رویکردهای نوین در مهندسی آب و محیط‌زیست
نشریه علمی

Evaluation of the AquaCrop Model in the simulation of the simultaneous effect of different water regimes and salinity on soybean's productivity and yield in the North of Iran

نوع مقاله : مقاله پژوهشی

نویسندگان

Esmaeil Shabani 1
Ali Sharafi 1
Mehdi Zakerinia 2
Moosa Hesam 2
seyede Soheila Ebrahimi 3
Meisam Abedinpour 4

1 Irrigation and drainage, Agriculture Science and Natural Resources University, Gorgan, Iran

2 Water Engineering department, College of Water and soil, Agriculture Science and Natural Resources University, Gorgan, Iran

3 Soil science department College of Water and soil, Agriculture Science and Natural Resources University, Gorgan, Iran

4 Golestan Agricultural and Natural Resources Research and Education Center, Gorgan, Iran

https://doi.org/10.22034/nawee.2025.505324.1138
چکیده
Objective:  This study investigates the feasibility of integration using Caspian Sea water and different fresh groundwater levels for soybean irrigation and performance evaluation of the Aqua Crop model at the Gorgan University of Agricultural Science and Natural Resources research field in the Golestan Province, northern Iran
 Material and Methods:  Irrigation applications comprised irrigation at 75% of field capacity (FC) (I1), 100 % FC (I2), and over irrigation at 125% FC (I3). Experiments were conducted during two consecutive seasons. It was done by grain yield (GY), biomass yield (BY), and water productivity (WP) under varying irrigation depths and saline water regimes. Model efficiency (E), coefficient of determination (R2), Root Mean Square error (RMSE), and Mean Absolute Error (MAE) were used to evaluate the model performance.
Results and Discussion: The calibration results for (GY) and (BY) were in line with observed data, with the estimation error statistics 0.97<E<0.99, 0.11<RMSE<1.51, 0.92<R2<0.96, and 0.33<MAE<1.02 t ha-1. The model prediction error in simulating the soybean WP varied from 2.35% to 27.5% for all treatments. Therefore, the AquaCrop model accurately estimated soybean yield under different saline water and irrigation levels.
Conclusions: According to the results of this study, Caspian Sea water can be considered an alternative irrigation water resource in combination with fresh groundwater for soybean crop irrigation at a ratio of 14 percent in the dry years.

کلیدواژه‌ها

Biomass
salinity
water deficit
water productivity

عنوان مقاله English

Evaluation of AquaCrop Performance for soybean water productivity and yield under the effect of irrigation with different saline water regimes

نویسندگان English

Esmaeil Shabani 1
Ali Sharafi 1
Mehdi Zakerinia 2
Moosa Hesam 2
seyede Soheila Ebrahimi 3
Meisam Abedinpour 4
1 Irrigation and drainage, Agriculture Science and Natural Resources University, Gorgan, Iran
2 Water Engineering department, College of Water and soil, Agriculture Science and Natural Resources University, Gorgan, Iran
3 Soil science department College of Water and soil, Agriculture Science and Natural Resources University, Gorgan, Iran
4 Golestan Agricultural and Natural Resources Research and Education Center, Gorgan, Iran
چکیده English

the aim of this study was feasibility of integration of saline water and fresh groundwater for soybean irrigation and Performance evaluation of AquaCrop model at the research field of Gorgan University of Agricultural Science and Natural Resources in the Golestan Province ,northern Iran. For this purpose, the AquaCrop model with salinity module (FAO-2012) was calibrated and validated with soybean crop data of 2013and 2014, by grain yield, biomass yield and water productivity under varying irrigation and salinity regimes. Irrigation applications comprised irrigation at 75% of field capacity (I1); at 100 % FC (I2); and over irrigation 125% FC (I3). The salinity application levels were fresh water with Electrical conductivity about 0.86 (S1); 5 (S2) and 8 dS/m (S3).The different saline water were made with mixing a ratio of the Caspian Sea water (ECw=26.5 dS/m) and fresh water. Model efficiency (E), coefficient of determination (R2), Root Mean Square error (RMSE) and Mean Absolute Error (MAE) were used to test the model performance. The model was calibrated for simulating soybean grain and biomass yield for all treatment levels with the prediction error statistics 0.97

کلیدواژه‌ها English

Biomass
salinity
water deficit
water productivity
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رویکردهای نوین در مهندسی آب و محیط‌زیست
دوره 4، شماره 2
مهر 1404
صفحه 56-78

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