Abstract
Abstract. Many studies have shown that downstream flood regimes have been significantly altered by upstream reservoir operation. Reservoir effects on the downstream flow regime are normally performed by comparing the pre-dam and post-dam frequencies of certain streamflow indicators, such as floods and droughts. In this study, a rainfall–reservoir composite index (RRCI) is developed to precisely quantify reservoir impacts on downstream flood frequency under a framework of a covariate-based nonstationary flood frequency analysis using the Bayesian inference method. The RRCI is derived from a combination of both a reservoir index (RI) for measuring the effects of reservoir storage capacity and a rainfall index. More precisely, the OR joint (the type of possible joint events based on the OR operator) exceedance probability (OR-JEP) of certain scheduling-related variables selected out of five variables that describe the multiday antecedent rainfall input (MARI) is used to measure the effects of antecedent rainfall on reservoir operation. Then, the RI-dependent or RRCI-dependent distribution parameters and five distributions, the gamma, Weibull, lognormal, Gumbel, and generalized extreme value, are used to analyze the annual maximum daily flow (AMDF) of the Ankang, Huangjiagang, and Huangzhuang gauging stations of the Han River, China. A phenomenon is observed in which although most of the floods that peak downstream of reservoirs have been reduced in magnitude by upstream reservoirs, some relatively large flood events have still occurred, such as at the Huangzhuang station in 1983. The results of nonstationary flood frequency analysis show that, in comparison to the RI, the RRCI that combines both the RI and the OR-JEP resulted in a much better explanation for such phenomena of flood occurrences downstream of reservoirs. A Bayesian inference of the 100-year return level of the AMDF shows that the optimal RRCI-dependent distribution, compared to the RI-dependent one, results in relatively smaller estimated values. However, exceptions exist due to some low OR-JEP values. In addition, it provides a smaller uncertainty range. This study highlights the necessity of including antecedent rainfall effects, in addition to the effects of reservoir storage capacity, on reservoir operation to assess the reservoir effects on downstream flood frequency. This analysis can provide a more comprehensive approach for downstream flood risk management under the impacts of reservoirs.
Highlights
River floods are generated by various complex nonlinear processes involving physical factors, including “hydrological pre-conditions, meteorological conditions, runoff generation processes, and river routing” (Wyzga et al, 2016)
Volpi et al (2018) suggested that for a single reservoir, the downstream flood peak reduction was primarily dependent on its position along the river, its spillway, and its storage capacity based on a parsimonious instantaneous unit-hydrograph-based model
The aim of the study is to develop an indicator, referred to as the rainfall–reservoir composite index (RRCI), that combines the effects of reservoir storage capacity and the multiday antecedent rainfall input (MARI) on reservoir operation
Summary
River floods are generated by various complex nonlinear processes involving physical factors, including “hydrological pre-conditions (e.g., soil saturation, snow cover), meteorological conditions (e.g., amount, intensity, and the spatial and temporal distribution of rainfall), runoff generation processes, and river routing (e.g., superposition of flood waves in the main river and its tributaries)” (Wyzga et al, 2016). The significant hydrological alterations caused by reservoirs have been demonstrated in the many areas of the world. Volpi et al (2018) suggested that for a single reservoir, the downstream flood peak reduction was primarily dependent on its position along the river, its spillway, and its storage capacity based on a parsimonious instantaneous unit-hydrograph-based model. These studies have revealed that it is crucial to assess the impacts of reservoirs on downstream flood regimes for the success of downstream flood risk management
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