Accurate estimation of Potential Evapotranspiration (PET) is vital for monitoring agricultural needs, managing water resources, and assessing meteorological droughts. A recent study delves into the effects of dynamical downscaling and boundary layer schemes on simulated PET in Egypt using the RegCM4 regional climate model.
This research evaluates PET simulations over a 20-year period (1997-2017), employing calibrated versions of the Hargreaves-Samani equation alongside ERA5 high-resolution datasets. By exploring two different methods—direct downscaling and one-way nesting—the study investigates their influence on PET simulations under varying climatic scenarios. Boundary layer schemes such as HOLTSLAG and the University of Washington model were also analyzed to determine their impact on atmospheric variables that drive PET estimations.
Key findings reveal that PET simulations remain largely unaffected by either dynamical downscaling options or boundary layer schemes. Instead, the primary influencing factor for PET changes is global incident solar radiation (RSDS), followed by mean air temperature. Statistical evaluations demonstrated high correlation coefficients, low root mean square errors, and improved model performance when bias-correction methods like Linear Scaling were applied.
This study emphasizes the importance of accurately modeling PET to address water resource management challenges in arid and semi-arid regions like Egypt. By refining climate models and incorporating advanced bias-correction techniques, researchers can provide critical insights for sustainable agricultural planning and water conservation strategies.
Full Text: https://www.igminresearch.com/articles/html/igmin229
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