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.

摘要 借助模型模拟开展作物生产力评估，可助力产量预测，并明晰土壤-作物-大气连续体（soil-plant-atmosphere continuum）所产生的交互作用。本研究旨在针对巴西巴拉那州坎波斯热赖斯区域的土壤气候条件，率定并验证AquaCrop模型在玉米种植中的适用性。本分析以玉米为研究对象，所用模型输入数据（气候、作物、土壤及土壤管理数据）取自卡斯特罗、蓬塔格罗萨与索卡旺三地的ABC基金会试验站。该区域气候为湿润亚热带气候，降水分布均匀；地形以平缓至缓起伏为主。率定与验证过程所分析的时段分别为2011-2016年与2012-2016年的玉米收获季。AquaCrop模型率定所用数据与验证阶段所用数据互不重叠。通过简单线性回归分析、绝对误差与相对误差、相关系数（r）、一致性系数（d）及性能系数（c）对实测产量与模拟产量开展评估。在本研究涉及的所有玉米种植点位中，AquaCrop模型的率定效果均较为理想，绝对误差范围为6~121 kg·ha⁻¹。卡斯特罗点位的率定误差最高，但该误差并未对该点位的验证阶段模型性能造成负面影响。所有评估点位的模型验证结果均达到"优秀"等级。在巴西巴拉那州坎波斯热赖斯区域，可借助AquaCrop模型以可接受的精度预测玉米产量。