 model is the most appropriate one at all stations, due to quantitative statistics indices values. The selected model that produces accurate precipitation has been applied in the near future period (2006 to 2018) for two representative concentrations pathway scenarios (RCP 4.5 and RCP 8.5) relative to the observed data to verify the suitability of using the model in the rainfall future prediction at the region. Since it is required to reduce the uncertainty of the selected model, two bias correction methods were applied on monthly rainfall data; Linear Scaling Method as a simple method and Power Transformation Method, as a complex correction technique, taking into consideration the usage of gridded satellite data as a base data for correction. One of the most approved gridded rainfall data is the Climate Hazards group Infra-Red Precipitation with Station data (CHIRPS) with resolution of 0.05̊ ×0.05̊ , which proved a good performance comparing with the observed data. The power transformation method (PT) showed a good performance over linear scaling method. (PT) method parameters have been estimated to facilitate future applications. The future simulated period (2021 to 2100) is divided into two periods; the Mid-century (2021-2060) and Far-century (2061-2100) for the two scenarios RCP 4.5 and RCP 8.5. To evaluate possible future changes in runoff depth under the two scenarios.