Soil water index;
Soil moisture;
Recession flow;
Recession coefficient;
Flow variability;
River flow regime;
DRAINABLE WATER STORAGE;
SPATIAL VARIABILITY;
PARAMETERS;
PATTERNS;
CLIMATE;
QUANTIFICATION;
VALIDATION;
DERIVATION;
MODELS;
INDEX;
D O I:
10.1016/j.scitotenv.2020.143469
中图分类号:
X [环境科学、安全科学];
学科分类号:
08 ;
0830 ;
摘要:
Hydrograph recessions, usually described through a power-law function of river flows, are among the most widely utilized hydrological signatures. Whereas theories explaining the genesis of recession exponents have been recently developed, ongoing discussions on the physical meaning and suitable proxies of recession coefficients suggest their linkage to soil moisture states of whole river basins. This work investigates the possibility to explain hydrograph recession coefficients by means of satellite-derived soil moisture products such as the Soil Water Index of Copernicus Global Land Service. Analyses of basin-averaged Soil Water Index, computed for eleven river basins from the Central and Eastern United States with varied climates and landscapes, reveal the existence of an inverse relation between mean soil moisture and its variability in time, and provide a glance into the variability of river flows. A visible signature of satellite-derived soil moisture conditions on the values of the recession coefficient as well emerges when statistics of the Soil Water Index are paired with recession properties obtained by means of hydrograph recession analysis. In particular, drier river basins characterized by larger soil moisture variability tend to exhibit larger and more variable recession coefficients. These results suggest reliability of existing conjectures about the role of soil moisture for determining recession properties, and indicate that satellite-derived products can inform understanding of the intrinsic variability of the hydrologic response in river basins. (C) 2020 The Author(s). Published by Elsevier B.V.
机构:
School of Civil and Environmental Engineering, University of New South Wales, Sydney, 2052, NSWSchool of Civil and Environmental Engineering, University of New South Wales, Sydney, 2052, NSW
Kim S.
Zhang R.
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机构:
School of Civil and Environmental Engineering, University of New South Wales, Sydney, 2052, NSW
School of Engineering Systems and Environment, University of Virginia, Charlottesville, 22904, VASchool of Civil and Environmental Engineering, University of New South Wales, Sydney, 2052, NSW
Zhang R.
Pham H.
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机构:
School of Civil and Environmental Engineering, University of New South Wales, Sydney, 2052, NSW
The University of Danang, University of Science and Technology, 54 Nguyen Luong Bang, Da NangSchool of Civil and Environmental Engineering, University of New South Wales, Sydney, 2052, NSW
Pham H.
Sharma A.
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机构:
School of Civil and Environmental Engineering, University of New South Wales, Sydney, 2052, NSWSchool of Civil and Environmental Engineering, University of New South Wales, Sydney, 2052, NSW