Analysis and modeling of spatio-temporal variability of crop and cropping systems processes at multiple scales

The spatial variability of crop and cropping system processes is not well understood. Different to natural vegetation, crops are not only affected by environmental conditions (e.g. soil and weather) but also by agricultural management. The spatial variability of management differs from that of soil and weather. Accordingly, modeling needs to represent the spatio-temporal patterns of model inputs and parameters. The key focus of this project is on crop production systems in the river Rur basin which is the central regional study of the collaborative research project. As arable land covers about one third of the catchment, the project fills an important gap in the regional modeling of the soil-vegetation-atmosphere system.
We aim to develop a modeling framework to simulate the spatio-temporal variability of crop and cropping system processes at field and regional scales. The framework will consider different model components including scaling methods that enable the composition of model solutions depending on the modeling objective and the scale of application. We will provide well-tested approaches to scale up processes such as growth and development, water and CO2 fluxes from the homogenous plot to the field and regional level considering the spatial heterogeneity in soil conditions, management activities and climate. Remote sensing technologies will be used to obtain spatially consistent model parameters and data for the model testing.
The main goal of this project is to analyse and model the spatial variability in growth and development processes including water and CO2 fluxes in relation to the spatial variability in soil conditions at the field scale. More specifically the project aims to:
-    describe the spatial variability of soil conditions and affected growth and development processes including water and CO2 fluxes and identify the characteristic pattern for each process
-    analyse relationships between the spatial variability and characteristic patterns in soil conditions and crop and cropping system processes
-    identify/develop appropriate up-scaling methods to simulate crops and cropping system processes at field scale considering the spatial heterogeneity in soil conditions
-    develop a modular modeling framework that supports the flexible generation of model solutions for specific objectives, here with respect to output variables (e.g. biomass productivity, CO2 uptake, transpiration) and scale (homogenous plot, field)
The developed spatial crop and cropping system modeling approach at field scale will be the basis for further up-scaling of crop and cropping system processes to the sub-regional and regional scale considering the spatial variability in crop management and environmental conditions (soil and weather).

Reichenau, T.G., W. Korres, C. Montzka, P. Fiener, F. Wilken, A. Stadler, G. Waldhoff, K. Schneider, 2016. Spatial heterogeneity of Leaf Area Index (LAI) and its temporal course on arable land: combining field measurements, remote sensing and simulation in a Comprehensive Data Analysis Approach (CDAA). PLoS ONE 11, e0158451. DOI:10.1371/journal.pone.0158451.

Van Bussel, L.G.J., F. Ewert, G. Zhao, H. Hoffmann, A. Enders, D. Wallach, S. Asseng, G.A. Baigorria, B. Basso, C. Biernath, D. Cammarano, J. Chryssanthacopoulos, J. Constantin, J. Elliott, M. Glotter, F. Heinlein, K.-C. Kersebaum, C. Klein, C. Nendel, E. Priesack, H. Raynal, C.C. Romero, R.P. Rötter, X. Specka, F. Tao, 2016. Spatial sampling of weather data for regional crop yield simulations. Agricultural and Forest Meteorology 220, 101-115. DOI:10.1016/j.agrformet.2016.01.014.

Wieneke, S., H. Ahrends, A. Damm, F. Pinto, A. Stadler, M. Rossini, U. Rascher, 2016. Airborne based spectroscopy of red and far-red sun-induced chlorophyll fluorescence: Implications for improved estimates of gross primary productivity. Remote Sensing of Environment 184, 654-667. DOI:10.1016/j.rse.2016.07.025.

Ali, M., C. Montzka, A. Stadler, G. Menz, F. Thonfeld, H. Vereecken, 2015. Estimation and validation of RapidEye-based time-series of leaf area index for winter wheat in the Rur catchment (Germany). Remote Sensing 7, 2808-2831. DOI:10.3390/rs70302808.

Kupisch, M., A. Stadler, M. Langensiepen, F. Ewert, 2015. Analysis of spatio-temporal patterns of CO2 and H2O fluxes in relation to crop growth under field conditions. Field Crops Research 176, 108-118. DOI:10.1016/j.fcr.2015.02.011.

Simmer, C. I. Thiele-Eich, M. Masbou, W. Amelung, H. Bogena, S. Crewell, B. Diekkrüger, F. Ewert, H.J. Hendricks Franssen, J.A. Huisman, A. Kemna, N. Klitsch, s. Kollet, M. Langensiepen, U. Löhnert, A.S. M.M. Rahman, U. Rascher, K. Schneider, J. Schween, Y. Shao, P. Shrestha, M. Stiebler, M. Sulis, J. Vanderborght, H. Vereecken, J. van der Kruk, G. Waldhoff, T. Zerenner, 2015. Monitoring and modeling the terrestrial system from pores to catchments: The transregional collaborative research center on patterns in the soil-vegetation-atmosphere system. Bulletin of the American Meteorological Society 96, 1765-1787. DOI:10.1175/bams-d-13-00134.1

Stadler, A., S. Rudolph, M. Kupisch, M. Langensiepen, J.v.d. Kruk, F. Ewert, 2015. Quantifying the effects of soil variability on crop growth using apparent soil electrical conductivity measurements. European Journal of Agronomy 64, 8-20. DOI:10.1016/j.eja.2014.12.004.

Zhao, G., S. Siebert, A. Enders, E. Eyshi Rezaei, C. Yan, F. Ewert, 2015. Demand for multi-scale weather data for regional crop modeling. Agricultural and Forest Meteorology 200, 156-171, DOI:10.1016/j.agrformet.2014.09.026.

Ahrends, H.E., R. Haseneder-Lind, J. H. Schween, S. Crewell, A. Stadler, U. Rascher, 2014. Diurnal dynamics of wheat evapotranspiration derived from ground-based thermal imagery. Remote Sensing 6, 9775-9801. DOI:10.3390/rs6109775.

Langensiepen, M., M. Kupisch, A. Graf, M. Schmidt, F. Ewert, 2014. Improving the stem heat-balance method for measuring sap-flow in wheat. Agricultural and Forest Meteorology 186, 34-42. DOI:10.1016/j.agrformet.2013.11.007.

Graf, A., J. Werner, M. Langensiepen, A. van de Boer, M. Schmidt, M. Kupisch, H. Vereecken, 2013. Validation of a minimum microclimate disturbance chamber for net ecosystem flux measurements. Agricultural and forest Meteorology 174-175, 1-14. DOI:10.1016/j.agrformet.2013.02.001.

Langensiepen, M., M. Kupisch, M. T. van Wijk, F. Ewert, 2012. Analyzing transient closed chamber effects on canopy gas exchange for optimizing flux calculation timing. Agricultural and Forest Meteorology 164, 61-70. DOI:10.1016/j.agrformet.2012.05.006.