2NDNATURE, LLC, 500 Seabright Avenue, Santa Cruz, CA, 95062, United States.
2NDNATURE, LLC, 500 Seabright Avenue, Santa Cruz, CA, 95062, United States.
J Environ Manage. 2017 May 15;193:257-269. doi: 10.1016/j.jenvman.2017.02.007. Epub 2017 Feb 20.
We present an urban runoff model designed for stormwater managers to quantify runoff reduction benefits of mitigation actions that has lower input data and user expertise requirements than most commonly used models. The stormwater tool to estimate load reductions (TELR) employs a semi-distributed approach, where landscape characteristics and process representation are spatially-lumped within urban catchments on the order of 100 acres (40 ha). Hydrologic computations use a set of metrics that describe a 30-year rainfall distribution, combined with well-tested algorithms for rainfall-runoff transformation and routing to generate average annual runoff estimates for each catchment. User inputs include the locations and specifications for a range of structural best management practice (BMP) types. The model was tested in a set of urban catchments within the Lake Tahoe Basin of California, USA, where modeled annual flows matched that of the observed flows within 18% relative error for 5 of the 6 catchments and had good regional performance for a suite of performance metrics. Comparisons with continuous simulation models showed an average of 3% difference from TELR predicted runoff for a range of hypothetical urban catchments. The model usually identified the dominant BMP outflow components within 5% relative error of event-based measured flow data and simulated the correct proportionality between outflow components. TELR has been implemented as a web-based platform for use by municipal stormwater managers to inform prioritization, report program benefits and meet regulatory reporting requirements (www.swtelr.com).
我们提出了一种城市径流模型,旨在为雨水管理者量化缓解措施的径流减少效益,该模型比大多数常用模型所需的输入数据和用户专业知识都要少。用于估算负荷削减的雨水工具 (TELR) 采用半分布式方法,其中景观特征和过程表示在 100 英亩(40 公顷)左右的城市集水区内空间聚集。水文计算使用一组描述 30 年降雨分布的指标,结合经过充分测试的降雨径流转化和路由算法,为每个集水区生成平均年径流量估算值。用户输入包括一系列结构最佳管理实践 (BMP) 类型的位置和规格。该模型在美国加利福尼亚州塔霍湖流域的一组城市集水区进行了测试,其中模拟的年流量与 6 个集水区中的 5 个集水区的观测流量的相对误差在 18%以内,并且对一系列性能指标具有良好的区域性能。与连续模拟模型的比较表明,对于一系列假设的城市集水区,TELR 预测的径流量平均存在 3%的差异。该模型通常能够以事件测量流量数据的 5%相对误差范围内识别出主要的 BMP 出流成分,并模拟出出流成分之间的正确比例关系。TELR 已作为一个基于网络的平台实现,供市政雨水管理者使用,以告知优先级、报告计划效益并满足监管报告要求(www.swtelr.com)。