Evaluation and Application of the AquaCrop Model in Simulating Soil Salinity and Winter Wheat Yield under Saline Water Irrigation

Abstract

Saline water irrigation has been considered a useful practice to overcome the freshwater shortage in arid and semi-arid regions. Assessing and scheduling the appropriate irrigation water amount, salinity, and timing is essential to maintaining crop yield and soil sustainability when using saline water in agriculture. A field experiment that included two irrigation levels (traditional and deficit irrigation) and three water salinities (0, 5, and 10 dS/m) was carried out in the North China Plain during the 2017/18 and 2018/19 winter wheat growing seasons. AquaCrop was used to simulate and optimize the saline water irrigation for winter wheat. The model displayed satisfactory performance when simulating the volumetric soil water content (R2 ≥ 0.85, RMSE ≤ 2.59%, and NRMSE ≤ 12.95%), soil salt content (R2 ≥ 0.71, RMSE ≤ 0.62 dS/m, and NRMSE ≤ 26.82%), in-season biomass (R2 ≥ 0.89, RMSE ≤ 1.03 t/ha, and NRMSE ≤ 18.92%), and grain yield (R2 ≥ 0.92, RMSE ≤ 0.35 t/ha, and NRMSE ≤ 7.11%). The proper saline water irrigation strategies were three irrigations of 60 mm with a salinity up to 4 dS/m each at the jointing, flowering, and grain-filling stage for the dry year; two irrigations of 60 mm with a salinity up to 6 dS/m each at the jointing and flowering stage for the normal year; and one irrigation of 60 mm with a salinity up to 8 dS/m at the jointing stage for the wet year, which could achieve over 80% of the potential yield while mitigating soil secondary salinization. Nonetheless, the model tended to overestimate the soil moisture and wheat production but underestimate the soil salinity, particularly under water and salt stress. Further improvements in soil solute movement and crop salt stress are desired to facilitate model performance. Future validation studies using long-term field data are also recommended to obtain a more reliable use of AquaCrop and to better identify the influence of long-term saline water irrigation. Finally, AquaCrop maintained a good balance between simplicity, preciseness, and user-friendliness, and could be a feasible tool to guide saline water irrigation for winter wheat.

Modelling effects of water stress on the productivity of irrigated wheat (Triticum Aestivum L.) in a semiarid condition of Northeastern Nigeria

“…AquaCrop model was calibrated and found to sufficiently predict wheat crop's GY, BMY and CC with similar statistical indices using wheat by Beltran et al [23], Kale et al [22] and Zhai et al [24]. Similarly, the findings of Umesh et al [20] and Guo et al [13], using maize and millet, respectively, were also in line with current work.…”

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

“…This means that the model being water driven responded well to the rainfall contributions in the root zone. The simulation compares well with R 2 ≥ 0.85, RMSE ≤ 2.59%, and NRMSE ≤ 12.95% [82] and better than R 2 of 0.62, and RMSE = 27.4 mm for SWS [83]. The model simulated SWS around the field capacity but not to saturation and wilting point.…”

Optimal land allocation and irrigation scheduling to maximize the economic utility

“…For the wheat, due to the insigni cant difference between the initial soil salinity and soil water salinity after irrigation (the difference is less than 0.1), the value of the in-class coe cient ( 1 ) and class change ( 2 ) is equal to 1. The crop yield and soil salinity could be signi cantly affected by rainfall conditions (Liu et al, 2019;Zhai et al, 2022). In the study area, during the growth period of crops such as wheat and the rstcultivation maize, rainfall distribution is higher, and crops obtain part of their water requirement from rainfall.…”