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<p>Outside the polar regions, Pakistan’s northern mountainous regions constitute one of the world’s largest mid-latitude seasonal snow and ice reservoirs. These cryospheric resources supply essential downstream water for hydropower generation and irrigated agriculture. Seasonal snowmelt during summer governs river discharge in the Indus Basin, while climate-driven changes in snow accumulation and melt dynamics have direct implications for runoff variability and flood risk. Accurate and consistent mapping of snow cover is therefore critical for hydrological assessment and climate-change impact analysis. This study presents an improved basin-scale snow cover mapping approach using freely available Landsat-8 and Sentinel-2 imagery with cloud cover below 1%, covering the period from 2015 to 2020. Snow cover was mapped using the Water-resistant Snow Index (WSI), a recently developed spectral index that enhances discrimination between snow and water bodies without requiring an external water mask. The performance of WSI was evaluated against the widely used Normalized Difference Snow Index (NDSI), particularly under complex terrain and mixed snow–water conditions. Results reveal a declining trend in January snow cover across the study period, with maximum snow-covered areas exceeding 7,000&#xa0;km² in the earlier years and a marked reduction by 2020. January represents the peak snowfall month in the Chitral Basin; therefore, the observed decrease in snow-covered area during this critical accumulation period indicates reduced winter snow storage. Such reductions are likely to accelerate snowmelt processes, alter seasonal runoff timing, and increase downstream flood susceptibility. The findings demonstrate that WSI provides a robust and efficient method for cloud-minimized, basin-scale snow cover mapping. This approach improves the reliability of snowmelt runoff estimation and supports informed water-resource management, flood risk assessment, and climate-change adaptation strategies in snow-dominated mountainous basins.</p>

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Cloud-free snow cover mapping for change detection using landsat-8/sentinel-2 and WSI in the Chitral Basin (2015–2020)

  • 期刊论文

  • 发表日期：

    2026年5月27日

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  • Iqra Munir,
  • Waqas Hassan

摘要

Outside the polar regions, Pakistan’s northern mountainous regions constitute one of the world’s largest mid-latitude seasonal snow and ice reservoirs. These cryospheric resources supply essential downstream water for hydropower generation and irrigated agriculture. Seasonal snowmelt during summer governs river discharge in the Indus Basin, while climate-driven changes in snow accumulation and melt dynamics have direct implications for runoff variability and flood risk. Accurate and consistent mapping of snow cover is therefore critical for hydrological assessment and climate-change impact analysis. This study presents an improved basin-scale snow cover mapping approach using freely available Landsat-8 and Sentinel-2 imagery with cloud cover below 1%, covering the period from 2015 to 2020. Snow cover was mapped using the Water-resistant Snow Index (WSI), a recently developed spectral index that enhances discrimination between snow and water bodies without requiring an external water mask. The performance of WSI was evaluated against the widely used Normalized Difference Snow Index (NDSI), particularly under complex terrain and mixed snow–water conditions. Results reveal a declining trend in January snow cover across the study period, with maximum snow-covered areas exceeding 7,000 km² in the earlier years and a marked reduction by 2020. January represents the peak snowfall month in the Chitral Basin; therefore, the observed decrease in snow-covered area during this critical accumulation period indicates reduced winter snow storage. Such reductions are likely to accelerate snowmelt processes, alter seasonal runoff timing, and increase downstream flood susceptibility. The findings demonstrate that WSI provides a robust and efficient method for cloud-minimized, basin-scale snow cover mapping. This approach improves the reliability of snowmelt runoff estimation and supports informed water-resource management, flood risk assessment, and climate-change adaptation strategies in snow-dominated mountainous basins.