Agronomy Journal

Evett, Steven R.; Tolk, Judy A.

doi: 10.2134/agronj2009.0038xspmid: N/A

Crop water use efficiency (WUE, yield per unit of water use) is key for agricultural production with limited water resources. Policymakers and water resource managers working at all scales need to address the multitudinous scenarios in which cropping systems and amounts, timing and methods of irrigation, and fertilizer applications may be changed to improve WUE while meeting yield and harvest quality goals. Experimentation cannot address all scenarios, but accurate simulation models may fill in the gaps. The nine papers in this special section explore how four simulation models were used to simulate yield, water use, and WUE of cotton (Gossypium hirsutum L.), maize (Zea mays L.), quinoa (Chenopodium quinoa Willd.), and sunflower (Helianthus annuus L.) in North and South America, Europe, and the Middle East. All the models simulated WUE adequately under well‐watered conditions, but tended to misestimate WUE under conditions of water stress, which limits their use for exploration of deficit irrigation scenarios or rain‐fed or dryland situations with expected soil water deficits. None of the experimental conditions reported involved separate measurements of evaporation (E) and transpiration (T); so there was no opportunity to test the separation of E and T simulated in the newest of the models, AquaCrop. The lack of separate E measurements also limited the authors in exploring reasons why WUE was not simulated well under water stress conditions. Future studies exploring WUE simulation should include E or T measurements so that effects of management methods that reduce E can be studied.

Steduto, Pasquale; Hsiao, Theodore C.; Raes, Dirk; Fereres, Elias

doi: 10.2134/agronj2008.0139spmid: N/A

This article introduces the FAO crop model AquaCrop. It simulates attainable yields of major herbaceous crops as a function of water consumption under rainfed, supplemental, deficit, and full irrigation conditions. The growth engine of AquaCrop is water‐driven, in that transpiration is calculated first and translated into biomass using a conservative, crop‐specific parameter: the biomass water productivity, normalized for atmospheric evaporative demand and air CO2 concentration. The normalization is to make AquaCrop applicable to diverse locations and seasons. Simulations are performed on thermal time, but can be on calendar time, in daily time‐steps. The model uses canopy ground cover instead of leaf area index (LAI) as the basis to calculate transpiration and to separate out soil evaporation from transpiration. Crop yield is calculated as the product of biomass and harvest index (HI). At the start of yield formation period, HI increases linearly with time after a lag phase, until near physiological maturity. Other than for the yield, there is no biomass partitioning into the various organs. Crop responses to water deficits are simulated with four modifiers that are functions of fractional available soil water modulated by evaporative demand, based on the differential sensitivity to water stress of four key plant processes: canopy expansion, stomatal control of transpiration, canopy senescence, and HI. The HI can be modified negatively or positively, depending on stress level, timing, and canopy duration. AquaCrop uses a relatively small number of parameters (explicit and mostly intuitive) and attempts to balance simplicity, accuracy, and robustness. The model is aimed mainly at practitioner‐type end‐users such as those working for extension services, consulting engineers, governmental agencies, nongovernmental organizations, and various kinds of farmers associations. It is also designed to fit the need of economists and policy specialists who use simple models for planning and scenario analysis.

Raes, Dirk; Steduto, Pasquale; Hsiao, Theodore C.; Fereres, Elias

doi: 10.2134/agronj2008.0140spmid: N/A

The AquaCrop model was developed to replace the former FAO I&D Paper 33 procedures for the estimation of crop productivity in relation to water supply and agronomic management in a framework based on current plant physiological and soil water budgeting concepts. This paper presents the software of AquaCrop for which the concepts and underlying principles are described in the companion paper (Steduto et al., 2009). Input consists of weather data, crop characteristics, and soil and management characteristics that define the environment in which the crop will develop. Algorithms and calculation procedures modeling the infiltration of water, the drainage out of the root zone, the canopy and root zone development, the evaporation and transpiration rate, the biomass production, and the yield formation are presented. The mechanisms of crop response to cope with water shortage are described by only a few parameters, making the underlying processes more transparent to the user. AquaCrop is a menu‐driven program with a well‐developed user interface. With the help of graphs which are updated each time step (1 d) during the simulation run, the user can track changes in soil water content, and the corresponding changes in crop development, soil evaporation and transpiration rate, biomass production, and yield development. One can halt the simulation at each time step, to study the effect of changes in water related inputs, making the model particularly suitable for developing deficit irrigation strategies and scenario analysis.

