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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.

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.

Th e fi rst 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 fi eld 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 diff erent conditions and not specifi c to a given crop cultivar, was evaluated by test simulations, and used to simulate the 6 yr of Davis data. Th e treatment variable was irrigation-withholding water aft er 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. Th e conservative parameters included: canopy growth and canopy decline coeffi cient (CDC); crop coeffi cient 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 (HI o ); and coeffi cients 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 fi nal 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 fi ve 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. Th e 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 diffi cult 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 simplifi cations in the model and inaccuracies in measurements. Th e usefulness of AquaCrop with well-calibrated conservative parameters in assessing water use effi ciency (WUE) of a crops under diff erent conditions and in devising strategies to improve WUE is discussed. area index; p, fractional depletion of total available water in the root zone; PWP, permanent wilting point; SWC, soil water content; Tr, crop transpiration; WP, water productivity (for biomass); WP*, normalized (for evaporative demand and atmospheric CO 2 ) water productivity (for biomass); WUE, water use effi ciency.

Seedlings of maize (Zea mays L. cv WF9 x Mo 17) were grown in vermiculite at various water potentials. The primary root continued slow rates of elongation at water potentials which completely inhibited shoot growth. To gain an increased understanding of the root growth response, we examined the spatial distribution of growth at various water potentials. Time lapse photography of the growth of marked roots revealed that inhibition of root elongation at low water potentials was not explained by a proportional decrease in growth along the length of the growing zone. Instead, longitudinal growth was insensitive to water potentials as low as -1.6 megapascal close to the root apex, but was inhibited increasingly in more basal locations such that the length of the growing zone decreased progressively as the water potential decreased. Cessation of longitudinal growth occurred in tissue of approximately the same age regardless of spatial location or water status, however. Roots growing at low water potentials were also thinner, and analysis revealed that radial growth rates were decreased throughout the elongation zone, resulting in greatly decreased rates of volume expansion.anism by which osmotic adjustment occurs in roots growing at low q. Specifically, our aim is to determine the extent to which the maintenance of lower 4i, in the growing zone under water deficits can be attributed to increased rates of solute deposition, or to reduced growth and hence slower rate of osmoticum dilution by volume expansion. In this paper, attention is focused on the effects of low qf,y on the spatial distribution of expansive growth rate. Although the spatial growth pattern at high q,, for roots of maize and other species has been well characterized for many years (8,11), the extent to which the pattern may change at low q is not known. Indeed, despite early recognition that knowledge of how plant growth patterns may be altered by environmental variation facilitates the opportunities to understand the regulation of the growth response (11), relatively little information of this kind is available. Here, we show that both longitudinal and radial growth patterns are altered markedly in roots growing at low qi,. In a forthcoming paper (RE Sharp, TC Hsiao, WK Silk, unpublished data), we combine this information with profiles of qi5 and component solutes to determine effects of low q on solute deposition rates in the root growing zone, and evaluate the relationship of the growth and solute deposition responses to osmotic adjustment.Plant growth is generally decreased when soil water is limited. Root growth is often less inhibited than shoot growth (2, 21), however. A recent study of maize has shown that root growth is intrinsically less sensitive than growth of the aerial plant parts to low water potentials (q') of the growing region (30), indicating some form of internal regulation. Root elongation is of obvious advantage to plants in drying soil, and may be particularly important for seedling establishment because of the vulnerabi...