停车场的连续水文建模及PCSWMM的相关最佳管理实践

Robson L. Pachaly, Don Guy V.V. Biessan, Jose G. Vasconcelos, Frances C. O’Donnell, Benjamin F. Bowers
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引用次数: 0

摘要

透水路面是一种绿色基础设施雨水管理实践,可以作为场地设计的功能组成部分。然而,先前的实地研究表明,用于进行透水路面水文计算的参数具有很高的不确定性。PCSWMM软件包中的环境保护局(EPA)暴雨水管理模型(SWMM)用于模拟奥本州一个停车场的水文动力学,该停车场覆盖25%的渗透性联锁混凝土摊铺机。该模型根据路面系统向生物保持盆地出口的两点的水位和附近气象站的降雨数据进行了校准。在SWMM中使用曲线数(CN)方法可以通过校准模型很好地预测路面流出量,除了降水数据覆盖的问题外,R2和Nash - Sutcliffe模型的效率均大于0.8。这表明,可渗透路面可以建模为土地覆盖类型,而不是滞留存储。透水路面的径流CN的校准值为60,远低于研究地点下垫土壤类型(水文土壤b组)的许多设计指南中推荐的值。基于对备选模型情景的评估,透水路面在对比降雨事件中减少了11‐38%的径流。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Continuous Hydrologic Modeling of a Parking Lot and Related Best Management Practices with PCSWMM

Permeable pavements are a green infrastructure stormwater management practice that can serve as a functional component of the site design. However, previous field studies suggest high uncertainty in the parameters used for performing hydrologic calculations for permeable pavements. The Environmental Protection Agency (EPA) Storm Water Management Model (SWMM) within the PCSWMM software package was used to simulate the hydrologic dynamics of a parking lot that is 25% covered with permeable interlocking concrete pavers in Auburn, AL. The model was calibrated to field observations of water level at two points where the pavement system outflows to a bioretention basin and rainfall data from a nearby weather station. The use of the Curve Number (CN) method within SWMM resulted in good prediction of pavement outflow by the calibrated model, with R2 and Nash-Sutcliffe model efficiency both greater than 0.8, except where issues with precipitation data coverage occurred. This demonstrates that permeable pavements can be modeled as a land cover type rather than as detention storage. The calibrated value of the runoff CN for permeable pavement was 60, much lower than what is recommended in many design guidelines for the underlying soil type at the research site, which is hydrologic soil group B. Based on evaluation of alternative model scenarios, the permeable pavement reduced runoff by 11-38% across contrasting rain events.

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