Your search found 2 records
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]
Crop management ; Crop yield ; Water balance ; Crop modelling ; Crop forecasting ; Strategies ; Evapotranspiration ; Drainage ; Wheat ; Maize / Germany / North Rhine-Westphalia
(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.
2 Tomasella, J.; Martins, M. A.; Shrestha, Nirman. 2023. An open-source tool for improving on-farm yield forecasting systems. Frontiers in Sustainable Food Systems, 7:1084728. [doi: https://doi.org/10.3389/fsufs.2023.1084728]
Yield forecasting ; Crop forecasting ; Soil fertility ; Irrigation management ; Yield gap ; Crop modelling ; Optimization ; On-farm research ; Wheat ; Maize ; Soil water content ; Water productivity ; Biomass ; Canopy ; Climate change ; Assessment ; Computer software / Tunisia / Nepal / Brazil / Tunis / Chitwan / Araripina
(Location: IWMI HQ Call no: e-copy only Record No: H052083)
https://www.frontiersin.org/articles/10.3389/fsufs.2023.1084728/pdf
https://vlibrary.iwmi.org/pdf/H052083.pdf
https://vlibrary.iwmi.org/pdf/H052083.pdf
(6.59 MB) (6.59 MB)
Introduction: The increased frequency of extreme climate events, many of them of rapid onset, observed in many world regions, demands the development of a crop forecasting system for hazard preparedness based on both intraseasonal and extended climate prediction. This paper presents a Fortran version of the Crop Productivity Model AquaCrop that assesses climate and soil fertility effects on yield gap, which is crucial in crop forecasting systems
Methods: Firstly, the Fortran version model - AQF outputs were compared to the latest version of AquaCrop v 6.1. The computational performance of both versions was then compared using a 100-year hypothetical experiment. Then, field experiments combining fertility and water stress on productivity were used to assess AQF model simulation. Finally, we demonstrated the applicability of this software in a crop operational forecast system.
Results: Results revealed that the Fortran version showed statistically similar results to the original version (r 2 > 0.93 and RMSEn < 11%, except in one experiment) and better computational efficiency. Field data indicated that AQF simulations are in close agreement with observation.
Conclusions: AQF offers a version of the AquaCrop developed for time-consuming applications, such as crop forecast systems and climate change simulations over large areas and explores mitigation and adaptation actions in the face of adverse effects of future climate change.
Methods: Firstly, the Fortran version model - AQF outputs were compared to the latest version of AquaCrop v 6.1. The computational performance of both versions was then compared using a 100-year hypothetical experiment. Then, field experiments combining fertility and water stress on productivity were used to assess AQF model simulation. Finally, we demonstrated the applicability of this software in a crop operational forecast system.
Results: Results revealed that the Fortran version showed statistically similar results to the original version (r 2 > 0.93 and RMSEn < 11%, except in one experiment) and better computational efficiency. Field data indicated that AQF simulations are in close agreement with observation.
Conclusions: AQF offers a version of the AquaCrop developed for time-consuming applications, such as crop forecast systems and climate change simulations over large areas and explores mitigation and adaptation actions in the face of adverse effects of future climate change.
Powered by DB/Text WebPublisher, from
