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Assessing and Mitigating the Hydrological Impacts of Urbanisation in Semi-Urban Catchments Using the Storm Water Management Model

Author

Listed:
  • S. K. Aryal

    (CSIRO Land and Water)

  • S. Ashbolt

    (CSIRO Land and Water, Highett)

  • B. S. McIntosh

    (International WaterCentre)

  • K. P. Petrone

    (CSIRO Land and Water)

  • S. Maheepala

    (CSIRO Land and Water, Highett)

  • R. K. Chowdhury

    (UAE University)

  • T. Gardener

    (Central Queensland University)

  • R. Gardiner

    (Information Technology and Innovation)

Abstract

Urbanisation causes a range of adverse impacts on stream physical and ecological conditions due to increases in catchment runoff caused by increased imperviousness. Developing ways to reduce these impacts on in-stream ecosystems is a major challenge and requires innovative catchment specific, high-time-resolution modelling methods. We employed a combination of high-time-resolution data collection, analysis and modelling methods to understand the underlying hydrological processes and evaluate a potentially significant management option – stormwater harvesting. A set of sensitive parameters of the Storm Water Management Model (SWMM) were optimised using an automatic calibration method and hourly data in eight catchments in South East Queensland, Australia. Systematic investigation of the effects of urbanisation and its mitigation through stormwater harvesting was achieved by modelling the impacts of increasing impervious area for three of the relatively undeveloped catchments. As the extent of impervious areas across the catchments increased we typically found increases in the duration of high flow spells together with increases in mean flow and the frequency of runoff events. However, many hydrologic responses to increasing imperviousness were specific to the physical characteristics of catchments, and to the spatio-temporal pattern of urbanisation. By implementing stormwater harvesting options the hourly flows were reduced by up to 60 % but the maximum flow was unchanged. Thus the option was able to reduce, but not totally ameliorate, the negative hydrological impacts of increasing imperviousness.

Suggested Citation

  • S. K. Aryal & S. Ashbolt & B. S. McIntosh & K. P. Petrone & S. Maheepala & R. K. Chowdhury & T. Gardener & R. Gardiner, 2016. "Assessing and Mitigating the Hydrological Impacts of Urbanisation in Semi-Urban Catchments Using the Storm Water Management Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(14), pages 5437-5454, November.
  • Handle: RePEc:spr:waterr:v:30:y:2016:i:14:d:10.1007_s11269-016-1499-z
    DOI: 10.1007/s11269-016-1499-z
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    References listed on IDEAS

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    1. Gassman, Philip W. & Reyes, Manuel R. & Green, Colleen H. & Arnold, Jeffrey G., 2007. "The Soil and Water Assessment Tool: Historical Development, Applications, and Future Research Directions," ISU General Staff Papers 200701010800001027, Iowa State University, Department of Economics.
    2. Karen Goff & Randall Gentry, 2006. "The Influence of Watershed and Development Characteristics on the Cumulative Impacts of Stormwater Detention Ponds," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 20(6), pages 829-860, December.
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    1. Jiake Li & Chenning Deng & Huaien Li & Menghua Ma & Yajiao Li, 2018. "Hydrological Environmental Responses of LID and Approach for Rainfall Pattern Selection in Precipitation Data-Lacked Region," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(10), pages 3271-3284, August.
    2. Xiaoyan Bai & Wen Shen & Peng Wang & Xiaohong Chen & Yanhu He, 2020. "Response of Non-point Source Pollution Loads to Land Use Change under Different Precipitation Scenarios from a Future Perspective," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(13), pages 3987-4002, October.
    3. Bartosz Szeląg & Roman Suligowski & Grzegorz Majewski & Przemysław Kowal & Adrian Bralewski & Karolina Bralewska & Ewa Anioł & Wioletta Rogula-Kozłowska & Francesco Paola, 2022. "Application of Multinomial Logistic Regression to Model the Impact of Rainfall Genesis on the Performance of Storm Overflows: Case Study," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(10), pages 3699-3714, August.
    4. Zening Wu & Bingyan Ma & Huiliang Wang & Caihong Hu & Hong Lv & Xiangyang Zhang, 2021. "Identification of Sensitive Parameters of Urban Flood Model Based on Artificial Neural Network," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(7), pages 2115-2128, May.
    5. Priscila Celebrini de Oliveira Campos & Tainá da Silva Rocha Paz & Letícia Lenz & Yangzi Qiu & Camila Nascimento Alves & Ana Paula Roem Simoni & José Carlos Cesar Amorim & Gilson Brito Alves Lima & Ma, 2020. "Multi-Criteria Decision Method for Sustainable Watercourse Management in Urban Areas," Sustainability, MDPI, vol. 12(16), pages 1-22, August.
    6. Jiake Li & Chenning Deng & Ya Li & Yajiao Li & Jinxi Song, 2017. "Comprehensive Benefit Evaluation System for Low-Impact Development of Urban Stormwater Management Measures," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(15), pages 4745-4758, December.

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