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Sensitivity of Probable Maximum Flood in a Changing Environment
Author(s) -
Gangrade Sudershan,
Kao ShihChieh,
Naz Bibi S.,
Rastogi Deeksha,
Ashfaq Moetasim,
Singh Nagendra,
Preston Benjamin L.
Publication year - 2018
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/2017wr021987
Subject(s) - environmental science , hydrometeorology , climate change , antecedent moisture , flood myth , precipitation , climatology , hydrology (agriculture) , flood forecasting , drainage basin , storm , land cover , land use , meteorology , runoff curve number , geography , geology , oceanography , cartography , geotechnical engineering , archaeology , civil engineering , engineering
With likely increases in probable maximum precipitation (PMP) in a changing environment, critical infrastructures such as major reservoirs and nuclear power plants are subject to elevated risk. To understand how factors such as PMP variability, climate change, land use land cover (LULC) change, antecedent soil moisture conditions, and reservoir storage may individually or jointly affect the magnitude of probable maximum flood (PMF), we conducted integrated hydrometeorological simulations involving both the Weather Research Forecasting model and the distributed hydrologic model (DHSVM) over the Alabama‐Coosa‐Tallapoosa (ACT) River Basin in the southeastern United States. A total of 120 relative humidity‐maximized PMP storms under historic and projected future climate conditions were used to drive DHSVM in current and projected future LULC conditions. Overall, PMP and PMF are projected to increase significantly over the ACT River Basin. Sources of meteorological forcing data sets and climate change were found to be the most sensitive factors affecting PMF, followed by antecedent soil moisture, reservoir storage, and then LULC change. The ensemble of PMP and PMF simulations, along with their sensitivity, allows us to better quantify the potential risks associated with hydroclimatic extreme events to critical infrastructures for energy‐water security.