Claudio O. Stöckle

CropSyst, a cropping systems simulation model

CropSyst is a multi-year, multi-crop, daily time step cropping systems simulation model developed to serve as an analytical tool to study the effect of climate, soils, and management on cropping systems productivity and the environment. CropSyst simulates the soil water and nitrogen budgets, crop growth and development, crop yield, residue production and decomposition, soil erosion by water, and salinity. The development of CropSyst started in the early 1990s, evolving to a suite of programs including a cropping systems simulator (CropSyst), a weather generator (ClimGen), GIS-CropSyst cooperator program (ArcCS), a watershed model (CropSyst Watershed), and several miscellaneous utility programs. CropSyst and associated programs can be downloaded free of charge over the Internet. One key feature of CropSyst is the implementation of a generic crop simulator that enables the simulation of both yearly and multi-year crops and crop rotations via a single set of parameters. Simulations can last a fraction of a year to hundreds of years. The model has been evaluated in many world locations by comparing model estimates to data collected in field experiments. CropSyst has been applied to perform risk and economic analyses of scenarios involving different cropping systems, management options, and soil and climatic conditions. An extensive list of references related to model development, evaluation, and application is provided.

Effects of climate change and elevated CO2 on cropping systems: model predictions at two Italian locations

The potential effects of future climate change were investigated, corresponding to a doubling of atmospheric CO2 from 350 to 700 ppm, on agricultural production of four different cropping systems at two Italian locations, Modena and Foggia. Climate change scenarios, derived from two general circulation models (GCMs), were used as weather input to a soil-plant growth simulator, CropSyst. This model was recently modified to include the effects of elevated CO2 on crop photosynthesis and transpiration. Six different crops in total were simulated at the two Italian sites. At Modena, a 3-year maize‐maize‐wheat rotation and a 2-year soybean‐barley‐summer sorghum rotation were studied. At Foggia, a 2-year sunflower‐wheat‐fallow rotation, and a 2-year wheat‐fallow‐spring sorghum rotation were simulated. Results suggested that the combined effects of elevated atmospheric CO2 and climate change at both sites would depress crop yields if current management practices were not modified. Specifically, predicted warmer air temperatures accelerated plant phenology, reducing dry matter accumulation and crop yields by 10‐40%. By investigating adaptation strategies, it was found that a combination of early planting for spring‐summer crops and the use of slower-maturing winter cereal cultivars succeeds in maintaining crop yields at current levels at both sites. For irrigated maize and soybean production at Modena, 60‐90% more irrigation water was required under climate change to keep grain yields at current levels. This implies that adaptation to climate change may be limited for irrigated crops, depending on site-specific water availability.

CropSyst, a cropping systems simulation model: water/nitrogen budgets and crop yield

Abstract In agriculture, water and nitrogen are two critical resources for growing a crop. However, their management cannot be analyzed independently of weather, soil characteristics, field hydrology, crop characteristics, crop rotation, and management factors. This paper describes the water, nitrogen, and crop growth components of CropSyst, a comprehensive cropping systems simulation model, and provides preliminary verification of these components. The water budget of the model properly describes crop water use. Predicted nitrogen contents throughout the soil profile did not exactly match the measured values from leaching experiments, but they did follow the general trends of the data. The agreement between simulated and observed biomass and yield of corn, winter wheat and spring wheat grown in two locations with a total of 77 data points was good as shown by several statistical indicators. Based on this preliminary validation, CropSyst appears promising as a tool to analyze management practices for water and nitrogen. Additional validation of model components, including a wide range of crops and conditions, should be conducted in the future.

