Evaluating AquaCrop for Soil Management and Water Efficiency in Corn Farming

Greg Howard
27th June, 2024

Evaluating AquaCrop for Soil Management and Water Efficiency in Corn Farming

To accurately simulate the impact of nutrient deficiency on Zea mays, the AquaCrop model was calibrated using this response curve which links the reduction in relative biomass production to a corresponding decrease in transpiration under soil fertility stress.

Image adapted from: Adeboye et al. / CC BY (Source)

Key Findings

  • The study in Ile-Ife, Nigeria, showed that the AquaCrop model accurately predicted maize canopy cover under different soil fertility conditions
  • The model effectively simulated maize grain yields, even with some underestimations in soil water storage and evapotranspiration
  • Applying 150% of the recommended NPK fertilizer levels significantly improved maize land and water productivity
The recent study conducted by Obafemi Awolowo University[1] aimed to evaluate the performance of the AquaCrop model in simulating the effects of soil fertility management on various parameters of rainfed maize. This research is particularly significant given the ongoing challenges in optimizing agricultural practices to ensure sustainable and high-yield crop production. Agricultural systems science has a rich history of employing models to address complex issues in farming[2]. These models have evolved significantly over the past six decades, incorporating a wide range of disciplines and methodologies. The AquaCrop model, developed by the Food and Agriculture Organization (FAO), is one such tool designed to simulate crop yield responses to water, making it highly relevant for regions like Ile-Ife, Nigeria, where rainfall variability can significantly impact crop productivity. In the study, field experiments were conducted over two seasons to assess the AquaCrop model's accuracy in predicting canopy cover (CC), soil water storage (SWS), cumulative aboveground biomass (BM), evapotranspiration (ETa), grain yields, and water productivity (WP) for maize. The experiments involved two maize cultivars, SUWAN 1-SR and PVA, and six levels of soil fertility management, creating a comprehensive factorial design. The AquaCrop model was calibrated using data from a wetter year, which is crucial for ensuring the model's accuracy under varying environmental conditions. The results demonstrated that the AquaCrop model effectively captured the variances in canopy cover (CC) with high accuracy (R2 ≥ 0.88, RMSE ≤ 14.2, and d-index ≥ 0.97) under both full and stressed soil fertility conditions. Although there were some over and underestimations in soil water storage (SWS), these were within acceptable limits, indicating the model's robustness. Interestingly, the AquaCrop model tended to underestimate evapotranspiration (ETa) under conditions of rainfall and NPK variability. Despite this, the model simulated grain yields excellently (R2 = 0.99, b = 1.00), suggesting that it can be a reliable tool for predicting crop productivity under different soil fertility management practices. The study found that applying 150% of the recommended NPK levels was most effective for improving land and water productivity of maize. This finding aligns with previous research on optimized fertilization strategies[3], which emphasized the importance of finding the economic optimum N rate for maintaining high crop yields while minimizing environmental impacts. The use of the AquaCrop model in this context helps to identify the most efficient fertilization practices, contributing to sustainable agriculture. Furthermore, the study's results are consistent with long-term simulations that have shown the benefits of optimized fertilization strategies in improving nitrogen use efficiency and maintaining soil organic carbon levels[3]. By accurately predicting the impacts of different soil fertility management practices, the AquaCrop model can guide farmers in making informed decisions that enhance crop productivity and sustainability. In conclusion, the AquaCrop model has proven to be a valuable tool for simulating the effects of soil fertility management on rainfed maize in Ile-Ife, Nigeria. The study conducted by Obafemi Awolowo University provides a solid foundation for further research on other maize cultivars and locations to generalize the model's adequacy. By incorporating lessons from past studies[2][3], this research contributes to the ongoing efforts to develop next-generation agricultural system tools and methods that address the increasingly complex challenges faced by modern agriculture.

AgricultureEcologyPlant Science

References

Main Study

1) Assessment of the AquaCrop model to simulate the impact of soil fertility management on evapotranspiration, yield, and water productivity of maize (Zea May L.) in the sub-humid agro-ecology of Nigeria

Published 26th June, 2024

https://doi.org/10.1007/s44279-024-00030-5

Related Studies

2) Brief history of agricultural systems modeling.

https://doi.org/10.1016/j.agsy.2016.05.014

3) Modelling maize yield, soil nitrogen balance and organic carbon changes under long-term fertilization in Northeast China.

https://doi.org/10.1016/j.jenvman.2022.116454


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