Statistical evaluation of the PHYGROW model: a case study in Ceará State, Brazil

[Avaliação estatística do modelo PHYGROW: um estudo de caso no estado do Ceará, Brasil]

ABSTRACT

This study was carried out to statistically evaluate the performance of the PHYGROW model in simulating the growth of corn and sorghum plants in different locations in the semi-arid region of Ceará State, Brazil. Corn and sorghum production data were obtained in seven macro-regions, where the characterization of ecological sites was previously performed using soil and vegetation information for model parameterization. Biomass production data were collected in the 2021 and 2022 rainy seasons. The obtained models were statistically analyzed by the following estimators: estimation bias (BIAS), mean absolute error (MAE), estimation efficiency (EE) and Willmott’s index of agreement (d). The results showed the suitability of the PHYGROW model to simulate the growth of corn and sorghum crops in different semi-arid regions of Ceará State; however, the statistical estimators stressed the need for a larger database to improve forecast accuracy.

Keywords:
mathematical estimators; mechanistic modelling; rainfed crops