Hsiao, Theodore C.; Heng, Lee; Steduto, Pasquale; Rojas‐Lara, Basilio; Raes, Dirk; Fereres, Elias

doi: 10.2134/agronj2008.0218spmid: N/A

The first crop chosen to parameterize and test the new FAO AquaCrop model is maize (Zea mays L.). Working mainly with data sets from 6 yr of maize field experiments at Davis, CA, plus another 4 yr of Davis maize canopy data, a set of conservative (nearly constant) parameters of AquaCrop, presumably applicable to widely different conditions and not specific to a given crop cultivar, was evaluated by test simulations, and used to simulate the 6 yr of Davis data. The treatment variable was irrigation—withholding water after planting continuously, only up to tasseling, from tasseling onward, or intermittently, and with full irrigation (FI) as the control. From year to year, plant density (7–11.9 plants m−2), planting date (14 May−15 June), cultivar (a total of four), and atmospheric evaporative demand varied. The conservative parameters included: canopy growth and canopy decline coefficient (CDC); crop coefficient for transpiration (Tr) at full canopy; normalized water productivity for biomass (WP∗); soil water depletion thresholds for the inhibition leaf growth and of stomatal conductance, and for the acceleration of canopy senescence; reference harvest index (HIo); and coefficients for adjusting harvest index (HI) in relation to inhibition of leaf growth and of stomatal conductance. With all 19 parameters held constant, AquaCrop simulated the final aboveground biomass within 10% of the measured value for at least 8 of the 13 treatments (6 yr of experiments) and also the grain yield for at least five of the cases. In at least four of the cases, the simulated results were within 5% of the measured for biomass as well as for grain yield. The largest deviation between the simulated and measured values was 22% for biomass, and 24% for grain yield. Importantly, the simulated pattern of canopy progression and biomass accumulation over time were close to those measured, with Willmott's index of agreement (d) for 11 of the 13 cases being ≥0.98 for canopy cover (CC), and ≥0.97 for biomass. Accelerated senescence of canopy due to water stress, however, proved to be difficult to simulate accurately; of the six cases, the index of agreement for the worst one was 0.957 for canopy and 0.915 for biomass. Possible reasons for the discrepancies between the simulated and measured results include simplifications in the model and inaccuracies in measurements. The usefulness of AquaCrop with well‐calibrated conservative parameters in assessing water use efficiency (WUE) of a crops under different conditions and in devising strategies to improve WUE is discussed.

Baumhardt, R. L.; Staggenborg, S. A.; Gowda, P. H.; Colaizzi, P. D.; Howell, T. A.

doi: 10.2134/agronj2008.0041xspmid: N/A

Increasing pumping costs and declining well capacities in the Southern High Plains compel producers to seek irrigation strategies to maximize yield and water use efficiency (WUE), which is the ratio of yield to evapotranspiration (ET). Cotton (Gossypium hirsutum L.) is suited to deficit irrigation using wells ranging from 0.29 to 0.93 L s−1 ha−1 capacity to supply limited, 2.5 mm d−1, to complete, 8.1 mm d−1 ET replacement. Our objectives were to (i) evaluate irrigation capacity and duration effects on lint yield, and (ii) compare application strategies that maximize yield and WUE. The simulation model GOSSYM was used with 1959 to 2000 weather records from Bushland, TX, to calculate yields of cotton grown on a Pullman clay loam (fine, mixed, superactive, thermic Torrertic Paleustoll) with 50 or 100% initial available soil water. We compared all combinations of irrigation duration (4, 6, 8, and 10 wk) and capacity (for ET replacement of 2.5, 3.75, and 5.0 mm d−1 and dryland). Simulated lint yield decreased as irrigation decreased; however, yields for similar irrigation totals increased with increasing irrigation capacity. Simulated yields for cotton irrigated > 8 wk did not differ among irrigation capacities, but cotton irrigated at 5.0 mm d−1 maintained yield with earlier irrigation termination at 6 wk. Based on mean yields, we determined that spreading water to deficit irrigate a field with 2.5 mm d−1 yielded ∼5% less lint than concentrating that water to irrigate smaller fields at 3.75 or 5.0 mm d−1 that were averaged with complementary (2:1 and 1:1) dryland areas.

Farahani, Hamid J.; Izzi, Gabriella; Oweis, Theib Y.

doi: 10.2134/agronj2008.0182spmid: N/A

Predicting yield is increasingly important to optimize irrigation under limited available water for enhanced sustainability and profitable production. Food and Agriculture Organization (FAO) of the United Nations addresses this need by providing a yield response to water simulation model (AquaCrop) with limited sophistication. In this study, AquaCrop was parameterized and tested for cotton (Gossypium hirsutum L.) under full (100%) and deficit (40, 60, and 80% of full) irrigation regimes in the hot, dry, and windy Mediterranean environment of northern Syria. Model parameterization used the 2006 data and was straightforward within the designed user‐interface, owing to the limited number of key parameters. Accurate simulation of canopy cover was central to sound prediction of evapotranspiration and biomass accumulation. Key user‐input parameters for this purpose were identified as the coefficients defining canopy development and the threshold soil water depletion levels for the water stress indices. The parameterized model was tested using data from the 2004 and 2005 seasons, resulting in accurate prediction of evapotranspiration (<13% error). The predicted yield values were within 10% of measurements, except in the 60 and 80% irrigation regimes in 2004, with errors up to 32%. The model closely predicted the trend in total soil water, but deviation existed for individual soil layers. This study provides first estimate values for cotton parameters useful for future model testing and use. Model parameterization is site‐specific, and thus the applicability of key calibrated parameters must to be tested under different climate, soil, variety, irrigation methods, and field management.

