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Chemical weathering and gully erosion causing land degradation in a complex river basin of Eastern India: an integrated field, analytical and artificial intelligence approach

Author

Listed:
  • Subodh Chandra Pal

    (The University of Burdwan)

  • Rabin Chakrabortty

    (The University of Burdwan)

  • Alireza Arabameri

    (Tarbiat Modares University)

  • M. Santosh

    (China University of Geosciences Beijing
    University of Adelaide)

  • Asish Saha

    (The University of Burdwan)

  • Indrajit Chowdhuri

    (The University of Burdwan)

  • Paramita Roy

    (The University of Burdwan)

  • Manisa Shit

    (Raiganj University)

Abstract

Hot and humid subtropical plateau regions are susceptible to land degradation in the form of weathering and gully erosion. Here, we investigate chemical weathering, gully erosion and cohesiveness through field-based measurements with a view to understand the controlling factors of potential land degradation, in complex river basin of the Chotanagpur plateau region in Eastern India. The layers of controlling factors of gully erosion were developed and prioritized considering boosted regression tree (BRT), alternative decision tree (ADT), particle swarm optimization (PSO) and random forest (RF) algorithms in the R software, and the results of these methods were also validated using receiver operating characteristic (ROC) curves. The spectroscopic analysis was carried out of collected soil samples to measure the degree of chemical weathering and cohesiveness. Furthermore, the climatic elements like temperature and rainfall were also considered for estimating the chemical weathering. The results of the gully erosion models (i.e., BRT, ADT, PSO and RF) show remarkable accuracy with ROC values of 0.93, 0.89, 0.91 and 0.84, respectively. An advanced decision tree model was integrated with the results of degree of chemical weathering and cohesiveness in geographical information system platform. The land degradation map developed from this approach shows that 10.53% of the study area is highly affected, whereas 17.36% area is moderately affected and the rest of the 73.85% area is less affected by land degradation. Our results provide essential information for policy makers in adopting measures for minimizing and controlling the land degradation. Our novel approach is significant to assess land degradation to a large scale.

Suggested Citation

  • Subodh Chandra Pal & Rabin Chakrabortty & Alireza Arabameri & M. Santosh & Asish Saha & Indrajit Chowdhuri & Paramita Roy & Manisa Shit, 2022. "Chemical weathering and gully erosion causing land degradation in a complex river basin of Eastern India: an integrated field, analytical and artificial intelligence approach," 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. 110(2), pages 847-879, January.
  • Handle: RePEc:spr:nathaz:v:110:y:2022:i:2:d:10.1007_s11069-021-04971-8
    DOI: 10.1007/s11069-021-04971-8
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    References listed on IDEAS

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    1. Md. Uzzal Mia & Tahmida Naher Chowdhury & Rabin Chakrabortty & Subodh Chandra Pal & Mohammad Khalid Al-Sadoon & Romulus Costache & Abu Reza Md. Towfiqul Islam, 2023. "Flood Susceptibility Modeling Using an Advanced Deep Learning-Based Iterative Classifier Optimizer," Land, MDPI, vol. 12(4), pages 1-26, April.
    2. Narges Kariminejad & Hamid Reza Pourghasemi & Mohsen Hosseinalizadeh & Mauro Rossi & Alessandro Mondini, 2023. "Evaluating land degradation by gully erosion through soil erosion indices and rainfall thresholds," 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. 117(3), pages 3353-3369, July.

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