Soil loss through erosion and its subsequent deposition is considered as an important challenge for watersheds. In this paper, attempt has been made to integrate the Revised Universal Soil Loss Equation, rainfall climatology from merged IMD gauge-TRMM (1998–2015) and soil hydraulic parameters to delineate the highly susceptible zones of the Kosi River Basin (KRB), Bihar, India for soil erosion assessment and watershed prioritization. The soil hydraulic parameters are calculated by using the ROSETTA model. Afterwards, the analytical hierarchy process based on multi-criteria evaluation method (AHP-MCE) was employed to assign the weighting to each factor (Soil erosion, Compound Factor, Field Capacity) depending on their erosion potential. Weighted overlay analysis is then performed to generate the watershed prioritization map for soil and water conservation. The overall findings suggest that the sub-watersheds 5, 8 and 7 required utmost attention and conservative measures because of their high erodibility characteristics.

Analysis of spatial and temporal changes of long-term precipitation and extreme precipitation distribution at a local scale is very important for the prevention and mitigation of water-related disasters. In the present study, we have analyzed the long-term trend of 116 years (1901–2016) of precipitation and distribution of extreme precipitation index over the Kosi River Basin (KRB), which is one of the frequent flooding rivers of India, using the 0.25° × 0.25° resolution gridded precipitation datasets obtained from the Indian Meteorological Department (IMD), India. The non-parametric Mann–Kendall trend test together with Sen’s slope estimator was employed to determine the trend and the magnitude of the trend of the precipitation time series. The annual and monsoon seasons revealed decreasing trends with Sen’s slope values of −1.88 and −0.408, respectively. For the extreme indices viz. R10 and R20 days, a decreasing trend from the northeastern to the southwest part of the basin can be observed, whereas, in the case of highest one-day precipitation (RX1 day), no clear trend was found. The information provided through this study can be useful for policymakers and may play an important role in flood management, runoff, and understanding related to the hydrological process of the basin. This will contribute to a better understanding of the potential risk of changing rainfall patterns, especially the extreme rainfall events due to climatic variations.