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United States Department of Agriculture

Agricultural Research Service

Research Project: IRRIGATION MANAGEMENT AND AUTOMATION FOR INCREASED WATER USE EFFICIENCY
2010 Annual Report


1a.Objectives (from AD-416)
Determine methods for improved quantification of evapotranspiration (ET) and crop coefficients under all constraints in order to improve irrigation scheduling and water use efficiency. Develop remote sensing technologies and tools designed for improved prediction of crop water use and water stress at field and watershed spatial scales. Develop, test, and implement feedback systems for spatially and temporally variable irrigation application of water and nutrients, and develop, test and implement improved sensors for soil water content and plant stress. Develop and validate remote sensing technologies and procedures to enhance spatially and temporally variable crop water status feedback systems for use in variable rate irrigation systems. Quantify and improve crop water use efficiency in dryland/irrigated cropping systems in relation to tillage, irrigation, and crop management practices.


1b.Approach (from AD-416)
Research approaches include determinations of crop water use by soil water balance techniques (weighing lysimeters and neutron scattering methods) in practically all experiments, which include variations in irrigation method (subsurface drip at several depths and spacings, sprinkler, and low energy precision application or LEPA), irrigation amount (full and two to three levels of deficit), tillage (no-tillage, conventional, strip till, etc.), and/or crop and crop rotation, including rotation between irrigated and dryland cropping. Automatic irrigation systems based on sensing of crop status are designed/engineered and tested for ability to control crop water use efficiency and yield, thus reducing management expense (time and effort) while allowing management to control irrigation for best profitability and optimum water use. Key in this effort is evaluation and design of new crop and soil water status sensors. Remote sensing approaches to water use prediction are expected to improve energy balance modeling methods to make them useful for managers at farm, irrigation project, and watershed scales, and for policy makers.


3.Progress Report
Final report for project 6209-13000-012-00D, which was rolled into project 6209-13000-013-00D. Project milestones have substantial overlap; 5th-year milestones for this project will be addressed under project 6209-13000-013-00D. Important progress was made during the 4 project years. 1. Crop water use can be calculated at multiple scales using computer models driven by satellite & weather data. The "2-source" model, previously validated in humid regions, was improved & tested for the semiarid warmer & windier High Plains where row crops often incompletely cover the soil. New row-crop submodels better partitioned sunshine between plants & soil, improving the model accuracy, key for widespread effective water resource management. 2. Cool weather limits cotton yields in the northern parts of the Southern High Plains. Sandy soils warm easily to growth-promoting temperatures, unlike silts & clays. Warmth in sandy soil resulted in greater early season growth, resulting in larger yields & more efficient use of limited irrigation water. But, high early season warmth quickly dried sandy soil, reversing the yield trends. In most years, to achieve the largest yields with the least water, cotton should be grown in sandy soils in this region. 3. Profitability of irrigated agriculture in the Texas High Plains is limited by large pumping costs & the loss of nutrients & water from over-irrigation, which decrease yields & increase expenses. With Texas AgriLife Research & Extension Service, the Texas High Plains ET Network & automated mailing list server was created. It delivers standardized, accurate irrigation scheduling & weather data from 19 weather stations to producers and over 20 federal and state research, teaching, and extension projects, including the Ogallala Aquifer Program. Increased yields reported by cotton & corn producers and reduced pumping costs translate into profits >$12 million. 4. Existing soil water content sensors often don't work well enough for efficient agricultural water management. With the International Atomic Energy Agency, the accuracy & utility of major sensor types were assessed and published in a guide to sensor selection and use that is used by irrigation & natural resource managers, scientists & engineers. New knowledge about common sensor problems was conveyed to the Irrigation Association to guide sensor evaluation in the Smart Water Application Technologies program approved by EPA. Sensor manufacturers & industry users were helped to solve sensor problems. The work led to a CRADA to develop an accurate deep, down-hole soil water sensing system. 5. Over irrigation reduces agricultural profits due to high pumping costs, & nutrient & water losses that decrease yields & increase expenses; yet producers lack time to manage irrigation. An automatic system was created to remotely read crop leaf temperatures & control a center pivot irrigation system to apply water according to crop water need. The system produced high yields & water use efficiency while applying water efficiently, reducing management effort & eliminating over irrigation. This work led to a CRADA for technology transfer to an irrigation systems manufacturer.


4.Accomplishments
1. Weather and crop water use network provides updated regional water use projections for next 50 years in northern Texas. In the northern Texas High Plains where irrigation accounts for 90% of all water use, accurate and representative irrigation water use estimates are key for sustainability of production agriculture. ARS and Texas AgriLife Research updated and improved evapotranspiration (ET) data from the Texas High Plains ET Network (TXHPET). The data are used to compute water use and irrigation water demand estimates for all crops grown in the Texas Panhandle. The ET data are used with Farm Service Agency crop acreage data and precipitation on a county basis to run the Texas A&M–Amarillo (TAMA) irrigation demand model, which was modified to include new crop categories and yearly and forecasted ET data inputs. Model output and trend analysis agreed very well with recorded producer values. Use of the accurate and representative TXHPET network-based water use data reflects actual reductions in water use by producers using new and improved irrigation management, technology and methods; and it accurately reflects the production potential going forward within the region. This information is being used by regional water planners for water demand planning purposes, by groundwater water conservation districts in establishing pumping regulations, and for regional socio-economic and sustainability analyses.

2. Crop water use model provides improved management of water resources. The two-source energy balance model provides vegetative water use data derived from satellite and airborne remote sensing by calculating water evaporated from the soil as well as that used by the crop. For accurate water use estimates, sunlight (solar energy) must be correctly partitioned between that striking the soil and that striking vegetation. Scientists at the USDA-ARS laboratory in Bushland, Texas, changed the solar energy partitioning component of the model, thus improving the accuracy of water use estimates. The changes are being incorporated to improve water use estimates at various scales from farm field to watershed and region. This will enhance on-farm management of both irrigated and dryland crops, and will also improve regional water resources management and planning in the Southern High Plains and Ogallala Aquifer. The model has application to vegetated surfaces worldwide and has potential as a tool to improve the management of water resources in both cultivated and non-cultivated land areas.


Review Publications
Price, J.A., Workneh, F., Evett, S.R., Jones, D., Arthur, J., Rush, C.M. 2010. Effects of wheat streak mosaic virus on root development and water-use efficiency of hard red winter wheat. Plant Disease. 94(6):766-770.

Evett, S.R., Schwartz, R.C., Tolk, J.A., Howell, T.A. 2009. Soil profile water content determination: Spatiotemporal variability of electromagnetic and neutron probe sensors in access tubes. Vadose Zone Journal. 8(4):926-941.

Logsdon, S.D., Green, T.R., Seyfried, M.S., Evett, S.R., Bonta, J.V. 2010. Hydra Probe and Twelve-wire Probe Comparisons in Fluids and Soil Cores. Soil Science Society of America Journal. 74:5-12.

Meek, D.W., Howell, T.A., Phene, C. Concordance correlation for model performance assessment: An example with reference evapotranspiration. Agronomy Journal. 101(4): 1012-1018.

Last Modified: 10/20/2014
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