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Simulating Maize Productivity under Selected Climate Smart Agriculture Practices Using AquaCrop Model in a Sub-humid Environment

Author

Listed:
  • Alex Zizinga

    (Africa Centre of Excellence for Climate Smart Agriculture and Biodiversity Conservation, Haramaya University, Dire Dawa P.O. Box 138, Ethiopia)

  • Jackson Gilbert Majaliwa Mwanjalolo

    (Africa Centre of Excellence for Climate Smart Agriculture and Biodiversity Conservation, Haramaya University, Dire Dawa P.O. Box 138, Ethiopia
    Regional Universities Forum for Capacity Building in Agriculture, Makerere University, Wandegeya, Kampala P.O. Box 16811, Uganda)

  • Britta Tietjen

    (Institute of Biology, Theoretical Ecology, Freie Universität Berlin, Königin-Luise-Str. 2/4, Gartenhaus, D-14195 Berlin, Germany)

  • Bobe Bedadi

    (College of Agriculture and Environmental Sciences, Haramaya University, Dire Dawa P.O. Box 138, Ethiopia)

  • Ramon Amaro de Sales

    (Department of Plant Science, Federal University of Viçosa, Viçosa 36570-900, MG, Brazil)

  • Dennis Beesigamukama

    (Department of Crop Production and Management, Busitema University, Soroti P.O. Box 203, Uganda
    International Centre of Insect Physiology and Ecology, Nairobi P.O. Box 30772-00100, Kenya)

Abstract

Crop models are crucial in assessing the reliability and sustainability of soil water conservation practices. The AquaCrop model was tested and validated for maize productivity under the selected climate smart agriculture (CSA) practices in the rainfed production systems. The model was validated using final biomass (B) and grain yield (GY) data from field experiments involving seven CSA practices (halfmoon pits, 2 cm thick mulch, 4 cm thick mulch, 6 cm thick mulch, 20 cm deep permanent planting basins (PPB), and 30 cm deep) and the control (conventional practice) where no CSA was applied. Statistics for coefficient of determination ( R 2 ), Percent bias (Pbias), and Nash–Sutcliffe ( E ) for B and GY indicate that the AquaCrop model was robust to predict crop yield and biomass as illustrated by the value of R 2 > 0.80, Pbias −1.52–1.25% and E > 0.68 for all the CSA practices studied. The relative changes between the actual and simulated water use efficiency (WUE) of grain yield was observed in most of the CSA practices. However, measured WUE was seemingly better in the 2 cm thick mulch, indicating a potential for water saving and yield improvement. Therefore, the AquaCrop model is recommended as a reliable tool for assessing the effectiveness of the selected CSA practices for sustainable and improved maize production; although, the limitations in severely low soil moisture conditions and water stressed environments should be further investigated considering variations in agroecological zones.

Suggested Citation

  • Alex Zizinga & Jackson Gilbert Majaliwa Mwanjalolo & Britta Tietjen & Bobe Bedadi & Ramon Amaro de Sales & Dennis Beesigamukama, 2022. "Simulating Maize Productivity under Selected Climate Smart Agriculture Practices Using AquaCrop Model in a Sub-humid Environment," Sustainability, MDPI, vol. 14(4), pages 1-17, February.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:4:p:2036-:d:746627
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    References listed on IDEAS

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