Research

Predicting nationwide crop water availability by understanding soil influences

USDA grant will fund Penn State researchers to incorporate satellite, sensor and soil core data into predictive models of nationwide crop water availability

More research is needed to accurately inform irrigation decisions across the United States, Penn State scientists said. Currently, 75% of irrigators rely on experiential or speculative approaches to make decisions regarding irrigation. Credit: Penn State. Creative Commons

UNIVERSITY PARK, Pa. — A team of researchers in Penn State’s College of Agricultural Sciences has received a $500,000 grant from the U.S. Department of Agriculture (USDA) to generate knowledge and tools, such as national-level predictive models, to develop a better understanding of how changes in soil texture and structure influence the availability of water for crops.

The three-year award, coming from USDA’s Natural Resources Conservation Service, will fund an effort to develop expertise to assist with soil management and irrigation decisions, according to team leader Meetpal Kukal, assistant research professor of agricultural and biological engineering.

Soil structure, or how the soil particles are arranged, and soil texture, or the proportion of clay, sand or silt comprising the soil, together determine how much water is available to crops, he explained. The structure can change, usually from management practices, becoming denser or looser. It is unclear, Kukal added, how such change will interact with soil texture in space and over time to influence not only potential retention of water but also the actual amount of water held in soils historically.

To gain insight, the researchers will rely on historical soil moisture content detected by satellites across the entire conterminous United States. Past research has been limited to the upper and lower bounds of available water, but this study will focus on the full range of soil moisture.

“There is a substantial need for robust estimates of agricultural water availability for understanding, tracking and managing a wide range of processes and decisions in agroecosystems,” Kukal said. “A primary area of need is supporting science-based irrigation decisions in the nation, because three-fourths of irrigators still rely on experiential or speculative methods. To this end, we will map irrigation triggers across the U.S. at high resolutions.”

Currently, Kukal noted, researchers lack high-resolution mapping of thresholds for soil water content at which crops undergo water stress to assist with irrigation decisions. In an effort to rectify this, the team will use state-of-the-art sensing advances and tens of thousands of soil cores sampled by the Natural Resources Conservation Service across the nation to inform such decisions.

According to Suat Irmak, project co-principle investigator and professor and head of the Department of Agricultural and Biological Engineering, determination of soil-water availability on large and spatial scales can be invaluable for a variety of reasons. Among them are hydrologic studies, water-quality assessments and modeling to predict run-off and leaching potential, climate change vs. water-availability assessments, water-use studies and effective water management.

“These types of datasets and information are especially critical in arid and semi-arid regions where water availability is usually limited,” Irmak said. “However, it is also critical for humid and sub-humid regions where addressing water-quality issues needs soil-water-availability data to determine water and chemical flow and sediment transport.”

This project will expand scientists’ ability to utilize data and information for improving various processes and developing best-management practices in different settings, Irmak pointed out. Among all science and technology-based methods, soil moisture-based techniques have emerged as an increasingly popular method of scheduling irrigations by U.S. irrigators, he said. In addition to irrigation management, reliable soil-water availability data is valuable for assessing soil-plant-water relationships, evapotranspiration, extreme weather and machineability of soils.

Other potential applications include tracking agricultural droughts and floods, crop establishment, crop management decisions and prediction of crop health and yields, the researchers said.

The team will collaborate with USDA Natural Resources Conservation Service soil scientist Amanda Pennino on this research project.

Last Updated October 24, 2023

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