ABSTRACT

Management of flood risk remains a major problem in many urban environments. To generate the data needed for estimation of the flood risk, catchment models have been used with the reliability of the predicted catchment response for design flood estimation dependent upon the model calibration. However, the level of calibration required to achieve reliable design flood estimation remains unspecified. The purpose of this paper is to assess the event modelling accuracy needed if data from the calibrated model are to be used for continuous simulation of data for flood frequency analysis. For this purpose, a SWMM-based catchment model was investigated using 25 monitored events, while the assessment of the calibration was based on a normalised peak flow error. Alternative sets of parameter values were used to obtain estimates of the peak flow for each of the selected events. The best performing sets of these sets of parameter values were used with SWMM in a continuous simulation mode to predict flow sequences for extraction of Annual Maxima Series for an At-Site Flood Frequency Analysis. From the analysis of these At-Site Flood Frequency Analyses, it was concluded that the normalised peak flow error needed to be less than 10% if reliable design flood quantile estimates were to be obtained.

摘要

在许多城市环境中，洪水风险管理仍然是一个主要问题。为了生成估计洪水风险所需的数据，已使用集水模型，预测集水响应的可靠性取决于模型校准，用于设计洪水估计。然而，实现可靠的设计洪水估计所需的校准水平仍未明确。如果将校准模型的数据用于洪水频率分析的数据连续模拟，本文的目的是评估所需的事件建模精度。为此，使用 25 个监测事件研究了基于 SWMM 的集水模型，而校准的评估基于标准化的峰值流量误差。使用替代参数值集来获得每个选定事件的峰值流量的估计值。这些参数值集的最佳性能集在连续模拟模式中与 SWMM 一起使用，以预测流量序列，以提取年度最大值序列以进行现场洪水频率分析。从这些现场洪水频率分析的分析中得出的结论是，如果要获得可靠的设计洪水分位数估计，则归一化峰值流量误差需要小于 10%。