caa a22 4500 46792239X CHVBK 20180406152920.0 cr unu---uuuuu 170328e20060501xx s 000 0 eng 10.1007/s00477-005-0017-2 doi (NATIONALLICENCE)springer-10.1007/s00477-005-0017-2 Improvement of overtopping risk evaluations using probabilistic concepts for existing dams [Elektronische Daten] [Hyun-Han Kwon, Young-Il Moon] Hydrologic risk analysis for dam safety relies on a series of probabilistic analyses of rainfall-runoff and flow routing models, and their associated inputs. This is a complex problem in that the probability distributions of multiple independent and derived random variables need to be estimated in order to evaluate the probability of dam overtopping. Typically, parametric density estimation methods have been applied in this setting, and the exhaustive Monte Carlo simulation (MCS) of models is used to derive some of the distributions. Often, the distributions used to model some of the random variables are inappropriate relative to the expected behaviour of these variables, and as a result, simulations of the system can lead to unrealistic values of extreme rainfall or water surface levels and hence of the probability of dam overtopping. In this paper, three major innovations are introduced to address this situation. The first is the use of nonparametric probability density estimation methods for selected variables, the second is the use of Latin Hypercube sampling to improve the efficiency of MCS driven by the multiple random variables, and the third is the use of Bootstrap resampling to determine initial water surface level. An application to the Soyang Dam in South Korea illustrates how the traditional parametric approach can lead to potentially unrealistic estimates of dam safety, while the proposed approach provides rather reasonable estimates and an assessment of their sensitivity to key parameters. Springer-Verlag, 2005 Dam safety nationallicence Overtopping probability nationallicence Nonparametric Monte Carlo simulation nationallicence Latin hypercube sampling nationallicence Bootstrap nationallicence Kwon Hyun-Han Department of Earth and Environmental Engineering, Columbia University, S.W. Mudd, Room 842A 500 West 120th Street, MC 4711, 10027, New York, NY, USA aut Moon Young-Il Department of Civil Engineering, University of Seoul, 130-743, Seoul, Korea aut Stochastic Environmental Research and Risk Assessment Springer-Verlag 20/4(2006-05-01), 223-237 1436-3240 20:4<223 2006 20 477 https://doi.org/10.1007/s00477-005-0017-2 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s00477-005-0017-2 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Kwon Hyun-Han Department of Earth and Environmental Engineering, Columbia University, S.W. Mudd, Room 842A 500 West 120th Street, MC 4711, 10027, New York, NY, USA aut NATIONALLICENCE 700 1- Moon Young-Il Department of Civil Engineering, University of Seoul, 130-743, Seoul, Korea aut NATIONALLICENCE 773 0- Stochastic Environmental Research and Risk Assessment Springer-Verlag 20/4(2006-05-01), 223-237 1436-3240 20:4<223 2006 20 477 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer