Abstract:The implementation of stormwater Best Management Practices (BMPs) could help re-establish the natural hydrological cycle of watersheds after urbanization, with each BMP presenting a different performance across a range of criteria (flood prevention, pollutant removal, etc.). Additionally, conflicting views from the relevant stakeholders may arise, resulting in a complex selection process. This paper proposes a methodology for BMP selection based on the application of multi-criteria decision aid (MCDA) methods, integrating multiple stakeholder priorities and BMP combinations. First, in the problem definition, the MCDA methods, relevant criteria and design guidelines are selected. Next, information from the preliminary analysis of the watershed is used to obtain a list of relevant BMPs. The third step comprises the watershed modeling and analysis of the BMP alternatives to obtain performance values across purely objective criteria. Afterwards, a stakeholder analysis based on survey applications is carried out to obtain social performance values and criteria priorities. Then, the MCDA methods are applied to obtain the final BMP rankings. The last step considers the sensitivity analysis and rank comparisons in order to draw the final conclusions and recommendations. Future improvements to the methodology could explore inclusion of multiple objective analysis, and alternative means for obtaining social performance values.
Abstract:The selection of stormwater Best Management Practices (BMPs) for mitigating the effects of urbanization on the hydrological cycle could be a complex process due to conflicting stakeholder views, and varying levels of performance of BMPs across a range of criteria (runoff reduction, erosion control, etc.). Part 1 of this article proposed a methodology based on the application of multi-criteria decision aid (MCDA) methods, which was tested here on a residential stormwater network in the Montreal area. The case study considered green roofs, rain gardens, rain barrels and pervious pavement over a range of economic, social, and water quality and quantity criteria by applying 4 MCDA methods under three different stakeholder views. The results indicated Elimination et Choix Traduisant la Réalité (ELECTRE) III to be the most appropriate method for the methodology, presenting flexibility concerning threshold values, criteria weights, and showing shared top choices across stakeholders (rain gardens, and rain gardens in combination with pervious pavement). The methodology shows potential for more formal applications and research opportunities. Future work may lie in the inclusion of multiple objective optimization, better stakeholder engagement, estimation of economic benefits, water quality modeling, long-term hydrological simulations, and estimating real BMP pollutant removal rates.
The need to provide adequate water quality control using best management practices (BMPs) requires accurate modeling in order to determine their ideal placement within the watershed. A case study in the Montréal area used PCSWMM software to analyse the implementation of green roofs, rain gardens, pervious pavement and vegetative swales, individually as well as in possible combinations, by comparing both outfall hydrographs and pollutant removal rates to assess the performance of each alternative.Of the individual BMPs, rain gardens provided the highest levels of runoff control, with slight performance improvements when they were coupled in series with green roofs, but with lower performance when adding pervious pavements. The overland flow path could significantly affect which pollutants were picked up by runoff, but to accurately model complex buildup and washoff processes requires information that might not be readily available for all watersheds. Even though the results can be highly case specific, the results obtained highlight the limitations still faced by water-resources professionals, and raise important points that challenge common conceptions regarding BMP implementation. More data on real life performance over long periods of time is still needed to better analyse BMP combinations.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.