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ARS Home » Plains Area » Bushland, Texas » Conservation and Production Research Laboratory » Soil and Water Management Research » Research » Publications at this Location » Publication #230178

Title: Validating the FAO AquaCrop model for irrigated and water deficient field maize

Author
item Heng, Lee
item Hsiao, Theodore
item Steduto, Pasquale
item Evett, Steven - Steve
item Howell, Terry
item Raes, Dirk
item Fereres, Elias

Submitted to: Agronomy Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/8/2008
Publication Date: 4/3/2009
Citation: Heng, L., Hsiao, T., Steduto, P., Evett, S.R., Howell, T.A., Raes, D., Fereres, E. 2009. Validating the FAO AquaCrop model for irrigated and water deficient field maize. Agronomy Journal. 101(3):488-498.

Interpretive Summary: The United Nations Food and Agriculture Organization (FAO) is interested in developing simple but robust methods to estimate the crop yield response to water. A new model named AquaCrop was developed for that purpose. The model was initially evaluated with maize (corn) response to water from previous experiments at the University of California at Davis. This paper further evaluated the AquaCrop model for predicting crop yield and water use (evapotranspiration, ET) with more diverse data from different environments and soils at Bushland, Texas; Gainesville, Florida; and Zaragoza, Spain. The three locations had extraordinarily high ET and wind speed in the Bushland studies; rainy weather and sandy soil in the Gainesville studies; and semi-arid condition in the Zaragoza studies in Spain. The model accurately estimated the ET under very high ET and wind conditions and performed satisfactorily for the growth of aboveground maize dry matter production, grain yield, and canopy cover in the more fully irrigated treatments and mild water deficit conditions. The model was less satisfactory in estimating ET or grain yields from more severely water-stressed treatments, especially when stress occurred during senescence of the crop season. The AquaCrop model was relatively easy to use and had a low data requirement for input parameters. The AquaCrop model was deemed to be a valuable tool for estimating crop productivity under rainfed conditions, supplementary and deficit irrigation, and on-farm water management strategies for improving the efficiency of water use in agriculture.

Technical Abstract: Accurate crop development models are important tools in evaluating the effects of water deficits on crop yield or productivity. The FAO AquaCrop model, predicting crop productivity and water requirement under water-limiting conditions, was calibrated and validated for maize (Zea mays L.) using six years of data sets from Davis, California (Hsiao et al., 2008). The set of conservative parameters obtained in that study, considered applicable to a wide range of conditions and not specific to a given maize cultivar, were used to further evaluate the performance of AquaCrop model for maize using data from three studies carried out under diverse environmental conditions: Bushland, Texas; Gainesville, Florida; and Zaragoza, Spain. The three locations were characterized by the extraordinarily high evapotranspiration and wind speed in the Bushland study; rainy weather and sandy soil in the Gainesville study; and the semi-arid conditions in the Zaragoza study. The model was able to simulate the crop water use (ET) under very high ET and wind conditions. Furthermore, the model performed satisfactorily for the growth of aboveground biomass, grain yield, and canopy cover in the non-water stress treatments and mild stress conditions, but it was less satisfactory in simulating severe water-stress treatments especially when stress occurred during senescence. The ease of use of AquaCrop model, the low requirement of input parameters, and its sufficient degree of simulation accuracy make it an invaluable tool for estimating crop productivity under rainfed conditions, supplementary and deficit irrigation, and on-farm water management strategies for improving the efficiency of water use in agriculture.