Abstract
AbstractWe present a risk‐based approach for incorporating nonstationary probabilistic climate projections into long‐term water resources planning. The proposed methodology uses nonstationary synthetic time series of future climates obtained via a stochastic weather generator based on the UK Climate Projections (UKCP09) to construct a probability distribution of the frequency of water shortages in the future. The UKCP09 projections extend well beyond the range of current hydrological variability, providing the basis for testing the robustness of water resources management plans to future climate‐related uncertainties. The nonstationary nature of the projections combined with the stochastic simulation approach allows for extensive sampling of climatic variability conditioned on climate model outputs. The probability of exceeding planned frequencies of water shortages of varying severity (defined as Levels of Service for the water supply utility company) is used as a risk metric for water resources planning. Different sources of uncertainty, including demand‐side uncertainties, are considered simultaneously and their impact on the risk metric is evaluated. Supply‐side and demand‐side management strategies can be compared based on how cost‐effective they are at reducing risks to acceptable levels. A case study based on a water supply system in London (UK) is presented to illustrate the methodology. Results indicate an increase in the probability of exceeding the planned Levels of Service across the planning horizon. Under a 1% per annum population growth scenario, the probability of exceeding the planned Levels of Service is as high as 0.5 by 2040. The case study also illustrates how a combination of supply and demand management options may be required to reduce the risk of water shortages.
Highlights
The increased awareness of the impacts of climate change on water resources [Kundzewicz et al, 2008; Vo€ro€smarty et al, 2000] has generated interest in new methodologies to help water resources managers deal with uncertain information from climate models [e.g., Brown et al, 2010; Groves et al, 2008a]
Population changes over the simulation period were modeled by adopting 0.7% growth per annum and 1% growth per annum scenarios, which result in a 1.3 million people and 2 million people increase by 2040 respectively from 2012 levels, again following the assumptions adopted for planning purposes in the London water resources zone level (WRZ)
This paper has formulated and demonstrated with an illustrative case study a methodology for using nonstationary probabilistic climate projections to inform risk-based water resources management decisions
Summary
The increased awareness of the impacts of climate change on water resources [Kundzewicz et al, 2008; Vo€ro€smarty et al, 2000] has generated interest in new methodologies to help water resources managers deal with uncertain information from climate models [e.g., Brown et al, 2010; Groves et al, 2008a]. Water utility companies produce a water resources management plan every 5 years where they describe the actions they plan to take to ensure security of supply for the 25 years. These plans are produced in consultation with the Environment Agency (the environmental protection and regulation agency in England). This 5 year cycle provides a water governance structure within which the current state of knowledge about the hydrological regime, water demands, and management options can be revisited and plans can be modified and adapted . A simplified representation of the London WRZ is used in this study
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