334-2 Quantifying and Modeling Crop Growth Heterogeneity At the Field Scale.

See more from this Division: ASA Section: Climatology & Modeling
See more from this Session: General Model Applications In Field Research: II

Wednesday, November 6, 2013: 8:20 AM
Tampa Convention Center, Room 37 and 38

Anja Stadler1, Sebastian Rudolph2, Moritz Kupisch1, Matthias Langensiepen1, Jan van der Kruk2 and Frank Ewert3, (1)Institute of Crop Science and Resource Conservation (INRES), University of Bonn, Bonn, Germany
(2)Institute of Bio- and Geosciences, IBG-3, Forschungszentrum Juelich, Juelich, Germany
(3)University of Bonn, Bonn, GERMANY
Pedosphere, biosphere and atmosphere form a complex system with strong interactions. Small scale variability in one sphere will find its counterpart in another. In an agricultural context, soil textural heterogeneity within a field will result in spatially variable crop growth and yield responses. Although often reported this relationship has rarely been quantified under field conditions. To study the interactions of the soil-crop response system we carried out geophysical and plant physiological measurements at three agricultural fields with high texture variability for winter wheat and sugar beet in the Western part of Germany. We also tested whether observed spatial patterns in crop growth and yield can be reproduced by a crop model (GECROS).

We used electromagnetic induction measurements (EMI) indicating the apparent soil electrical conductivity (ECa) to reveal spatial differences in soil texture. According to the respective patterns of ECa repeated crop measurements of leaf area index, crop dry matter and yield were taken. Using linear regression we found moderate to high correlations between crop measurements and ECa (R2 0.39 – 0.89). We conclude that these statistical relationships are controlled by variabilities in clay content and hence are a function of soil water holding capacity and nutrient distribution.

For evaluating the crop growth model GECROS we used the soil-related information as input. Since this model comprises a detailed, dynamic photosynthesis part we evaluated it for individual processes, for instance the daily CO2 and H20 fluxes as well as the organ-specific biomass growth and LAI. When initially applied the model was not able to reproduce the spatial differences in measured crop data. Replacing its soil routines with a more advanced soil model (SLIM) improved the simulation results noticeably. The simulation results of winter wheat were closer to the measured than those of sugar beet which is likely due to a larger growth variability of sugar beet. The validated soil-crop model is used to identify those crop physiological processes that are particularly influenced by soil textural heterogeneity.

See more from this Division: ASA Section: Climatology & Modeling
See more from this Session: General Model Applications In Field Research: II