Probability studies of floods |
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| Institution: | 1. Northeast Climate Science Center, University of Massachusetts Amherst, MA, United States;2. Dept. of Civil and Environmental Engineering, University of Massachusetts Amherst, MA, United States;1. College of Hydrology and Water Resources, Hohai University, Nanjing, China;2. Dept of Civil Engineering, The University of Hong Kong, Pokfulam, Hong Kong, China;1. State Key Laboratory of Water Resources & Hydropower Engineering Science, Wuhan University, 299 Bayi Road, Wuchang Distinct, Wuhan, Hubei 430072, China;2. Hubei Key Laboratory of Water System Science for Sponge City Construction, Wuhan University, Wuhan, China;3. NORCE Norwegian Research Centre, Bjerknes Centre for Climate Research, Bergen, Norway;4. Department of Geosciences, University of Oslo, P.O. Box 1047 Blindern, 0316 Oslo, Norway;1. Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA;2. Science Systems and Applications, Inc., Lanham, MD, USA;3. Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA;4. Science Applications International Corporation, Reston, VA, USA;5. Centre Regional AGRHYMET, Niamey, Niger;1. Earth System Science Interdisciplinary Center, University of Maryland, College Park, 5825 University Research Ct, College Park, MD 20740, USA;2. Joint Global Change Research Institute, Pacific Northwest National Laboratory and University of Maryland, College Park, MD 20740, USA;3. College of Environment and Resources, Fuzhou University, Fuzhou, Fujian 350116, China;1. School of Civil Engineering and Geosciences, Newcastle University, Newcastle Upon Tyne, NE1 7RU, UK;2. School of Water Resources and Hydro-power Engineering, Xi’an University of Technology, Xi’an, China, 710048 |
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| Abstract: | Floods are common hazards which recur at various frequencies and intensities. For rational planning of water resources development, the risks of floods should be determined in probabilistic terms. Many parts of the world have a sparse hydrometric network, however, and the records are often not very long. In this paper, two approaches that extract salient information from short-term records are presented and a method that estimates the probability distribution of flood characteristics for ungauged basins is also given. Studies were made using northern Ontario as an example. The experience gained in analysing the floods of this region can be applied profitably to those countries where hydrological data are limited. |
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