Executive Summary

GreenPlan-IT is a planning level tool that was developed by SFEP and SFEI with support and oversight from BASMAA to provide Bay Area municipalities with the ability to evaluate multiple management alternatives using green infrastructure for addressing stormwater issues in urban watersheds. GreenPlan-IT combines sound science and engineering principles with GIS analysis and optimization techniques to support the cost-effective selection and placement of Green Infrastructure (GI) at a watershed scale.  Tool outputs can be used to develop quantitatively-derived watershed master plans to guide future GI implementation for improving water quality in the San Francisco Bay and its tributary watersheds.

Structurally, the GreenPlan-IT is comprised of three components: (a) a GIS-based Site Locator Tool to identify potential GI sites; (b) a Modeling Tool that quantifies anticipated watershed-scale runoff and pollutant load reduction from GI sites; and (c) an Optimization Tool that uses a cost-benefit analysis to identify the best combinations of GI types and number of sites within a watershed for achieving flow and/or load reduction goals. The three tool components were designed as standalone modules to provide flexibility and their interaction is either through data exchange, or serving as a subroutine to another tool.

This report provides an overview of the GreenPlan-IT Tool and demonstrates its utility and power through two pilot studies which is summarized in this report as a case study. The pilot studies with the City of San Mateo and the City of San Jose explored the use of GreenPlan-IT for identifying feasible and optimal GI locations for mitigation of stormwater runoff. They are provided here to give the reader an overview of the user application process from start to finish, including problem formulation, data collection, GIS analysis, establishing a baseline condition, GI representation, and the optimization process. Through the pilot study application process the general steps and recommendations for how GreenPlan-IT can be applied and interpreted are presented.

The pilot with the City of San Mateo utilized only the GIS Site Locator Tool to screen potential sites for GI implementation in five discrete watersheds (Borel Creek, Laurel Creek, Leslie Creek, Poplar Creek, San Mateo Creek) as well as multiple unnamed drainages. Using selected regional and local data layers and the City’s ranking and weighting and using all five optional analyses, the Site Locator Tool identified 18 acres of City-owned property or right-of-way as highly ranked locations for potential GI implementation, 113 acres as moderately ranked, and 11 acres as lower ranked locations. A remote data vaGIation exercise confirmed that many of the sites identified and ranked highly by the locator tool were also sites previously identified as potential GI opportunities by the city of San Mateo.

The pilot study with City of San Jose used the full Toolkit to support a cost-benefit evaluation of stormwater runoff control. The objective of this pilot was to demonstrate the capacities and usability of GreenPlan-IT for identifying feasible and cost-effective GI locations at a watershed scale. The focus area was a 4300 acre proposed development area within the lower part of the Guadalupe River Watershed. The Site Locator Tool identified possible GI locations that serve as the constraints for the optimization process; the Modeling Tool established a representative baseline condition through calibration to local data; and then the Optimization Tool was used to repeatedly run the Modeling Tool to iteratively arrive at the optimized GI scenario that minimized the total cost of management while satisfying water quality and quantity constraints. The results of the application included the cost/benefit associated with a range of flow or loads reduction targets, ranking of sites for specific optimal solutions, and maps showing the distribution of GI within the study area under a specific optimal solution.

The Site Locator Tool has end-user flexibility that results in an iterative tool that can be fine-tuned as questions and goals change or more accurate local data are available. Establishing a representative baseline model is crucial for meaningful results and requires the calibration of the Modeling Tool to local data. The Optimization Tool can be very powerful when combined with hydrologic modeling and cost analyses. Successful and meaningful application of the Optimization Tool largely depends on accurate representation of the watershed baseline condition, GI configurations, and the associated GI costs. The cost-effective solutions from the optimization process must be interpreted in the context of specific problem formulation, assumptions, constraints, and optimization goals unique to each application. With the help of this information, decision makers can set realistic goals on how much can be achieved and the level of investment required, as well as determine at what point further investment on GI will yield no improvement in runoff reduction.