ANNOUNCEMENT

NOBEL PRIZE 2026

This year's laureates, their fields, and the discoveries that earned them the prize.Live nowSee the winners
Moonbase
← Back to Awards
NSFDirectorate for Technology, Innovation, and Partnerships

NSF Convergence Accelerator Track K: Spatially Resolved Solutions for Field to Regional Irrigation Water Management to Promote Equitable Sharing of Limited Water Resources

Completed
Institution
University of California-Los Angeles, CA
Principal investigator
Mekonnen Gebremichael
Funding
$650K
Duration
2024–2026
Open portfolio

Moonbase score

Still being scored

Abstract

In response to the pressing challenge of freshwater scarcity, particularly impacting vulnerable communities, this Convergence Accelerator Track K Project proposes the development of a user-tailored irrigation water management decision-support hub, focusing on Central Valley, California. Utilizing satellite remote sensing, weather forecasts, and soil/crop models, the project aims to provide individual growers with daily irrigation advice at a high spatial resolution, integrating available soil water and crop water demand. Additionally, the tool will offer water districts and regulators aggregated crop water demand and consumption data, supporting regional-level decisions on equitable water allocation. When the proposed tool is developed and distributed for public use, it will help mitigate groundwater depletion, enhance water use efficiency, lower irrigation costs, and contribute to regional water allocations that take into account water resource availability and environmental constraints. The project's technical goals encompass stakeholder engagement, conceptual model development, web-based tool creation, and testing and evaluation. Stakeholders will be engaged throughout the research, contributing to design requirements and evaluation analysis. The conceptual model, which integrates innovative remote sensing products, weather forecasts, and user inputs, will guide the development of a web-based decision-support tool. This research will involve creating innovative remote sensing products, such as high-resolution (10-m, daily) data for near-surface soil moisture, root-zone soil moisture, and evapotranspiration based on satellite data. The tool will produce farm-level outputs, including irrigation advice, and regional-level outputs including aggregated water consumption and demand data. The prototype tool will undergo testing on various pilot farms in Central Valley, encompassing diverse climates, crop types, and irrigation methods. This testing phase will include the installation of sensors to measure soil moisture and evapotranspiration data, as well as field campaigns to monitor crop growth conditions and irrigation scheduling decisions. Additionally, economic analysis will be conducted to assess growers' willingness to adopt the tool and quantify its impacts on irrigation efficiency and farm productivity. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Research team

  • Mekonnen GebremichaelPI
  • Dani OrCo-PI
  • Mani Rouhi RadCo-PI
  • Aliasghar MontazarCo-PI
  • Regan F PattersonCo-PI

LOADING MOONBASE SCORE

Directorate for Technology, Innovation, and PartnershipsConvergence Accelerator Resrchirrigationremote sensingsoil moisturecropdecision-supportmoisturewatersoil

Questions for University of California-Los Angeles

Answered by the team behind this research.

Same researchers, same institution, same topic, scored first.