Research Projects

Agriculture is the main economy of our country, and most of the livelihoods depend on farming activities, which mostly depend on groundwater, especially in semi-humid to arid regions. Under climate uncertainty groundwater recharge as well as agriculture is under threat. This directly reflects on agricultural livelihood patterns mostly in underdeveloped tribal region. The proposed study aims to create a Climate-Water-Agriculture-Livelihood Nexus model for tribal area to understanding climate change, ground water scarcity and agricultural vulnerability, and farmer’s community resilience in Jhargram and East Singhbhum districts. Scientific research, indigenous knowledge, and innovative agriculture will be used to create context-specific solutions that minimize vulnerabilities, increase adaptive ability, and promote sustainable agricultural livelihoods for tribal groups. An integrated study of the climate-water-agriculture nexus is critical to concentrate on these livelihood challenges and develop sustainable, climate-resilient strategies for socio-economic stability in the entire region and also in livelihoods who are involved directly and indirectly. This approach will use RS and GIS, and multi-disciplinary techniques with hydrological modeling like SWAT, MODFLOW, and WAP to generate actionable insights for policymakers and stakeholders, linking science, society, and sustainable development. Using machine learning (ML) methods like SVM, Random Forest, and XGBoost, the study will be able to assess vulnerability across water scarcity, agricultural, and livelihood dimensions. Vulnerability will be explored in terms of adaptive capacity, exposure, and sensitivity and also sustaining targeted policy generation. The main indicators for water insufficiency will be incorporated on groundwater storage, recharge rates, and drawing out of the life living water; agricultural susceptibility will think about factors like cropping intensity, soil erosion, and rainfall; while agricultural livelihood susceptibility will issue within families to earning generations and learning of them about all types of things which are all related with its. Ground-based validation, including AUC-ROC, RMSE, and R2 analysis and cross-validation include machine leering base K-fold, SHAP analysis and ground photos, will strengthen results for the effective areas of the region. The WEAP modeling framework will be applied for future water use planning, supporting policy development and advancing UN SDGs 2, 6, and 13.