An Assessment of the Rainfall Change Scenarios Projection Until 2050 -A Case Study of Iraq
An Assessment of the Rainfall Change Scenarios Projection Until 2050 -A Case Study of Iraq
Fadia W. Al-Azawi1* , Huda M. Hamid2, Husam Jasim Mohammed1 and Jan Muhammad3
ABSTRACT
The decrease in precipitation is the foremost noteworthy perspective within the period of climate inconstancy. Information was utilized for surveying precipitation alter scenarios in the whole of Iraq amid the period (1951-2020), at that point predicate, the alter until 2050. The PRECIS Regional Climate Model (RCM) is utilized to simulate the current time period from 1951 to 2020, as well as a future time period from 2021 to 2050. The model operates at a spatial resolution of 25 x 25 km. The RCM can provide timely and appropriate forecasts for usage in rainfall scenarios. The study aim to prepare maps to predicate rainfall changes in the twenty-two stations over a wide range of Iraq. Rainfall data for 100 years from 1951-2050 were analyzed and annual rainfall amounts predicated to measure the amount of rainfall in the Region of Interest (ROI) in the next years. The data and extraction process runs through various techniques by analyzing data statistically using SPSS and interpolation techniques using GIS. In this study, IDW estimated the rainfall distribution in the ROI. Furthermore, to obtain optimal interpolation rainfall data, root mean squared error value for Kriging, and IDW was measured. The results showed that IDW interpolation for rainfall data can obtain more accurate results; a smaller RMSE is due to an accurate method; and the better kriging method should produce a smaller value. It is used for evaluating the goodness of a prediction interpolation task. To obtain a more precise picture of the scenarios for changing rainfall, the analysis was performed in most districts of Iraq. Dry seasons yield more reliable results than flood seasons. High correlation coefficients above 0.95 validated IDW for spatial interpolation to predict ROI rainfall data.
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