Waterlogging Impact Assessment using Geospatial Approach: A Case Study of Bhiwani District, Haryana
DOI:
https://doi.org/10.48165/prakriti.2026.3.02.02Keywords:
Waterlogging, Remote Sensing, GIS, NDWI, Pre-MonsoonAbstract
Waterlogging has emerged as a major environmental and agricultural problem in irrigated regions of north-western India, adversely affecting crop productivity, soil quality, and sustainable land use. The present study aims to map and assess the seasonal dynamics of waterlogged areas in Bhiwani district, Haryana, using Remote Sensing (RS) and Geographic Information System (GIS) techniques. Sentinel-2 multispectral satellite imagery acquired during the pre-monsoon and post-monsoon periods of 2025 was analyzed using the Normalized Difference Water Index (NDWI) and supervised classification in the QGIS environment to delineate waterlogged areas and evaluate Land Use/Land Cover (LULC) changes. The classification accuracy was assessed using a confusion matrix, yielding an Overall Accuracy of 91% and a Kappa Coefficient (κ) of 0.82, indicating high reliability of the classification results. The analysis revealed that the waterlogged area increased significantly from 5,511.8 ha (1.63%) during the pre-monsoon season to 41,786.0 ha (12.36%) during the post-monsoon season, representing an increase of 36,274.2 ha (10.73%). The LULC change analysis showed that the expansion of waterlogged areas occurred primarily at the expense of cropland, accompanied by increases in fallow land, salt-affected areas, and waterbodies. Spatial analysis indicated that waterlogging is predominantly concentrated in the eastern and north-eastern parts of the district, where flat topography, poor natural drainage, dense canal irrigation networks, canal seepage, excessive irrigation, and sediment deposition in drainage channels collectively contribute to prolonged surface water stagnation and groundwater rise. The expansion of waterlogged areas caused severe damage to Kharif crops, including cotton, pearl millet (bajra), guar, and moong, disrupted agricultural operations, delayed the sowing of Rabi crops, and resulted in considerable economic losses to farmers. The findings demonstrate that the integration of Sentinel-2 imagery, NDWI, and GIS provides an effective, rapid, and reliable approach for monitoring seasonal waterlogging and associated LULC changes. The study offers valuable spatial information for planners, irrigation engineers, agricultural departments, water resource managers, and policymakers to formulate appropriate drainage improvement, canal management, and salinity control strategies for sustainable land and water resource management in waterlogging-prone regions.
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Others References
NDWI methodology
(McFeeters, 1996)
Accuracy assessment (Congalton
& Green, 2019)
Classification accuracy evaluation (Foody, 2002)
Kappa coefficient interpretation (Landis & Koch, 1977
