Browsing by Author "Deb, Chandrika"

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    Municipal Solid Waste Land fill Site-Hydrological Risk Factors
    (National Institute of Technology, Silchar, 2026) Deb, Chandrika
    The rapid growth of urban population and waste generation has made the selection of environmentally suitable landfill sites a critical challenge for sustainable solid waste management. This study aims to identify optimal landfill locations in the Silchar Municipal Area using a Geographic Information System (GIS)-based Multi-Criteria Decision Analysis (MCDA) integrated with the Analytic Hierarchy Process (AHP). Multiple environmental, hydrological, and infrastructural parameters—including land use/land cover (LULC), rainfall, groundwater depth, slope, elevation, and proximity to road sand streams—were considered for suitability analysis. Spatial datasets were processed and reclassified into thematic layers, and AHP was employed to assign relative weights to each criterion through pairwise comparison, ensuring a consistent and systematic decision-making framework. The weighted overlay analysis classified the study area into five suitability zones ranging from not suitable to most suitable, leading to the identification of potential landfill sites. To enhance the reliability of the results, a detailed hydrological risk assessment was conducted using stream proximity, rainfall distribution, and ground water depth, highlighting areas prone to contamination risks. Sensitivity analysis was further performed by varying the weights of key criteria, and the results demonstrated minimal variation in site selection, confirming the robustness of the model. Field validation was carried out for the shortlisted sites to verify ground conditions, resulting in the rejection of unsuitable locations and the final selection of the most feasible site. The selected land fill site satisfies both environmental and practical criteria, ensuring minimal impact on surrounding ecosystems. The study presents an integrated and systematic approach that combines spatial analysis, risk assessment, and field verification for reliable landfill site selection. The methodology can serve as a decision-support tool for urban planner sand policy makers in achieving sustainable and environmentally sound solid waste management, particularly in data-limited urban regions