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Article

Land-Use and Land Cover Is Driving Factor of Runoff Yield: Evidence from A Remote Sensing-Based Runoff Generation Simulation

1
College of Urban and Environmental Sciences, Peking University, No. 5 Yiheyuan Road, Haidian District, Beijing 100871, China
2
Chemical Science College, Bordeaux University, UMR EPOC CNRS 5805, 33400 Talence, France
*
Author to whom correspondence should be addressed.
Academic Editors: Xuan Zhang and Xiran Li
Water 2022, 14(18), 2854; https://doi.org/10.3390/w14182854
Received: 18 July 2022 / Revised: 7 September 2022 / Accepted: 8 September 2022 / Published: 13 September 2022
The spatial distribution of water storage capacity has always been the critical content of the study of saturation-excess runoff. Xin’anjiang model uses the water storage capacity curve (WSCC) to characterize the distribution of water storage capacity for runoff yield calculation. However, the mathematical and physical foundations of WSCC are unclear, which is impossible to simulate runoff generation with complex basins accurately. To fill this gap, we considered the dominant role of basin physical characteristics in water storage capacity and developed a new integrated approach to solve the spatial distribution of water storage capacity (L-WSCC) to account for the spatiotemporal dynamics of their impact on runoff generation. The main contribution of L-WSCC was to confer WSCC more physical meaning and the spatial distribution of water storage capacity was explicitly represented more accurately, so as to better express the runoff generation and provide a new approach for runoff yield calculation in non-data basin. L-WSCC was applied to Misai basin in China and promising results had been achieved, which verified the rationality of the method (the mean Nash–Sutcliffe efficiency (NSE):0.86 and 0.82 in daily and hourly scale, respectively). Compared with WSCC, the performance of L-WSCC was improved (mean NSE: 0.82 > 0.78, mean absolute value of flood peak error (PE): 12.74% < 21.66%). Moreover, the results of local sensitivity analyses demonstrated that land-use and land cover was the major driving factor of runoff yield (the change of mean absolute error (ΔMAE): 131.38%). This work was significant for understanding the mechanisms of runoff generation, which can be used for hydrological environmental management and land-use planning. View Full-Text
Keywords: land-use; land cover; hydrological simulation; runoff generation; water storage capacity curve (wscc); hydrological environmental management land-use; land cover; hydrological simulation; runoff generation; water storage capacity curve (wscc); hydrological environmental management
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MDPI and ACS Style

Xu, C.; Fu, H.; Yang, J.; Gao, C. Land-Use and Land Cover Is Driving Factor of Runoff Yield: Evidence from A Remote Sensing-Based Runoff Generation Simulation. Water 2022, 14, 2854. https://doi.org/10.3390/w14182854

AMA Style

Xu C, Fu H, Yang J, Gao C. Land-Use and Land Cover Is Driving Factor of Runoff Yield: Evidence from A Remote Sensing-Based Runoff Generation Simulation. Water. 2022; 14(18):2854. https://doi.org/10.3390/w14182854

Chicago/Turabian Style

Xu, Chaowei, Hao Fu, Jiashuai Yang, and Chan Gao. 2022. "Land-Use and Land Cover Is Driving Factor of Runoff Yield: Evidence from A Remote Sensing-Based Runoff Generation Simulation" Water 14, no. 18: 2854. https://doi.org/10.3390/w14182854

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