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<p>This study investigates soil moisture (SM) characteristics in the Barak and Brahmaputra River basins of North-East India (NEI), emphasising spatiotemporal variability and its interaction with climatic parameters, land use land cover (LULC), and soil texture. The study leverages datasets from satellite and reanalysis sources, including Landsat (5,7 and 8), SMAP, MODIS, ERA5-Land, and Dynamic World LULC, to evaluate SM characteristics. Pearson Correlation analyses highlight the interdependencies between SM indices viz. Normalized Difference Moisture Index (NDMI) and Soil Moisture Index (SMI), as well as between SM measurements (from ERA5-Land and SMAP) and other climatic factors, provide insights into their hydrological implications. Results reveal significant variability in SM indices across the different LULC classes depicting the highest for vegetation cover, with SMI consistently exceeding NDMI for all the classes. The Digital Soil Map of the World (DSMW) from FAO (Food and Agriculture Organization) confirms clay and clay-loam soils exhibit the highest SM retention, contrasting with sandy soils in the basins. Monthly analysis underscores March as the driest month, while monsoonal months exhibit peak SM levels, which are highest during June. Findings emphasise the critical role of SM in hydrological processes, regional climate feedback, and sustainable land management strategies amidst hydroclimatic changes.</p>

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Evaluation of the Soil Moisture Characteristics in the Barak and Brahmaputra River Basins of North-East India

  • 期刊论文

  • 发表日期：

    2025年12月22日

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  • Aniket Chakraborty,
  • Binita Pathak,
  • Pradip Kumar Bhuyan

摘要

This study investigates soil moisture (SM) characteristics in the Barak and Brahmaputra River basins of North-East India (NEI), emphasising spatiotemporal variability and its interaction with climatic parameters, land use land cover (LULC), and soil texture. The study leverages datasets from satellite and reanalysis sources, including Landsat (5,7 and 8), SMAP, MODIS, ERA5-Land, and Dynamic World LULC, to evaluate SM characteristics. Pearson Correlation analyses highlight the interdependencies between SM indices viz. Normalized Difference Moisture Index (NDMI) and Soil Moisture Index (SMI), as well as between SM measurements (from ERA5-Land and SMAP) and other climatic factors, provide insights into their hydrological implications. Results reveal significant variability in SM indices across the different LULC classes depicting the highest for vegetation cover, with SMI consistently exceeding NDMI for all the classes. The Digital Soil Map of the World (DSMW) from FAO (Food and Agriculture Organization) confirms clay and clay-loam soils exhibit the highest SM retention, contrasting with sandy soils in the basins. Monthly analysis underscores March as the driest month, while monsoonal months exhibit peak SM levels, which are highest during June. Findings emphasise the critical role of SM in hydrological processes, regional climate feedback, and sustainable land management strategies amidst hydroclimatic changes.