García‐Vila, M.; Fereres, E.; Mateos, L.; Orgaz, F.; Steduto, P.

doi: 10.2134/agronj2008.0179spmid: N/A

Given the current pressures to reduce irrigation water use, it is important to optimize the use of water in irrigated agriculture. This work was aimed at determining the optimum level of applied irrigation water (AIW) for cotton (Gossypium hirsutum L.) production in southern Spain under several climatic and agricultural policy scenarios. To generate the yield response to variations in AIW, we used the FAO crop water productivity (WP) model, AquaCrop. Model calibration and validation using four experiments conducted in the region showed that AquaCrop adequately simulated the yield response to AIW. The model was then used to determine the yield–AIW functions for different scenarios, assuming the best deficit irrigation (DI) strategy. An economic optimization procedure showed that maximum profits occurred at AIW values between 540 and 740 mm, depending on the climatic scenario. However, profits stayed close to the maximum (above 95%) for AIW levels exceeding 300–350 mm, indicating that under DI, AIW may be reduced significantly with little impact on profits. A sensitivity analysis suggested that increasing the price of water above the current level will have only a limited impact on optimum AIW, and that the current Common Agricultural Policy (CAP) of the European Union does not encourage water conservation in cotton irrigation. We conclude that AquaCrop is a useful tool to assist managers for making decisions in cotton irrigation under water supply restrictions.

Heng, Lee Kheng; Hsiao, Theodore; Evett, Steve; Howell, Terry; Steduto, Pasquale

doi: 10.2134/agronj2008.0029xspmid: N/A

Accurate crop development models are important tools in evaluating the effects of water deficits on crop yield or productivity. The FAO AquaCrop model predicts crop productivity, water requirement, and water use efficiency (WUE) under water‐limiting conditions. A set of conservative parameters [calibrated and validated for maize (Zea mays L.) in a prior study and 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 performed under diverse environmental conditions: Bushland, TX; Gainesville, FL; and Zaragoza, Spain. The three locations were characterized by the extraordinarily high evapotranspiration (ET) and wind speed in the Bushland study; rainy weather and sandy soil in the Gainesville study; and the semiarid 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 (CC) 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 the AquaCrop model, the low requirement of input parameters, and its sufficient degree of simulation accuracy make it 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.

Geerts, Sam; Raes, Dirk; Garcia, Magali; Miranda, Roberto; Cusicanqui, Jorge A.; Taboada, Cristal; Mendoza, Jorge; Huanca, Ruben; Mamani, Armando; Condori, Octavio; Mamani, Judith; Morales, Bernardo; Osco, Victor; Steduto, Pasquale

Todorovic, Mladen; Albrizio, Rossella; Zivotic, Ljubomir; Saab, Marie‐Therese Abi; Stöckle, Claudio; Steduto, Pasquale

doi: 10.2134/agronj2008.0166spmid: N/A

This work compares the performance of AquaCrop, a crop simulation model developed by FAO, with that of two well established models, CropSyst and WOFOST, in simulating sunflower (Helianthus annuus L.) growth under different water regimes in a Mediterranean environment. The models differ in the level of complexity describing crop development, in the main growth modules driving the simulation of biomass growth, and in the number of input parameters. AquaCrop is exclusively based on the water‐driven growth module, in that transpiration is converted into biomass through a water productivity (WP) parameter; Cropsyst is based on both water and radiation driven modules, while WOFOST simulates crop growth using a carbon driven approach and fraction of intercepted radiation. The data used in the analysis were obtained in field experiments with hybrid Sanbro_MR, performed in a typical Mediterranean area of Southern Italy in 2005 and 2007. The models were calibrated on data from a full irrigation treatment in 2007, and were validated on a full irrigation treatment in 2005 and several deficit irrigation (DI) treatments, including regulated deficit irrigation (RDI) and rain‐fed (RF) conditions. Although AquaCrop required less input information than CropSyst and WOFOST, it performed similarly to them in simulating both biomass and yield at harvesting. The use of different numbers of parameters and crop growth modules by the tested models did not influence substantially the simulation results. Therefore, for management purposes and in conditions of limited input information, the use of simpler models should be encouraged.