Combining input uncertainty and residual error in crop model predictions: A case study on vineyards
• We study uncertainty in crop model predictions. • We combine two approaches: Estimation of average overall model error and propagation of uncertainties in model inputs. • We apply the method to a model for evaluating water stress in intercropped vineyards. • We show that the results can help growe...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Roux, Sébastien [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2014 |
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| Schlagwörter: |
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| Umfang: |
7 |
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| Übergeordnetes Werk: |
Enthalten in: Barriers and benefits to the adoption of a third party certified food safety management system in the food processing sector in Shanghai, China - Qijun, Jiang ELSEVIER, 2016transfer abstract, the official journal of the European Society for Agronomy, Amsterdam [u.a.] |
|---|---|
| Übergeordnetes Werk: |
volume:52 ; year:2014 ; pages:191-197 ; extent:7 |
| Links: |
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| DOI / URN: |
10.1016/j.eja.2013.09.008 |
|---|
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ELV039492443 |
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| 520 | |a • We study uncertainty in crop model predictions. • We combine two approaches: Estimation of average overall model error and propagation of uncertainties in model inputs. • We apply the method to a model for evaluating water stress in intercropped vineyards. • We show that the results can help growers decide on the cost-effectiveness of more accurate estimation of model inputs. | ||
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• We study uncertainty in crop model predictions. • We combine two approaches: Estimation of average overall model error and propagation of uncertainties in model inputs. • We apply the method to a model for evaluating water stress in intercropped vineyards. • We show that the results can help growers decide on the cost-effectiveness of more accurate estimation of model inputs. |
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• We study uncertainty in crop model predictions. • We combine two approaches: Estimation of average overall model error and propagation of uncertainties in model inputs. • We apply the method to a model for evaluating water stress in intercropped vineyards. • We show that the results can help growers decide on the cost-effectiveness of more accurate estimation of model inputs. |
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• We study uncertainty in crop model predictions. • We combine two approaches: Estimation of average overall model error and propagation of uncertainties in model inputs. • We apply the method to a model for evaluating water stress in intercropped vineyards. • We show that the results can help growers decide on the cost-effectiveness of more accurate estimation of model inputs. |
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