This invention presents a method and electronic device for irrigation water management based on weather forecasts and real-time soil moisture monitoring. It integrates a stochastic farm-scale hydrologic model with probabilistic rainfall forecasts and optimization techniques to provide accurate, adaptive, and sustainable irrigation recommendations. The system minimizes water usage while maintaining optimum crop yield, aligning with the principles of precision agriculture and climate resilience.
Figure 1. Overall methodology proposed for irrigation prediction
Traditional irrigation methods are largely based on fixed schedules or manual judgment, leading to inefficient water use and overexploitation of groundwater. Most existing models either neglect short-range weather forecasts or fail to incorporate their uncertainties. As a result, irrigation strategies do not optimally account for the actual water demand of crops under changing climatic and soil conditions. There is a pressing need for a farm-scale irrigation solution that can dynamically adapt based on reliable data and forecast uncertainties.
- Forecast-Based Irrigation: This technology integrates short-term weather forecasts (1/3/7 days) into irrigation planning.
- Stochastic Modelling: It uses a probabilistic hydrological model to simulate soil moisture dynamics.
- Optimization Framework: It minimizes water use while avoiding crop water stress.
- Monte Carlo Simulation: This technology incorporates forecast uncertainty into irrigation decisions.
- Sensor Integration: It utilizes soil moisture sensors or satellite inputs for initialization.
- Crop and Soil Adaptability: This Technology can be customized for various crops, soils, and climate zones.
- Electronic Device Implementation: This technology uses real-time processing via an electronic system.
The system includes a processor-equipped electronic device that collects weather forecast data and soil moisture readings (from sensors or satellites). Using these, it configures a stochastic rainfall model and hydrologic simulation. An optimization module computes the minimum irrigation needed to avoid water stress with high reliability (e.g., 95%). Algorithms tested include genetic and brute-force search methods.
The method and system have been developed, simulated, and tested. Optimization accuracy has been verified across various scenarios using historical weather and soil data. The system is ready for field deployment and real-time trials.
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This technology empowers farmers with scientific, reliable irrigation guidance. It contributes to groundwater conservation, improves agricultural productivity, and supports national goals for water-efficient and climate-resilient agriculture. Especially impactful in water-scarce regions, it enhances both environmental sustainability and livelihood security.
- Precision Agriculture: The method integrates stochastic soil models with forecast uncertainty to deliver precise irrigation recommendations at farm scale.
- Smart Irrigation Systems: It enables automated irrigation decisions using real-time soil moisture and weather data through electronic devices.
- Weather Forecasting Services: The framework incorporates short-range weather forecasts into probabilistic rainfall modelling for enhanced agricultural planning.
- Agricultural Extension Services: It provides farmers with actionable, optimized irrigation scheduling advice through a user-oriented electronic platform.
- Hydrological Modelling: A stochastic farm-scale hydrological model simulates soil moisture evolution considering evapotranspiration, runoff, and leakage.
- Water Resource Management: The technology minimizes water consumption while maintaining crop yield, contributing to sustainable resource use in agriculture.
Geography of IP
Type of IP
201921049095
552587