Geospatial assessment of soil erosion in Chamba, Himachal Pradesh using RUSLE and GIS-based remote sensing

Abstract Soil erosion is a major environmental issue that adversely affects agricultural productivity, soil fertility, water quality, and reservoir sustainability, particularly in fragile mountainous regions such as the Chamba district of Himachal Pradesh, India. This study aims to quantify and map the spatial distribution of soil erosion using the Revised Universal Soil Loss Equation (RUSLE) integrated with remote sensing and GIS techniques. The analysis was performed using CRU rainfall data, FAO soil maps, ASTER DEM, and Landsat 8 satellite imagery to derive the five RUSLE factors: rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), crop management (C), and conservation practice (P). The estimated annual soil loss ranges from 0–5 Mg ha⁻ 1 yr⁻ 1 in low-risk zones to more than 80 Mg ha⁻ 1 yr⁻ 1 in highly vulnerable areas. The results reveal that 72.00% (4643.7 km 2 ) of the study area falls under the very severe erosion category, while 27.91% (1800.5 km 2 ) is classified under slight erosion. The remaining categories (moderate to severe) collectively account for less than 0.1% of the total area. High erosion rates are predominantly associated with steep slopes, intense rainfall, sparse vegetation, and inadequate conservation practices. The findings highlight critical erosion hotspots and provide a scientific basis for implementing targeted soil and water conservation strategies, thereby supporting sustainable land management and ecological restoration in the Himalayan region.

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Publication Details

Journal
Discover Geoscience
Published
2026-06-18
DOI
https://doi.org/10.1007/s44288-026-00592-5
Primary Topic
Soil erosion and sediment transport
Type
article
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article

Geospatial assessment of soil erosion in Chamba, Himachal Pradesh using RUSLE and GIS-based remote sensing

Vishwajeet Kumar, Teena Kuhade, Jitendra Rajput, Divyanshu Singh
Discover Geoscience
Soil erosion and sediment transport
article

Geospatial assessment of soil erosion in Chamba, Himachal Pradesh using RUSLE and GIS-based remote sensing

Vishwajeet Kumar, Teena Kuhade, Jitendra Rajput, Divyanshu Singh
article en

Abstract

Abstract Soil erosion is a major environmental issue that adversely affects agricultural productivity, soil fertility, water quality, and reservoir sustainability, particularly in fragile mountainous regions such as the Chamba district of Himachal Pradesh, India. This study aims to quantify and map the spatial distribution of soil erosion using the Revised Universal Soil Loss Equation (RUSLE) integrated with remote sensing and GIS techniques. The analysis was performed using CRU rainfall data, FAO soil maps, ASTER DEM, and Landsat 8 satellite imagery to derive the five RUSLE factors: rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), crop management (C), and conservation practice (P). The estimated annual soil loss ranges from 0–5 Mg ha⁻ 1 yr⁻ 1 in low-risk zones to more than 80 Mg ha⁻ 1 yr⁻ 1 in highly vulnerable areas. The results reveal that 72.00% (4643.7 km 2 ) of the study area falls under the very severe erosion category, while 27.91% (1800.5 km 2 ) is classified under slight erosion. The remaining categories (moderate to severe) collectively account for less than 0.1% of the total area. High erosion rates are predominantly associated with steep slopes, intense rainfall, sparse vegetation, and inadequate conservation practices. The findings highlight critical erosion hotspots and provide a scientific basis for implementing targeted soil and water conservation strategies, thereby supporting sustainable land management and ecological restoration in the Himalayan region.

Discover GeoscienceVol. 4(1)
Indian Council of Agricultural Research (IN), Indian Agricultural Research Institute (IN)
Life in Land
Openalex Percentile: Top 9%
Soil erosion and sediment transport
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Geospatial assessment of soil erosion in Chamba, Himachal Pradesh using RUSLE and GIS-based remote sensing — Vishwajeet Kumar, Teena Kuhade, et al. · Discover Geoscience (2026) | TGRS Research Map | TGRS