Groundwater depletion poses a serious threat to water security in arid regions worldwide, risking sustainable water resources and agricultural stability. This study examines groundwater dynamics and water resource sustainability in the arid Barind Tract of Northwest Bangladesh using integrated remote sensing techniques and logistic regression modeling. It employed three key indices to assess water resource vulnerability: Normalized Difference Vegetation Index, Topsoil Grain Size Index, and Aridity Index, integrating them through logistic regression to evaluate desertification susceptibility and water sustainability. The regression model boasts an ROC value of 96.22% and R² of 0.3893, indicating good classification performance with acceptable class variance. Results show that 82.66% of the area faces significant water resource challenges, with 6.27% (103.26 km²) at very high risk, 10.80% (177.89 km²) at high risk, and 28.17% (464.05 km²) at moderate risk. The northern regions, especially Porsha, Gomastapur, and Nachole Upazillas, are the most vulnerable to water depletion. The study recommends sustainable water management strategies, including surface water use through floating pontoons and rubber dams, emphasizing the urgent need for integrated water resource management to ensure long-term water security. Additionally, the research analyzed soil-vegetation feedback using rain use efficiency and found a negative loop in highly desertification-prone areas like Porsha and Nachole, indicating the need for regulation-based cropping practices and improved water governance in zones at risk of desertification to reduce crop-water redundancy. This research offers valuable insights for water resource planning and management in arid regions, supporting sustainable water governance and locally-led adaptation strategies for water-stressed environments.

Groundwater depletion in arid regions poses a significant threat to agricultural sustainability and rural livelihoods. This study employs geospatial analysis and economic modeling to address groundwater depletion in the arid Barind region of Northwest Bangladesh, where 84% of the rural population depends on agriculture. Using remote sensing and GIS, we developed an elevation map revealing areas up to 60 m above sea level, exacerbating evaporation and aquifer dryness. Field data collected through Participatory Rural Appraisal tools showed farmers exhibiting “ignorant myopic” behavior, prioritizing short-term profits over resource conservation. To address this, an Increasing Block Tariff (IBT) water pricing model was developed, dividing water usage into three blocks based on irrigation hours: 1–275 h, 276–550 h, and 551+ h. The proposed IBT model significantly increases water prices across the three blocks: 117 BDT/hour for the first block (from current 100–110 BDT/hour), 120 BDT/hour for the second block, and 138 BDT/hour for the third block. A demand function (y = −0.1178x + 241.8) was formulated to evaluate the model’s impact. The results show potential reductions in groundwater consumption: 59 h in the first block, 26 h in the second block, and 158 h in the third block. These reductions align with the principles of integrated water resource management (IWRM): social equity, economic efficiency, and environmental integration. The model incorporates economic externalities (e.g., well lifting costs) and environmental externalities (e.g., crop pattern shifts), with total costs reaching 92,709,049 BDT for environmental factors. This research provides a framework for sustainable groundwater management in arid regions, potentially reducing overextraction while maintaining agricultural productivity. The proposed IBT model offers a locally driven solution to balance resource conservation with the livelihood needs of farming communities in the Barind tract. By combining remote sensing, GIS, and economic modeling, this research provides a framework for sustainable groundwater management in arid regions, demonstrating the power of geospatial technologies in addressing complex water resource challenges.

In Bangladesh, agriculture has been the most significant sector of the economy, contributing about 11.02 percent of the country's total GDP in the FY2023-24 (BBS, 2024). It offers direct and indirect em-ployment to nearly 45 percent of the total population against the global average employment rate of 26.86 percent employment in ag-riculture, with more than 70 percent of its land dedicated to growing crops. The Barind tract, a special topographic upland in the North-Western part of Bangladesh, is a noteworthy agrarian region contrib-uting the lion's share to this sectoral GDP of Bangladesh. Owing to the significant dependency upon groundwater-based irrigation, the whole region is now going through a critical phase of agricultural dis-economies and livelihood insecurity. This research attempts to estimate the costs of groundwater depletion and the resulting negative externalities in three topographically different areas within the Barind region. Alongside, a household income function will be established which can be replicated in similar contexts to understand and monitor resource vulnerability. Intensive agricultural drive has been obtained from the study areas, with almost 60-85 percent of their total land area being used for farming. The essentially closer proximity between ir-rigation wells (0.13-0.16km) has significantly hampered adjacent aq-uifers and equitability of groundwater access. While investigating probable shifts in irrigation infrastructure in the past 05 years, it was found that Porsha, located within the elevated lands, had to deepen almost 03 times (-21.32 ft) more than Godagari, a comparatively low Barind region. The direct cost of resource degradation, depicting eco-nomic externalities, ranges from BDT 52 to 250 per acre, varying due to the linear correlation with water resource depletion. The gradual economic burden has resulted into 3-8 percent decline in area under irrigation within the study region, mostly depriving the marginal farmers. The indirect costs highlighted a contrasting scenario, exhib-iting inverse relationship with the groundwater level which pointed out a key outcome of the study; shifting towards low-intensive crops being an economically and environmentally ideal solution of dealing with groundwater vulnerability. Calculating household income func-tion by Ordinary Least Squares Regression method depicted similar assumptions, negative externalities caused by over-irrigation, dimin-ishing social profit that suggests regulation for sustainable resource utilization.