Rice in cropping systems - Modelling transitions between flooded and non-flooded soil environments
Gaydon, DS and Probert, ME and Buresh, RJ and Meinke, H and Suriadi, A and Dobermann, A and Bouman, A and Timsina, J, Rice in cropping systems - Modelling transitions between flooded and non-flooded soil environments, European Journal of Agronomy, 39 pp. 9-24. ISSN 1161-0301 (2012) [Refereed Article]
Water shortages in many rice-growing regions, combined with growing global imperatives to increase food production, are driving research into increased water use efficiency and modified agricultural practices in rice-based cropping systems. Well-tested cropping systems models that capture interactions between soil water and nutrient dynamics, crop growth, climate and management can assist in the evaluation of new agricultural practices. The APSIM model was designed to simulate diverse crop sequences, residue/tillage practices and specification of field management options. It was previously unable to simulate processes associated with the long-term flooded or saturated soil conditions encountered in rice-based systems, due to its heritage in dryland cropping applications. To address this shortcoming, the rice crop components of the ORYZA2000 rice model were incorporated and modifications were made to the APSIM soil water and nutrient modules to include descriptions of soil carbon and nitrogen dynamics under anaerobic conditions. We established a process for simulating the two-way transition between anaerobic and aerobic soil conditions occurring in crop sequences of flooded rice and other nonflooded crops, pastures and fallows. These transitions are dynamically simulated and driven by modelled hydraulic variables (soil water and floodwater depth). Descriptions of floodwater biological and chemical processes were also added. Our assumptions included a simplified approach to modelling O2 transport processes in saturated soils. The improved APSIM model was tested against diverse, replicated experimental datasets for rice-based cropping systems, representing a spectrum of geographical locations (Australia, Indonesia and Philippines), soil types, management practices, crop species, varieties and sequences. The model performed equally well in simulating rice grain yield during multi-season crop sequences as the original validation testing reported for the stand-alone ORYZA2000 model simulating single crops (n = 121, R2 = 0.81 with low bias (slope, α = 1.02, intercept, β = −323 kg ha−1), RMSE = 1061 kg ha−1 (cf. SD of measured data = 2160 kg ha−1)). This suggests robustness in APSIM’s simulation of the rice-growing environment and provides evidence on the usefulness of our modifications and practicality of our assumptions. Aspects of particular strength were identified (crop rotations; response to applied fertilizers; the performance of bare fallows), together with areas for further development work (simulation of retained crop stubble during fallows, greenhouse gas emissions). APSIM is now suitable to investigate production responses of potential agronomic and management changes in rice-based cropping systems, particularly in response to future imperatives linked to resource availability, climate change, and food security. Further testing is required to evaluate the impact of our simplified assumptions on the model’s simulation of greenhouse gas emissions in rice-based cropping systems.