H025
Advancing the Estimation of Hydrometeorologic Extremes for Flood Preparedness in a Changing Climate
Session ID#: 160673
Session Description:
Flooding of high-risk structures such as dams and nuclear power plants has the potential to cause tremendous damage and loss of life. The magnitude of extreme floods can be estimated with Probable Maximum Precipitation (PMP), “the greatest depth of precipitation that is physically possible” obtained by scaling precipitation from severe historical storms, until the recent development of more physically-based approaches using the Weather and Forecasting (WRF) model. Alternatively, probabilistic flood hazard analysis allows the assessment of a wider range of hydrologic loading conditions, of which a deterministic maximum event such as the PMF is just one outcome. We invite submissions addressing traditional or model-based PMP/PMF estimation, the probability of PMP/PMF, uncertainty in PMP/PMF, paleoflood estimation, risk-informed decision making and precipitation/flood frequency estimation. This session will also explore flood risk implications of a warming climate including rainfall extremes and changing snowmelt patterns.
Index Terms:
1807 Climate impacts [HYDROLOGY]
1821 Floods [HYDROLOGY]
1854 Precipitation [HYDROLOGY]
4313 Extreme events [NATURAL HAZARDS]
Primary Convener: Emilie Gaelle Tarouilly, University of California Los Angeles, Los Angeles, CA, United States
Conveners: Conrad Wasko, University of New South Wales, Sydney, Australia and Kenneth Kunkel, North Carolina State University, North Carolina Institute for Climate Studies, Asheville, NC, United States
Student/Early Career Convener: Emilie Gaelle Tarouilly, University of California Los Angeles, Los Angeles, CA, United States
Applicability of Seamless 150-year climate simulations to continuous non-stationary 100-year basin rainfall in a changing climate over Japan (1057441)
Tomohiro Tanaka1, Yuki Kawai2 and Yasuto Tachikawa1, (1)Kyoto University, Department of Civil and Earth Resources Engineering, Graduate School of Engineering, Kyoto, Japan, (2)Mitsubishi UFJ Research and Consulting Co., Ltd., Osaka, Japan
Assessing the Potential Rice Damages of Extreme Floods in the Cambodian Floodplain of the Mekong River Under Future Climate and Dam Development (1070638)
Sophal Try1, Takahiro Sayama1, Sophea Rom Phy2, Ty Sok3, Steven Ly4 and Chantha Oeurng3, (1)Disaster Prevention Research Institute, Kyoto University, Kyoto, Japan, (2)Kyoto Unversity, Graudate School of Agriculture, Kyoto, Japan, (3)Institute of Technology of Cambodia, Phnom Penh, Cambodia, (4)Graduate School of Engineering, Kyoto University, Kyoto, Japan
Expected Changes in Monthly River Runoff Under CMIP5 Emission Scenarios. Case Study in Iowa, United States (1074989)
Felipe Quintero, University of Iowa, Iowa City, IA, United States, Alexander Michalek, University of Iowa, Civil and Environmental Engineering, Iowa City, IA, United States, Gabriele Villarini, University of Iowa, IIHR—Hydroscience & Engineering, Iowa City, IA, United States and Witold F Krajewski, University of Iowa, Iowa City, United States
Continental-Scale Mapping of Extreme Precipitation for Durations Ranging from Sub-Hourly to Monthly Using a Gridded Stochastic Dataset (1118147)
Andrew Fullhart, Southwest Watershed Research Center, Tucson, AZ, United States, Dave Goodrich, US Department of Agriculture, Tucson, United States, Menberu B. Meles, Agricultural Research Services, USDA, Tucson, United States, Guillermo Ponce-Campos, University of Arizona, Tucson, AZ, United States, Ryan McGehee, Purdue University, Agricultural & Biological Engineering, West Lafayette, United States, Paulo T. S. Oliveira, Federal University of Mato Grosso do Sul, Brasil, Campo Grande, Brazil, Cristiano Almeida, Federal University of Paraiba, João Pessoa, Brazil and José Carlos de Araújo, UFC Federal University of Ceará, Fortaleza, Brazil
Spatial-temporal Capability of IMERG Gridded Precipitation Dataset for Estimating Probable Maximum Precipitation (1125444)
Kenneth Ekpetere1, James Matthew Matthew Coll2, Xingong Li1, Jude Kastens3 and David B Mechem3, (1)University of Kansas, Lawrence, United States, (2)NOAA Affiliate, Lynker, Lawrence, United States, (3)University of Kansas, Lawrence, KS, United States
