Stochastic Modeling of Extreme Precipitation: a Regional Approach
- Authors: Bolgov M.V.1, Filippova I.A.1, Trubetskova M.D.1, Osipova N.V.1
- 
							Affiliations: 
							- Water Problems Institute, Russian Academy of Sciences
 
- Issue: Vol 46, No Suppl 2 (2019)
- Pages: S1-S7
- Section: Water Resources and the Regime of Water Bodies
- URL: https://journals.rcsi.science/0097-8078/article/view/175312
- DOI: https://doi.org/10.1134/S0097807819080025
- ID: 175312
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Abstract
A generalized step-by-step statistical method for calculating the maximal precipitation sums of low probability is proposed. The method is applied to the case of daily precipitation for the Amur River basin. Refined statistical characteristics of maximum daily precipitation for the warm period are obtained. A map of daily precipitation of 1% exceedance probability is compiled over the territory of the Amur River. The obtained quantiles of the daily maximum precipitation are compared with probable maximum precipitation values obtained using WMO methodology.
About the authors
M. V. Bolgov
Water Problems Institute, Russian Academy of Sciences
														Email: trubets@mail.ru
				                					                																			                												                	Russian Federation, 							Moscow, 119333						
I. A. Filippova
Water Problems Institute, Russian Academy of Sciences
							Author for correspondence.
							Email: irinafil@yandex.ru
				                					                																			                												                	Russian Federation, 							Moscow, 119333						
M. D. Trubetskova
Water Problems Institute, Russian Academy of Sciences
							Author for correspondence.
							Email: trubets@mail.ru
				                					                																			                												                	Russian Federation, 							Moscow, 119333						
N. V. Osipova
Water Problems Institute, Russian Academy of Sciences
														Email: trubets@mail.ru
				                					                																			                												                	Russian Federation, 							Moscow, 119333						
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