Bakinam T. Essawy’s research while affiliated with Nile University and other places

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Publications (1)


The KSA’s location and topography.
Average annual rainfall over the KSA, adopted from Helmi and Abdelhamed (2023) [29].
(A) The collected 128 rainfall gauges’ locations, (B) types of available rainfall gauges, (C) the selected rainfall gauges for the current study, and (D) elevations of the selected rain gauges.
Temporal variation in available rain gauge data in the study area.
Taylor diagram depicting total rainfall interpolation models for the year 1998.

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Evaluation of Geospatial Interpolation Techniques for Enhancing Spatiotemporal Rainfall Distribution and Filling Data Gaps in Asir Region, Saudi Arabia
  • Article
  • Full-text available

September 2023

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118 Reads

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13 Citations

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Mohamed Elgamal

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Bakinam T. Essawy

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.

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Citations (1)


... This requires a careful analysis to choose the suitable sites for wind farms and study the factors affecting them to obtain the highest productivity [5]. Türkiye is one of the countries that seek to invest heavily in the field of sustainable energy, and its wind energy production increased from 1375.80 MW in 2010 to 11,101.82 MW by January 2022, indicating significant growth, especially after adding 1797 MW between 2020 and 2021, which made Türkiye take its place in the global renewable energy ranking. ...

Reference:

Wind farm sites selection using a machine learning approach and geographical information systems in Türkiye
Evaluation of Geospatial Interpolation Techniques for Enhancing Spatiotemporal Rainfall Distribution and Filling Data Gaps in Asir Region, Saudi Arabia