4.7 Article

Linking climate projections to performance: A yield- based decision scaling assessment of a large urban water resources system

Journal

WATER RESOURCES RESEARCH
Volume 50, Issue 4, Pages 3553-3567

Publisher

AMER GEOPHYSICAL UNION
DOI: 10.1002/2013WR015156

Keywords

water resources planning; Australia; decision scaling; yield analysis; eWater Source; bottom-up climate impact assessment

Funding

  1. UK Engineering and Physical Sciences Research Council
  2. United Utilities PLC
  3. Anglian Water
  4. Severn Trent Water through the STREAM Industrial Doctorate Centre
  5. Engineering and Physical Sciences Research Council [1037784] Funding Source: researchfish

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Despite a decade of research into climate change impacts on water resources, the scientific community has delivered relatively few practical methodological developments for integrating uncertainty into water resources system design. This paper presents an application of the decision scaling methodology for assessing climate change impacts on water resources system performance and asks how such an approach might inform planning decisions. The decision scaling method reverses the conventional ethos of climate impact assessment by first establishing the climate conditions that would compel planners to intervene. Climate model projections are introduced at the end of the process to characterize climate risk in such a way that avoids the process of propagating those projections through hydrological models. Here we simulated 1000 multisite synthetic monthly streamflow traces in a model of the Melbourne bulk supply system to test the sensitivity of system performance to variations in streamflow statistics. An empirical relation was derived to convert decision-critical flow statistics to climatic units, against which 138 alternative climate projections were plotted and compared. We defined the decision threshold in terms of a system yield metric constrained by multiple performance criteria. Our approach allows for fast and simple incorporation of demand forecast uncertainty and demonstrates the reach of the decision scaling method through successful execution in a large and complex water resources system. Scope for wider application in urban water resources planning is discussed.

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