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• W4385803510 abstract "Abstract Water resource management plays a crucial role in promoting sustainable development and protecting the environment. However, estimating evaporation rates in complex terrains, such as the Omo Gibe III Reservoir area, poses significant challenges due to limited data availability and the influence of natural formations on local weather patterns. To solve this problem Weather Research and Forecasting (WRF) model employed. The WRF model employs the European Centre for Medium-Range Weather Forecasts (ECMWF) Fifth generation of atmospheric reanalysis (ERA5) climate dataset to simulate key meteorological parameters. The simulation period covers 2014 to 2020, with a one-month spin-up period (December 1–30, 2013) to ensure model stability. To evaluate the model performance, various metrics such as Mean Squared Error (MSE), Nash-Sutcliffe Efficiency (NSE), Pearson correlation coefficient (r), Kling-Gupta Efficiency (KGE), and Mean Absolute Error (MAE) are employed. Reservoir evaporation is estimated by employing the mass transfer method and using WRF simulated meteorological variables. The findings highlight the WRF model-based estimatessuperiority over the MOD16 dataset, displaying lower MSE (85.22 versus 168.13) and higher NSE (0.91 versus 0.82), and signifying better agreement with observed evaporation patterns. Both models exhibit robust positive correlations with observed data (r: WRF − 0.97, MOD16–0.98), effectively capturing overall trends. The WRF model calculates a mean monthly average evaporation rate of 72.79 mm, which falls between Wolaita Station’s estimate (76.70 mm) and is lower than MOD16 (86.61 mm). The standard deviation values indicate that MOD16 exhibits the highest variability (36.67 mm), whereas the WRF model-based estimates(26.58 mm) and estimates of observed Station at Wolaita (30.91 mm) show comparatively lower variability, suggesting more consistent estimates. The research emphasizes the importance of the WRF model in estimating evaporation rates at Gibe III Reservoir, assisting in water allocation, reservoir operation, and environmental preservation. Furthermore, its applicability in climate resilience and sustainable development." @default.
• W4385803510 created "2023-08-15" @default.
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• W4385803510 date "2023-08-01" @default.
• W4385803510 modified "2023-09-27" @default.
• W4385803510 title "Estimating Reservoir Evaporation using Numerical Weather Prediction: A Case Study of the Gibe III Reservoir in Ethiopia" @default.
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• W4385803510 doi "https://doi.org/10.1088/2515-7620/acf02d" @default.
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