Data‐driven modeling to enhance municipal water demand estimates in response to dynamic climate conditions
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Data‐driven modeling to enhance municipal water demand estimates in response to dynamic climate conditions

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  • Journal Title:
    JAWRA Journal of the American Water Resources Association
  • Personal Author:
  • NOAA Program & Office:
    NWS (National Weather Service)
  • Description:
    Altered precipitation and temperature patterns from a changing climate will affect supply, demand, and overall municipal water system operations throughout the arid western U.S. While supply forecasts leverage hydrological models to connect climate influences with surface water availability, demand forecasts typically estimate water use independent of climate and other externalities. Stemming from an increased focus on seasonal water demand management, we use the Salt Lake City, Utah municipal water system as a test bed to assess model accuracy versus complexity trade‐offs between simple climate‐independent econometric‐based models and complex climate‐sensitive data‐driven models to average to extreme wet and dry climate conditions—representative of a new climate normal. The climate‐independent model displayed low performance during extreme dry conditions with predictions exceeding 90% and 40% of the observed monthly and seasonal volumetric demands, respectively, which we attribute to insufficient model complexity. The climate‐sensitive models displayed greater accuracy in all conditions, with an ordinary least squares model demonstrating a measurable reduction in prediction bias (3.4% vs. −27.3%) and RMSE (74.0 lpcd vs. 294 lpcd) compared to the climate‐independent model. The climate‐sensitive workflow increased model accuracy and characterized climate‐demand interactions, demonstrating a novel tool to enhance water system management.
  • Keywords:
  • Source:
    JAWRA Journal of the American Water Resources Association, 60(2), 687-706
  • DOI:
  • ISSN:
    1093-474X;1752-1688;
  • Format:
    PDF
  • Publisher:
    Wiley
  • Document Type:
    Journal Article
  • Funding:
    Grant no. NA22NWS4320003
  • Rights Information:
    Accepted Manuscript
  • Rights Statement:
    The NOAA IR provides access to this content under the authority of the government's retained license to distribute publications and data resulting from federal funding. While users may legally access this content, the copyright owners retain rights that govern the reproduction, redistribution, and re-use of this work. The user is solely responsible for complying with applicable copyright law.
  • Compliance:
    Library
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  • Download URL:
  • File Type:

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