Evaluation of Aquacrop Model in Simulating Bitter Gourd Water Productivity Under Saline Irrigation

Soomro, Kamran Baksh; Alaghmand, Sina; Shahid, Muhammad; Andriyas, Sanyogita; Talei, Amin

doi:10.1002/ird.2395

Cited by 5 publications

(6 citation statements)

References 56 publications

(64 reference statements)

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“…The AquaCrop model performed well in predicting the grain yield under saline water irrigation, though it tended toward overestimation. Consistent with our results, Soomro et al [24] reported that the simulated values of AquaCrop were slightly higher than the measured yield for bitter gourd under saline water irrigation. In the study, this discrepancy could have been caused by the overestimation of soil moisture, biomass, and the underestimation of soil salinity.…”

Section: Model Performancesupporting

confidence: 92%

“…AquaCrop is also capable of simulating salt stress effects on canopy development, stomatal closure, and biomass production using a salt stress-response curve. The model provides accurate crop simulations under saline conditions for barley, wheat, rice, bitter gourd, and cotton [20,[23][24][25]29]. Furthermore, Mohammadi et al [30] verified the good performance of AquaCrop for the wheat grain yield prediction response to water and salt stress simultaneously.…”

Section: Introductionmentioning

confidence: 96%

“…However, these models usually require substantial input parameters and complex calibration and validation processes. Recently, the AquaCrop model has been increasingly selected to assess crop responses and field management for saline conditions [23][24][25][26]. AquaCrop is a water-driven model and was extensively tested for various soils, crops, and climates to identify crop growth and production under different soil moisture and irrigation strategies [4,27,28].…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2022

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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.

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Section: Model Performancesupporting

confidence: 92%

Section: Introductionmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

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

et al. 2022

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“…Better simulation results were found for yield (nRMSE = 8.8%) than for biomass (nRMSE = 9.8%) in the case of the cowpea, which was in contradiction with our results because a lower nRMSE was found for biomass when evaluating the final yields [5]. Overestimation of bitter-gourd biomass and yield was found in a study conducted for two growing seasons [48]. Both over-and underestimation was revealed according to our findings.…”

Section: Discussioncontrasting

confidence: 99%

Performance Evaluation of AquaCrop Model in Processing Tomato Biomass, Fruit Yield and Water Stress Indicator Modelling

Takács

Csengeri

Pék

et al. 2021

Water

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A three-year long experiment was conducted on open-field tomato with different levels of water shortage stress. Three different water supply levels were set in 2017 and four levels for 2018 and 2019. Biomass and yield data were collected, along with leaf-temperature-based stress measurements on plants. These were used for calibration and validation of the AquaCrop model. The validation gave various results of biomass and yield simulation during the growing season. The largest errors in the prediction occurred in the middle of the growing seasons, but the simulation became more accurate at harvest in general. The prediction of final biomass and yields were good according to the model evaluation indicators. The relative root mean square error (nRMSE) was 12.1 and 13.6% for biomass and yield prediction, respectively. The modeling efficiency (EF) was 0.96 (biomass) and 0.99 (yield), and Willmott’s index of agreement (d) was 0.99 for both predicted parameters at harvest. The lowest nRMSE (4.17) was found in the simulation of final yields of 2018 (the calibration year). The best accuracy of the validation year was reached under mild stress treatment. No high correlation was found between the simulated and measured stress indicators. However, increasing and decreasing trends could be followed especially in the severely stressed treatments.

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“…In this regard, crop modelling is an efficient approach for estimating WP. Crop modelling plays a significant role in addressing water management strategies (Soomro et al, 2020). Dynamic crop growth modelling and simulation have become accepted tools for agricultural research (Yang et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of AquaCrop model of cucumber under greenhouse cultivation

et al. 2020

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Water consumption in agriculture is impossible without considering relations between water, soil and plant. In this regard, there are various models and developed software in order to evaluate relation between soil, water and crop growth stages. These models can be used for irrigation planning if properly optimized and applied. AquaCrop is one of the known crop models, which was developed by the Food and Agriculture Organization of the United Nations. In order to optimize this model for crop production and irrigation management, an experiment was developed in a hydroponic cucumber greenhouse. Various parameters including water consumption volume, crop yield and leaf area index were measured during a season. A fuzzy control system was utilized for controlling temperature, relative humidity, planting bed moisture, light intensity and carbon dioxide values. The main purpose of designing a control system in the greenhouse is to achieve the desired values of temperature and relative humidity. In this model, evapotranspiration, irrigation requirements and crop yield were simulated. The results show that the AquaCrop model can estimate evapotranspiration with the least error in the greenhouse environment, which is controlled by a fuzzy controller. Also the system has estimated the crop yield and biomass of the product with a good degree of precision and it may support crop production in a greenhouse, including crop management and environmental control.

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Evaluation of Aquacrop Model in Simulating Bitter Gourd Water Productivity Under Saline Irrigation

Cited by 5 publications

References 56 publications

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

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

Performance Evaluation of AquaCrop Model in Processing Tomato Biomass, Fruit Yield and Water Stress Indicator Modelling

Evaluation of AquaCrop model of cucumber under greenhouse cultivation

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