PROMET is a hydrological land surface process model, which has been extended by a biophysical dynamic vegetation component to model crop growth and yield formation. It uses first order physical and physiological principles to determine net primary production and respiration based on approaches from Farquhar et al. (1980) and Ball et al. (1987), combined with a phenology and a two-layer canopy architecture component of Yin et al (2005). PROMET takes into account the dependency of net primary production and phenology on environmental conditions including meteorology, CO2 concentration for C3 and C4 pathways as well as water and temperature stress. The mass and energy balance of the canopy and underlying soil surface are iteratively closed for each simulation time step. The canopy and phenology component allocates assimilates into the different plant organs of the canopy depending on the phenological stage of development. Assimilates that are accumulated within the fruit fraction during the growing period determine the dry biomass available for yield formation. The simulation is performed on an hourly time step to account for non-linear reactions of crop growth to environmental conditions (mainly light, water, temperature and wind). Conversion of daily climate model data to hourly values is done by the TeddyTool v1.1 (Zabel and Poschlod 2023). Depending on the reaction of the considered crop to meteorological and soil-specific conditions, the crop may either die due to water, heat or cold stress before being harvested or it may not reach maturity. In both cases, this results in total yield loss.
Zabel, F., Poschlod, B. (2023): The Teddy-Tool v1.1: temporal disaggregation of daily climate model data for climate impact analysis. Geoscientific Model Development. doi: 10.5194/gmd-16-5383-2023.
Jaegermeyr, J., Müller, C., Ruane, A., Elliott, J., Balkovic, J., Castillo, O., Faye, B., Foster, I., Folberth, Ch., Franke, J., Fuchs, K., Guarin, J., Heinke, J., Hoogenboom, G., Iizumi, T., Jain, A., Kelly, D., Khabarov, N., Lange, S., Lin, T-S., Liu, W., Mialyk, O., Minoli, S., Moyer, E., Okada, M., Phillips, M., Porter, C., Rabin, S., Scheer, C., Schneider, J.M., Schyns, J., Skalský, R., Smerald, A., Stella, T., Stephens, H., Webber, H., Zabel, F., Rosenzweig, C. (2021): Climate change signal in agriculture emerges earlier in new generation of projections. Nature Food. doi: 10.1038/s43016-021-00400-y.
Zabel, F., Mueller, C., Elliott, J., Minoli, S., Jägermeyr, J., Schneider, M. J., Franke, J. A., Moyer, E., Dury, M., Francois, L., Folberth, C. Wenfeng, L., Ogh, T. A. M., Olin, S., Rabin, S. S., Mauser, W., Hank, T., Ruane, A. C., Asseng, S. (2021): Large potential for crop production adaptation depends on available future varieties. Global Change Biology. doi: 10.1111/gcb.15649.
Jägermeyr, J., Robock, A., Elliott, J., Müller, C., Xia, L., Khabarov, N., Folberth, C., Schmid, E., Liu, W., Zabel, F., Rabin, S.S., Puma, M.J., Heslin, A., Franke, J., Foster, I., Asseng, S., Bardeen, C.G., Toon, O.B., Rosenzweig, C. (2020). A regional nuclear conflict would compromise global food security. PNAS, 201919049. doi: 10.1073/pnas.1919049117.
Zabel, F., Delzeit, R., Schneider, J. M., Seppelt, R., Mauser, M., Václacík, T. (2019): Global impacts of future cropland expansion and intensification on agricultural markets and biodiversity. Nature Communications, 10:2844, 11. doi: 10.1038/s41467-019-10775-z.
Mauser, W., Klepper, G., Zabel, F., Delzeit, R., Hank, T. Putzenlechner, B., Cazadilla, A. (2015): Global biomass production potentials exceed expected future demand without the need for cropland expansion. Nature Communications, 6:8946, 11. doi: 10.1038/ncomms9946.
Hank, T.B., H. Bach, and W. Mauser, Using a Remote Sensing-Supported Hydro-Agroecological Model for Field-Scale Simulation of Heterogeneous Crop Growth and Yield: Application for Wheat in Central Europe. Remote Sensing, 2015. 7(4). 3934-3965. doi: 10.3390/rs70403934.
Mauser, W., et al., PROMET - Processes of Mass and Energy Transfer - An Integrated Land Surface Processes and Human Impacts Simulator for the Quantitative Exploration of Human-Environment Relations. Part 1: Algorithms Theoretical Baseline Document. http://www.geographie.uni-muenchen.de/department/fiona/forschung/projekte/promet_handbook/index.html. 2015, Department of Geography: Munich.
