Risk-based water resources planning: Incorporating probabilistic nonstationary climate uncertainties
We 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 Project...
| मुख्य लेखकों: | , , , , , |
|---|---|
| स्वरूप: | Journal article |
| भाषा: | English |
| प्रकाशित: |
American Geophysical Union
2014
|
| _version_ | 1826308658163613696 |
|---|---|
| author | Borgomeo, E Hall, JW Fung, F Watts, G Colquhoun, K Lambert, C |
| author_facet | Borgomeo, E Hall, JW Fung, F Watts, G Colquhoun, K Lambert, C |
| author_sort | Borgomeo, E |
| collection | OXFORD |
| description | We 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. |
| first_indexed | 2024-03-07T07:22:35Z |
| format | Journal article |
| id | oxford-uuid:40587941-f60e-41d6-bda4-d8b24625db9d |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T07:22:35Z |
| publishDate | 2014 |
| publisher | American Geophysical Union |
| record_format | dspace |
| spelling | oxford-uuid:40587941-f60e-41d6-bda4-d8b24625db9d2022-10-28T11:08:53ZRisk-based water resources planning: Incorporating probabilistic nonstationary climate uncertaintiesJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:40587941-f60e-41d6-bda4-d8b24625db9dEnglishSymplectic Elements at OxfordAmerican Geophysical Union2014Borgomeo, EHall, JWFung, FWatts, GColquhoun, KLambert, CWe 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. |
| spellingShingle | Borgomeo, E Hall, JW Fung, F Watts, G Colquhoun, K Lambert, C Risk-based water resources planning: Incorporating probabilistic nonstationary climate uncertainties |
| title | Risk-based water resources planning: Incorporating probabilistic nonstationary climate uncertainties |
| title_full | Risk-based water resources planning: Incorporating probabilistic nonstationary climate uncertainties |
| title_fullStr | Risk-based water resources planning: Incorporating probabilistic nonstationary climate uncertainties |
| title_full_unstemmed | Risk-based water resources planning: Incorporating probabilistic nonstationary climate uncertainties |
| title_short | Risk-based water resources planning: Incorporating probabilistic nonstationary climate uncertainties |
| title_sort | risk based water resources planning incorporating probabilistic nonstationary climate uncertainties |
| work_keys_str_mv | AT borgomeoe riskbasedwaterresourcesplanningincorporatingprobabilisticnonstationaryclimateuncertainties AT halljw riskbasedwaterresourcesplanningincorporatingprobabilisticnonstationaryclimateuncertainties AT fungf riskbasedwaterresourcesplanningincorporatingprobabilisticnonstationaryclimateuncertainties AT wattsg riskbasedwaterresourcesplanningincorporatingprobabilisticnonstationaryclimateuncertainties AT colquhounk riskbasedwaterresourcesplanningincorporatingprobabilisticnonstationaryclimateuncertainties AT lambertc riskbasedwaterresourcesplanningincorporatingprobabilisticnonstationaryclimateuncertainties |