Affiliation:
1. Guangdong Engineering Technology Research Center of Water Security Regulation and Control for Southern China, Sun Yat-sen University, Guangzhou 510275, China and Julie Ann Wrigley Global Institute of Sustainability, Arizona State University, Tempe, AZ 85287, USA
2. Institute of Estuarine and Coastal Research, School of Marine Sciences, Sun Yat-sen University, Guangzhou 510275, China
3. Chair of Hydrology and River Basin Management, Technical University of Munich, Arcisstrasse 21, 80333 Munich, Germany
Abstract
Abstract
In various conceptual models, the shape parameter (β) of the storage capacity curve, representing the non-linear relationship between relative soil moisture and runoff, determines runoff yield given certain circumstances of rainfall and antecedent soil moisture. In practice, β is typically calibrated for individual catchments and for different purposes, which limits more systematic understanding and also prediction in ungauged basins. Moreover, its regionalization and linkage to catchment characteristics is also not well understood, especially in relation to large-sample datasets. In this study, we used 404 catchments in the USA to explore β regionalization and attributes in relation to key catchment characteristics: elevation, slope, depth-to-bedrock, soil erodibility, forest cover, urban area, aridity index, catchment area, and stream density. We found a clear regionalized pattern of β, coherent with topography. Comparisons between β and various features demonstrated that slope has the largest impact. Land-cover, soil, geology, and climate also have an impact, but with lower correlation coefficients. This finding not only reveals spatial variation in β, but also deepens our understanding of its linkage to catchment features and flood flows. Moreover, the results provide a useful reference for decision-makers for flood prevention and mitigation.
Subject
Water Science and Technology
Cited by
17 articles.
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