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The effect of modeling choices on updating intensity-duration-frequency curves and stormwater infrastructure designs for climate change

Author

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  • Lauren M. Cook

    (Carnegie Mellon University
    Swiss Federal Institute of Aquatic Science and Technology)

  • Seth McGinnis

    (National Center for Atmospheric Research)

  • Constantine Samaras

    (Carnegie Mellon University)

Abstract

Intensity-duration-frequency (IDF) curves, commonly used in stormwater infrastructure design to represent characteristics of extreme rainfall, are gradually being updated to reflect expected changes in rainfall under climate change. The modeling choices used for updating lead to large uncertainties; however, it is unclear how much these uncertainties affect the design and cost of stormwater systems. This study investigates how the choice of spatial resolution of the regional climate model (RCM) ensemble and the spatial adjustment technique affect climate-corrected IDF curves and resulting stormwater infrastructure designs in 34 US cities for the period 2020 to 2099. In most cities, IDF values are significantly different between three spatial adjustment techniques and two RCM spatial resolutions. These differences have the potential to alter the size of stormwater systems designed using these choices and affect the results of climate impact modeling more broadly. The largest change in the engineering decision results when the design storm is selected from the upper bounds of the uncertainty distribution of the IDF curve, which changes the stormwater pipe design size by five increments in some cases, nearly doubling the cost. State and local agencies can help reduce some of this variability by setting guidelines, such as avoiding the use of the upper bound of the future uncertainty range as a design storm and instead accounting for uncertainty by tracking infrastructure performance over time and preparing for adaptation using a resilience plan.

Suggested Citation

  • Lauren M. Cook & Seth McGinnis & Constantine Samaras, 2020. "The effect of modeling choices on updating intensity-duration-frequency curves and stormwater infrastructure designs for climate change," Climatic Change, Springer, vol. 159(2), pages 289-308, March.
    • Handle: RePEc:spr:climat:v:159:y:2020:i:2:d:10.1007_s10584-019-02649-6
    DOI: 10.1007/s10584-019-02649-6
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    1. Yeowon Kim & Daniel A. Eisenberg & Emily N. Bondank & Mikhail V. Chester & Giuseppe Mascaro & B. Shane Underwood, 2017. "Fail-safe and safe-to-fail adaptation: decision-making for urban flooding under climate change," Climatic Change, Springer, vol. 145(3), pages 397-412, December.
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    Cited by:

    1. Yuchuan Lai & Matteo Pozzi, 2024. "Sequential learning of climate change via a physical-parameter-based state-space model and Bayesian inference," Climatic Change, Springer, vol. 177(6), pages 1-22, June.
    2. Buddhi Wijesiri & Erick Bandala & An Liu & Ashantha Goonetilleke, 2020. "A Framework for Stormwater Quality Modelling under the Effects of Climate Change to Enhance Reuse," Sustainability, MDPI, vol. 12(24), pages 1-12, December.
    3. Subhra Sekhar Maity & Rajib Maity, 2022. "Changing Pattern of Intensity–Duration–Frequency Relationship of Precipitation due to Climate Change," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(14), pages 5371-5399, November.
    4. Moulay Driss Hasnaoui & Oumaima Rami & Driss Ouazar, 2024. "Territorial Decision Support System Based on IDF Curves’ Parameters Regionalization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 38(3), pages 1181-1204, February.
    5. Shadi Arfa & Mohsen Nasseri & Hassan Tavakol-Davani, 2021. "Comparing the Effects of Different Daily and Sub-Daily Downscaling Approaches on the Response of Urban Stormwater Collection Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(2), pages 505-533, January.
    6. Raúl Montes-Pajuelo & Ángel M. Rodríguez-Pérez & Raúl López & César A. Rodríguez, 2024. "Analysis of Probability Distributions for Modelling Extreme Rainfall Events and Detecting Climate Change: Insights from Mathematical and Statistical Methods," Mathematics, MDPI, vol. 12(7), pages 1-24, April.
    7. Jonathan B. Butcher & Tan Zi & Brian R. Pickard & Scott C. Job & Thomas E. Johnson & Bryan A. Groza, 2021. "Efficient statistical approach to develop intensity-duration-frequency curves for precipitation and runoff under future climate," Climatic Change, Springer, vol. 164(1), pages 1-20, January.
    8. Andrés Fortunato & Helmut Herwartz & Ramón E. López & Eugenio Figueroa B., 2022. "Carbon dioxide atmospheric concentration and hydrometeorological disasters," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 112(1), pages 57-74, May.

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