GIS-MCDA assessment of landfill suitability in flood-prone coastal Alappuzha, Kerala.

Abstract

Rapid urban growth, tourism pressure, and ecological sensitivity pose significant challenges to solid waste management in coastal districts. Alappuzha District of Kerala state of India, characterized by the Vembanad-Kol Ramsar wetland system, dense backwater networks, and recurrent flooding, represents a complex setting where conventional landfill siting approaches are often inadequate. This study applies and refines a Geographic Information System (GIS)-based Multi-Criteria Decision Analysis (MCDA) framework integrated with the Analytical Hierarchy Process (AHP) to identify suitable landfill sites in Alappuzha District, with emphasis on methodological transparency in a hydrologically constrained coastal environment. Ten criteria were integrated into the spatial model: distance from water bodies, settlements, road networks, agricultural land, and plantation areas; flood-prone areas; slope; groundwater depth; soil permeability; and population density. Seven primary environmental criteria were evaluated using expert-based pairwise comparisons (n = 12) following the AHP protocol (Consistency Ratio, CR = 0.003), while groundwater depth, soil permeability, and population density were incorporated through a structured supplementary elicitation process involving the same expert panel. Standardized criteria layers were integrated using a weighted-overlay approach in ArcGIS, and model stability was evaluated through sensitivity analysis applying ± 15% variation in criterion weights. Only 51.0 km² (3.6%) of the district was classified as moderately to highly suitable for landfill siting, reflecting substantial hydrological, hydrogeological, and environmental constraints. Three candidate sites ranging from 2.1 to 4.8 hectares were identified in Cherthala and Chengannur taluks, all requiring field verification and statutory Environmental Impact Assessment before implementation. Sensitivity analysis indicated strong model stability (Spearman's r ≥ 0.88) across all perturbation scenarios. This study refines GIS-MCDA-based landfill suitability assessment for flood-prone coastal environments and provides a transferable framework for hydrologically constrained regions where comparable spatial datasets are available.