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Simulating Cotton Growth and Productivity Using AquaCrop Model under Deficit Irrigation in a Semi-Arid Climate

Author

Listed:
  • Marjan Aziz

    (Department of Agricultural Engineering, Barani Agricultural Research Institute, Chakwal 48800, Pakistan)

  • Sultan Ahmad Rizvi

    (Water Conservation Division, Soil and Water Conservation Research Institute, Chakwal 48800, Pakistan)

  • Muhammad Sultan

    (Department of Agricultural Engineering, Bahauddin Zakariya University, Bosan Road, Multan 60800, Pakistan)

  • Muhammad Sultan Ali Bazmi

    (Department of Agronomy, Fodder Research Institute, Sargodha 40100, Pakistan)

  • Redmond R. Shamshiri

    (Department of Engineering for Crop Production, Leibniz Institute for Agricultural Engineering and Bioeconomy, 14469 Potsdam, Germany)

  • Sobhy M. Ibrahim

    (Department of Biochemistry, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia)

  • Muhammad A. Imran

    (School of Environmental and Municipal Engineering, Xi’an University of Architecture and Technology, Shaanxi, Xi’an 710055, China)

Abstract

AquaCrop is a water-driven model that simulates the effect of environment and management on crop production under deficit irrigation. The model was calibrated and validated using three databases and four irrigation treatments (i.e., 100%ET, 80%ET, 70%ET, and 50%ET). Model performance was evaluated by simulating canopy cover (CC), biomass accumulation, and water productivity (WP). Statistics of root mean square error ( RMSE ) and Willmott’s index of agreement ( d ) showed that model predictions are suitable for non-stressed and moderate stressed conditions. The results showed that the simulated biomass and yield were consistent with the measured values with a coefficient of determination (R 2 ) of 0.976 and 0.950, respectively. RMSE and d-index values for canopy cover (CC) were 2.67% to 4.47% and 0.991% to 0.998% and for biomass were 0.088 to 0.666 ton/ha and 0.991 to 0.999 ton/ha, respectively. Prediction of simulated and measured biomass and final yield was acceptable with deviation ˂10%. The overall value of R 2 for WP in terms of yield was 0.943. Treatment with 80% ET consumed 20% less water than the treatment with 100%ET and resulted in high WP in terms of yield (0.6 kg/m 3 ) and biomass (1.74 kg/m 3 ), respectively. The deviations were in the range of −2% to 11% in yield and −2% to 4% in biomass. It was concluded that AquaCrop is a useful tool in predicting the productivity of cotton under different irrigation scenarios.

Suggested Citation

  • Marjan Aziz & Sultan Ahmad Rizvi & Muhammad Sultan & Muhammad Sultan Ali Bazmi & Redmond R. Shamshiri & Sobhy M. Ibrahim & Muhammad A. Imran, 2022. "Simulating Cotton Growth and Productivity Using AquaCrop Model under Deficit Irrigation in a Semi-Arid Climate," Agriculture, MDPI, vol. 12(2), pages 1-18, February.
    • Handle: RePEc:gam:jagris:v:12:y:2022:i:2:p:242-:d:744594
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    References listed on IDEAS

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    2. Marjan Aziz & Madeeha Khan & Naveeda Anjum & Muhammad Sultan & Redmond R. Shamshiri & Sobhy M. Ibrahim & Siva K. Balasundram & Muhammad Aleem, 2022. "Scientific Irrigation Scheduling for Sustainable Production in Olive Groves," Agriculture, MDPI, vol. 12(4), pages 1-14, April.
    3. Imran Sajid & Bernhard Tischbein & Christian Borgemeister & Martina Flörke, 2022. "Assessing Barriers in Adaptation of Water Management Innovations under Rotational Canal Water Distribution System," Agriculture, MDPI, vol. 12(7), pages 1-16, June.
    4. Haoteng Zhao & Liping Di & Liying Guo & Chen Zhang & Li Lin, 2023. "An Automated Data-Driven Irrigation Scheduling Approach Using Model Simulated Soil Moisture and Evapotranspiration," Sustainability, MDPI, vol. 15(17), pages 1-17, August.

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