A method for estimating the direct and climatic effects of rising atmospheric carbon dioxide on growth and yield of crops: Part I--Modification of the EPIC model for climate change analysis

The potential impact of the global rise in atmospheric CO2 concentration and associated climatic change on agricultural productivity needs assessment. The complexity of climate-crop production interactions makes computer simulation a natural approach for such assessment. EPIC, a comprehensive mathematical cropping system model, was modified to account for the effects of change in CO2 concentration and vapor pressure deficit on the radiation-use efficiency, leaf resistance and transpiration of crops. Details of these modifications are presented in this paper. A companion paper describes an application of the modified model (this issue).

Multimodel ensembles of wheat growth: many models are better than one.

Crop models of crop growth are increasingly used to quantify the impact of global changes due to climate or crop management. Therefore, accuracy of simulation results is a major concern. Studies with ensembles of crop models can give valuable information about model accuracy and uncertainty, but such studies are difficult to organize and have only recently begun. We report on the largest ensemble study to date, of 27 wheat models tested in four contrasting locations for their accuracy in simulating multiple crop growth and yield variables. The relative error averaged over models was 24-38% for the different end-of-season variables including grain yield (GY) and grain protein concentration (GPC). There was little relation between error of a model for GY or GPC and error for in-season variables. Thus, most models did not arrive at accurate simulations of GY and GPC by accurately simulating preceding growth dynamics. Ensemble simulations, taking either the mean (e-mean) or median (e-median) of simulated values, gave better estimates than any individual model when all variables were considered. Compared to individual models, e-median ranked first in simulating measured GY and third in GPC. The error of e-mean and e-median declined with an increasing number of ensemble members, with little decrease beyond 10 models. We conclude that multimodel ensembles can be used to create new estimators with improved accuracy and consistency in simulating growth dynamics. We argue that these results are applicable to other crop species, and hypothesize that they apply more generally to ecological system models.

Evaluation of CropSyst for cropping systems at two locations of northern and southern Italy

Abstract We tested the capability of CropSyst, a cropping system simulation model, to simulate cropping systems at two locations (Modena and Foggia) representative of the largest plain areas of Italy. Experimental data collected from rotation experiments during the period 1985–1991 were used to calibrate and validate the model. The data set available was not detailed enough to test most of the sub-models, but it was adequate for a satisfactory test of overall model performance. Simulations were conducted for 6-year rotations providing initial conditions of the first year without reinitializing the model in later years in the rotation sequence. Model evaluation was performed with the understanding that a large amount of variability was present in the data and that rotation effects other than water (e.g., diseases) were not accounted for by the model. The phenology sub-model proved sufficiently accurate, showing some limitation only in the case of winter cereals. Model simulations of maize, soybean, and barley growth at Modena, and sorghum and sunflower growth at Foggia were reasonably accurate. CropSyst was able to predict neither the yields of soybean grown as a second crop, nor the durum wheat yield variability in the rotations at Foggia. Although CropSyst was able to simulate reasonably well a number of cropping systems, the development of a more detailed field data base is desirable for further evaluation and improvement of the model for Italian conditions.

A method for estimating the direct and climatic effects of rising atmospheric carbon dioxide on growth and yield of crops: Part II—Sensitivity analysis at three sites in the Midwestern USA

Abstract That atmospheric CO2 concentration is increasing is well established, and it is generally well accepted that this increase will have beneficial effects on plant productivity. What remains most uncertain is the nature and magnitude of the climatic changes that will occur as a result of the increase of carbon dioxide and other radiatively active trace gases. Thus, it is difficult to predict the combined impact of increasing atmospheric carbon dioxide on agricultural productivity. A comprehensive cropping system simulation model, EPIC, was used in a sensitivity analysis of crop growth response to the combined effects of CO2 concentration increase and CO2-induced climate change. Maize, soybean and wheat cropping systems in the midwestern USA were studied.

