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ARS Home » Plains Area » Fort Collins, Colorado » Center for Agricultural Resources Research » Water Management and Systems Research » Research » Publications at this Location » Publication #281057

Title: Improving evapotranspiration simulations in the CERES-maize model under limited irrigation

item DeJonge, Kendall
item Ascough Ii, James
item ANDALES, ALLAN - Colorado State University
item HANSEN, NEIL - Colorado State University
item GARCIA, LUIS - Colorado State University
item ABABI, MADAZ - Colorado State University

Submitted to: Agricultural Water Management
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/24/2012
Publication Date: 9/19/2012
Citation: DeJonge, K.C., Ascough II, J.C., Andales, A.A., Hansen, N.C., Garcia, L.A., Ababi, M. 2012. Improving evapotranspiration simulations in the CERES-maize model under limited irrigation. Agricultural Water Management (2012), pp. 92-103.

Interpretive Summary: Recent studies have shown that the CERES-Maize crop growth model performs well under full irrigation, but overestimates evapotranspiration (ET) of corn under limited irrigation management. This study aimed to improve ET simulation under limited irrigation while having no detrimental effects in regard to other outputs, by changing the model code to create a dynamic crop coefficient (Kc) as a function of the crop leaf area index. The new model showed significant decreases in ET simulation error under limited irrigation, and hypothetical simulations indicate the model may predict increases in water use efficiency with decreasing water applications in the vegetative growth stage.

Technical Abstract: Limitations on water resources for agriculture in places such as Colorado, USA, have caused farmers to consider limited irrigation as an alternative to full irrigation practices, where the crop is intentionally stressed during specific growth stages in an effort to maximize yield per unit water consumed, or evapotranspiration (ET). Crop growth models such as CERES-Maize provide the ability to evaluate numerous management scenarios without the costs associated with multiyear field experiments. However, recent studies have shown that CERES-Maize performs well under full irrigation but overestimates ET of corn under limited irrigation management. The primary objective of this study was to improve CERES-Maize ET simulation under limited irrigation without introducing detrimental effects in regard to other model output responses. The local sensitivity of model input parameters affecting ET was evaluated, prompting a change to the coefficient that partitions potential ET into plant transpiration and soil evaporation. More significantly, model code was adjusted to create a dynamic crop coefficient (KCD) as a function of the crop leaf area index. The modified CERES-Maize model more accurately represented expected ET under full and limited irrigation, for example reducing late-season ET potential from a plant with reduced canopy and more closely matched FAO-56 crop coefficient curves under full irrigation. Field experiments with corn were performed in northern Colorado, USA from 2006-10, where four replicates each of full (100% of ET requirement for an entire season) and limited (100% of ET during reproductive stage only) irrigation treatments were analyzed. Using the limited irrigation data for evaluation, the new model showed significant decreases in model error for seasonal cumulative ET (root mean square deviation RMSD from 80.9 mm to 49.9 mm) and water use efficiency (RMSD from 5.97 kg ha-mm-1 to 2.86 kg ha-mm-1) as compared to the original model. The modified model was subsequently applied using the same northern Colorado, USA datasets under several hypothetical irrigation management strategies, with limited irrigation results exhibiting a water production function (yield vs. ET) different from the other management strategies. An additional hypothetical model application (using strictly limited irrigation management strategies) was conducted where rainfall in the precipitation inputs was excluded and water inputs were controlled entirely by weekly irrigations, with decreasing levels of irrigation during the vegetative stage but no water stress after anthesis. Results indicate that reducing weekly vegetative water applications from 20 mm to 2.5 mm increase simulated water use efficiency from 19.85 kg ha-mm-1 to 22.93 kg ha-mm-1. While these synthetic water production functions may not be feasible in a production field with natural climate variability, the new ET model indicates promise for limited irrigation management increasing water use efficiency. Additional studies are recommended for continued validation of the new dynamic KCD function and physiological response to water stress, as well as model studies evaluating potential benefits of limited irrigation management.