Solving groundwater depletion in India while achieving food security

India's food procurement and distribution system, established after the 1960s' food crises, aims to ensure food security for lower-income households. To reduce costs, procurement focuses on a few regions, significantly altering cropping patterns. The increased demand for irrigation in these regions, coupled with subsidized electricity for groundwater pumping, has led to widespread groundwater depletion. This system, offering farmers guaranteed revenue and subsidies, creates political resistance to change. The study investigates the distortionary impacts of this system and explores whether shifting grain procurement can achieve food security goals while mitigating groundwater stress and considering climatic factors, economic feasibility, and energy needs. Previous research highlighted the need for improved water use and crop diversification, but this study provides a novel economic analysis suggesting actionable changes to the procurement system. The research uses a model that maximizes net national farm income by allocating 12 major crops across districts, accounting for climate variables, regional productivity, cultivation costs, and irrigation scenarios (Irrigation Zero and Irrigation Capped) under the Minimum Support Price (MSP) regime. The model aims to address India's food security and nutritional needs while considering climate variability and district-level crop choices, providing a more comprehensive approach than prior studies.

The literature review highlights several key studies. The impacts of the Green Revolution and the subsequent changes to the Indian government's food procurement and distribution system are examined. Studies analyzing the system's effects on cropping patterns and food prices are discussed, emphasizing the difficulties in enacting necessary reforms. The challenges associated with crop diversification, particularly in Punjab, are reviewed, along with research demonstrating the need for improved water use and nutritional diversity in India's agricultural practices. These prior works set the stage for the current study's unique contribution: a detailed economic analysis suggesting concrete entry points for reforming India's food procurement system.

The study utilizes a linear programming model to optimize crop allocation across India's districts. The objective is to maximize the expected value of net national farm income, considering district-level crop productivity, cultivation costs, weather/climate variables, and spatially specified incentives and policies. The model incorporates two irrigation scenarios: "Irrigation Zero" (rainfed agriculture) and "Irrigation Capped" (irrigated agriculture under current limits). Constraints include national-level crop demand satisfaction, nutritional requirements, district-level water supply limits, and land use constraints. The model uses daily precipitation and temperature data from 1901-2009 to account for climate variability's impact on crop yields. Data on district-level crop productivity, cultivation costs, cropped area, irrigation, demographics, infrastructure, and government Minimum Support Prices (MSP) were compiled from various sources (detailed in the Methods section and Supplemental Material). The model's decision variables are the fractions of current cropped area allocated to each of the 12 crops in each district. The key constraints ensure national-level crop demand and nutritional needs are met, while considering district-level water supply limits in both irrigation scenarios. The study incorporates climate variability and its effects on yield by using historical daily precipitation and temperature data to estimate crop water requirements and yield variations. FAO methods are used to assess this impact at the district level. The costs, nutritional value, groundwater usage, and energy consumption associated with each crop are meticulously detailed to inform the constraints. The analysis focuses solely on Kharif (summer monsoon) season crops and irrigation, using annual values for procurement targets and nutrition.

The model's results reveal that meeting India's food security targets is achievable even without irrigation ("Irrigation Zero" scenario) by shifting cropping patterns. This leads to a 5% increase in national agricultural revenue compared to the current system. The "Irrigation Capped" scenario, allowing continued irrigation at current levels, increases net national revenue by 30%. Both scenarios show that nutritional targets can be met or exceeded. The optimal cropping patterns show significant reductions (over 75%) in rice cultivation in traditionally high-producing regions like Punjab and Haryana, shifting production to other areas better suited for rice and other crops based on climate and yield potential. Other cereals are optimally grown in areas like Punjab and Haryana, while pulses and oilseeds are identified for other regions. These optimal patterns broadly align with pre-Green Revolution cropping patterns, suggesting the current PDS procurement system has created a suboptimal outcome for water management. A sensitivity analysis confirms that the optimal allocation for rice, other cereals, and oilseeds is robust to changes in net unit revenue, whereas pulse allocation is more sensitive. The "Irrigation Zero" scenario shows considerable reductions in national water (146 billion m³) and energy (2625.2 GW) use. A state-level analysis reveals varied impacts; while some states experience significant income gains, others (e.g., Punjab) face net losses, although these losses can be potentially offset by the value of reduced electricity costs and groundwater savings. The study also indicates that states with significant losses might benefit from shifting to higher-value crops like fruits and vegetables, albeit acknowledging challenges in establishing reliable supply chains.

The findings demonstrate the potential for reforming India's Public Distribution System (PDS) to address groundwater depletion while maintaining food security. The model showcases the effectiveness of a single policy lever (PDS reform) to achieve substantial changes in water, food, and energy sectors. The results highlight the need for a transition from the current, highly subsidized and water-intensive agricultural practices. While acknowledging the political and economic complexities, the study provides a data-driven framework for informed policy decisions. Addressing concerns about income redistribution is crucial; mechanisms to compensate states experiencing income losses, such as investing in alternative, less water-intensive agricultural supply chains, should be explored. The study’s findings demonstrate the potential for policy interventions, even at the national level, to produce significant positive effects on water resource sustainability and agricultural revenues while enhancing national food security.

This study presents a data-driven approach to reforming India's PDS, demonstrating the potential for simultaneously achieving food security and mitigating groundwater depletion. The optimization model reveals the feasibility of meeting national food and nutritional targets, even without irrigation, by strategically reallocating crop production. The analysis underscores the need for policy interventions that incentivize sustainable agricultural practices and address income redistribution challenges. Future research should explore multi-criteria decision-making frameworks that consider equity across states and incorporate additional risk management tools.

The study focuses on Kharif season crops and doesn't account for inter-seasonal crop variations. The model relies on historical climate data, and its predictions may not perfectly capture future climate variability or its impact on crop yields. Economic factors beyond minimum support prices and cultivation costs are not fully incorporated. The model does not fully capture the complexity of the social and political factors that could influence the success of these policy changes.