Fluvial floods are commonly studied as an occurrence at the level of a specific basin and are speculated to be closely related to the basin's morphometry. It is possible to identify and rank sub-basins based on how susceptible they are to fluvial flooding events using morphometric criteria. However, one of the key causes that triggers fluvial flooding is the increase in precipitation extremes and changes to their patterns. In this study, influence of morphometric factors and extreme precipitation events on the hydrological responses of the Brahmani River, India as well as their sensitivity to fluvial flooding, are investigated to identify the most vulnerable sub-basin in a catchment. The morphometric parameters were calculated from a digital elevation model (DEM), and the change in trend of extreme precipitation indices was detected using precipitation data of period 1991 to 2021. Furthermore, the Standardized Precipitation Index (SPI) was used to determine the frequency of wet cycles on time scale of 1, 3, 12, and 24 months, as well as their link to fluvial flooding. The two sub-basins of the catchment that are most vulnerable to river flooding are recognised as Noamundi and Gomlai based on morphometric criteria. However, analysis of SPI and extreme precipitation indices showed that the Jenapur sub-basin is the most vulnerable to flooding. It is also corroborated with analytic hierarchy process (AHP) based weighted overlay analysis and historical flood records. The outcomes will assist researchers in better understanding the mechanisms causing flooding in the Brahamni River Basin and in developing flood mitigation practices for the most vulnerable Jenapur sub-basin.

河流洪水通常被研究为特定盆地水平的发生，并推测与盆地的形态密切相关。可以使用形态测量标准根据子流域对河流洪水事件的敏感程度来识别子流域并对其进行排名。然而，引发河流洪水的关键原因之一是极端降水的增加及其模式的变化。在这项研究中，研究了形态因素和极端降水事件对印度婆罗门河水文响应的影响及其对河流洪水的敏感性，以确定流域中最脆弱的子流域。形态参数是根据数字高程模型（DEM）计算的，利用1991年至2021年的降水数据检测极端降水指数的变化趋势。此外，利用标准化降水指数（SPI）确定1、3、12和24年时间尺度上的湿循环频率。月，以及它们与河流洪水的联系。根据形态测量标准，流域内最容易遭受河流洪水影响的两个子流域被认为是诺阿蒙迪 (Noamundi) 和戈姆莱 (Gomlai)。然而，SPI和极端降水指数分析表明，杰纳普尔次流域最容易遭受洪水侵袭。它还通过基于加权叠加分析和历史洪水记录的层次分析法 (AHP) 得到证实。