The DSSAT cropping system model☆

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Abstract

The decision support system for agrotechnology transfer (DSSAT) has been in use for the last 15 years by researchers worldwide. This package incorporates models of 16 different crops with software that facilitates the evaluation and application of the crop models for different purposes. Over the last few years, it has become increasingly difficult to maintain the DSSAT crop models, partly due to fact that there were different sets of computer code for different crops with little attention to software design at the level of crop models themselves. Thus, the DSSAT crop models have been re-designed and programmed to facilitate more efficient incorporation of new scientific advances, applications, documentation and maintenance. The basis for the new DSSAT cropping system model (CSM) design is a modular structure in which components separate along scientific discipline lines and are structured to allow easy replacement or addition of modules. It has one Soil module, a Crop Template module which can simulate different crops by defining species input files, an interface to add individual crop models if they have the same design and interface, a Weather module, and a module for dealing with competition for light and water among the soil, plants, and atmosphere. It is also designed for incorporation into various application packages, ranging from those that help researchers adapt and test the CSM to those that operate the DSSAT–CSM to simulate production over time and space for different purposes. In this paper, we describe this new DSSAT–CSM design as well as approaches used to model the primary scientific components (soil, crop, weather, and management). In addition, the paper describes data requirements and methods used for model evaluation. We provide an overview of the hundreds of published studies in which the DSSAT crop models have been used for various applications. The benefits of the new, re-designed DSSAT–CSM will provide considerable opportunities to its developers and others in the scientific community for greater cooperation in interdisciplinary research and in the application of knowledge to solve problems at field, farm, and higher levels.

Introduction

Information needs for agricultural decision making at all levels are increasing rapidly due to increased demands for agricultural products and increased pressures on land, water, and other natural resources. The generation of new data through traditional agronomic research methods and its publication are not sufficient to meet these increasing needs. Traditional agronomic experiments are conducted at particular points in time and space, making results site- and season-specific, time consuming and expensive. Unless new data and research findings are put into formats that are relevant and easily accessible, they may not be used effectively. The decision support system for agrotechnology transfer (DSSAT) was originally developed by an international network of scientists, cooperating in the International Benchmark Sites Network for Agrotechnology Transfer project (IBSNAT, 1993, Tsuji, 1998, Uehara, 1998, Jones et al., 1998), to facilitate the application of crop models in a systems approach to agronomic research. Its initial development was motivated by a need to integrate knowledge about soil, climate, crops, and management for making better decisions about transferring production technology from one location to others where soils and climate differed (IBSNAT, 1993, Uehara and Tsuji, 1998). The systems approach provided a framework in which research is conducted to understand how the system and its components function. This understanding is then integrated into models that allow one to predict the behavior of the system for given conditions. After one is confident that the models simulate the real world adequately, computer experiments can be performed hundreds or even thousands of times for given environments to determine how to best manage or control the system. DSSAT was developed to operationalize this approach and make it available for global applications. The DSSAT helps decision-makers by reducing the time and human resources required for analyzing complex alternative decisions (Tsuji et al., 1998). It also provides a framework for scientific cooperation through research to integrate new knowledge and apply it to research questions.
Prior to the development of the DSSAT, crop models were available, but these were used mostly in labs where they were created. For example, the original crop models implemented in DSSAT, the CERES models for maize (Jones and Kiniry, 1986) and wheat (Ritchie and Otter, 1985) and the SOYGRO soybean (Wilkerson et al., 1983) and PNUTGRO peanut (Boote et al., 1986) models, were already enjoying early successes. Those models required different file and data structures and had different modes of operation. Because the IBSNAT project aimed to provide a framework for cropping system analysis, these crop models had to be revised to make them compatible regarding data inputs and application modes. The decision to make these models compatible led to the design of the DSSAT and the ultimate development of compatible models for additional crops, such as potato, rice, dry beans, sunflower, and sugarcane (Hoogenboom et al., 1994a, Jones et al., 1998, Hoogenboom et al., 1999). In DSSAT v3.5, the latest release at the time this paper was written, there are models for 16 different crops and a bare fallow simulation.
The DSSAT is a collection of independent programs that operate together; crop simulation models are at its center (Fig. 1). Databases describe weather, soil, experiment conditions and measurements, and genotype information for applying the models to different situations. Software helps users prepare these databases and compare simulated results with observations to give them confidence in the models or to determine if modifications are needed to improve accuracy (Uehara, 1989, Jones et al., 1998). In addition, programs contained in DSSAT allow users to simulate options for crop management over a number of years to assess the risks associated with each option. DSSAT was first released (v2.1) in 1989; additional releases were made in 1994 (v3.0) (Tsuji et al., 1994) and 1998 (v3.5) (Hoogenboom et al., 1999).
The DSSAT is currently undergoing major revisions, not in its aim but in its design. One major reason for this re-design is that each individual crop model in DSSAT v3.5 had its own soil model components. Although simulation of crop rotations was possible in that version, the approach that was used was fraught with many problems regarding programming, compatibility of soil models, and potential bugs in different sets of code. At the heart of the DSSAT revisions is a new cropping system model (DSSAT–CSM), which incorporates all crops as modules using a single soil model. This was accomplished by completely redesigning the crop models, starting with CROPGRO, using a modular structure (Jones et al., 2001). This design was motivated to a large extent by the modular features of APSIM (McCown et al., 1996), but it uses the approach developed by van Kraalingen, 1990, Kraalingen, 1991, Kraalingen, 1995, Kraalingen et al., 2003 in the FSE/FST software for programming the behavior of each module. The new CSM now contains models of 16 crops derived from the old DSSAT CROPGRO and CERES models (maize, wheat, soybean, peanut, rice, potato, tomato, drybean, sorghum, millet, pasture, chickpea, cowpea, velvetbean, brachiaria grass, and faba bean).
The aims of the DSSAT–CSM are (1) to simulate monocrop production systems considering weather, genetics, soil water, soil carbon and nitrogen, and management in single or multiple seasons and in crop rotations at any location where minimum inputs are provided, (2) to provide a platform for easily incorporating modules for other abiotic and biotic factors, such as soil phosphorus and plant diseases, (3) to provide a platform that allows one to easily compare alternative modules for specific components to facilitate model improvement, evolution, and documentation, and (4) to provide a capability for easily introducing the CSM into additional application programs in a modular, well documented way. The purpose of this paper is to describe the DSSAT–CSM, its design, data requirements, evaluation and applications.

