TY  - JOUR
AU  - Constantin, Julie
AU  - Raynal, Helene
AU  - Casellas, Eric
AU  - Hoffmann, Holger
AU  - Bindi, Marco
AU  - Doro, Luca
AU  - Eckersten, Henrik
AU  - Gaiser, Thomas
AU  - Grosz, Balász
AU  - Haas, Edwin
AU  - Kersebaum, Kurt-Christian
AU  - Klatt, Steffen
AU  - Kuhnert, Matthias
AU  - Lewan, Elisabet
AU  - Maharjan, Ganga Ram
AU  - Moriondo, Marco
AU  - Nendel, Claas
AU  - Roggero, Pier Paolo
AU  - Specka, Xenia
AU  - Trombi, Giacomo
AU  - Villa, Ana
AU  - Wang, Enli
AU  - Weihermüller, Lutz
AU  - Yeluripati, Jagadeesh
AU  - Zhao, Zhigan
AU  - Ewert, Frank
AU  - Bergez, Jacques-Eric
TI  - Management and spatial resolution effects on yield and water balance at regional scale in crop models
JO  - Agricultural and forest meteorology
VL  - 275
SN  - 0168-1923
CY  - Amsterdam [u.a.]
PB  - Elsevier
M1  - FZJ-2019-04528
SP  - 184 - 195
PY  - 2019
AB  - Due to the more frequent use of crop models at regional and national scale, the effects of spatial data input resolution have gained increased attention. However, little is known about the influence of variability in crop management on model outputs. A constant and uniform crop management is often considered over the simulated area and period. This study determines the influence of crop management adapted to climatic conditions and input data resolution on regional-scale outputs of crop models. For this purpose, winter wheat and maize were simulated over 30 years with spatially and temporally uniform management or adaptive management for North Rhine-Westphalia (˜34 083 km²), Germany. Adaptive management to local climatic conditions was used for 1) sowing date, 2) N fertilization dates, 3) N amounts, and 4) crop cycle length. Therefore, the models were applied with four different management sets for each crop. Input data for climate, soil and management were selected at five resolutions, from 1 × 1 km to 100 × 100 km grid size. Overall, 11 crop models were used to predict regional mean crop yield, actual evapotranspiration, and drainage. Adaptive management had little effect (<10% difference) on the 30-year mean of the three output variables for most models and did not depend on soil, climate, and management resolution. Nevertheless, the effect was substantial for certain models, up to 31% on yield, 27% on evapotranspiration, and 12% on drainage compared to the uniform management reference. In general, effects were stronger on yield than on evapotranspiration and drainage, which had little sensitivity to changes in management. Scaling effects were generally lower than management effects on yield and evapotranspiration as opposed to drainage. Despite this trend, sensitivity to management and scaling varied greatly among the models. At the annual scale, effects were stronger in certain years, particularly the management effect on yield. These results imply that depending on the model, the representation of management should be carefully chosen, particularly when simulating yields and for predictions on annual scale.
LB  - PUB:(DE-HGF)16
UR  - <Go to ISI:>//WOS:000480376400016
DO  - DOI:10.1016/j.agrformet.2019.05.013
UR  - https://juser.fz-juelich.de/record/864925
ER  -