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Multi Criteria Decision Making in Selecting Stormwater Management Green Infrastructure for Industrial areas Part 2: A Case Study with TOPSIS

Author

Listed:
  • V. M. Jayasooriya

    (Victoria University
    University of Sri Jayewardenepura)

  • S. Muthukumaran

    (Victoria University)

  • A. W. M. Ng

    (Victoria University)

  • B. J. C. Perera

    (Victoria University)

Abstract

The changes of land surface characteristics due to urbanization lead to various environmental problems such as increasing the runoff which can lead to flooding and the poor quality of receiving waters. Among different land uses in urban areas, the industrial areas are highly environmentally degraded land areas which annually discharge high amounts of contaminated stormwater to natural waterways. However, industrial areas plays major role in a country’s economy and therefore it is important to identify optimum strategies to improve the quality of runoff in such areas. Green Infrastructure (GI) practices integrate measures to restore the green space in urban areas and are currently becoming one of the promising strategies around the world as source control measures of stormwater, especially when implemented as treatment trains. For a complex land use like an industrial area, the reality in optimizing GI treatment trains can incorporate several aspects related to environmental, economic and social objectives which are expected of GI through their implementation. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was used in this study to identify compromise optimum treatment train configurations and the sizing combinations of GI treatment trains for a case study industrial area in Melbourne, Australia. Moreover, a sensitivity analysis was performed to validate the results obtained through TOPSIS by considering several weighting schemes for different performance measures. The results of the sensitivity analysis assessed the most sensitive performance measures for the weight changes. The methodology proposed in this study was successful in optimizing both the selection and sizing of a GI treatment train for an industrial area simultaneously.

Suggested Citation

  • V. M. Jayasooriya & S. Muthukumaran & A. W. M. Ng & B. J. C. Perera, 2018. "Multi Criteria Decision Making in Selecting Stormwater Management Green Infrastructure for Industrial areas Part 2: A Case Study with TOPSIS," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(13), pages 4297-4312, October.
    • Handle: RePEc:spr:waterr:v:32:y:2018:i:13:d:10.1007_s11269-018-2052-z
    DOI: 10.1007/s11269-018-2052-z
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    1. Lin, Sheng-Hau & Zhao, Xiaofeng & Wu, Jiuxing & Liang, Fachao & Li, Jia-Hsuan & Lai, Ren-Ji & Hsieh, Jing-Chzi & Tzeng, Gwo-Hshiung, 2021. "An evaluation framework for developing green infrastructure by using a new hybrid multiple attribute decision-making model for promoting environmental sustainability," Socio-Economic Planning Sciences, Elsevier, vol. 75(C).
    2. Amirhossein Nazari & Abbas Roozbahani & Seied Mehdy Hashemy Shahdany, 2023. "Integrated SUSTAIN-SWMM-MCDM Approach for Optimal Selection of LID Practices in Urban Stormwater Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(9), pages 3769-3793, July.
    3. Juliana Uribe-Aguado & Sara L. Jiménez-Ariza & María N. Torres & Natalia A. Bernal & Mónica M. Giraldo-González & Juan P. Rodríguez, 2022. "A SUDS Planning Decision Support Tool to Maximize Ecosystem Services," Sustainability, MDPI, vol. 14(8), pages 1-22, April.
    4. Sabina Kordana-Obuch & Mariusz Starzec, 2020. "Statistical Approach to the Problem of Selecting the Most Appropriate Model for Managing Stormwater in Newly Designed Multi-Family Housing Estates," Resources, MDPI, vol. 9(9), pages 1-20, September.
    5. Marchetti, Dalmo & Wanke, Peter, 2020. "Efficiency of the rail sections in Brazilian railway system, using TOPSIS and a genetic algorithm to analyse optimized scenarios," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 135(C).
    6. Suphicha Muangsri & Wendy McWilliam & Gillian Lawson & Tim Davies, 2022. "Evaluating Capability of Green Stormwater Infrastructure on Large Properties toward Adaptive Flood Mitigation: The HLCA+C Methodology," Land, MDPI, vol. 11(10), pages 1-18, October.
    7. Samanta Bačić & Hrvoje Tomić & Katarina Rogulj & Goran Andlar, 2024. "Fuzzy Decision-Making Valuation Model for Urban Green Infrastructure Implementation," Energies, MDPI, vol. 17(20), pages 1-15, October.

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