Risk-based flood protection decisions in the context of climatic variability and change
<p>Flood events have caused detrimental impacts to humans' lives and anthropogenic climate change is anticipated to exacerbate the impact. It has been recognized that a long-term planning through risk-based optimization of flood defence will lead to a cost-effective solution for managing...
| Hoofdauteur: | |
|---|---|
| Andere auteurs: | |
| Formaat: | Thesis |
| Taal: | English |
| Gepubliceerd in: |
2016
|
| Onderwerpen: |
| _version_ | 1826298712844926976 |
|---|---|
| author | Rehan, B |
| author2 | Hall, J |
| author_facet | Hall, J Rehan, B |
| author_sort | Rehan, B |
| collection | OXFORD |
| description | <p>Flood events have caused detrimental impacts to humans' lives and anthropogenic climate change is anticipated to exacerbate the impact. It has been recognized that a long-term planning through risk-based optimization of flood defence will lead to a cost-effective solution for managing flood risk, but the prevailing assumption of stationarity may lead to an erroneous solution. In attempt to investigate the potential impact of the uncertain underlying statistical characteristics of extreme flow series to flood protection decisions, this research explores risk-based flood protection decisions in the context of climatic variability and change. In particular, the implications of persistence series and nonstationarity were investigated through hypothetical and real case studies. Monte Carlo simulation approach was adopted to capture the uncertainty due to the natural variability. For persistence model, AR(1) was integrated with the GEV model to simulate extreme flow series with persistence. To test the effects of nonstationary, GEV models with a linear location parameter and time as covariate were adopted. Rational decision makers' behaviours were simulated through a designed decision analysis framework. One of the main findings from the research is that the traditional stationary assumption should remain the basic assumption due to insignificant difference of the decisions’ economic performance. However, exploration of the nonstationarity assumption enabled identification of options that are robust to climate uncertainties. It is also found that optimized protection of combined measures of flood defence and property-level protection may provide a cost-effective solution for local flood protection. Overall, the simulation and case studies enlighten practitioners and decision makers with new evidence, and may guide to practical enhancement of long term flood risk management decision making.</p> |
| first_indexed | 2024-03-07T04:51:01Z |
| format | Thesis |
| id | oxford-uuid:d4f3ecc7-0a85-46fe-a66c-4251ddbca83a |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T04:51:01Z |
| publishDate | 2016 |
| record_format | dspace |
| spelling | oxford-uuid:d4f3ecc7-0a85-46fe-a66c-4251ddbca83a2022-03-27T08:22:29ZRisk-based flood protection decisions in the context of climatic variability and changeThesishttp://purl.org/coar/resource_type/c_db06uuid:d4f3ecc7-0a85-46fe-a66c-4251ddbca83aFlood risk managementNonstationarity in flood probabilityEnglishORA Deposit2016Rehan, BHall, J<p>Flood events have caused detrimental impacts to humans' lives and anthropogenic climate change is anticipated to exacerbate the impact. It has been recognized that a long-term planning through risk-based optimization of flood defence will lead to a cost-effective solution for managing flood risk, but the prevailing assumption of stationarity may lead to an erroneous solution. In attempt to investigate the potential impact of the uncertain underlying statistical characteristics of extreme flow series to flood protection decisions, this research explores risk-based flood protection decisions in the context of climatic variability and change. In particular, the implications of persistence series and nonstationarity were investigated through hypothetical and real case studies. Monte Carlo simulation approach was adopted to capture the uncertainty due to the natural variability. For persistence model, AR(1) was integrated with the GEV model to simulate extreme flow series with persistence. To test the effects of nonstationary, GEV models with a linear location parameter and time as covariate were adopted. Rational decision makers' behaviours were simulated through a designed decision analysis framework. One of the main findings from the research is that the traditional stationary assumption should remain the basic assumption due to insignificant difference of the decisions’ economic performance. However, exploration of the nonstationarity assumption enabled identification of options that are robust to climate uncertainties. It is also found that optimized protection of combined measures of flood defence and property-level protection may provide a cost-effective solution for local flood protection. Overall, the simulation and case studies enlighten practitioners and decision makers with new evidence, and may guide to practical enhancement of long term flood risk management decision making.</p> |
| spellingShingle | Flood risk management Nonstationarity in flood probability Rehan, B Risk-based flood protection decisions in the context of climatic variability and change |
| title | Risk-based flood protection decisions in the context of climatic variability and change |
| title_full | Risk-based flood protection decisions in the context of climatic variability and change |
| title_fullStr | Risk-based flood protection decisions in the context of climatic variability and change |
| title_full_unstemmed | Risk-based flood protection decisions in the context of climatic variability and change |
| title_short | Risk-based flood protection decisions in the context of climatic variability and change |
| title_sort | risk based flood protection decisions in the context of climatic variability and change |
| topic | Flood risk management Nonstationarity in flood probability |
| work_keys_str_mv | AT rehanb riskbasedfloodprotectiondecisionsinthecontextofclimaticvariabilityandchange |