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Title: Incorporating field wind data to improve crop evapotranspiration parameterization in heterogeneous regions

item Anderson, Raymond - Ray
item Ferreira, Jorge
item Jenkins, Dennise
item DA SILVA DIAS, NILDO - Federal Rural University Of The Semi-Arid
item Suarez, Donald

Submitted to: Irrigation Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/11/2017
Publication Date: 9/16/2017
Publication URL:
Citation: Anderson, R.G., Ferreira, J.F., Jenkins, D.L., da Silva Dias, N., Suarez, D.L. 2017. Incorporating field wind data to improve crop evapotranspiration parameterization in heterogeneous regions. Irrigation Science. 35(6):533-547.

Interpretive Summary: Accurate estimation of agricultural crop water consumption is necessary for proper irrigation scheduling. Overestimation of crop water requirements may lead to over-irrigation and unnecessary use of potentially expensive and scarce water and energy. Underestimation of crop water demand may lead to under-irrigation and crop water stress than can reduce crop yield and quality. Currently, crop water consumption is estimated by multiplying a “reference evapotranspiration” by a crop coefficient which accounts for the specific crop, plant density, and growth stage. The reference evapotranspiration is computed from meteorological data gathered over a short, well-watered, grass field. Many states have networks of reference evapotranspiration stations for farmers to use in calculating crop water consumption. However, the density of these stations can be low relative to the local topographic and climatic variability of an agricultural region, resulting in fields and farms that have a substantially different microclimate and reference evapotranspiration than the closest reference evapotranspiration station. In this study we use data from a reference and non-reference meteorological station to estimate crop water consumption at two research fields in Southern California, a region with high microclimate variability, high value specialty crops, and very expensive water. The results illustrate the impact of local microclimates on agricultural crop water consumption and the potential improvement in crop water use estimation from an on field wind speed sensor than can be integrated with other meteorological data (air temperature, sunlight, and relative humidity) from reference evapotranspiration stations. The results highlight the potential value for farmers to have at least some meteorological sensors on their own field(s). The research benefits farmers, irrigation managers, and irrigation districts in the Western U.S. who experience high microclimatic variation and who need to maximize crop water productivity due to scarcity or expense of irrigation water.

Technical Abstract: Accurate parameterization of reference evapotranspiration (ET0) is necessary for optimizing irrigation scheduling and avoiding costs associated with over-irrigation (water expense, loss of water productivity, energy costs, pollution) or with under-irrigation (crop stress and suboptimal yields or quality). ET0 is often estimated using the FAO-56 method with meteorological data gathered over a reference surface, usually short grass. However, the density of suitable ET0 stations is often low relative to the microclimatic variability of many arid and semi-arid regions, leading to a potentially inaccurate ET0 for irrigation scheduling. In this study we investigated multiple ET0 products from six meteorological stations, a satellite ET0 product, and integration (merger) of two stations’ data in Southern California, USA. We evaluated ET0 against lysimetric ET observations from two lysimeter systems (weighing and volumetric) and two crops (wine grapes and Jerusalem artichoke) by calculating crop ET (ETc) using crop coefficients for the lysimetric crops with the different ET0. ETc calculated with ET0 products that incorporated field-specific wind speed had closer agreement with lysimetric ET, with RMSE reduced by 36% and 45% for grape and Jerusalem artichoke, respectively, with on field anemometer data compared to wind data from the nearest station. The results indicate the potential importance of on-site meteorological sensors for ET0 parameterization; particularly where microclimates are highly variable and/or irrigation water is expensive or scarce.