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India, a subtropical country, also has relatively more environmental problems because of intense rainfall that occurs quickly, as well as other natural and man-made causes of soil degradation. The use of predictive models in GIS is observed beneficial for computing the virgin net soil erosion as well as deposition. Thus, the study aims to evaluate the spatial long-term average annual soil erosion (gross soil erosion rate), net soil erosion as well as a deposition for the east-flowing Cauvery River Basin (CRB) using RUSLE integrated with the TLA-SDR model in Geographic Information System (GIS) at recent (2020 to 2022) periods. The estimation of gross soil erosion rates (A) ranges between 0 and 94,194.4 t h−1 year−1, mean of ~ 223 t h−1 year−1. The sediment yield (SY) of CRB varies from 0 to 10,895.4 t h−1 year−1 with a mean of 26 t h−1 year−1. Moreover, the transport capacity (TC) of CRB varies between 0 and 5,339,136 t h−1 year−1, with a mean of 16 t h−1 year−1. Further, net erosion is estimated with TC and deposition which has an average value of ~ 4.5 t ha−1 year−1 (i.e., ~ 2% of the gross erosion), of which 1.15% of CRB shows very severe erosion while 56.68% shows high deposition. The study also addresses the effect of various LULC types on soil loss and reveals that barren rocks have the highest soil loss, followed by forest, build-up, barren land, agricultural land, and plantation. Likewise, the study assesses whether rapid climate change may exacerbate erosion rates and concludes that greater erosion rates are recorded with rising rainfall. Additionally, when comparing the total erosion to total sediment yield rate of CRB with major basins like Ganga (GBA) and Kosi (KB), signifying the topographical, climatic as well as tectonic setup of the region. The study's findings will be an important tool for decision-makers as they execute management plans over the CRB, and this technique will used broadly to identify management methods in river catchments worldwide. [ABSTRACT FROM AUTHOR]

Soil erosion inventory of a river basin is vital for effective soil conservation and sustainable development considering the ongoing Global change. In the current study, gross soil erosion rates (A) are estimated for a mountainous river in a tropical climate, the Karamana River Basin (KRB), southern India by utilizing the Revised Universal Soil Loss Equation (RUSLE). The RUSLE model computes 'A', as a product function of five variables; rainfall erosivity (R), soil erodibility (K), topographic factor (LS), crop management factor (C), and erosion control practice factor (P). To compute these five parameters, the digital elevation model, slope, normalized vegetation index (NDVI), rainfall and land use/land cover (LULC) are used along with the texture data of soil samples collected from KRB. The estimated A values range between 0 to 738.44 t ha−1 year−1, with an average of 10.22 t ha−1 year−1 whereas the sediment yield (SY) estimated by utilizing the sediment delivery ratio (SDR) model ranges between 0 to 246.68 t ha−1 year−1 with an average of 1.58 t ha−1 year−1 for KRB. For further validation, a soil erosion potential index (SEPI) map is developed to identify the soil erosion-prone zones of KRB using the geo-environmental thematic maps following the analytic hierarchy process (AHP). Finally, rainfall impacts on soil erosion are evaluated and quantified for KRB, considering the recent marked variations in rainfall that are induced by the extreme climatic events (cyclones/high rainfall/floods) along the West coast of India. The outcome of this study suggests that increasing rainfall by one standard deviation of the long-term average causes a significant increase in low and medium soil erosion regions. [ABSTRACT FROM AUTHOR]