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Title: Nonlinear Filtering Effects of Reservoirs on Flood Frequency Curves at the Regional Scale

Journal Article · · Water Resources Research
DOI:https://doi.org/10.1002/2017WR020871· OSTI ID:1411920
ORCiD logo [1];  [2]; ORCiD logo [3];  [4]; ORCiD logo [5]; ORCiD logo [6];  [3]; ORCiD logo [7];  [8]
  1. Tsinghua Univ., Beijing (China); Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  2. Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Montana State Univ., Bozeman, MT (United States)
  3. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  4. Montana State Univ., Bozeman, MT (United States)
  5. Tsinghua Univ., Beijing (China)
  6. Tsinghua Univ., Beijing (China); Joint Center for Global Change Studies, Beijing (China)
  7. Washington State Univ., Pullman, WA (United States)
  8. Vienna Univ. of Technology, Vienna (Austria)
+ Show Author Affiliations

Anthropogenic activities, e.g., reservoir operation, 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 the nonlinear filtering effects of reservoirs on the FFCs over the contiguous United States. 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 with an average record length of 50 years. The first two moments of the FFC, mean annual maximum flood (MAF) and coefficient of variations (CV), are calculated for the pre- and post-dam periods and compared to elucidate the reservoir regulation effects as a function of RII. 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. The processes underlying the nonlinear threshold behavior of MAF and CV are investigated using three reservoir models with different levels of complexity. All models capture the non-linear relationships of MAF and CV with RII, suggesting that the basic flood control function of reservoirs is key to the non-linear relationships. The relative roles of reservoir storage capacity, operation objectives, available storage prior to a flood event, and reservoir inflow pattern are systematically investigated. Our findings may help improve flood-risk assessment and mitigation in regulated river systems at the regional scale.

Research Organization:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER); National Basic Research Program of China; National Natural Science Foundation of China (NSFC); Austrian Science Funds FWF; ERC Flood Change Project
Grant/Contract Number:
AC05-76RL01830; 2015CB953703; 91537210; 41371328; 291152
OSTI ID:
1411920
Report Number(s):
PNNL-SA-125216; KP1703030; KP1703010
Journal Information:
Water Resources Research, Vol. 53, Issue 10; ISSN 0043-1397
Publisher:
American Geophysical Union (AGU)Copyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 24 works
Citation information provided by
Web of Science

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Cited By (1)

Assessing the impacts of reservoirs on downstream flood frequency by coupling the effect of scheduling-related multivariate rainfall with an indicator of reservoir effects journal January 2019

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58 GEOSCIENCES
reservoir regulation
flood frequency curve
threshold behavior