Year: 2025
Type: article
Abstract: Due to recent climate change, the Teesta River Basin is severely affected by extreme hydrological events like floods. The recent flood events in this river affected millions of people residing in this catchment area across India and Bangladesh. In this present study, the univariate and copula-based multivariate flood frequency model is analysed to estimate the flood magnitude with different return periods using long-term time series data. The result shows that the univariate model overestimates the flood magnitude compared to the copula-based flood frequency model as it is associated with different flood variables like flood peak, volume, and duration. Four copula families are chosen for multivariate flood frequency modelling. From the statistical analysis, Gumbel-Hougaard and Frank copula families are chosen for the best fit joint distribution of flood variables.
Author: Abhranil Adak
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4409431235