Author(s): Achala Singh; Priyank J. Sharma; Ramesh S. V. Teegavarapu
Linked Author(s): Priyank J. Sharma
Keywords: Flood Frequency Analysis Annual Maxima Series Multivariate analysis Copula analysis Semi-arid River basin
Abstract: Flood frequency analysis (FFA) is typically conducted using univariate analysis of peaks, relying on the best-fit distribution of annual maxima series (AMS). However, additional flood characteristics such as volume and duration are crucial, providing a more comprehensive understanding of flood events. This study performs both univariate and bivariate FFA. Further, it investigates the joint behavior of key pairs of flood characteristics specifically peak volume (P-V), volume duration (V-D), and peak duration (P-D) across two major semi-arid river basins in India: the Sabarmati and Mahi. By analyzing these bivariate relationships, the research aims to provide deeper insights into the dynamics of flooding in these regions, ultimately enhancing the understanding of flood risks and informing effective management practices. The volume and duration of flood peaks are extracted, and distribution fitting is performed to estimate the return period calculations for these characteristics. The study employs the Archimedean copula family to find the best-fitting copula for bivariate analysis. Furthermore, joint return period estimation allows for comparing the univariate and bivariate return periods of the flood characteristics, providing a comprehensive understanding of their relationships. A thorough correlation analysis reveals a strong dependence between peak flow and volume, as well as between volume and duration, with the latter showing slightly greater dependency than peak flow and duration, which exhibits the weakest correlation. The Clayton and Gumbel copulas are noted as the most suitable options for modeling the dependencies between flood characteristics in the Mahi and Sabarmati basins, respectively. This study underscores the critical importance of understanding flood characteristics in risk assessments, directly supporting the achievement of Sustainable Development Goals (SDGs) related to water management.
Year: 2025