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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.
Details
Erosion models;
Swarm intelligence;
Information systems;
Artificial intelligence;
Rainfall;
Geographic information systems;
Chemical weathering;
Weathering;
Rivers;
Land degradation;
Decision trees;
Cohesion;
Algorithms;
Spectroscopic analysis;
Regression analysis;
Erosion control;
Gullies;
Rain;
Particle swarm optimization;
Environmental degradation;
Gully erosion
; Rabin, Chakrabortty 1 ; Arabameri Alireza 2 ; Santosh, M 3 ; Saha Asish 1 ; Chowdhuri Indrajit 1 ; Roy, Paramita 1 ; Manisa, Shit 4 1 The University of Burdwan, Department of Geography, Bardhaman, India (GRID:grid.411826.8) (ISNI:0000 0001 0559 4125)
2 Tarbiat Modares University, Department of Geomorphology, Tehran, Iran (GRID:grid.412266.5) (ISNI:0000 0001 1781 3962)
3 China University of Geosciences Beijing, School of Earth Sciences and Resources, Beijing, China (GRID:grid.162107.3) (ISNI:0000 0001 2156 409X); University of Adelaide, Department of Earth Science, Adelaide, Australia (GRID:grid.1010.0) (ISNI:0000 0004 1936 7304)
4 Raiganj University, Department of Geography, Raiganj, Uttar Dinajpur, India (GRID:grid.460977.b)