Water Resources Research

Decision scaling: Linking bottom-up vulnerability analysis with climate projections in the water sector

Authors

  • Casey Brown,

    Corresponding author
    1. Department of Civil and Environmental Engineering, University of Massachusetts Amherst,Amherst, Massachusetts,USA
      Corresponding author: C. Brown, Department of Civil and Environmental Engineering, University of Massachusetts Amherst, 12B Marston Hall, 130 Natural Resources Rd., Amherst, MA 01003-9293, USA. (cbrown@ecs.umass.edu)
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  • Yonas Ghile,

    1. Department of Civil and Environmental Engineering, University of Massachusetts Amherst,Amherst, Massachusetts,USA
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  • Mikaela Laverty,

    1. Department of Civil and Environmental Engineering, University of Massachusetts Amherst,Amherst, Massachusetts,USA
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  • Ke Li

    1. Department of Civil and Environmental Engineering, University of Massachusetts Amherst,Amherst, Massachusetts,USA
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Corresponding author: C. Brown, Department of Civil and Environmental Engineering, University of Massachusetts Amherst, 12B Marston Hall, 130 Natural Resources Rd., Amherst, MA 01003-9293, USA. (cbrown@ecs.umass.edu)

Abstract

[1] There are few methodologies for the use of climate change projections in decision making or risk assessment processes. In this paper we present an approach for climate risk assessment that links bottom-up vulnerability assessment with multiple sources of climate information. The three step process begins with modeling of the decision and identification of thresholds. Through stochastic analysis and the creation of a climate response function, climate states associated with risk are specified. Climate information such as available from multi-GCM, multirun ensembles, is tailored to estimate probabilities associated with these climate states. The process is designed to maximize the utility of climate information in the decision process and to allow the use of many climate projections to produce best estimates of future climate risks. It couples the benefits of stochastic assessment of risks with the potential insight from climate projections. The method is an attempt to make the best use of uncertain but potentially useful climate information. An example application to an urban water supply system is presented to illustrate the process.

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