Análisis de Frecuencia de Inundaciones a lo largo de la Cuenca del Río Bagmati en el Distrito de Khagaria, Bihar, utilizando el Método de Gumbel y la Distribución Log Pearson Tipo III

Flood frequency analysis is an essential hydrological method for determining the size and recurrence intervals of flood events, especially in areas vulnerable to flooding. One such area where frequent flooding has a major effect on the environment, the economy, and local inhabitants is Khagaria in Bihar, India. This study uses the Log-Pearson Type III Distribution and the Gumbel Extreme Value Distribution to analyze historical discharge data spanning 40 years (1985–2024) from the Bagmati River Basin in Khagaria District. Important statistical measures, including the mean, standard deviation, and skewness, are used to predict catastrophic hydrological events and to assess flood magnitudes for various return periods. The findings show that while both methods effectively model catastrophic floods, the Log-Pearson Type III Distribution more accurately captures variability at longer return periods. The results indicate the highest recorded flood discharge of 30734.001 m³/s in 2023 and the lowest discharge of 884.77 m³/s in 2011. The analysis calculates the anticipated inundation for the return periods of 2, 10, 25, 50, 100, and 1000 years. The expected flood for the two-year return period is 2833.731 cumecs according to the Gumbel distribution, while the Log-Pearson III distribution predicts a flood of 1169.9 cumecs. It has been noted that Gumbel estimated higher values for all of the aforementioned return periods, except for 1000 years, where Log Pearson III predicted significantly higher values. The 2-year flood event has a 50% possibility of occurrence in any year with average impacts, while severe flooding events are predicted at longer return periods, with discharge values exceeding the river’s carrying capacity. The results highlight the urgent need for proactive floodplain management, infrastructure planning, and risk reduction strategies by illustrating the region's increasing flood frequency and severity. This study provides valuable information for sustainable flood management, hydrological modelling, and infrastructure design in the area under study.