Comparison of Simulated Precipitation Data in South Korea based on the GCM and RCM (1140645)
Sunghun Kim1, Jihye Kwon1, Changsam Jeong2 and Jun-Haeng Heo1, (1)Yonsei University, School of Civil and Environmental Engineering, Seoul, South Korea, (2)Induk University, Department of Civil & Environmental Engineering, Seoul, Korea, Republic of (South)
Intensity-Duration-Frequency Curves using Nonstationary GEV model based on RCP scenarios. (1162782)
Heechul Kim1, Miru SEO1, Gyobeom Kim2 and Jun-Haeng Heo3, (1)Yonsei University, Seoul, Korea, Republic of (South), (2)Korea Environment Institute(KEI), Environmental Assessment Group, Sejong, South Korea, (3)Yonsei University, Department of Civil & Environmental Engineering, Seoul, South Korea
Projected Changes in Extreme Streamflow and Inland Flooding in the Mid-21st Century over Northeastern US Using Ensemble WRF-Hydro Simulations (1167944)
Sujan Pal1, Jiali Wang2, Jeremy Feinstein3, Eugene Yan4 and Veerabhadra Rao Kotamarthi1, (1)Argonne National Laboratory, Argonne, IL, United States, (2)Argonne National Laboratory, Argonne, United States, (3)Argonne National Labratory, Chicago, United States, (4)Argonne Natl Lab-Bldg 203, Argonne, IL, United States
Assessing Future Climate Change Impacts Using CMIP6 Projections to Design Climate Resilient Infrastructures in North Central Bangladesh (1170960)
Faruque Abdullah1, Wasif Bin Mamoon2, Akm Saiful Islam3, GM Tarekul Islam3 and Sujit Kumar Bala3, (1)Bangladesh University of Engineering and Technology, Department of Water Resources Engineering, Dhaka, Bangladesh, (2)Marquette University, Department of Civil, Construction and Environmental Engineering, Milwaukee, United States, (3)Bangladesh Institute of Water and Flood Management, Dhaka, Bangladesh
Can We Rely on Trend Test for Identifying Non-stationarity in Floods? (1176271)
Chandramauli Awasthi, North Carolina State University Raleigh, Raleigh, NC, United States, Brian J Reich, North Carolina State University Raleigh, Statistics, Raleigh, NC, United States and Sankar Arumugam, NC State University, Raleigh, NC, United States
Non-stationary extreme rainfall frequency analysis: the impact of separating storm intensities and arrival rate (1201584)
Declan O'Shea1, Rory Nathan1, Ashish Sharma2 and Conrad Wasko1, (1)University of Melbourne, Department of Infrastructure Engineering, Parkville, VIC, Australia, (2)University of New South Wales, School of Civil and Environmental Engineering, Sydney, NSW, Australia
On the need for non-stationarity in operational estimates of Probable Maximum Precipitation (1202021)
Johan Visser, University of New South Wales, Sydney, NSW, Australia, Seokhyeon Kim, Kyung Hee University, Department of Civil Engineering, Yongin, South Korea, Conrad Wasko, University of New South Wales, Sydney, Australia, Rory Nathan, University of Melbourne, Department of Infrastructure Engineering, Parkville, VIC, Australia and Ashish Sharma, University of New South Wales, School of Civil and Environmental Engineering, Sydney, NSW, Australia
Future Changes in Intensity and Frequency of Sub-daily and Daily Extreme Precipitation in the USFS Experimental Forests from Dynamically and Statistically Downscaled Simulations (1202909)
Anna M Jalowska, US Environmental Protection Agency Research Triangle Park, Durham, NC, United States, Devendra Amatya, USDA Forest Service, Center for National Forested Wetlands Research, Cordesville, United States, Sourav Mukherjee, USDA Forest Service Southern Research Station, Hot Springs National, AR, United States, Tanya Spero, US Environmental Protection Agency, Research Triangle Park, NC, United States, Jared Bowden, North Carolina State University, Applied Ecology, Raleigh, NC, United States, Geneva Marie Ely Gray, North Carolina State University at Raleigh, Raleigh, NC, United States, Megan Mallard, US EPA, Research Triangle Park, NC, United States, Gregory Tierney, ORISE, USEPA, Rtp, United States and Jeffrey Willison, US Environmental Protection Agency Research Triangle Park, Durham, United States
