article · The Journal of Agricultural Science
This research evaluates AquaCrop, a crop water productivity model that uses a semi-quantitative approach for modelling crop response to soil fertility. Unlike most models requiring extensive nutrient data, AquaCrop allows users to input soil fertility levels based on expected impact on biomass production. The study describes, calibrates, and evaluates this approach, which simulates fertility stress by affecting canopy expansion, maximum canopy cover, early canopy decline, and biomass water productivity. Field experiments with tef in Ethiopia, maize and wheat in Nepal, and quinoa in Bolivia demonstrated AquaCrop's ability to accurately simulate soil water content, canopy development, biomass, and grain yield under varying soil fertility levels. The model performed well, even under combined water and fertility stress, after case-specific calibration.
Understanding how crops respond to soil fertility is crucial for optimising agricultural practices and ensuring food security. This model offers a practical tool for predicting crop yields under varying soil conditions with less data, which can help farmers and agricultural planners make more informed decisions, especially in resource-limited settings.
This research presents an applied modelling tool, AquaCrop, which can be used by agricultural researchers, extension services, and potentially large-scale farming operations. It enables the simulation of crop production under different soil fertility conditions without requiring extensive soil nutrient data. This could support better crop management, resource allocation, and yield forecasting. The model requires case-specific calibration, indicating it is an applied tool ready for practical use after adaptation.
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SUMMARY Most crop models make use of a nutrient-balance approach for modelling crop response to soil fertility. To counter the vast input data requirements that are typical of these models, the crop water productivity model AquaCrop adopts a semi-quantitative approach. Instead of providing nutrient levels, users of the model provide the soil fertility level as a model input. This level is expressed in terms of the expected impact on crop biomass production, which can be observed in the field or obtained from statistics of agricultural production. The present study is the first to describe extensively, and to calibrate and evaluate, the semi-quantitative approach of the AquaCrop model, which simulates the effect of soil fertility stress on crop production as a combination of slower canopy expansion, reduced maximum canopy cover, early decline in canopy cover and lower biomass water productivity. AquaCrop's fertility response algorithms are evaluated here against field experiments with tef ( Eragrostis tef (Zucc.) Trotter) in Ethiopia, with maize ( Zea mays L.) and wheat ( Triticum aestivum L.) in Nepal, and with quinoa ( Chenopodium quinoa Willd.) in Bolivia. It is demonstrated that AquaCrop is able to simulate the soil water content in the root zone, and the crop's canopy development, dry above-ground biomass development, final biomass and grain yield, under different soil fertility levels, for all four crops. Under combined soil water stress and soil fertility stress, the model predicts final grain yield with a relative root-mean-square error of only 11–13% for maize, wheat and quinoa, and 34% for tef. The present study shows that the semi-quantitative soil fertility approach of the AquaCrop model performs well and that the model can be applied, after case-specific calibration, to the simulation of crop production under different levels of soil fertility stress for various environmental conditions, without requiring detailed field observations on soil nutrient content.
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DOI: 10.1017/s0021859614000872
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