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Resolution and Sensitivity Analysis of a Block-Scale Urban Drainage Model

机译:大规模城市排水模型的分辨率和灵敏度分析

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The complexity of the urban watershed requires engineers to use computer models for water planning purposes. A widely-used industry standard model is the U.S. EPA Stormwater Management Model (SWMM) which predicts flow rates from watersheds characterized by the modeler in terms of both their hydrologic and hydraulic characteristics. To cost effectively model large urban areas within the time and budget constraints, engineers simplify the watershed domain of the model by aggregating subcatchments and conduit skeletonization. The process of selecting model inputs introduces uncertainty into SWMM predictions. Other sources of uncertainty include the mathematical equations used to represent the flow process, the measurement error associated with physical parameters in the field, and the determination of non-physical parameters. This study evaluates the sensitivity of user-specified subcatchment characteristics in predicting total volumetric runoff and peak runoff flow in SWMM. The model variables were adjusted according to a Monte Carlo simulation using a uniform distribution for the input parameters. The sensitivity of parameters will determine the criteria for calibrating the model and for representing low-impact development techniques.
机译:城市流域的复杂性要求工程师使用计算机模型进行水规划。美国EPA暴雨水管理模型(SWMM)是一种广泛使用的行业标准模型,该模型可以根据流域的水文和水力特征预测由建模者表征的流域的流量。为了在时间和预算限制内以经济有效的方式对大型城市区域进行建模,工程师通过汇总子汇水面积和管道骨架化来简化模型的分水岭范围。选择模型输入的过程将不确定性引入到SWMM预测中。其他不确定性来源包括用于表示流动过程的数学方程式,与现场物理参数相关的测量误差以及非物理参数的确定。这项研究评估了用户指定的子汇水特征在预测SWMM中总体积径流量和峰值径流量方面的敏感性。根据蒙特卡洛模拟,使用均匀分布的输入参数来调整模型变量。参数的敏感性将确定校准模型和代表低影响开发技术的标准。

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