Author:
Gabriel Rosemary Kiama,Fan Yurui
Abstract
This study analyzed the multivariate flood risk for the river Thames at Kingston based on historical flood data from the National River Flow Archive (NRFA) website. The bivariate risk analysis framework was prepared from the joint return periods of the peak flow (m3/s) and 3-day annual maximum flow (m3/s) flood pair. A total of 137 samples of flood pairs from 1883 to 2019 were adopted for risk analysis. The multivariate return periods were characterized depending on the quantification of the bivariate flood frequency analysis of the pair through copulas methods. The unknown parameter of each copula was estimated using the method-of-moment (MOM) estimator based on Kendall’s tau inversion, in which the Clayton copula performed best to model the dependence of the two flood variables. Then, the bivariate hydrologic risk was characterized based on the joint return period in AND, established from the Clayton copula method. The results reveal that the flood pair would keep a constant hydrologic risk value for some time then moderately decrease as the 3-day AMAX flow increases from 700 m3/s. This hydrologic risk indicator was analyzed under four service time scenarios and three peak flows whose return periods were positioned at 50, 100, and 150 years. The outcomes from the bivariate risk analysis of the flood pairs can be used as decision support during the design of flood defenses and hydraulic facilities.
Subject
Water Science and Technology,Aquatic Science,Geography, Planning and Development,Biochemistry
Reference35 articles.
1. Study of Climate Change Impact on Flood Frequencies: A Combined Weather Generator and Hydrological Modeling Approach*
2. Multivariate hydrological frequency analysis using copulas
3. CRED Crunch 64—Extreme Weather Events in Europehttps://cred.be/sites/default/files/CredCrunch64.pdf
4. CRED Crunch 53—Flash Floods—Sharing of Field Experience—Keralahttps://cred.be/sites/default/files/CREDCrunch53N.pdf
5. Decision support system for flood risk analysis for the River Thames, United Kingdom: Decision support systems;Sanders;Photogramm. Eng. Remote Sens.,2000
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