Accurate prediction of wheat yield under combined saline water irrigation and arid stress: a comprehensive analysis of the FAO-AquaCrop model

The AquaCrop model was calibrated and validated for durum wheat in the arid region of Biskra, Algeria. using field data from the CAZDA COSIDER farm during the 2022/2023 growing season. The wheat field was irrigated using a center pivot system with saline water at 4.45 dS m −1 . Validation was performed with independent yield data from the Technical Institute for the Development of Saharan Agronomy (TIDSA) in Biskra region; to take into consideration the differences in weather conditions, soil, salinity levels and irrigation management. The calibration process involved adjusting only the non-conservative crop parameters. The model accurately simulated canopy cover (RMSE = 3.7%, NRMSE = 5.5%, EF = 0.99, R = 1) and above-ground biomass (RMSE = 1.1 t ha −1 , NRMSE = 9.6%, EF = 0.78, R = 0.95), with a slight underestimation of 0.25 t ha −1 in the final above-ground biomass. The model captured the temporal trends in soil water content, but with low quantitative accuracy (RMSE = 40.2 mm, NRMSE = 14.9%, EF = −0.42, R = 0.94). Validation confirmed very good predictive performance for grain yield ( R 2 = 0.92, RMSE = 0.2 t ha −1 , NRMSE = 2.76%, EF = 0.9, d = 0.98). Overall, the results demonstrate that, with rigorous calibration using field measured data, the AquaCrop model can accurately predict durum wheat grain yield and final above-ground biomass under the arid and saline conditions of the studied area. In contrast, the use of default parameters resulted in poor yield prediction performance, underscoring the critical need for site-specific calibration. The locally calibrated AquaCrop model can effectively support water managers and decision-makers in optimizing irrigation scheduling and enhancing durum wheat yields under the challenging saline and arid conditions characteristic of the Biskra region. Serving as a robust decision support tool, the model enables the implementation of improved agricultural practices that ultimately benefit farmers and promote sustainable agriculture in the area.

Authors

Institutions

Publication Details

Journal
Frontiers in Sustainable Food Systems
Published
2025-11-06
DOI
https://doi.org/10.3389/fsufs.2025.1709629
Citations
1
Primary Topic
Plant Water Relations and Carbon Dynamics
Type
article
Field-Weighted Citation Impact
1.11

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Accurate prediction of wheat yield under combined saline water irrigation and arid stress: a comprehensive analysis of the FAO-AquaCrop model

Larbi Sekhri, Dmitry E. Kucher, Nazih Y. Rebouh, Anton Poddubsky et al.
1 citations
Frontiers in Sustainable Food Systems
Plant Water Relations and Carbon Dynamics
1.11
article

Accurate prediction of wheat yield under combined saline water irrigation and arid stress: a comprehensive analysis of the FAO-AquaCrop model

Larbi Sekhri, Dmitry E. Kucher, Nazih Y. Rebouh, Anton Poddubsky, Mohamed E. Fadl, Sabah Razi, Samir Merdaci, Fouad Sellem, Yacine Daibouche
article en
1 citations

Abstract

The AquaCrop model was calibrated and validated for durum wheat in the arid region of Biskra, Algeria. using field data from the CAZDA COSIDER farm during the 2022/2023 growing season. The wheat field was irrigated using a center pivot system with saline water at 4.45 dS m −1 . Validation was performed with independent yield data from the Technical Institute for the Development of Saharan Agronomy (TIDSA) in Biskra region; to take into consideration the differences in weather conditions, soil, salinity levels and irrigation management. The calibration process involved adjusting only the non-conservative crop parameters. The model accurately simulated canopy cover (RMSE = 3.7%, NRMSE = 5.5%, EF = 0.99, R = 1) and above-ground biomass (RMSE = 1.1 t ha −1 , NRMSE = 9.6%, EF = 0.78, R = 0.95), with a slight underestimation of 0.25 t ha −1 in the final above-ground biomass. The model captured the temporal trends in soil water content, but with low quantitative accuracy (RMSE = 40.2 mm, NRMSE = 14.9%, EF = −0.42, R = 0.94). Validation confirmed very good predictive performance for grain yield ( R 2 = 0.92, RMSE = 0.2 t ha −1 , NRMSE = 2.76%, EF = 0.9, d = 0.98). Overall, the results demonstrate that, with rigorous calibration using field measured data, the AquaCrop model can accurately predict durum wheat grain yield and final above-ground biomass under the arid and saline conditions of the studied area. In contrast, the use of default parameters resulted in poor yield prediction performance, underscoring the critical need for site-specific calibration. The locally calibrated AquaCrop model can effectively support water managers and decision-makers in optimizing irrigation scheduling and enhancing durum wheat yields under the challenging saline and arid conditions characteristic of the Biskra region. Serving as a robust decision support tool, the model enables the implementation of improved agricultural practices that ultimately benefit farmers and promote sustainable agriculture in the area.

Frontiers in Sustainable Food SystemsVol. 9
National Authority for Remote Sensing and Space Sciences (EG), Peoples' Friendship University of Russia (RU), University of Biskra (DZ), Russian New University (RU), École Nationale Supérieure Agronomique (DZ), Centre Hospitalo-Universitaire Bab El Oued (DZ), University of Eloued (DZ)
RUDN University
Openalex Percentile: Top 18%
Plant Water Relations and Carbon Dynamics
1.11
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.