Calibration and validation of the AquaCrop model for simulating cotton growth under a semi-arid climate in Uzbekistan

Cotton is a crucial fiber crop, but its conventional production methods are heavily water intensive. In regions where water availability already limits cotton yields, there is a growing need to explore alternative field management practices that stabilize yields while reducing irrigation demands. Crop models, such as the AquaCrop model, are instrumental in these efforts, enabling simulations of the complex interactions between field management, water dynamics, crop growth, and yield. However, the variability in calibrated parameter values reported across AquaCrop studies for cotton raises concerns about the transferability and reliability of previously calibrated models. In this study, we calibrated and validated the AquaCrop crop model, developed by the Food and Agriculture Organization (FAO), to predict canopy growth, biomass accumulation and yield of cotton. The calibration protocol developed here is rather conservative, adhering strictly to the guidelines provided in the AquaCrop documentation. The calibration involved approximately 1500,000 simulations per treatment, employing a Monte Carlo (MC) protocol to systematically assess the effects of varying input parameters across multiple evaluation criteria, including their impact on water stress. The calibrated AquaCrop model delivered good to acceptable performance levels in simulating canopy growth, biomass accumulation, and yield under various irrigation treatments, comparable to previous AquaCrop cotton applications. Additionally, the MC protocol uncovered a previously undiscover bug in the model, which shifted the crop’s planting date by approximately two weeks without user awareness, when the minimum rooting depth is set below 0.18 m. Furthermore, the rigorous calibration protocol clearly depicted compensatory interactions between parameters, where changes to one parameter can be offset by adjustments to another, highlighting the subjectivity and limitations encompassed in trial-and-error calibration approaches. • Calibrated and validated AquaCrop for simulating cotton growth in Uzbekistan. • Performance of the calibrated AquaCrop model comparable to previous cotton studies. • Monte Carlo simulations of input parameters was effective in model calibration. • Inconsistency in calibrated parameters in previous cotton AquaCrop studies.

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Publication Details

Journal
Agricultural Water Management
Published
2025-02-12
DOI
https://doi.org/10.1016/j.agwat.2025.109360
Citations
7
Primary Topic
Climate change impacts on agriculture
Type
article
Field-Weighted Citation Impact
21.19
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article

Calibration and validation of the AquaCrop model for simulating cotton growth under a semi-arid climate in Uzbekistan

Sirojiddin Nizamov, Bakhtiyor Kamilov, Musulmon Ziyatov, Aziz Nurbekov et al.
7 citations
Agricultural Water Management
Climate change impacts on agriculture
21.19
article

Calibration and validation of the AquaCrop model for simulating cotton growth under a semi-arid climate in Uzbekistan

Sirojiddin Nizamov, Bakhtiyor Kamilov, Musulmon Ziyatov, Aziz Nurbekov, Julien Boulangé, Hirozumi Watanabe, Sherzod Nizamov, Abduaziz Abduvasikov, Gulnoza Khamdamova
article en
7 citations

Abstract

Cotton is a crucial fiber crop, but its conventional production methods are heavily water intensive. In regions where water availability already limits cotton yields, there is a growing need to explore alternative field management practices that stabilize yields while reducing irrigation demands. Crop models, such as the AquaCrop model, are instrumental in these efforts, enabling simulations of the complex interactions between field management, water dynamics, crop growth, and yield. However, the variability in calibrated parameter values reported across AquaCrop studies for cotton raises concerns about the transferability and reliability of previously calibrated models. In this study, we calibrated and validated the AquaCrop crop model, developed by the Food and Agriculture Organization (FAO), to predict canopy growth, biomass accumulation and yield of cotton. The calibration protocol developed here is rather conservative, adhering strictly to the guidelines provided in the AquaCrop documentation. The calibration involved approximately 1500,000 simulations per treatment, employing a Monte Carlo (MC) protocol to systematically assess the effects of varying input parameters across multiple evaluation criteria, including their impact on water stress. The calibrated AquaCrop model delivered good to acceptable performance levels in simulating canopy growth, biomass accumulation, and yield under various irrigation treatments, comparable to previous AquaCrop cotton applications. Additionally, the MC protocol uncovered a previously undiscover bug in the model, which shifted the crop’s planting date by approximately two weeks without user awareness, when the minimum rooting depth is set below 0.18 m. Furthermore, the rigorous calibration protocol clearly depicted compensatory interactions between parameters, where changes to one parameter can be offset by adjustments to another, highlighting the subjectivity and limitations encompassed in trial-and-error calibration approaches. • Calibrated and validated AquaCrop for simulating cotton growth in Uzbekistan. • Performance of the calibrated AquaCrop model comparable to previous cotton studies. • Monte Carlo simulations of input parameters was effective in model calibration. • Inconsistency in calibrated parameters in previous cotton AquaCrop studies.

Agricultural Water ManagementVol. 310
Tashkent State Agrarian University (UZ), Ministry of Health of the Republic of Uzbekistan (UZ), Interstate Commission for Water Coordination of Central Asia (UZ), Cotton Research Institute (CN), Tokyo University of Agriculture and Technology (JP)
Climate action
Openalex Percentile: Top 1%
Climate change impacts on agriculture
21.19
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