CANDY

Authors

Uwe Franko, Burkhard Oelschlaegel, Stefan Schenk, Martina Puhlmann, Katrin Kuka, Janine Mallast née Krueger, Enrico Thiel, Nadia Prays, Katharina Meurer, Eric Boenecke, Lukas Hey, Stefan Gasser

Website

website: https://www.somod.info

Contact

Description

CANDY (Carbon And Nitrogen DYnamics) is a process-based agro-ecosystem model designed to simulate carbon (C) and nitrogen (N) dynamics in the unsaturated (vadose) zone of agriculturally used mineral soils. Operating on a daily time step, CANDY is suitable for sites with rooting depths up to 2 meters, where the soil profile is discretized into homogeneous layers of 1 dm thickness. CANDY simulates the interaction of climate, soil physical processes, biogeochemical turnover, crop growth, and agricultural management at a daily time step, requiring corresponding input data. Unlike many other models, CANDY stores all input data, parameters, and simulation results in a PostgreSQL database, ensuring organized and efficient data management. CANDY provides an extensive graphical user interface (GUI) designed with user accessibility in mind. This GUI simplifies key tasks such as database management, scenario and agricultural management preparation, simulation control and result visualization, and also includes tools for parameter optimization and uncertainty analysis, making it an ideal tool for both newbies and experienced users. CANDY also functions as a console application supporting automated batch execution through command-line calls or shell scripts. A dedicated automation table within the database allows for efficient execution of multiple simulation runs, including dynamic scenario generation, sensitivity analysis, and pre- and post-processing via SQL scripts.

Key Features

1.Integrated Database Management: CANDY stores all input data, parameters, and simulation results in a PostgreSQL database, enhancing data management and retrieval efficiency. 2. User-Friendly Interface: The model features an extensive graphical user interface (GUI) that simplifies database management, scenario preparation, simulation control, and result visualization, making it accessible to a broader range of users. 3. Automation Capabilities: CANDY supports batch mode simulations via command-line calls or shell scripts. An automation table within the database facilitates dynamic scenario generation, sensitivity analysis, and SQL-based pre- and post-processing. Additional to the GUI, CANDY is also available as a console application.

Special Features

1. Biological Active Time (BAT): CANDY calculates BAT to assess organic matter turnover conditions, crucial for understanding soil activity and nutrient cycling. 2. Intercropping Simulation: CANDY allows for intercropping simulations, enhancing the realism of crop growth models and soil health assessments. 3. Automatic Management Options: The model offers automatic features for fertilizer application, irrigation, harvest and grassland cutting, simulating standard agricultural practices without manual input. 4. Parameter Optimization and Uncertainty Analysis: Integrated tools within the GUI enable users to refine model parameters and assess simulation uncertainties. 5. Weather Generator: This feature enables long-term scenario simulations, valuable for studying climate change impacts and agricultural practices on soil dynamics.

Outputs

The model results consist of soil and crop related state variables and fluxes connected to soil organic matter, nitrogen, and water in daily time steps. Outputs are stored in a linked PostgreSQL Database.

Technical information

Operating Systems: MacOS, Windows, Linux Licence: freely available

Scientific articles

Turek, Maria Eliza, Johannes Wilhelmus Maria Pullens, Katharina Hildegard Elisabeth Meurer, Edberto Moura Lima, Bano Mehdi-Schulz, Annelie Holzkämper. 2025. “Pedotransfer Function Versus Model Structure: What Drives Variance in Agro-Hydrological Model Results?” European Journal of Soil Science 76, e70088, https://doi.org/10.1111/ejss.70088

Filipiak, Matthias, Doreen Gabriel, and Katrin Kuka. 2023. ‘Simulation-Based Assessment of the Soil Organic Carbon Sequestration in Grasslands in Relation to Management and Climate Change Scenarios’. Heliyon 9 (6): e17287. https://doi.org/10.1016/j.heliyon.2023.e17287.

Hey, Lukas, Katharina H. E. Meurer, and Hermann F. Jungkunst. 2025. ‘On the Potential of Biogeochemical Models to Predict Hot Moments of N2O Following Dry-Wet Cycles’. Atmospheric Environment: X 27 (August): 100347. https://doi.org/10.1016/j.aeaoa.2025.100347.

Kuka, Katrin, Martin Schädler, Thomas Reitz, and Uwe Franko. 2025. ‘Evaluating Grassland Ecosystem Responses to Management Practices and Climate Change: Results from the Global Change Experimental Facility in Bad Lauchstädt (Germany)’. Plant and Soil, ahead of print, August 5. https://doi.org/10.1007/s11104-025-07729-4.

Meurer, Katharina H. E., Eric Boenecke, and Uwe Franko. 2019. ‘Evaluating Emissions of Nitrous Oxide from Cropland Soils Under Different Rotations in Mato Grosso, Brazil: A Scenario Simulation Study’. Pedosphere 29 (4): 432–43. https://doi.org/10.1016/S1002-0160(19)60812-X.

