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Forecasting Future Precipitation in Basrah City, Iraq Using the Statistical Downscaling Model (SDSM)
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Accurate rainfall predicting has become for securing managing water resources, chiefly in light of escalating climate crises. Basrah is among the Iraqi cities most vulnerable to these changes, as climate fluctuations are clearly impacting water availability and hydrological sustainability indicators in the region. The results of this study, through using the Statistical Downscaling Model (SDSM), indicate that the future precipitation was predicted for Basrah Governorate/Iraq up to 2085. Future precipitation projections were developed under group of Representative Concentration Pathway (RCP) scenarios which RCP (2.6, 4.5, and 8.5). The CanESM2 global climate model was used to generate large-scale atmospheric predictors for the statistical downscaling process, and daily precipitation from the Hay Al-Hussein meteorological station in Basrah were used for the period 1980–2025. The model was calibrated to find the optimal parameters for the period 1980 to 2012 and then verified for the period 2013–2025. In calibration, the coefficient of determination (R2) and the Nash-Sutcliffe efficiency (NSE) were 0.905 and 0.810, respectively. However, in validation, values of R2 and NSE were 0.874 and 0.844, respectively. These values confirm reliability model. The results indicated that a decrease in annual precipitation was noticed for the three future scenarios for three periods: 2035s, 2055s, and 2075s. The outputs of the model can be utilized for sustainable water resource planning for Basrah Governorate.
University of Warith Al-Anbiyaa - DIGITAL COMMONS JOURNALS
Title: Forecasting Future Precipitation in Basrah City, Iraq Using the Statistical Downscaling Model (SDSM)
Description:
Accurate rainfall predicting has become for securing managing water resources, chiefly in light of escalating climate crises.
Basrah is among the Iraqi cities most vulnerable to these changes, as climate fluctuations are clearly impacting water availability and hydrological sustainability indicators in the region.
The results of this study, through using the Statistical Downscaling Model (SDSM), indicate that the future precipitation was predicted for Basrah Governorate/Iraq up to 2085.
Future precipitation projections were developed under group of Representative Concentration Pathway (RCP) scenarios which RCP (2.
6, 4.
5, and 8.
5).
The CanESM2 global climate model was used to generate large-scale atmospheric predictors for the statistical downscaling process, and daily precipitation from the Hay Al-Hussein meteorological station in Basrah were used for the period 1980–2025.
The model was calibrated to find the optimal parameters for the period 1980 to 2012 and then verified for the period 2013–2025.
In calibration, the coefficient of determination (R2) and the Nash-Sutcliffe efficiency (NSE) were 0.
905 and 0.
810, respectively.
However, in validation, values of R2 and NSE were 0.
874 and 0.
844, respectively.
These values confirm reliability model.
The results indicated that a decrease in annual precipitation was noticed for the three future scenarios for three periods: 2035s, 2055s, and 2075s.
The outputs of the model can be utilized for sustainable water resource planning for Basrah Governorate.
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