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SAW and CF were applied for subbasins prioritization towards analysis of erosion susceptibility (ES) using morphometric parameters. • SWAT model applied for estimation of soil erosion and sediment yield using hydrological parameters.

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Soil erosion trend depends on effective land use and land cover dynamics since overwhelming population growth in tropical region. The objective of this paper is to assess potential mean annual soil erosion rate, and conversion of erosion class incorporate with land use and land cover change in plateau fringe, undulating and low land of Kangsabati basin using Revised Universal Soil Loss Equation (RUSLE) and multiple logistic regression (MLR). Both models denote potential mean soil erosion zone as 55% corresponds at low level in low land than medium level as 30% in undulating topography and high level as 15% in plateau fringe site. RUSLE indicates erosion rate increases with expanding area in degraded forest (169 ton ha −1 year −1 , 137 km 2 ), dense forest (134 ton ha −1 year −1 , 55 km 2 ) and settlement area (30 ton ha −1 year −1 , 105 km 2 ), whereas erosion rate decreases with reducing the area in barren land with laterite outcrop (− 154 ton ha −1 year −1 , − 93 km 2 ), double crop (− 40 ton ha −1 year −1 , − 201 km 2 ) and single crop yield (− 1 ton ha −1 year −1 , − 62 km 2 ) from 2002 to 2016. MLR predicts barren land with laterite outcrop and dense forest play a crucial role to determine the erosion susceptibility in plateau fringe, while degraded forest and single crop signify erosion susceptibility in undulating topography. Settlement and double crop are more significant in low land with proper validation. Model comparison depicts same class conversion finds out as 63.73% (low-to-low class, 41%) in low land, whereas high-to-low class finds in undulating topography (23%) and low-to-high class in plateau fringe (13%).

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Escalation of human-elephant conflict (HEC) in India threatens its Asian elephant (Elephas maximus) population and victimizes local communities. India supports 60% of the total Asian elephant population in the world. Understanding HEC spatial patterns will ensure targeted mitigation efforts and efficient resource allocation to high-risk regions. This study deals with the spatial aspects of HEC in Keonjhar forest division, where 345 people were killed and 5,145 hectares of croplands were destroyed by elephant attacks during 2001–2018. We classified the data into three temporal phases (HEC1: 2001–2006, HEC2: 2007–2012, and HEC3: 2013–2018), in order to (1) derive spatial patterns of HEC; (2) identify the hotspots of HEC and its different types along with the number of people living in the high-risk zones; and (3) assess the temporal change in the spatial risk of HEC. Significantly dense clusters of HEC were identified in Keonjhar and Ghatgaon forest ranges throughout the 18 years, whereas Champua forest range became a prominent hotspot since HEC2. The number of people under HEC risk escalated from 14,724 during HEC1 and 34,288 in HEC2, to 65,444 people during HEC3. Crop damage was the most frequent form of HEC in the study area followed by house damage and loss of human lives. Risk mapping of HEC types and high priority regions that are vulnerable to HEC, provides a contextual background for researchers, policy makers and managers.

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