Analysis of The Joint Impact of Synchronous Discharges in Estimating the Flood Risk: Case Study on Hron River

World Multidisciplinary Earth Sciences Symposium

Mitkova, Veronika Bacova^1 ; Halmova, Dana^1

Institute of Hydrology SAS, Dúbravská cesta 9, Bratislava

841 04, Slovakia^1

关键词: Anthropogenic climate changes;    Coincidence analysis;    Conditional probability distributions;    Conventional approach;    Dependency structures;    Distribution probability;    Statistical techniques;    Synchronous discharge;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/221/1/012034/pdf
DOI  :  10.1088/1755-1315/221/1/012034

来源: IOP

【 摘 要 】

The paper presents the methodology of bivariate statistical analysis of the joint impact of synchronous discharges in estimating the flood risk on Hron River and its tributary Slatina in Central Slovakia. Basic statistical analysis approach gives satisfactory results in the case of simple systems, for example, where the main river does not capture major tributaries. These conventional approaches may not give satisfactory results for the evaluation of flood risk in situations where floods occur on two or more rivers and join together at the same time. As input data mean daily discharges were used. Some Archimedean copula functions as a mathematical tool for joint as well as conditional probability distribution calculation of the synchronous variables were used. This class of copulas is popular in empirical applications for flexibility, easy construction and includes a whole suite of closed-form copulas that covers a wide range of dependency structures, including comprehensive and non-comprehensive copulas, radial symmetry and asymmetry, and asymptotic tail dependence and independence. The first part of the paper presents the preparation of the input data and choice of appropriate marginal probability distributions. The next part, presents the testing and selection of the appropriate copula function for the bivariate joint statistical analysis of the synchronous discharges. Tested Archimedes copula functions have achieved relatively equal calculated distribution probabilities. Probabilities calculated using the Gumbel-Hougaard copula function achieved the least error of the estimation. This copula function has been selected as the most appropriate for illustrating the joint distribution probability and consequently to determine the joint probability of occurrence of the synchronic discharges. The results showed that the joint probability of maximum discharges is relatively low, but not unlikely. In the context of climatic extreme events, statistical techniques such as event coincidence analysis will be relevant for investigating the impacts of anthropogenic climate change on human societies and ecosystems worldwide. The results obtained by the bivariate analysis of the variables which characterize the hydrological regime can contribute to a more reliable assessment of the flood risks.