Calibration and Validation of the AquaCrop Model to Estimate Maize Production in Campos Gerais, Paraná State, Brazil

Abstract

Crop productivity evaluation with models simulations can help in the prediction of harvests and in the understanding of the interactions resulting from the soil-plant-atmosphere continuum. The aim of this study was to calibrate and validate the AquaCrop model for maize crop in the edaphoclimatic conditions of Campos Gerais region, Paraná State, Brazil. The analyses were carried out for maize crop with model input data (climate, crop, soil and soil management) obtained from the ABC Foundation Experimental Station in Castro, Ponta Grossa and Socavão. The climate in the region is humid subtropical, with rainfall evenly distributed. The relief varies from flat to gently undulating. The period analyzed in the calibration and validation process comprised 2011 to 2016 and 2012 to 2016 harvests, respectively. The data used in the calibration of AquaCrop was different from those used in the validation process. Observed and simulated yields were evaluated by simple linear regression analyses, absolute and relative errors, correlation coefficient (r), concordance (d) and performance (c) indexes. The calibration of AquaCrop was satisfactory in the locations studied for maize crop, obtaining absolute errors varying from 6 to 121 kg ha–1. The highest calibration errors occurred in Castro. However, the errors were not enough to reduce the performance in the validation process for this localitie. The model validation resulted in “excellent” performance in all locations evaluated. The AquaCrop can be used to predict the maize yield with acceptable accuracy in the Campos Gerais Region, Paraná State, Brazil.

Calibration and evaluation of JULES‐crop for maize in Brazil

“…Thus, PBCMs aim to simulate crop dynamics in a specific environment, considering management differences, enabling analysis with practicality and speed (Marin et al., 2014). Several PBCMs have been used to simulate maize systems in Brazil, such as Aquacrop (Silvestre et al., 2019; T. Souza et al., 2019), DSSAT‐CERES‐Maize (J. Souza et al., 2020; Duarte & Sentelhas, 2020), and APSIM‐Maize (M. Santos et al., 2020). For studies on climate change on large territorial areas, there is a need for PBCMs that integrate crop physiology principles with biosphere–atmosphere processes.…”

“…Souza et al, 2019), DSSAT-CERES-Maize (J. Souza et al, 2020;Duarte & Sentelhas, 2020), and APSIM-Maize (M. Santos et al, 2020). For studies on climate change on large territorial areas, there is a need for PBCMs that integrate crop physiology principles with biosphere-atmosphere processes.…”

Prediction of tomato yield and water productivity under deficit irrigation scenarios using AquaCrop model in Afaka, Kaduna, Nigeria

“…Advances in software technology has enabled development of models (software) which can be used for simulating crop production. This is an excellent strategy for conducting tests and experiments, availing data already collected, wrapping few people, low cost, speed, creation and guessing of ideal scenarios to assist in decision making for public and private sectors [14], [15]. Hence, modeling becomes a valuable tool to study and develop promising deficit irrigation strategies as it allows a combination of different factors affecting yield under different scenarios [16].…”