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A diagnostic decision support system for selecting best management practices in urban/suburban watersheds.

机译:一种诊断决策支持系统,用于选择城市/郊区流域的最佳管理方法。

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摘要

Best Management Practices (BMPs) have become the most effective way to mitigate the non-point source pollution (NPS) problems. Much attention has been paid on NPS in rural areas, where agricultural activities increase the nutrients, toxics, and sediments in surface water. Urban and suburban areas are also major contributors of NPS, largely due to stormwater. For watersheds bearing various soil types and land uses, a single type of BMP cannot be the panacea to all stormwater and related water quality problems. There is a need for a series of spatially distributed small-scale BMPs aimed at reducing flow volume and improving urban stormwater quality. This research seeks to develop a Diagnostic Decision Support System (DDSS) for urban BMP selection. The process-based distributed hydrologic model, Soil and Water Assessment Tool (SWAT), was used to simulate the hydrologic processes, estimate water quality variables, and to model the urban BMPs. The DDSS consists of three parts: a Hotspot Identifier, which locates the water quality and quantity hotspots; a Diagnostic Expert System (DES), which identifies the most likely physical reasons for excessive pollutants; and a Prescriptive Expert System (PES), which selects a proper set of spatially distributed BMPs. SWAT was calibrated and validated first to simulate pre-BMP watershed responses. The DDSS was then applied for BMP recommendation. The prescribed BMPs were modeled back into SWAT to quantify their effectiveness. Total Cost for BMP implementation was calculated as a function of BMP coverage area, BMP numbers and types, and residents' preferences. Protocols for urban BMP modeling were developed based on the BMPs' mechanism and the hydrologic processes involved. The DDSS was tested in Watts Branch, a small urban watershed in metropolitan Washington D.C., and Wilde Lake, a suburban watershed in Columbia, MD. Comparisons were carried out in terms of hotspots distribution and BMP recommendation between the two study areas. The hotspots identified and BMPs prescribed by the DDSS were also examined under future climate scenarios. The prescribed BMPs and GIS maps will be useful in agency-level decision making and in developing appropriate educational material for residents and the general public.
机译:最佳管理实践(BMP)已成为缓解面源污染(NPS)问题的最有效方法。在农村地区,由于农业活动增加了地表水中的养分,有毒物质和沉积物,NPS引起了人们的广泛关注。城市和郊区也是NPS的主要贡献者,很大程度上是由于暴雨。对于具有各种土壤类型和土地用途的流域,单一类型的BMP不能成为解决所有雨水和相关水质问题的灵丹妙药。需要一系列空间分布的小型BMP,以减少流量并改善城市雨水质量。本研究旨在开发用于城市BMP选择的诊断决策支持系统(DDSS)。基于过程的分布式水文模型,土壤和水评估工具(SWAT),用于模拟水文过程,估算水质变量并为城市BMP建模。 DDSS由三部分组成:热点标识符,用于定位水质和水量热点;诊断专家系统(DES),用于确定污染物过多的最可能物理原因;以及规范性专家系统(PES),该系统选择一组适当的空间分布BMP。首先对SWAT进行了校准和验证,以模拟BMP之前的分水岭响应。然后将DDSS应用于BMP推荐。将规定的BMP重新建模为SWAT,以量化其有效性。 BMP实施的总成本是根据BMP覆盖范围,BMP数量和类型以及居民的偏好来计算的。基于BMP的机制和所涉及的水文过程,开发了用于城市BMP建模的协议。 DDSS在华盛顿特区大城市流域瓦茨分公司(Watts Branch)和马里兰州哥伦比亚市郊区流域王尔德湖(Wilde Lake)中进行了测试。在两个研究区域之间的热点分布和BMP建议方面进行了比较。在未来的气候情景下,还检查了DDSS确定的热点和BMP规定的BMP。规定的BMP和GIS地图将有助于机构一级的决策,并为居民和公众开发适当的教育材料。

著录项

  • 作者

    Wang, Yan.;

  • 作者单位

    University of Maryland, College Park.;

  • 授予单位 University of Maryland, College Park.;
  • 学科 Hydrologic sciences.;Civil engineering.;Water resources management.
  • 学位 Ph.D.
  • 年度 2015
  • 页码 312 p.
  • 总页数 312
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:52:12

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