Comparing the effects of calibration and climate errors on a statistical crop model and a process-based crop model
Understanding the relationship between climate and crop productivity is a key component of projections of future food production, and hence assessments of food security. Climate models and crop yield datasets have errors, but the effects of these errors on regional scale crop models is not well cate...
| Autores principales: | , , , |
|---|---|
| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Springer
2015
|
| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/76592 |
Ejemplares similares: Comparing the effects of calibration and climate errors on a statistical crop model and a process-based crop model
- Calibration and bias correction of climate projections for crop modelling: An idealised case study over Europe
- The relative importance of rainfall, temperature and yield data for a regional scale crop model
- Increasing influence of heat stress on French maize yields from the 1960s to the 2030s
- Identifying traits for genotypic adaptation using crop models
- Estimating model prediction error: Should you treat predictions as fixed or random?
- Calibrated Models for Major Crops and Cropping System using Existing Datasets in Morocco and Uzbekistan