AquaCrop Simulation of Winter Wheat under Different N Management Practices

Abstract

AquaCrop is a well-known water-oriented crop model. The model has been often used to simulate various crops and the water balance in the field under different irrigation treatments, but studies that relate AquaCrop to fertilization are rare. In this study, the ability of this model to simulate yield and the water balance parameters was investigated in a wheat field under different nitrogen management practices. During the 2015–2016 and 2016–2017 growing seasons, meteorological data were provided from a nearby meteorological station, and the evolution of soil water content and final yields were recorded. The model showed a very good performance at simulating the soil water content evolution in the root zone. Notwithstanding its simplicity, AquaCrop based on a semi-quantitative approach for fertility performed well at the field level for the final yield estimation under different nitrogen treatments and field topography variation. Although the correlation coefficient between simulated and measured final yields was high, increased values of variations were observed in the various zones of this experimental field (−50% to +140%). The model appears to be an efficient tool for evaluating and improving the management practices at the field level. The experiments were conducted in Thessaly, which is the largest plain and the main agricultural area of Greece. Thessaly, however, has a strong negative water balance, which has led to a strong decrease in the level of the aquifer and, at the same time, to sea intrusion. There is also a significant risk of contamination of the groundwater aquifer due to increased use of agrochemicals. This analysis is particularly important for Thessaly due to the need for improvement of agricultural practices in this area, to decrease the pressure of agricultural activities on natural resources (soil, water) and reverse the consequences of current management.

Land Surface Modeling as a Tool to Explore Sustainable Irrigation Practices in Mediterranean Fruit Orchards

“…The adjusted parameters for apple were used as described in Section 2.3.1 while a separate parameter set was used for cherries to account for the earlier start of the growing season and harvest, and lower productivity as compared to apples. For the sake of consistency, parameters for winter wheat and potato were also modified based on Boas et al (2021) with minor adjustments to growing seasons to account for the local climate (Dercas et al, 2022;FAO, 2023).…”

“…For the sake of consistency, parameters for winter wheat and potato were also modified based on Boas et al. (2021) with minor adjustments to growing seasons to account for the local climate (Dercas et al., 2022; FAO, 2023).…”

Assessing the impact of emerging technologies on sustainable fruit production: A systematic review of the literature

“…uses predictive models to anticipate the effects of biotic and abiotic factors on agriculture, including crop growth and ecological models. Some examples of these models are the DSSAT model (Decision Support System for Agrotechnology Transfer), which simulates the development of different crops under different climatic, management and fertilization conditions, and which has been applied in Colombia to assess the impact of climate change and climate variability on crops such as maize, rice, beans and potatoes (Sarkar, 2012); another example is the AquaCrop model, which estimates the water consumption and biomass production of crops as a function of water availability in the soil and atmosphere (Dercas et al, 2022). Finally, the CROPGRO (Crop Growth) model, which simulates the growth and development of leguminous crops such as beans, peanuts and soybeans, considering the effects of biotic factors such as insects, diseases and weeds, has been used in Colombia to optimize integrated pest and disease management practices (Van Loon et al, 2018).…”

Land surface modeling as a tool to explore sustainable irrigation practices in Mediterranean fruit orchards

“…The adjusted parameters for apple were used as described in section 2.3.1 while a separate parameter set was used for cherries to account for the earlier start of the growing season and harvest, and lower productivity as compared to apples. For the sake of consistency, parameters for winter wheat and potato were also modified based on Boas et al [2021] with minor adjustments to growing seasons to account for the local climate [Dercas et al , 2022;FAO , 2023].…”