Use of green stormwater infrastructure (GSI) to mitigate urban runoff impacts has grown substantially in recent decades, but municipalities often lack an integrated approach to prioritize areas for implementation, demonstrate compelling evidence of catchment-scale improvements, and communicate stormwater program effectiveness. We present a method for quantifying runoff reduction benefits associated with distributed GSI that is designed to align with the spatial scale of information required by urban stormwater implementation. The model was driven by a probabilistic representation of rainfall events to estimate annual runoff and reductions associated with distributed GSI for various design storm levels. Raster-based calculations provide estimates on a 30-m grid, preserving unique combinations of drainage factors that drive runoff production, hydrologic storage, and infiltration benefits of GSI. The model showed strong correspondence with aggregated continuous runoff data from a set of urbanized catchments in Salinas, California, USA, over a three-year monitoring period and output sensitivity to the storm drain network inputs. Because the model runs through a web browser and the parameterization is based on readily available spatial data, it is suitable for nonmodeling experts to rapidly update GSI features, compare alternative implementation scenarios, track progress toward urban runoff reduction goals, and demonstrate regulatory compliance.

中文翻译：

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评估基于云的空间分布式建模方法跟踪绿色雨水基础设施径流减少的可行性

在最近几十年中，使用绿色雨水基础设施（GSI）减轻城市径流的影响已显着增加，但是市政当局通常缺乏一种综合的方法来对实施区域进行优先排序，证明流域规模改善的令人信服的证据以及传达雨水计划的有效性。我们提出了一种量化与分布式GSI相关的径流减少收益的方法，该方法旨在与城市雨水实施所需的信息空间规模保持一致。该模型由降雨事件的概率表示驱动，以估算各种设计暴风雨水平下与分布式GSI相关的年度径流和减少量。基于栅格的计算可在30米长的网格上提供估算值，并保留可驱动径流产生的独特排水因子组合，水文存储和GSI的渗透优势。该模型显示，在为期三年的监测期内，与美国加利福尼亚州萨利纳斯市一系列城市化集水区的连续连续径流量数据相一致，并且其输出对雨水排放管网的敏感性。由于该模型通过Web浏览器运行，并且参数化基于随时可用的空间数据，因此适合非建模专家快速更新GSI功能，比较替代实施方案，跟踪实现城市径流减少目标的进度以及证明合规性。在三年的监控期内，输出对雨水排放管网输入的敏感性。由于该模型通过Web浏览器运行，并且参数化基于随时可用的空间数据，因此适合非建模专家快速更新GSI功能，比较替代实施方案，跟踪实现城市径流减少目标的进度以及证明合规性。在三年的监控期内，输出对雨水排放管网输入的敏感性。由于该模型通过Web浏览器运行，并且参数化基于随时可用的空间数据，因此适合非建模专家快速更新GSI功能，比较替代实施方案，跟踪实现城市径流减少目标的进度以及证明合规性。