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Uncertainty analysis of the influence of rainfall time resolution in the modelling of urban drainage systems

机译:降雨时间分辨率对城市排水系统建模影响的不确定性分析

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摘要

In urban drainage modelling, rainfall temporal variability can be considered as one of the most critical knowledge elements when dealing with rainfall-runoff models input data. The rainfall data temporal resolution usually available for practical applications is often lower than that requested for the rainfall-runoff simulation in urban areas, greatly compromising model accuracy. The present paper evaluates the influence of rainfall temporal resolution on the uncertainty of the response of rainfall-runoff modelling in urban environments. Analyses have been carried out using historical rainfall-discharge data collected for about 10 years in Parco d'Orleans experimental catchment (Palermo, Italy). The historical rainfall data have been taken as a reference rainfall, and resampled data have been obtained through a rescaling procedure with variable temporal windows. The shape comparison between 'true' and rescaled rainfall data has been carried out using a non-dimensional performance index. Monte Carlo simulations have been carried out, applying two different rainfall-runoff models, using the recorded data and the resampled events. The results of the simulations were used to derive, for both models, the cumulative probabilities of peak discharges conditioned on the observation according to the GLUE (Generalized Likelihood Uncertainty Estimation) methodology.
机译:在城市排水模型中,当处理降雨-径流模型输入数据时,降雨时间变化可以被认为是最关键的知识要素之一。通常可用于实际应用的降雨数据时间分辨率通常低于城市地区降雨径流模拟所需的分辨率,从而极大地影响了模型的准确性。本文评估了降雨时间分辨率对城市环境中降雨径流模拟响应不确定性的影响。使用在奥尔科斯帕尔科实验流域(意大利巴勒莫)收集了大约10年的历史降雨-流量数据进行了分析。历史降雨量数据已作为参考降雨量,并且通过具有可变时间窗的重新缩放过程获得了重新采样的数据。 “真实”和重新定标的降雨数据之间的形状比较已使用无量纲的性能指标进行了。使用记录的数据和重采样的事件,应用两个不同的降雨径流模型进行了蒙特卡洛模拟。模拟的结果用于根据GLUE(广义似然不确定性估计)方法,以观测为条件,为两个模型得出峰值放电的累积概率。

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