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Geospatial Appraisal of Gully Erosion Vulnerability in the Rarh Bengal of India through Analyzing the Multiple Discriminating Factors

Author

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  • Biraj Kanti Mondal

    (Department of Geography, Netaji Subhas Open University, Kolkata 700064, West Bengal, India)

  • Tanmoy Basu

    (Department of Geography, Katwa College, Katwa, Purba Barddhaman, West Bengal 713130, India)

  • Malini Biswas

    (Department of Geography, Netaji Subhas Open University, Kolkata 700064, West Bengal, India)

  • Ming-An Lee

    (Department of Environmental Biology Fisheries Science, National Taiwan Ocean University, 2 Pei-Ning Rd., Keelung 20224, Taiwan)

Abstract

This study aims to determine the degree and vulnerability of gully erosion and related soil erosion in the Birbhum district of West Bengal, India. Composite maps of gully erosion susceptibility were created using sophisticated geospatial methods and remotely sensed satellite data. The normalized indicator values were obtained using factor analysis of the 2001 data. Gully erosion during the monsoon season was the main cause of the considerable loss of lateritic soil cover in the Rampurhat-I and Bolpur-Santiniketan blocks, according to the analysis, which also showed a strong relationship between soil erosivity and other influencing factors. Gully erosion impacted 69.81 square kilometers (20.59%) of Bolpur-Santiniketan, primarily in the southeast and northwest, and 68.97 square kilometers (23.45%) of Rampurhat-I, primarily in the southwest and northwest. The topographic wetness index showed the most variability, accounting for 77% and 74% of the erosion variance, respectively, with seven major components. The Rampurhat-I and Bolpur-Santiniketan susceptibility indices ranged from 0.833 to -0.772 and 0.756 to -1.060, respectively. Significant agricultural land loss (from 165.54 to 128.44 square kilometers) in Rampurhat-I and the existence of 26.98 square km of badlands in Bolpur-Santiniketan were also noted by the study, even though places like Ballavpur still had deep forest cover. Land use, land cover, and landholding sizes have all been greatly impacted by the rising rate of soil erosion, particularly in places prone to gullies. Finding hotspots for gully erosion, charting its severity, and making accurate predictions can help guide initiatives to reduce soil loss and degradation, promoting environmentally friendly farming methods and sustainable land management in the area.

Suggested Citation

  • Biraj Kanti Mondal & Tanmoy Basu & Malini Biswas & Ming-An Lee, 2025. "Geospatial Appraisal of Gully Erosion Vulnerability in the Rarh Bengal of India through Analyzing the Multiple Discriminating Factors," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 12(5), pages 1943-1999, May.
  • Handle: RePEc:bjc:journl:v:12:y:2025:i:5:p:1943-1999
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    References listed on IDEAS

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    1. Hamed Ahmadpour & Ommolbanin Bazrafshan & Elham Rafiei-Sardooi & Hossein Zamani & Thomas Panagopoulos, 2021. "Gully Erosion Susceptibility Assessment in the Kondoran Watershed Using Machine Learning Algorithms and the Boruta Feature Selection," Sustainability, MDPI, vol. 13(18), pages 1-24, September.
    2. Sandipta Debanshi & Swades Pal, 2020. "Assessing gully erosion susceptibility in Mayurakshi river basin of eastern India," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(2), pages 883-914, February.
    3. Ion Ionita & Michael Fullen & Wojciech Zgłobicki & Jean Poesen, 2015. "Gully erosion as a natural and human-induced hazard," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 79(1), pages 1-5, November.
    4. Karen C Seto & Michail Fragkias & Burak Güneralp & Michael K Reilly, 2011. "A Meta-Analysis of Global Urban Land Expansion," PLOS ONE, Public Library of Science, vol. 6(8), pages 1-9, August.
    5. Li, Baibing & Martin, Elaine B. & Morris, A. Julian, 2002. "On principal component analysis in L1," Computational Statistics & Data Analysis, Elsevier, vol. 40(3), pages 471-474, September.
    6. Max Engelhart, 1941. "The analysis of variance and covariance techniques in relation to the conventional formulas for the standard error of a difference," Psychometrika, Springer;The Psychometric Society, vol. 6(4), pages 221-233, August.
    7. Álvaro Gómez-Gutiérrez & Christian Conoscenti & Silvia Angileri & Edoardo Rotigliano & Susanne Schnabel, 2015. "Using topographical attributes to evaluate gully erosion proneness (susceptibility) in two mediterranean basins: advantages and limitations," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 79(1), pages 291-314, November.
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