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<p>Gully erosion, exacerbated by dynamic LULC changes, poses severe threats to environmental stability and socio-economic systems in vulnerable regions. This study integrates the Digital Shoreline Analysis System (DSAS) and CA–Markov model to quantify gully erosion rates and LULC transformations in two contrasting watersheds—Raiboni (RSW) and Sita Nala (SNSW)—within India’s tropical monsoon climate. Analyzing eight gullies (four per watershed) from 2002–2022, with projections to 2032, DSAS revealed significant spatial disparities: SNSW exhibited triple the erosion rate of RSW (− 0.49 vs. − 0.15&#xa0;m/year), with gully SNSWG-1 experiencing the highest retreat (− 1.15&#xa0;m/year). Projections indicate accelerating erosion, particularly in RSWG-1 (− 0.48&#xa0;m/year by 2032). Concurrent LULC analysis using CA-Markov highlighted rapid agricultural expansion, with SNSW undergoing a 33.8% vegetation-to-agriculture conversion (3.73% annual change rate) compared to RSW’s 26% bare land-to-agriculture shift (2.24% annual rate). These transformations correlate strongly with erosion severity, underscoring the cyclic degradation pattern of deforestation → gully expansion → agricultural encroachment. Validation via ROC (80.3–86.9%), R<sup>2</sup> (0.87), and Kappa coefficients (83.5–86.67%) confirmed model robustness. The findings emphasize the urgency of targeted interventions, prioritizing vegetation conservation in high-conversion zones (e.g., SNSW) and implementing soil stabilization measures (e.g., contour trenching) in erosion hotspots. This study pioneers the application of DSAS for gully assessment in India’s tropical regions, bridging critical gaps in rate-based erosion analysis and integrated LULC modeling. The results provide a spatial framework for sustainable land management, aligning with global efforts to mitigate land degradation and enhance climate resilience in rapidly developing watersheds.</p>

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Integrated DSAS and CA–Markov model approach for assessing gully erosion dynamics and land use transformations: evidence from Chotanagpur plateau region, Eastern India

  • 期刊论文

  • 发表日期：

    2025年11月23日

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  • Md Hasanuzzaman,
  • Partha Pratim Adhikary,
  • Pravat Kumar Shit

摘要

Gully erosion, exacerbated by dynamic LULC changes, poses severe threats to environmental stability and socio-economic systems in vulnerable regions. This study integrates the Digital Shoreline Analysis System (DSAS) and CA–Markov model to quantify gully erosion rates and LULC transformations in two contrasting watersheds—Raiboni (RSW) and Sita Nala (SNSW)—within India’s tropical monsoon climate. Analyzing eight gullies (four per watershed) from 2002–2022, with projections to 2032, DSAS revealed significant spatial disparities: SNSW exhibited triple the erosion rate of RSW (− 0.49 vs. − 0.15 m/year), with gully SNSWG-1 experiencing the highest retreat (− 1.15 m/year). Projections indicate accelerating erosion, particularly in RSWG-1 (− 0.48 m/year by 2032). Concurrent LULC analysis using CA-Markov highlighted rapid agricultural expansion, with SNSW undergoing a 33.8% vegetation-to-agriculture conversion (3.73% annual change rate) compared to RSW’s 26% bare land-to-agriculture shift (2.24% annual rate). These transformations correlate strongly with erosion severity, underscoring the cyclic degradation pattern of deforestation → gully expansion → agricultural encroachment. Validation via ROC (80.3–86.9%), R2 (0.87), and Kappa coefficients (83.5–86.67%) confirmed model robustness. The findings emphasize the urgency of targeted interventions, prioritizing vegetation conservation in high-conversion zones (e.g., SNSW) and implementing soil stabilization measures (e.g., contour trenching) in erosion hotspots. This study pioneers the application of DSAS for gully assessment in India’s tropical regions, bridging critical gaps in rate-based erosion analysis and integrated LULC modeling. The results provide a spatial framework for sustainable land management, aligning with global efforts to mitigate land degradation and enhance climate resilience in rapidly developing watersheds.