Optimizing Regional Climate Model Output for Hydro-Climate Applications in the Eastern Nile Basin

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1007/s41748-021-00222-9. This is version 4 of this Preprint.

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Authors

Mahmoud Osman , George Zittis, Mohammed AbouElHaggag, Ahmad W. Abdeldayem, Jos Lelieveld

Abstract

This study focuses on the Eastern Nile (EN) Basin, most of whose water flows into the High Aswan Dam (HAD), Egypt. It is, therefore, crucial to have an accurate hydrological assessment overtime to plan water resource management in the area. With complex topography, it is important to capture most of the physics captured with the least bias in meteorological information. Weather Research and Forecasting (WRF) model was configured for a nested domain centered over the EN basin with a parent domain defined over the larger Middle East–North Africa (MENA) region at 0.09 degrees and 0.44 degrees spatial resolution, respectively. The bias correction of the model is performed with associated meteorological parameters. WRF physics parameterization sensitivity experiments were carried out to select an optimum combination of physics schemes. The model skill was also examined by downscaling the ERA-Interim reanalysis dataset from 1980 to 2009 over the EN basin domain. The WRF performance was assessed using gridded observational datasets for precipitation and temperature output. The results revealed significant positive precipitation bias, especially over the highlands. The bias-corrected precipitation data is coupled to the semi-distributed hydrological rainfall-runoff—Soil and Water Assessment Tool (SWAT)—model, previously configured for the Baro-Akobo-Sobat sub-basin. The simulated flow hydrograph based on bias-corrected WRF simulations enhanced high correlations and Nash–Sutcliffe Efficiency coefficients (from 0.61 to 0.79) for the observed flow hydrographs, hence improved hydrologic simulations. Results indicated that the bias-corrected precipitation fields from WRF can contribute to improved hydrological impact assessments.

DOI

https://doi.org/10.31223/osf.io/fx7aw

Subjects

Civil and Environmental Engineering, Climate, Earth Sciences, Engineering, Hydrology, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics

Keywords

bias correction, WRF, Dynamic downscaling, Eastern Nile Basin, Precipitation patterns

Dates

Published: 2019-06-18 13:16

Last Updated: 2022-02-02 17:02

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License

CC BY Attribution 4.0 International

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