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1 Constantin, J.; Raynal, H.; Casellas, E.; Hoffmann, H.; Bindi, M.; Doro, L.; Eckersten, H.; Gaiser, T.; Grosz, B.; Haas, E.; Kersebaum, K.-C.; Klatt, S.; Kuhnert, M.; Lewan, E.; Maharjan, G. R.; Moriondo, M.; Nendel, C.; Roggero, P. P.; Specka, X.; Trombi, G.; Villa, A.; Wang, E.; Weihermuller, L.; Yeluripati, J.; Zhao, Z.; Ewert, F.; Bergez, J.-E. 2019. Management and spatial resolution effects on yield and water balance at regional scale in crop models. Agricultural and Forest Meteorology, 275:184-195. [doi: https://doi.org/10.1016/j.agrformet.2019.05.013]
(Location: IWMI HQ Call no: e-copy only Record No: H049327)
(2.99 MB)
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.
(Location: IWMI HQ Call no: e-copy only Record No: H049628)
(0.66 MB)
The traditional agriculture production system in sub-Saharan Africa (SSA) caused significant soil erosion and degradation of soil quality. In addition, dependability of rainfall for irrigation needs limits the crop production. Advanced agricultural practices are thus needed at the local level to sustain the livelihood of smallholder farmers in the region. In this study, conservation agriculture (CA) practice with drip irrigation technology was compared (using field experiments and watershed modeling) with the traditional conventional tillage (CT) practice for its potential in improving soil quality and crop productivity in the region. Biophysical data were collected (2015 to 2017) from a total of 43 paired plots (CA and CT) at four study sites in SSA: Dangishita and Robit in Ethiopia, Yemu in Ghana, and Mkindo in Tanzania. The Agricultural Policy/Environmental eXtender (APEX) model was calibrated and validated with reasonable efficiency in simulating crop yields for both CA and CT practices; average PBIAS =±12% and =±11%, for CA and CT. The impact of the CA system on soil quality (soil carbon [C] and nitrogen [N]) was analyzed based on the well-tested model prediction results. The total C and N were increased under CA across the study sites on average by 6% and 4.1%, when compared to CT over the study period. Both the experiment and model prediction showed that crop yield was significantly improved by CA—on average 37.4% increases across the sites when compared to CT. Conservation agriculture with drip irrigation was an efficient local strategy to improve crop production in the region while enhancing the ecosystem.
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