Article written by Mahmoud A. Abd El-Basir, Yasser Hamed, Tarek Selim, Ronny Berndtsson, Ahmed M. Helmi.
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Abstract:
Arid mountainous regions are vulnerable to extreme hydrological events such as floods
and droughts. Providing accurate and continuous rainfall records with no gaps is crucial
for effective flood mitigation and water resource management in these and downstream
areas. Satellite data and geospatial interpolation can be employed for this purpose and to
provide continuous data series. However, it is essential to thoroughly assess these methods
to avoid an increase in errors and uncertainties in the design of flood protection and water
resource management systems. The current study focuses on the mountainous region in
northern Oman, which covers approximately 50,000 square kilometers, accounting for 16%
of Oman’s total area. The study utilizes data from 279 rain gauges spanning from 1975 to
2009, with varying annual data gaps. Due to the limited accuracy of satellite data in arid
and mountainous regions, 51 geospatial interpolations were used to fill data gaps to yield
maximum annual and total yearly precipitation data records. The root mean square error
(RMSE) and correlation coefficient (R) were used to assess the most suitable geospatial
interpolation technique. The selected geospatial interpolation technique was utilized to
generate the spatial distribution of annual maxima and total yearly precipitation over the
study area for the period from 1975 to 2009. Furthermore, gamma, normal, and extreme
value families of probability density functions (PDFs) were evaluated to fit the rain gauge
gap-filled datasets. Finally, maximum annual precipitation values for return periods of
2, 5, 10, 25, 50, and 100 years were generated for each rain gauge. The results show that
the geostatistical interpolation techniques outperformed the deterministic interpolation
techniques in generating the spatial distribution of maximum and total yearly records over
the study area.