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Incorporating green infrastructure into water management plans using multi-objective optimization
Citation:
Piscopo, A., N. Detenbeck, AND T. Stagnitta. Incorporating green infrastructure into water management plans using multi-objective optimization. In Proceedings, 9th International Congress Environmental Modelling and Software, Fort Collins, Colorado, June 24 - 28, 2018. Brigham Young University, Provo, UT, 130, (2018).
Impact/Purpose:
Green infrastructure (GI) is more commonly being used in urban areas to alleviate these water quantity and quality issues. However, to have a meaningful impact on water quantity and quality, GI should be implemented at the watershed scale. This research uses multi-objective optimization to strategically develop a set of GI management plans, each of which specifies where to locate GI within a watershed and how much to implement to meet management goals. These management plans reflect tradeoffs between stakeholder objectives, which include minimizing costs while also mitigating issues related to both water quantity and quality, specifically, maximizing reductions in cumulative runoff volume and maximizing reductions in cumulative nitrogen and phosphorus loads.
Description:
Sustainable management of water resources is challenged by numerous conflicting interests and objectives. Decision support tools (DSTs) are evolving to incorporate multiple objectives (e.g. economic, social, and environmental) into the development of water management plans, rather than focus only on minimizing cost. A recent version of the DST known as WMOST (Watershed Management Optimization Support Tool) uses a multi-objective evolutionary algorithm to generate management plan options that specify the location, quantity, and types of green infrastructure (GI) to implement in a watershed. In this study, we applied WMOST to a watershed in southern Massachusetts to develop management plan options that minimize cost, nutrient loads, and runoff. The resultant set of options are indicative of tradeoffs between these objectives, which were visualized multi-dimensionally to help inform the decision-making processes of stakeholders. Preliminary takeaways include: (1) implementing GI with small storage capacity on higher permeability soils leads to stronger performance in the objectives than implementing GI with large storage capacity on lower permeability soils and (2) implementing more units of GI on the categories of land use with low nutrient loads is more cost-effective than implementing fewer units of GI on the categories of land use with high nutrient loads.
