Placement of Cost-Effectiveness Nature-based Stormwater Solutions Using a Combined GIS Multi-Criteria and Genetic Algorithm Approach

Abstract Submission: Investments in stormwater management are typically reactive in many cities because of a lack of proper regulation and funding mechanisms. The result is poor drainage services, which impacts water quality and often results in flooding, negatively impacting society and the environment. One alternative to address some of these issues is the implementation of Nature-based Stormwater Solutions (NbS). One of the issues that is often overlooked by municipalities is how to assess the cost-benefit ratio of a portfolio of NbS in urban watersheds. Such understanding could encourage the large-scale use of NbS. This work focused on optimizing the location of four different types of Nature-based Solutions (Porous Pavement, Rain Garden, Infiltration Trenches and Media Filter). The cost-effectiveness of each NbS is compared to determine the near-optimal NbS arrangement under the hydraulic-hydrological and socio-economic aspects. In this approach, we optimize the cost-effectiveness using a Genetic Algorithm (GA) and a physics-based GIS Multi-Criteria Decision-Making model (GIS-MCDM). The proposed methodology is tested in the Olympic Center Catchment, Brasilia, Brazil. The results indicate that urban typology influences the selection of which type of NbS should be placed in which location to maximize cost-benefit ratios. The results also suggest that the need to select the most appropriate NbS for each implementation site is observed to increase with the level of land use. The proposed methods may be useful to local planners and water resource managers to reduce costs and increase the efficiency of stormwater infrastructure to improve water quality and reduce localized flooding.

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