Academic Journal
Revisiting the hydrological basis of the Budyko framework with the principle of hydrologically similar groups.
| Title: | Revisiting the hydrological basis of the Budyko framework with the principle of hydrologically similar groups. |
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| Authors: | Chen, Yuchan, Chen, Xiuzhi, Xue, Meimei, Yang, Chuanxun, Zheng, Wei, Cao, Jun, Yan, Wenting, Yuan, Wenping |
| Source: | Hydrology & Earth System Sciences; 2023, Vol. 27 Issue 9, p1929-1943, 15p |
| Abstract: | The Budyko framework is a simple and effective tool for estimating the water balance of watersheds. Quantification of the watershed-characteristic-related parameter (Pw) is critical for accurate water balance simulations with the Budyko framework. However, there is no universal method for calculating Pw as the interactions between hydrologic, climatic, and watershed characteristic factors differ greatly across watersheds. To fill this research gap, this study introduced the principle of hydrologically similar groups into the Budyko framework for quantifying the Pw of watersheds in similar environments. We first classified the 366 selected watersheds worldwide into six hydrologically similar groups based on watershed attributes, including climate, soil, and vegetation. Results show that soil moisture (SM) and fractional vegetation cover (FVC) are two controlling factors of the Pw in each group. The SM exhibits a power-law relationship with the Pw values, with increasing SM leading to higher Pw values in dry watersheds (SM ≤ 20 mm) and lower Pw values in humid watersheds (SM > 20 mm). Additionally, the FVC shows to be linearly correlated with the Pw values in most hydrologically similar groups, except in that group with moist soil and no strong rainfall seasonality (SM >20 mm and seasonal index (SI) ≤ 0.4). Multiple non-linear regression models between Pw and the controlling factors (SM and FVC) were developed to individually estimate the Pw of six hydrologically similar groups. Cross-validations using the bootstrap sampling method (R2=0.63) and validations of time-series Global Runoff Data Centre (GRDC) data (R2=0.89) both indicate that the proposed models perform satisfactorily in estimating the Pw parameter in the Budyko framework. Overall, this study is a new attempt to quantify the unknown Pw in the Budyko framework using the method for hydrologically similar groups. The results will be helpful in improving the applicability of the Budyko framework for estimating the annual runoff of watersheds in diverse climates and with different characteristics. [ABSTRACT FROM AUTHOR] |
| Subject Terms: | SERVER farms (Computer network management), NONLINEAR regression, EVIDENCE gaps, RAINFALL, SOIL moisture, WATERSHEDS |
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| ISSN: | 10275606 |
| DOI: | 10.5194/hess-27-1929-2023 |
| Database: | Complementary Index |
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