Assessing the Influence of a Bias Correction Method on Future Climate Scenarios Using SWAT as an Impact Model Indicator
نویسندگان
چکیده
In this study, we evaluate the implications of a bias correction method on combination Global/Regional Climate Models (GCM and RCM) for simulating precipitation and, subsequently, streamflow, surface runoff, water yield in Soil Water Assessment Tool (SWAT). The study area is Des Moines River Basin, U.S.A. climate projections are two RCMs driven by GCMs historical simulations (1981–2005) future (2030–2050). Bias improves annual volumes, seasonality, spatial distribution, mean error. Simulated monthly streamflow was compared across 26 monitoring stations with mostly satisfactory results percent (Pbias). There were no changes trends scenarios except raw WRF models. Seasonal variability remained same; however, most models predicted an increase from January to March reduction June July. Meanwhile, bias-corrected showed prediction signals. some cases, projected runoff yield, but these variables. This suggests may be larger than climate-change signal indicates procedure not small major factor.
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Introduction Conclusions References
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ژورنال
عنوان ژورنال: Water
سال: 2023
ISSN: ['2073-4441']
DOI: https://doi.org/10.3390/w15040750