Land Use Changes and Future Runoff Projections in the Tawi Catchment of the Western Himalayas: a Comprehensive Analysis Using CA-Markov and SWAT Models

This study employs a transition matrix and cellular automata-Markov chain framework to analyse spatiotemporal variations in land cover and land utilisation employing Landsat "Thematic Mapper" (TM) and "Operational Land Imager" (OLI) datasets during the period 2000, 2010, and 2020 and its future runoff projections. The "Soil & Water Assessment Tool" (SWAT) simulation integrates climate and soil data with the cellular automata-Markov framework to forecast runoff. Specifically, the cellular automata-Markov model forecasts urban growth patterns and trends. The assessment reveals significant changes in land use transition probabilities from the baseline (2000) to 2010-2020: rangeland decreased by 0.01%, forest land by 0.88%, agricultural land increased by 0.88%, and urban land by 0.21%. Projections for 2020-2050 and 2020-2080 indicate further declines in forest land (- 6.77% and - 8.51%) and rangeland (- 0.30% and - 0.41%), while agricultural land is projected to increase (2.10% and 3.68%) along with urban land (5.47% and 5.88%). Perennial snow or ice cover is expected to decrease by - 1.05% and - 1.24%, while water bodies will increase by 0.53% and 0.58%. SWAT analysis for Jammu and Udhampur stations demonstrates strong simulation performance (R2 and NSE values exceeding 0.6). Results indicate a slight increase in annual runoff during the future period (2020-2080). Seasonal runoff projections show an increase in winter and pre-monsoon runoff at Jammu, contrasting with declines in monsoon runoff. Udhampur exhibits a more balanced runoff pattern, with slight increases across seasons. These findings underscore the need for adaptive water management strategies to mitigate impacts from environmental changes and land use alterations.