Crop simulation model

On the basis of the literature reviewed in Section 2.1, the use of crop simulation models is iden- tified as the most promising method for deriving the crop-water production function. The crop simulation model that is selected for use in this thesis is AquaCrop. AquaCrop is a water-limited yield model developed by the Food and Agriculture Organization of the United Nations (FAO) (Raes et al., 2012). AquaCrop simulates above and below-ground crop growth processes across the soil-vegetation-atmosphere continuum on a daily time step at the field-scale. Model inputs include soil hydraulic properties and crop characteristics, daily weather data (maximum and minimum temperature, precipitation, and computed reference evapotranspiration), and irriga- tion management practices. A brief description of the key calculations that are performed by AquaCrop is provided below, and the reader is referred to the model documentation for a detailed account of model calculation procedures and equations (Raes et al., 2012).

AquaCrop uses a water-driven growth equation to predict daily crop transpiration, and trans- lates simulated transpiration into an estimate of accumulated above-ground biomass using a crop-specific water productivity parameter that captures the fundamental biophysical relation- ship between assimilation of carbon and transpiration of water by a crop (Steduto et al., 2007, 2009). On any given day of the crop growing season, the estimated crop transpiration is calcu- lated a function of the crop canopy size, root depth and distribution, water availability within the soil profile, and the reference evapotranspiration rate. The crop canopy cover and root system develop during the growing season based on the accumulation of growing degree days. Growing degree day accumulation is calculated using the maximum and minimum temperature inputs, and the specified crop phenological calendar. Crop yield that has developed by the end of a given day is then calculated as the product of the simulated above-ground biomass and crop harvest index. The crop harvest index defines the portion of accumulated biomass that is harvestable yield, and increases over the growing season towards a maximum reference value of between 0 % and 100 %. The reference harvest index value and the trajectory of harvest index build-up over the growing season are a function of crop type, and are also influenced by water and temperature stress effects that may restrict the development of harvestable yield.

Soil water availability in AquaCrop is simulated using a linked soil water balance model that divides the total depth of the soil profile into a set of discretised compartments. A finite- difference solution is used to solve for updated values of water contents in each compartment on each day of the simulation. The soil water balance solution explicitly considers processes of

surface runoff, drainage, infiltration, soil evaporation, and crop transpiration. First, drainage of water stored within the soil profile at the start of a time step is calculated. This calculation assumes that drainage from a soil compartment only occurs when the soil water content is greater than field capacity, and that drainage is an exponential function of the soil water content and a soil drainage parameter (Raes et al., 2006, 2009). Subsequently, incoming water from precipitation and irrigation is partitioned into surface runoff and infiltration using the curve number methodology (Rallison, 1980), and the percolation and storage of infiltrating water is calculated. Finally, processes of soil evaporation and crop transpiration are simulated, dependent on the availability of soil water to satisfy reference evapotranspiration and the canopy cover size that determines the partitioning of atmospheric demand between the two processes. Importantly, the simulated soil water content in compartments within the crop root zone directly determines the presence and magnitude of water stress effects on crop development. The effect of water stress on crop growth process in AquaCrop is dependent on both the level of soil moisture depletion and the sensitivity of the specific biological process, such as canopy expansion, stomatal closure, canopy senescence, and pollination, to water stress. For example, the rate of canopy cover or root depth expansion may be reduced at only moderate levels of soil water depletion, whereas premature canopy senescence or pollination failure will only occur in the presence of more significant levels of depletion.

For the purposes of this research, AquaCrop offers a number of advantages over alterna- tive crop simulation models. The use of a water-driven growth engine in AquaCrop ensures that important biophysical crop-water relations are represented. AquaCrop also has the ability to con- sider a variety of irrigation management strategies, making the model ideally suited for analysing crop-water production relationships. Furthermore, AquaCrop is substantially less complex and requires the specification of fewer input parameters than many other mechanistic crop simula- tion models, such as the Agricultural Production Systems Simulator model (APSIM) (Keating et al., 2003) or the Decision Support System for Agrotechnology Transfer model (DSSAT) (Jones et al., 2003) that, similarly to AquaCrop, have the capability of simulating multiple crop types. This relative computational simplicity is beneficial, particularly when seeking to apply the model within an integrated framework for the purposes of water resources management where highly complex crop simulation models may impose an unrealistic computational burden for both sim- ulation and calibration. Moreover, this simplicity does not compromise prediction accuracy, as illustrated by the fact that AquaCrop has been successfully applied to a wide variety of crops in a diverse range of geographic locations, including studies related to corn production in the United States (Heng et al., 2009; Hsiao et al., 2009; Mebane et al., 2013) and elsewhere (Stricevic et al.,

2011; Abedinpour et al., 2012; García-Vila and Fereres, 2012) that are of specific relevance to the case studies that AquaCrop is applied to in this thesis.

Despite these advantages, a major limitation of the original AquaCrop model is that all model runs must be conducted through a restrictive user-interface system. Combined with the lack of access to the original model source code, this setup presents problems for application of the model in integrated hydro-economic analysis and also for future model improvement. As a result, the decision was made to recode AquaCrop into the Matlab programming language version 2013b (Mathworks Inc., 2013). Significantly, while recoding was a time consuming and challenging task to undertake, the resultant Matlab-AquaCrop model provides greater potential for use in integrated hydro-economic analysis that would not be feasible using the original model setup. Appendix A describes the recoding procedure and shows the outputs from test simulations that have been conducted to illustrate the accurate reproduction of the original model code.