Abstract
Crop models serve as powerful tools for investigating the interaction of crop traits, environmental fluctuations, and management practices. However, the calibration of these models relies heavily on experiments conducted under specific conditions or within particular years. The adaptability and efficacy of these calibrated models across different year patterns of climate remain uncertain. Our analysis aimed to evaluate the utility of these models across diverse climatic patterns and explore potential factors contributing to their performance variations. In this study, experiments were conducted in a semi-arid region characterized by significant climate variability, and data collection was undertaken to assess the performance of five distinct crop models (APSIM, AquaCrop, DSSAT, SSM-iCrop, WOFOST). The field experimental results indicated that year patterns of climate for rainfed spring wheat was jointly determined by soil water at planting and atmospheric moisture conditions during the growing season. After calibration, all five crop models effectively captured the growth, development, and yield formation of spring wheat. Notably, both simple and complex models exhibited similar performance in simulating the spring wheat growth and yield formation. However, the simulation results for spring wheat yield varied among the different year patterns of climate. Particularly in drier climate regimes, most models tended to overestimate spring wheat yields, with calculated relative root mean square errors exceeding 30 %. These findings suggested that calibrated models might not universally represent crop growth, development, and yield formation processes across all climatic patterns in regions characterized by substantial climate variability. In specific years, they were prone to either overestimating or underestimating crop yields. Furthermore, our study raised questions about the direct transferability of models to neighboring regions within the same climatic zone and application in future climatic scenarios. Without local climate-specific model calibration and with current climate-specific model calibration, the use of models might lead to inaccurate estimations of crop yields in other climatic area and future dryer climatic scenarios.
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Claims 6
Claim · model-written summary
After calibration, all five crop models effectively captured the growth, development and yield formation of spring wheat.
- Taxon
- spring wheat
Triticum aestivume1 - Outcome
- growth, development, and yield formatione1
- Direction
- effectively capturede1
Not reportedComparator
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e1“After calibration, all five crop models effectively captured the growth, development, and yield formation of spring wheat”
Claim · model-written summary
Simple and complex crop models performed similarly in simulating spring wheat growth and yield formation.
- Taxon
- spring wheatTriticum aestivume2
- Outcome
- performance in simulating the spring wheat growth and yield formatione2
- Direction
- similare2
- Comparator
- complex modelse2
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e2“both simple and complex models exhibited similar performance in simulating the spring wheat growth and yield formation”
Claim · model-written summary
In drier climate regimes most models overestimated spring wheat yields, with relative RMSE exceeding 30 %.
- Taxon
- spring wheatTriticum aestivume3
- Outcome
- spring wheat yieldse3
- Direction
- overestimatee3
- Value
- exceeding 30 %e3
- Qualifier
- drier climate regimese3
Not reportedComparator
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e3“Particularly in drier climate regimes, most models tended to overestimate spring wheat yields, with calculated relative root mean square errors exceeding 30 %”
Claim · model-written summary
Simulated spring wheat yield varied among the different year patterns of climate.
- Taxon
- spring wheatTriticum aestivume4
- Outcome
- simulation results for spring wheat yielde4
- Direction
- variede4
- Comparator
- different year patterns of climatee4
Not reportedValue
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e4“the simulation results for spring wheat yield varied among the different year patterns of climate”
Claim · model-written summary
Year patterns of climate for rainfed spring wheat were jointly determined by soil water at planting and atmospheric moisture during the growing season.
- Taxon
- spring wheatTriticum aestivume5
- Treatment
- soil water at plantinge5
- Outcome
- year patterns of climatee5
- Setting
- growing seasone5
Not reportedDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e5“year patterns of climate for rainfed spring wheat was jointly determined by soil water at planting and atmospheric moisture conditions during the growing season”
Claim · model-written summary
Calibrated models may not universally represent wheat growth and yield formation across all climatic patterns, and may give inaccurate yield estimates in other areas and dryer future scenarios.
- Taxon
- spring wheatTriticum aestivumt0
- Outcome
- crop growth, development, and yield formation processese6
Not reportedComparatorValue
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e6“calibrated models might not universally represent crop growth, development, and yield formation processes across all climatic patterns”
t0“rainfed spring wheat production”