An integrated assessment approach to conduct analyses of climate change impacts on whole-farm systems

Abstract This paper argues that an integrated assessment (IA) approach, combining simulation modelling with deliberative processes involving decision makers and other stakeholders, has the potential to generate credible and relevant assessments of climate change impacts on farming systems. The justification for the approach proposed is that while simulation modelling provides an effective way of exploring the range of possible impacts of climate change and a means of testing the consequences of possible management or policy interventions, the interpretation of the outputs is highly dependent on the point of view of the stakeholder. Inevitably, whatever the responses to climate change, there will be trade-offs between the benefits and costs to a range of stakeholders. The use of a deliberative process that includes stakeholders, both in defining the topics addressed and in debating the interpretations of the outcomes, addresses many of the limitations that have been previously identified in the use of computer-based tools for agricultural decision support. The paper further argues that the concepts of resilience and adaptive capacity are useful for the assessment of climate change impacts as they provide an underpinning theory for processes of change in land use systems. The integrated modelling framework (IMF) developed for the simulation of whole-farm systems is detailed, including components for crop and soil processes, livestock systems and a tool for scheduling of resource use within management plans. The use of the IMF for assessing climate change impacts is then outlined to demonstrate the range of analyses possible. The paper concludes with a critique of the IA approach and notes that issues of quantification and communication of uncertainty are central to the success of the methodology.

Dynamics of nitrate leaching under irrigated potato rotation in Washington State: a long-term simulation study

Abstract In Washington State, nitrate is the most prevalent and frequently documented groundwater contaminant. The process appears driven by irrigation development associated with excessive use of fertilizers. A significant concentration of the problem is located in the Quincy–Pasco area. A computer simulation study was conducted with the objective of estimating the amount and dynamics of nitrate leaching from a typical irrigated crop rotation in this area. A 30-year record of daily weather from Richland, WA (near Pasco), a representative sandy soil (Quincy series, mesic Xeric Torripsamments), and a center pivot-irrigated crop rotation including potato (Solanum tuberosum L.), winter wheat (Triticum aestivum L.) and maize (Zea mays L.) were considered. CropSyst, a cropping systems model, was used to simulate the interactions between soils, crops, weather, and irrigation and fertilization management scenarios. When scenarios with fertilization rates above current recommended rates were simulated, potato had the largest nitrate leaching amounts during the growing season. When fertilization approached recommended rates, the simulated nitrate leaching during the potato growing seasons was low and not different from that of maize growing seasons. Excess irrigation did not affect significantly the bulk of simulated nitrate leaching, although it enhanced leaching during crop periods. Nitrate leaching was found to be more significant during no-crop periods (fall and winter), particularly following potato. Precipitation variability resulted in cycles of nitrate accumulation in the soil followed by leaching, at times producing some large events. Overall, the simulation study showed that reducing fertilization rates was the only effective approach to reducing nitrate leaching.

Simulation of durum wheat (Triticum turgidum ssp. durum) growth under different water and nitrogen regimes in a mediterranean environment using CropSyst

Abstract CropSyst, a cropping system simulation model, was evaluated for its ability to simulate growth, yield, and water and nitrogen use of two wheat cultivars (Cham 1 and Hourani). These cultivars were grown under different water (rainfed, 60% and 100% of crop water requirements) and nitrogen (without and with 100 kg N/ha) regimes in a Mediterranean type of environment at the Tel Hadya Research Station of ICARDA. Data from three contrasting growing seasons (1989/90 to 1991/1992) were used in these simulations. Soil characteristics, initial conditions of available moisture, N and organic matter, and daily weather data were input to CropSyst. Crop input parameters were mostly selected from the model documentation or determined from the experimental data. A few cultivar-specific parameters were adjusted within a narrow range of typical fluctuation by model calibration. Results showed that CropSyst was generally able to simulate evapotranspiration, crop N content, green leaf area, aboveground biomass, and grain yield as observed in the field experiments. Overall, the magnitude of the root mean square errors was about 10% of the observed means with two exceptions (25% and 32%). Index of agreement between predicted and observed values fluctuated from 0.90 to 0.98 (a value of 1.0 indicating excellent agreement), with most values equal or better than 0.95.