The Cycles agroecosystem model: Fundamentals, testing, and applications

• This paper introduces and applies the Cycles Agroecosystem Model. • Tests show excellent simulation of ET, plant growth, and soil moisture. • Among its innovations is modeling soil carbon and nitrogen saturation explicitly. • An autonomous crop sequence builder illustrates its power in data-model workflows. Models of the soil–plant-atmosphere continuum are repositories of knowledge and gears in analytical and decision support tools applied to agroecosystems. In this paper, we present the Cycles agroecosystem model theory along with test cases and applications. Cycles combines innovations for simulating soil hydrology and biogeochemistry, including carbon and nitrogen saturation theory, with a modular software architecture. These elements enable simulating monoculture or polyculture crop sequences and associated management practices, containerizing for applications that require high-performance computing, and data assimilation at runtime. A comparison of simulated and measured daily evapotranspiration (ET) obtained with the eddy covariance method for maize ( Zea mays L.) and shrub willow ( Salix spp.) shows that Cycles represents well meteorological and vegetation controls of ET (root mean square error or RMSE = 0.75 mm d -1 ). Cycles accurately simulated differences of 150 mm in growing season ET between these two plant communities. Comparisons of modeled versus measured soil water content under soybean ( Glycine max [L.] Merr.) in southeastern Pennsylvania for six soil layers at 0.1-m increments show accurate representation of water depletion and recharge (RMSE of 0.027–0.011 m 3 m −3 ). Simulations of growth and nitrogen uptake of wheat ( Triticum aestivum L.) in eastern Washington also highlight the model’s skill simulating processes that affect water and nutrient fluxes simultaneously. To highlight Cycles’ suitability for incorporation in high performance computing applications, we present a coupling of Cycles with an autonomous crop sequence builder (Cycles-A) in the Chesapeake Bay watershed. This system automatically identified areas for double cropping and selected the optimum combination of annual crops across the watershed. The Cycles model innovations and agroecosystem framing continue advancing the premise of making models not only dynamic knowledge repositories but useful tools for research and landscape management.