Using a Statistical Crop Model to Predict Maize Yield by the End-Of-Century for the Azuero Region in Panama Article uri icon

Abstracto

  • AUTHORS
    Marlemys M. Martínez
    Tosiyuki Nakaegawa
    Shoji Kusunoki
    Román Gordón
    Javier E. Sanchez-Galan

    ABSTRACT
    In this article, we evaluate the impact of temperature and precipitation at the end of the 21st century (2075–2099) on the yield of maize in the Azuero Region in Panama. Using projected data from an atmospheric climate model, MRI-ACGM 3.2S, the study variables are related to maize yield (t ha−1
    ) under four different sea surface Temperature (SST) Ensembles (C0, C1, C2, and C3) and in three different planting dates (21 August, 23 September, and 23 October). In terms climate, results confirm the increase in temperatures and precipitation intensity that has been projected for the region at the end of the century. Moreover, differences are found in the average precipitation patterns of each SST-ensemble, which leads to difference in maize yield. SST-Ensembles C0, C1, and C3 predict a doubling of the yield observed from baseline period (1990–2003), while in C1, the yield is reduced around 5%. Yield doubling is attributed to the increase in rainfall, while yield decrease is related to the selection of a later planting date, which is indistinct to the SST-ensembles used for the calculation. Moreover, lower yields are related to years in which El Niño Southerm Oscilation (ENSO) are projected to occur at the end of century. The results are important as they provide a mitigation strategy for maize producers under rainfed model on the Azuero region, which is responsible for over 95% of the production of the country.

fecha de publicación

  • 2020

Palabras clave

    • Azuero;
    • bias correction;
    • climate prediction;
    • crop yield;
    • GCM;
    • maize;
    • MRI-AGCM;
    • Panama;
    • precipitation;
    • statistical model;
    • temperature

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