Meurer, Katharina H. E., Uwe Franko, Oliver Spott, C. Florian Stange, and Hermann F. Jungkunst. 2016. ‘Model Testing for Nitrous Oxide (N2O) Fluxes from Amazonian Cattle Pastures’. Atmospheric Environment 143 (October): 67–78. https://doi.org/10.1016/j.atmosenv.2016.08.047.

Meurer, Katharina H. E., Uwe Franko, Claus F. Stange, Jaqueline Dalla Rosa, Beata E. Madari, and Hermann F. Jungkunst. 2016. ‘Direct Nitrous Oxide (N2O) Fluxes from Soils under Different Land Use in Brazil—a Critical Review’. Environmental Research Letters 11 (2): 023001. https://doi.org/10.1088/1748-9326/11/2/023001.

Carauta, M. & Guzman-Bustamante, I. & Meurer, K. & Hampf, A. & Troost, C. & Rodrigues, R. & Berger, T., 2018. "Assessing the full distribution of greenhouse gas emissions from crop, livestock and commercial forestry plantations in Brazil's Southern Amazon," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277118, International Association of Agricultural Economists. DOI: 10.22004/ag.econ.277118

Franko, U., Oelschlägel. B., Schenk, S. (1995): Simulation of Temperature-, Water- and Nitrogen dynamics using the Model CANDY. Ecol. Model., 81, S. 213-222

Franko,U., Crocker, G.J., Grace, P.R., Klir, J., Körschens, M., Poulton, P.R., Richter, D.D. (1997): Simulating trends in soil organic carbon in long-term experiments using the CANDY model. Geoderma, 81, 109-120

Franko, U., Schenk, S. (2001): Modelling of Carbon Dynamics in a Rural Area of Central Germany. In: Rees, R.M., Ball, B.C., Campbell, C.D., Watson, C.A. (eds): Sustainable Management of Soil Organic Matter

Franko, U., Mirschel, W. (2001): Integration of a Crop Growth Model with a Model of Soil Dynamics. Agronomy Journal, 93, S. 60-66 Franko,U. and Puhlmann,M., (2002). Potential for optimisation of Carbon and Nitrogen dynamics on Black Earth in Central Germany - and N-turnover. Arch. Acker-Pfl.. Boden., 48: 1-6.

Franko, U., Kuka, K., Romanenko, I. A., Romanenkov, V. A. (2007): Validation of the CANDY model with Russian long-term experiments. Regional Environmental Change 7 (2), 79-91

Hesser, F.B., Franko, U. and M. Rode (2010): Spatially distributed lateral nitrate transport at the catchment scale. J. Environ. Qual. 39, 193-210

Krüger, J., Franko, U., Fank, J., Stelzl, E., Dietrich, P., Pohle, M., Werban, U., (2013): Linking geophysics and soil function modeling — an application study for biomass production Vadose Zone J. 12 (4), 10.2136/vzj2013.01.0015

Kuka, K., Franko, U., Rühlmann, J. (2007): Modelling the impact of pore space distribution on carbon turnover. Ecol.Modell. 208 (2-4), 295-306

Puhlmann, M., Kuka, K., Franko, U. (2006): Comparison of methods for the estimation of inert carbon suitable for initialisation of the CANDY model Nutr.Cycl.Agroecosys. 74 (3), 295-304

Richter, G.M., Schmidt, T., and Franko,U. (2004): Using long-term experiments to evaluate models for assessing climatic impacts on future crop production. Archives of Agronomy and Soil Science 50 (6), 553-562

Rode, M., Thiel, E., Franko, U. Wenk, G., Hesser, F. (2009). Impact of selected agricultural management options on the reduction of nitrogen loads in three representative meso scale catchments in Central Germany. Science of the Total Environment,407, 3459-3472

Ludwig, B., Kuka, K., Franko, U., von Lützow, M. (2008): Comparison of two quantitative soil organic carbon models with a conceptual model using data from an agricultural long term experiments. J. Plant Nutr. Soil Sci. 171, 83-90

Smith, P., Smith, J.U., Powlson, D.S., McGill, W.B., Arah, J.R.M., Chertov, O.G., Coleman, K., Franko, U. et al. (1997): A comparison of the performance of nine soil organic matter models using datasets from seven long-term experiments. Geoderma, 81, S. 153-225

Smith, P., Smith, J. U., Franko, U., Kuka, K., Romanenkov, V. A., Shevtsova, L. K., Wattenbach, M., Gottschalk, P., Sirotenko, O. D., Rukhovich, D. I., Koroleva, P. V., Romanenko, I. A., Lisovoi, N. V. (2007): Changes in mineral soil organic carbon stocks in the croplands of European Russia and the Ukraine, 1990-2070; comparison of three models and implications for climate mitigation Regional Environmental Change 7 (2), 105-119

Schmidt, T.; Franko, U., Meissner, R. (2008): Uncertainties in large-scale analysis of agricultural land use-A case study for simulation of nitrate leaching Ecological Modelling 217, 174-180