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

机译:通过耦合调度相关多变量降雨与水库效应指标的影响,评估水库对下游洪水频率的影响

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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.
机译:许多研究表明,下游洪水制度因上游储层操作而显着改变。通常通过比较某些流流量指示器(例如洪水和干旱)的坝体和坝后频率进行下游流动制度对下游流动制度的储层效应。在这项研究中,开发了一种降雨 - 储层复合指数(RRCI),以便在使用贝叶斯推理方法的基于协变量的非间断泛频分析框架下精确地量化储层对下游洪水频率的影响。 RRCI源自储层指数(RI)的组合来测量储层储存能力和降雨指数的影响。更确切地说,更精确地(基于或运算符的可能的联合事件的类型)超出某些调度相关变量的概率(OR-JEP),其中包含了描述了多个变量的五个变量,这些变量用于描述多日期前进的降雨输入(MARI)的变量衡量前进降雨对水库运作的影响。然后,RI依赖性或依赖于RRCI依赖的分布参数和五个分布,伽玛,威布尔,伐木,Gumbel和广义极值,用于分析Ankang,Huangjiagang和Huangzhuang的年度最大日常流量(AMDF)汉江,中国的衡量站。观察到一种现象,但虽然储层下游的大部分洪水的大部分都是由上游水库减少,但仍然发生了一些相对较大的洪水事件,例如在1983年的黄庄站。非间断洪水频率分析的结果展示与RI相比,结合RI和OR-JEP的RRCI导致了对储层下游的洪水发生现象的更好的解释。 AMDF的100年返回水平的贝叶斯推断表明,与RI依赖性相比,最佳RRCI依赖性分布导致相对较小的估计值。但是,由于一些低或JEP值,存在异常。此外,它还提供较小的不确定性范围。本研究突出了包括在水库储存能力的影响外,储层储存能力的储存能力的必要性,以评估水库对下游洪水频率的影响。该分析可以在水库的影响下提供更全面的下游洪水风险管理方法。

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