Evaluation of Geospatial Interpolation Techniques for Enhancing Spatiotemporal Rainfall Distribution and Filling Data Gaps in Asir Region, Saudi Arabia

Ahmed M. Helmi (), Mohamed Elgamal, Mohamed I. Farouk, Mohamed S. Abdelhamed and Bakinam T. Essawy
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Ahmed M. Helmi: Irrigation and Hydraulics Department, Faculty of Engineering, Cairo University, Giza 12613, Egypt
Mohamed Elgamal: Civil Engineering Department, College of Engineering, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 13318, Saudi Arabia
Mohamed I. Farouk: Civil Engineering Department, College of Engineering, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 13318, Saudi Arabia
Mohamed S. Abdelhamed: Global Institute for Water Security, University of Saskatchewan, Saskatoon, SK S7N 3H5, Canada
Bakinam T. Essawy: Civil and Infrastructure Engineering and Management Department, Nile University, Sheikh Zayed City 12588, Egypt

Sustainability, 2023, vol. 15, issue 18, 1-32

Abstract: Providing an accurate spatiotemporal distribution of rainfall and filling data gaps are pivotal for effective water resource management. This study focuses on the Asir region in the southwest of Saudi Arabia. Given the limited accuracy of satellite data in this arid/mountain-dominated study area, geospatial interpolation has emerged as a viable alternative approach for filling terrestrial records data gaps. Furthermore, the irregularity in rain gauge data and the yearly spatial variation in data gaps hinder the creation of a coherent distribution pattern. To address this, the Centered Root Mean Square Error (CRMSE) is employed as a criterion to select the most appropriate geospatial interpolation technique among 51 evaluated methods for maximum and total yearly precipitation data. This study produced gap-free maps of total and maximum yearly precipitation from 1966 to 2013. Beyond 2013, it is recommended to utilize ordinary Kriging with a J-Bessel semivariogram and simple Kriging with a K-Bessel semivariogram to estimate the spatial distribution of maximum and total yearly rainfall depth, respectively. Additionally, a proposed methodology for allocating additional rain gauges to improve the accuracy of rainfall spatial distribution is introduced based on a cross-validation error (CVE) assessment. Newly proposed gauges in the study area resulted in a significant 21% CVE reduction.

Keywords: geospatial interpolation; data gaps; kriging; optimum rainfall locations; arid region (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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