Evaluation of AquaCrop model of cucumber under greenhouse cultivation

Khafajeh, Hamid; Banakar, Ahmad; Minaei, Saeid; Delavar, Majid

doi:10.1017/s0021859621000472

Cited by 6 publications

(2 citation statements)

References 38 publications

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“…This shows that applying stage deficit irrigation improves yield and water productivity compared to FI [8]. This result is also confirmed by [23,37,38,39,40,41]; the best WP was observed at the lowest irrigation depth.…”

Section: Validation Parameter Of Measured and Simulatedsupporting

confidence: 78%

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Performance Evaluation of AquaCrop Model of Tomato under Stage Wise Deficit Drip Irrigation at Southern Ethiopia

Yersaw,

Ebstu,

Areru

et al. 2024

Advances in Agriculture

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Crop modeling is a powerful tool for predicting yield and water productivity. The aim of the study was to calibrate and validate the AquaCrop model for tomato under staged deficit drip irrigation in Ethiopia. The AquaCrop model was calibrated and validated by using the observed data of canopy cover, biomass, dry yield, and soil water content. The results showed that the model was accurate in predicting canopy cover, biomass, and dry yield under different water levels. The overall performance in simulating canopy cover of AquaCrop, biomass, and soil water content showed a good match between measured and simulated data. The calibration results indicated good performance on canopy cover with 0.96 ≤ r ≤ 1.00, 2.9% ≤ RMSE ≤ 8.0%, 7.5% ≤ CV (RMSE) ≤ 21.1%, 0.91 ≤ EF ≤ 0.99, and 0.98 ≤ d ≤ 1.00. On biomass, the model calibration values were 0.99 ≤ r ≤ 1.00, 0.3 t/ha ≤ RMSE ≤ 0.8 t/ha, 8.3% ≤ CV (RMSE) ≤ 25.2%, 0.92 ≤ EF ≤ 0.99, and 0.98 ≤ d ≤ 1.00. Soil water content displayed poor performance on calibration, with performance values of 0.54 ≤ r ≤ 0.82, 3.6 mm ≤ RMSE ≤ 24.4 mm, 1.30% ≤ CV (RMSE) ≤ 9.00%, −4.18 ≤ EF ≤ 0.00, and 0.66 ≤ d ≤ 0.81. The validation results demonstrated that the model performed well on canopy cover with 0.96 ≤ r ≤ 1.00, 3.1% ≤ RMSE ≤ 7.7%, 8.2% ≤ CV (RMSE) ≤ 20.8%, EF ≥ 0.91, and d ≥ 0.9. The model validation correctly predicted biomass with r ≥ 0.98, 0.3 t/ha ≤ RMSE ≤ 0.7 t/ha, 8.9% ≤ CV (RMSE) ≤ 21.8%, EF ≥ 0.94, and d ≥ 0.98. The model validation poorly performed in forecasting soil water content, 0.20 ≤ r ≤ 0.80, 10.2 t/ha ≤ RMSE ≤ 24.0 t/ha, 3.5% ≤ CV (RMSE) ≤ 9.0%, −22.76 ≤ EF ≤ 0.63, and 0.40 ≤ d ≤ 0.87. The AquaCrop model is easy to use, requires less input data, and has high simulation accuracy, making it a useful tool for predicting crop yields and water productivity under staged deficit irrigation in areas with limited data.

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Section: Validation Parameter Of Measured and Simulatedsupporting

confidence: 78%

“…3 Normalized root mean square error CV ðRMSEÞ: [28], lettuce by Sabzian et al [37], and for cucumber by Khafajeh et al [38]. The AquaCrop model accurately simulated the SWC of the tomato, yet it consistently overestimated SWC across all irrigation treatments (EF ≤ 0.00).…”

Section: Performance Evaluation Of Aquacropmentioning

confidence: 99%