Sustainable Land-Use Policy Development Using Fuzzy Multi-Criteria Decision Analysis: A Case Study from the Ranganadi River Basin

Land degradation in river basins is a critical issue influenced by hydrological changes, sediment deposition, and deforestation. This study presents an innovative Agroforestry-Based Multi-Criteria Decision Analysis Model integrating Fuzzy Logic to assess land degradation risks in the Ranganadi River Basin, India. By leveraging remote sensing and geographic information system, key risk factors such as rainfall intensity (2,500 mm/year), river sinuosity (1.73), sediment deposition (200 tons/km2/year), soil erosion (15 tons/ha/year), and land-use changes (17%) were analyzed. The model assigns weighted significance to these factors using Analytical Hierarchy Process and applies fuzzy logic to classify risk zones. Results reveal that the Ranganadi River Basin faces a moderate risk level (risk score = 0.53), warranting targeted agroforestry interventions. Alley cropping is recommended as a suitable agroforestry strategy to reduce runoff, stabilize soil, and enhance agricultural productivity. The study estimates a net agricultural loss of 2.38 million pounds (1,080,140 kg) of paddy production annually, leading to an economic loss of approximately US$262,000. The findings highlight the importance of integrating geospatial analysis with sustainable land management practices to mitigate environmental degradation. Future work will refine the model by incorporating climate resilience strategies and expanding its application to other river basins for broader environmental impact assessment.