Influence of land use activities on predicted soil loss in a semi-arid river basin

ABSTRACT Soil loss due to land transformations is a serious issue confronting the globe nowadays. The research's main focus was to predict future land use and land cover (LULC) and quantify soil loss, which is exacerbated by excessive rainfall following uneven topography, intensive agriculture, and a lack of adequate watershed management strategies. The Landsat satellite data were classified using maximum likelihood algorithm, and future LULC (2030 and 2040) was quantified using TerrSet Land Change Modeler through Markov Chain Model. In addition, the RUSLE was applied to estimate soil loss based on LULC data from various years, and the results were evaluated using sediment observation data. In this research, the LS-factor has been quantified by employing open-source digital elevation models (DEMs) (SRTM, ASTER, MERIT, AW3D30, NASADEM, CARTOSAT, and TanDEM-X). Furthermore, hypsometry analysis was carried out to assess erosion vulnerability at the sub-watershed. The results showed that SRTM 30-m DEM-based soil loss corresponds to observation. Moreover, soil loss is estimated at 16.55 t/ha/year for 2015, whereas future soil loss may be reduced to 14.51 and 14.46 t/ha/year in 2030 and 2040, respectively.

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Publication Details

Journal
Journal of Hydroinformatics
Published
2025-02-01
DOI
https://doi.org/10.2166/hydro.2025.216
Citations
21
Primary Topic
Soil erosion and sediment transport
Type
article
Field-Weighted Citation Impact
24.91
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article

Influence of land use activities on predicted soil loss in a semi-arid river basin

Luc Cimusa Kulimushi, Vikram Singh, Adeyemi Oludapo Olusola, Sudhir Kumar Singh et al.
21 citations
Journal of Hydroinformatics
Soil erosion and sediment transport
24.91
article

Influence of land use activities on predicted soil loss in a semi-arid river basin

Luc Cimusa Kulimushi, Vikram Singh, Adeyemi Oludapo Olusola, Sudhir Kumar Singh, Kishan Singh Rawat, Padam Jee Omar, Keval H. Jodhani, Siham Acharki, Pandurang Choudhari, Nitesh Gupta, Nirmal Kumar
article en
21 citations

Abstract

ABSTRACT Soil loss due to land transformations is a serious issue confronting the globe nowadays. The research's main focus was to predict future land use and land cover (LULC) and quantify soil loss, which is exacerbated by excessive rainfall following uneven topography, intensive agriculture, and a lack of adequate watershed management strategies. The Landsat satellite data were classified using maximum likelihood algorithm, and future LULC (2030 and 2040) was quantified using TerrSet Land Change Modeler through Markov Chain Model. In addition, the RUSLE was applied to estimate soil loss based on LULC data from various years, and the results were evaluated using sediment observation data. In this research, the LS-factor has been quantified by employing open-source digital elevation models (DEMs) (SRTM, ASTER, MERIT, AW3D30, NASADEM, CARTOSAT, and TanDEM-X). Furthermore, hypsometry analysis was carried out to assess erosion vulnerability at the sub-watershed. The results showed that SRTM 30-m DEM-based soil loss corresponds to observation. Moreover, soil loss is estimated at 16.55 t/ha/year for 2015, whereas future soil loss may be reduced to 14.51 and 14.46 t/ha/year in 2030 and 2040, respectively.

Journal of HydroinformaticsVol. 27(2)
Babasaheb Bhimrao Ambedkar University (IN), Nirma University (IN), University of Allahabad (IN), University of Mumbai (IN), York University (CA), Abdelmalek Essaâdi University (MA), University of Lay Adventists of Kigali (RW), Université Catholique de Bukavu (CD), Université Mohammed VI Polytechnique (MA), Graphic Era University (IN)
Openalex Percentile: Top 0%
Soil erosion and sediment transport
24.91
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