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Probabilistic structure of storm surface runoff considering the dependence between average intensity and storm duration of rainfall events

机译:考虑平均强度与降雨事件的风暴持续时间之间的依赖关系的风暴面径流的概率结构

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摘要

The probabilistic nature of rainfall and surface runoff events forms the basis of hydrologic design. Two defining characteristics of rainfall events, average intensity and duration, are selected to construct the probabilistic structure of storms using Gumbel's bivariate exponential distribution. This bivariate stochastic rainfall model is then utilized to derive the probabilistic structure of surface runoff using the Soil Conservation Service rainfall runoff model. The zero-runoff probability, mean, and standard deviation of rainfall excess are evaluated. Copulas serve as an alternative way to derive zero-runoff probability. The results indicate that the dependence between average intensity and duration has a significant effect on statistical properties of rainfall excess. The advantage of using copulas for complicated multivariate stochastic models is demonstrated. The proposed model is associated with land use and soil type information from the geographic information system to produce maps of statistical properties of rainfall excess. A case study of model application is performed for the state of Indiana, United States. Results show that while the mean and standard deviation of rainfall excess increase with curve number, these quantities are very sensitive to the dependence between average intensity and duration of storm events.
机译:降雨和地表径流事件的概率性质构成了水文设计的基础。选择了两个降雨事件的定义特征,即平均强度和持续时间,以使用Gumbel的双变量指数分布来构造风暴的概率结构。然后,使用土壤保护局降雨径流模型,利用该双变量随机降雨模型来推导地表径流的概率结构。评估了零径流概率,降雨过量的平均值和标准偏差。 Copulas是推导出零径流概率的替代方法。结果表明,平均强度和持续时间之间的依赖性对降雨过剩的统计特性具有显着影响。证明了使用copulas处理复杂的多元随机模型的优势。所提出的模型与地理信息系统中的土地利用和土壤类型信息相关联,以产生降雨过量统计特性的地图。在美国印第安纳州进行了模型应用的案例研究。结果表明,尽管降雨过量的平均值和标准偏差随曲线数增加,但这些数量对平均强度和风暴事件持续时间之间的依赖性非常敏感。

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