Geostatistics-guided optimization for deficit irrigation in agriculture
A solution that combines satellite remote sensing and geostatistics to optimize irrigation. It generates uncertainty-quantified, high-resolution soil moisture maps and integrates them into a decision-support workflow that uses a mixed-integer optimization model to allocate limited water and select deficit-irrigation strategies while maintaining yield under constraints. The approach is designed to be cost-effective and scalable using freely available data sources such as NASA and OpenET.
Overview
This solution integrates satellite remote sensing with geostatistics to optimize irrigation efficiency in agriculture, particularly in the Western Corn Belt. Using NASA SMAP satellite data, it produces real-time, high-resolution soil moisture maps that are uncertainty-quantified. These maps feed into a mixed-integer optimization model that allocates limited water resources and selects deficit-irrigation strategies, maximizing yield under constraints. The approach is cost-effective and scalable, leveraging freely available data sources such as NASA and OpenET, and is designed to provide robust, risk-aware irrigation plans.
Technical specifications
- Satellite Data Integration: Utilizes NASA SMAP soil moisture data, downscaled using area-to-area kriging with auxiliary inputs such as NDVI and land surface temperature.
- Optimization Model: Employs a mixed-integer linear programming (MILP) model that incorporates risk through scenarios and chance constraints.
- Decision-Support Tool: A prototype tool that provides real-time irrigation recommendations.
- Validation: Ground network validation in Iowa, with expansion plans across the Western Corn Belt including Kansas, Nebraska, Colorado, Oklahoma, and Texas.
Technology readiness level
Currently at Technology Readiness Level 3. The solution is in the early stages of development, with ongoing field validation and stakeholder feedback being integrated into the prototype. Plans for rapid adoption and field readiness are set within a year.
About Iowa State University
Iowa State University is a large, comprehensive public land‑grant research university based in Ames, known for combining fundamental discovery with translational, industry‑relevant work. Companies collaborate through a research and technology park that co‑locates corporate R&D with faculty labs and startups, creating steady talent pipelines. Pilot‑scale facilities, field test sites, and a statewide extension network support prototyping, validation, and deployment with partners across the region. Research is supported by competitive federal funding, including awards from NSF, USDA, and DOE. A dedicated technology transfer office and affiliated research foundation streamline IP, licensing, and startup formation, with incubator space on site.
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