Recursive AI for Groundwater Management

Predict Groundwater Levels, Prevent Risks, Increase Yield

Proper management of the groundwater levels in forestry and agricultural sectors are of utmost importance. If levels drop excessively, drying out can occur, turning the forests and crops into highly flammable areas prone to fires. Conversely, overly high groundwater levels can inhibit plants growth, underscoring the necessity of continually maintaining an optimal balance.

However, predicting and managing groundwater levels has traditionally depended on experienced technicians, which is time-consuming and inefficient. Conventional methods require manual surveying and the creation of topographic & contour maps as detailed as 50 centimeters, which typically takes up to 5 years.

Recursive AI for Groundwater Management addresses these challenges by combining machine learning and physics-based modeling to deliver highly accurate groundwater level predictions. Using over 10 years of data, including topography, rainfall, and waterway details, the system provides actionable insights to optimize plantation site selection, improve irrigation scheduling, and reduce environmental risks like fires and floods.

Highlights

• Accurate Groundwater Predictions: Forecast groundwater levels up to 7 days in advance, using topographic data, precipitation statistics, and real-time measurements to enable proactive decision-making.
• Flood Prevention and Fire Risk Mitigation: Receive early warnings when groundwater levels approach critical thresholds, helping stakeholders take timely action to prevent floods or fires.
• Improved Water Management: Plan irrigation, channel operations, and dam placements with data-driven insights to balance water availability and ensure sustainable usage.
• Customizable and Scalable: Adaptable to diverse industries and regions, the solution supports use cases in forestry, agriculture, and environmental conservation.

Implementation