Year Established: 2015 Start Date: 2015-03-01 End Date: 2016-02-28
Total Federal Funds: $27,464 Total Non-Federal Funds: $55,874
Principal Investigators: Li Chen
Abstract: Although climate change has been shown to contribute to a rise in extreme weather events, its impact on flooding has not yet been fully addressed. Low-probability, high-risk (LPHR) floods can result in high fatality rates, substantial property damage, and drastic alterations to the environment, which makes them a major natural-disaster concern. The southwestern regions of the United States, such as southern Nevada, have become more vulnerable to extreme flood conditions due to increasing populations and aging infrastructure. Therefore, studying future LPHR flooding scenarios in these regions is critical in order for water managers and policy makers to identify and mitigate the risks associated with extreme floods. Because precipitation is the driver for flood events, this study will investigate historical and future LPHR precipitation characteristics and derive future flood frequency based on precipitation statistical analysis. Both intensity-duration-frequency (IDF) relationships and single event characteristics will be examined for the historical data. To obtain future precipitation scenarios, a stochastic precipitation model will be developed based on global climate model and/or regional climate model (GCM/RCM) projections. Both natural and human-induced climate oscillations in the southwestern United States will be considered in order to improve the representation of the multiscale temporal variability of precipitation. Two approaches are proposed in this study to develop future flood frequency based on precipitation input. The first approach will correlate the statistical characteristics of historical precipitation and flood frequency using a multiple linear regression analysis. This correlation will then be extrapolated to future scenarios based on the projected precipitation. The second approach adopts a continuous rainfall-runoff hydrologic simulation in a Monte Carlo simulation framework. Because the future precipitation data series is provided by the stochastic precipitation model, the simulated flow can generate the frequency of future floods with quantitative uncertainties. Therefore, future LPHR flood occurrences can be obtained from future flood frequencies. The methodology developed in this project will be broadly applicable to arid and semiarid regions. The results of this project will advance our understanding of future flood potential due to climate change, particularly the occurrence of LPHR events in the southwestern United States. The results will also allow flood control managers and water resources policy makers to better understand the impacts of climate change on water resources. The project is also expected to foster new expertise and revenues for Desert Research Institute (DRI) in water resources research.