Section snippets

Overall description of the DSSAT cropping system model

The DSSAT–CSM simulates growth, development and yield of a crop growing on a uniform area of land under prescribed or simulated management as well as the changes in soil water, carbon, and nitrogen that take place under the cropping system over time. The DSSAT–CSM is structured using the modular approach described by Jones et al. (2001) and Porter et al. (2000). The most important features of our approach are:
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    It separates modules along disciplinary lines,
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    It defines clear and simple interfaces

Component descriptions

The main program reads information from the DSSAT standard file that describes a particular experiment or situation to be simulated (Hunt et al., 2001) and sets a number of variables for controlling a simulation run. It initiates the simulation by setting the DYNAMIC variable for initializing the run and calls the Land Unit module. It then starts a crop season time loop and calls the Land Unit module for initializing variables that must be set at the start of each season. After initialization

Data requirements

The DSSAT models require the minimum data set for model operation. The contents of such a dataset have been defined based on efforts by workers in IBSNAT and ICASA (Jones et al., 1994, Hunt and Boote, 1998, Hunt et al., 2001), and are shown in Table 7. They encompass data on the site where the model is to be operated, on the daily weather during the growing cycle, on the characteristics of the soil at the start of the growing cycle or crop sequence, and on the management of the crop (e.g.

Software implementation, distribution policy

The DSSAT–CSM is a new implementation of the individual crop models contained in DSSAT v3.5. Its first release was in June 2002 where it was used in a course on application of CSMs at the University of Florida. Thus, although this version of the DSSAT models has not achieved widespread distribution yet, it is the latest release of the widely used DSSAT suite of crop models in a much more integrated format that was designed in part for better capabilities for simulating cropping systems. At the

Model evaluation and testing

Evaluation involves comparison of model outputs with real data and a determination of suitability for an intended purpose. It is useful to think of model evaluation as a documentation of its accuracy for specific predictions in specified environments, with appropriate consideration given to possible errors in input variables or evaluation data. Essential parts of any minimum data set for evaluation are: (1) a complete record of the information required to run the model (Table 7a), and (2) field

Example applications

The DSSAT crop models have been widely used over the last 15 years by many researchers for many different applications. Many of these applications have been done to study management options at study sites, including fertilizer, irrigation, pest management, and site-specific farming. These applications have been conducted by agricultural researchers from different disciplines, frequently working in teams to integrate cropping systems analysis using models with field agronomic research and

Closing the loop between development and application

As shown in the previous section, researchers have been applying DSSAT crop models for many purposes. However, as more experience has been gained by the scientific community in using these models, the demands have increased beyond those that motivated many of these studies. In many past studies, researchers accepted the crop and soil models in DSSAT as they were, but many studies showed that improvements were needed in various parts of the models. In some cases, researchers modified the code to
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Contribution from Florida Agricultural Experiment Station, University of Florida. Journal Series No. R-08916.
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