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Nonlinear Filtering Effects of Reservoirs on Flood Frequency Curves at the Regional Scale
Author(s) -
Wang Wei,
Li HongYi,
Leung L. Ruby,
Yigzaw Wondmagegn,
Zhao Jianshi,
Lu Hui,
Deng Zhiqun,
Demisie Yonas,
Blöschl Günter
Publication year - 2017
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1002/2017wr020871
Subject(s) - routing (electronic design automation) , flood myth , hydrology (agriculture) , environmental science , surface runoff , nonlinear system , streamflow , 100 year flood , dimensionless quantity , flood control , scale (ratio) , geology , drainage basin , geotechnical engineering , computer science , physics , mechanics , geography , computer network , cartography , archaeology , quantum mechanics , biology , ecology
Reservoir operations may alter the characteristics of Flood Frequency Curve (FFC) and challenge the basic assumption of stationarity used in flood frequency analysis. This paper presents a combined data‐modeling analysis of reservoir as a nonlinear filter of runoff routing that alters the FFCs. A dimensionless Reservoir Impact Index (RII), defined as the total upstream reservoir storage capacity normalized by the annual streamflow volume, is used to quantify reservoir regulation effects. Analyses are performed for 388 river stations in the contiguous U.S. using the first two moments of the FFC, mean annual maximum flood (MAF) and coefficient of variations (CV), calculated for the pre and post‐dam periods. It is found that MAF generally decreases with increasing RII but stabilizes when RII exceeds a threshold value, and CV increases with RII until a threshold value beyond which CV decreases with RII. Hence depending on the magnitude of RII, reservoir regulation acts as a filter to increase or reduce the nonlinearity of the natural runoff routing process and alters flood characteristics. The nonlinear relationships of MAF and CV with RII can be captured by three reservoir models with different levels of complexity, suggesting that they emerge from the basic flood control function of reservoirs. However, the threshold RII values in the nonlinear relationships depend on the more detailed reservoir operations and objectives that can only be captured by the more complex reservoir models. Our conceptual model may help improve flood‐risk assessment and mitigation in regulated river systems at the regional scale.