Modeling climate change impact on dryland wheat production for increased crop yield in the Free State, South Africa, using GCM projections and the DSSAT model

被引:3
|
作者
Ajilogba, Caroline F. [1 ,2 ]
Walker, Sue [1 ,3 ]
机构
[1] Agr Res Council Nat Resources & Engn, Pretoria, South Africa
[2] North West Univ, Fac Nat & Agr Sci, Food Secur & Safety Niche, Mmabatho, South Africa
[3] Univ Free State, Dept Soil Crop & Climate Sci, Bloemfontein, South Africa
基金
新加坡国家研究基金会;
关键词
crop model; DSSAT; South Africa; wheat; global climate model (GCM); representative concentration pathway (RCP); SUB-SAHARAN AFRICA; WINTER-WHEAT; CERES-WHEAT; RISING TEMPERATURES; SIMULATION; PHENOLOGY; MANAGEMENT; SYSTEMS; CHINA; APSIM;
D O I
10.3389/fenvs.2023.1067008
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Introduction: The impact of climate change on food production in South Africa is likely to increase due to low rainfall and frequent droughts, resulting in food insecurity in the future. The use of well-calibrated and validated crop models with climate change data is important for assessing climate change impacts and developing adaptation strategies. In this study, the decision support system for agrotechnology transfer (DSSAT) crop model was used to predict yield using observed and projected climate data.Materials and Methods: Climate, soil, and crop management data were collected from wheat-growing study sites in Bethlehem, South Africa. The DSSAT wheat model (CROPSIM-CERES) used was already calibrated, and validated by Serage et al. (Evaluating Climate Change Adaptation Strategies for Disaster Risk Management: Case Study for Bethlehem Wheat Farmers, South Africa, 2017) using three wheat cultivar coefficients obtained from the cultivar adaptation experiment by the ARC-Small Grain Institute. The model was run with historical climate data for the eastern Free State (Bethlehem) from 1999 to 2018 as the baseline period. To determine the effects of climate change, the crop model simulation for wheat was run with future projections from four Global Climate Models (GCM): BCC-CSM1_1, GFDL-ESM2G, ENSEMBLE, and MIROC from 2020 to 2077.Results: The average wheat yield for the historic climate data was 1145.2 kg/ha and was slightly lower than the highest average yield of 1215.9 kg/ha from GCM ENSEMBLE during Representative concentration pathways (RCP) 2.6, while the lowest yield of 29.8 kg/ha was produced during RCP 8.5 (GCM GFDL-ESM2G). Model GFDL-ESM2G produced low yields (29.8-47.74 kg/ha) during RCP 8.5 and RCP 6.0, respectively. The yield range for GCM BCC-CSM1_1 was 770.2 kg/ha during RCP 2.6 to 921.68 kg/ha during RCP 4.5 and 547.84 kg/ha during RCP 8.5 to 700.22 kg/ha during RCP 2.6 for GCM MIROC.Conclusion: This study showed a declining trend in yield for future climate projections from RCP2.6 to RCP8.5, indicating that the possible impacts of higher temperatures and reduced rainfall in the projected future climate will slightly decrease wheat production in the eastern Free State. Adaptation measures to mitigate the potential impact of climate change could include possible changes in planting dates and cultivars. Using a crop model to simulate the response of crops to variations in weather conditions can be useful to generate advisories for farmers to prevent low yield.
引用
收藏
页数:18
相关论文
共 38 条
  • [31] Statistical-dynamical modeling of the maize yield response to future climate change in West, East and Central Africa using the regional climate model REMO
    Bangelesa, Freddy
    Pollinger, Felix
    Sponholz, Barbara
    Mapatano, Mala Ali
    Hatloy, Anne
    Paeth, Heiko
    SCIENCE OF THE TOTAL ENVIRONMENT, 2023, 905
  • [32] Impact Assessment of Climate Change on Rice Yield Using a Crop Growth Model and Activities Toward Adaptation: Targeting Three Provinces in Indonesia
    Kinose, Yoshiyuki
    Masutomi, Yuji
    ADAPTATION TO CLIMATE CHANGE IN AGRICULTURE: RESEARCH AND PRACTICES, 2019, : 67 - 80
  • [33] Mapping the spatial distribution of underutilised crop species under climate change using the MaxEnt model: A case of KwaZulu-Natal, South Africa
    Mugiyo, H.
    Chimonyo, V. G. P.
    Kunz, R.
    Sibanda, M.
    Nhamo, L.
    Masemola, C. Ramakgahlele
    Modi, A. T.
    Mabhaudhi, T.
    CLIMATE SERVICES, 2022, 28
  • [34] Assessing the Impact of Agricultural Drought on Yield over Maize Growing Areas, Free State Province, South Africa, Using the SPI and SPEI
    Makuya, Vuwani
    Tesfuhuney, Weldemichael
    Moeletsi, Mokhele E.
    Bello, Zaid
    SUSTAINABILITY, 2024, 16 (11)
  • [35] Use of crop growth model to simulate the impact of climate change on yield of various wheat cultivars under different agro-environmental conditions in Khyber Pakhtunkhwa, Pakistan
    Farhana Gul
    Ishfaq Ahmed
    Muhammad Ashfaq
    Dawood Jan
    Shah Fahad
    Xiuling Li
    Depeng Wang
    Muhammad Fahad
    Muhammad Fayyaz
    Syed Attaullah Shah
    Arabian Journal of Geosciences, 2020, 13
  • [36] Use of crop growth model to simulate the impact of climate change on yield of various wheat cultivars under different agro-environmental conditions in Khyber Pakhtunkhwa, Pakistan
    Gul, Farhana
    Ahmed, Ishfaq
    Ashfaq, Muhammad
    Jan, Dawood
    Fahad, Shah
    Li, Xiuling
    Wang, Depeng
    Fahad, Muhammad
    Fayyaz, Muhammad
    Shah, Syed Attaullah
    ARABIAN JOURNAL OF GEOSCIENCES, 2020, 13 (03)
  • [37] Drought Characterization and Trend Detection Using the Reconnaissance Drought Index for Setsoto Municipality of the Free State Province of South Africa and the Impact on Maize Yield
    Abubakar, Hadisu B.
    Newete, Solomon W.
    Scholes, Mary C.
    WATER, 2020, 12 (11) : 1 - 16
  • [38] Modeling climate change impact on inflow and hydropower generation of Nangbeto dam in West Africa using multi-model CORDEX ensemble and ensemble machine learning
    Obahoundje, Salomon
    Diedhiou, Arona
    Dubus, Laurent
    Alamou, Eric Adechina
    Amoussou, Ernest
    Akpoti, Komlavi
    Ofosu, Eric Antwi
    APPLIED ENERGY, 2022, 325