Calibration and validation of the AquaCrop model for wheat grown under full and deficit irrigation with acidic soil management strategies

IF 6.4 1区农林科学 Q1 AGRONOMY

Field Crops Research Pub Date : 2025-09-24 DOI:10.1016/j.fcr.2025.110160

Desale Kidane Asmamaw , Kristine Walraevens , Habtamu Assaye , Fenta Nigate , Enyew Adgo , Abera Asefa , Wim M. Cornelis

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引用次数: 0

Abstract

Context

Previous studies using the AquaCrop model have shown that deficit irrigation (DI) and soil management independently influence wheat production. However, their combined effects on wheat production remain poorly understood. To address this research gap, a comprehensive study involving field experiments and modeling was conducted to evaluate how the interaction between DI and integrated acidic soil management (IASM) impacts soil water content, canopy cover, biomass, and grain yield.

Objective

The aim of this study was to calibrate and validate AquaCrop, allowing to further investigate how the interaction between DI and IASM influences wheat production; and to evaluate the model's performance, with a focus on addressing specific challenges related to the calibration and validation of wheat growth under DI and IASM scenarios.

Methods

The accuracy of the AquaCrop model was evaluated for predicting soil water content (SWC), wheat (Triticum aestivum L.) canopy cover (CC), biomass, and grain yield (GY) under DI combined with IASM strategies. Model input data for calibration and validation were obtained from field experiments conducted in the 2018 and 2019 irrigated seasons. These experiments included four irrigation scenarios (full irrigation [100 % crop water requirement, ETc], 80 % ETc, 60 % ETc and 50 % ETc), and five IASM strategies. The SWC was measured before and after irrigation events, while CC and biomass accumulation (BM) were monitored every 15 days post-sowing. Final biomass (FBM) and GY were recorded at harvest. The model was calibrated using 2018 data and validated with 2019 data.

Results

The simulated SWC, CC, BM, FBM, and GY results closely matched the field-measured results for all treatments. Statistical analysis revealed a precise agreement between simulated and field-measured values. The coefficients of determination (R²) ranged from 0.83 to 0.99, and the normalized root mean square error (NRMSE) ranged from 2.1 % to 9.1 % for SWC. For CC, R² ranged from 0.86 to 0.99 with NRMSE from 1.2 % to 9.8 %; for BM, R² ranged from 0.81 to 0.99 with NRMSE from 1.1 % to 7.8 %; and for GY, R² ranged from 0.87 to 0.99 with NRMSE from 1.4 % to 7.4 %.

Conclusions

The model performed well under severe water stress, proving its suitability for predicting wheat productivity. However, challenges were encountered in adjusting soil fertility levels, particularly with the uniform application of mineral fertilizers across all treatments. More iterations were required to match the simulated values with the field-measured values as water and soil fertility stress increased.

Implications or significance

Despite these challenges, the AquaCrop model demonstrated strong performance, especially under optimal soil fertility and irrigation conditions.

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酸性土壤管理策略下全亏灌小麦AquaCrop模型的校正与验证

以往使用AquaCrop模型的研究表明，亏缺灌溉（DI）和土壤管理对小麦产量的影响是独立的。然而，它们对小麦生产的综合影响仍然知之甚少。为了弥补这一研究空白，开展了一项包括田间试验和模型的综合研究，以评估DI和综合酸性土壤管理（IASM）之间的相互作用如何影响土壤含水量、冠层盖度、生物量和粮食产量。目的对AquaCrop进行标定和验证，进一步研究DI和IASM的相互作用对小麦产量的影响；并评估模型的性能，重点解决与DI和IASM情景下小麦生长的校准和验证相关的具体挑战。方法对AquaCrop模型在DI与IASM联合预测土壤含水量（SWC）、小麦（Triticum aestivum L.）冠层盖度（CC）、生物量和粮食产量（GY）方面的准确性进行评价。用于校准和验证的模型输入数据来自2018年和2019年灌溉季节进行的田间试验。试验包括4种灌溉方案（全灌[100% %作物需水量等]、80% %等、60% %等和50% %等）和5种IASM策略。灌水前后分别测量SWC，播种后每15 d监测CC和生物量积累（BM）。在收获时记录最终生物量（FBM）和GY。该模型使用2018年的数据进行校准，并使用2019年的数据进行验证。结果模拟的SWC、CC、BM、FBM和GY结果与所有处理的现场测量结果非常吻合。统计分析表明，模拟值与现场实测值之间具有精确的一致性。测定系数（R²）范围为0.83 ~ 0.99，归一化均方根误差（NRMSE）范围为2.1 % ~ 9.1 %。CC的R²范围为0.86 ~ 0.99，NRMSE范围为1.2 % ~ 9.8 %；BM的R²范围为0.81 ~ 0.99，NRMSE范围为1.1 % ~ 7.8 %；对于GY， R²范围为0.87 ~ 0.99，NRMSE范围为1.4 % ~ 7.4 %。结论该模型在严重水分胁迫下表现良好，可用于小麦产量预测。然而，在调整土壤肥力水平方面遇到了挑战，特别是在所有处理中均匀施用矿物肥料。随着水分和土壤肥力胁迫的增加，模拟值与田间实测值的匹配需要更多的迭代。尽管存在这些挑战，但AquaCrop模型表现出强大的性能，特别是在最佳土壤肥力和灌溉条件下。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Field Crops Research 农林科学-农艺学

CiteScore

9.60

自引率

12.10%

发文量

307

审稿时长

46 days

期刊介绍： Field Crops Research is an international journal publishing scientific articles on: √ experimental and modelling research at field, farm and landscape levels on temperate and tropical crops and cropping systems, with a focus on crop ecology and physiology, agronomy, and plant genetics and breeding.