Sensitivity Analysis of the Model Warm in Five European Rice Districts Using Different Methods: Morris and Sobol

Biophysical models (including crop models) may require a large number of input parameters, which values are not known with certainty. Parameterization errors are considered one of the primary sources of uncertainty in model response. In general, model which respond to minor changes in inputs with large changes in outputs are of suspect reliability, especially if the sensitive parameters are difficult to determine accurately. The understanding of model response to the variation of parameter values is therefore needed as one of the pre-requisites for model use. Sensitivity analysis (SA) calculates to which extent the outputs of a model depend on its inputs and is an important step of model evaluation to address parameter uncertainty. Advanced software tools are required to perform SA on crop models because of links needed and data-intensive processing (Confalonieri et al., 2006). This paper reports on the results of a SA study performed on a model for rice (Oryza sativa L.) simulation (WARM, http://agrifish.jrc.it/marsstat/WARM), run over sites representative of important rice districts in Europe.

CONFALONIERI Roberto;  ACUTIS Marco;  DONATELLI Marcello;  BELLOCCHI Gianni;  GENOVESE Giampiero; 

2007-10-23

La Goliardica Pavese

JRC38210

https://publications.jrc.ec.europa.eu/repository/handle/JRC38210,