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Climate change effects on soil salinity in rainfed maize areas: a case study from South Africa
In maize fields, few studies have been conducted to identify the temporal trend of soil salinity and formulate optimal irrigation plans under climate change. Therefore, the main goals of this study were to predict changes in soil salinity over 2022–2050 and to formulate an optimal supplemental irrigation plan preventing soil salinity in a South African rainfed maize field. The study used the Global Climate Model (GCM) MPI-ESM1-2-LR to obtain future climate data for the study area from 2022 to 2050 and applied the HYDRUS-1D model to project the effects of these future climate data on soil salinity over the same period and to identify the best irrigation plan under climate change. Two key findings were revealed: first, the combined use of GCMs (i.e., MPI-ESM1-2-LR model) and soil-water models (i.e., HYDRUS-1D) was a powerful tool to identify soil salinity trends and formulate optimal irrigation plan under climate change. Second, in addition to rainfall amount, supplying a limited supplemental irrigation amount equal to 8% of the actual evapotranspiration of maize at the mid-season stage of maize growth can significantly reduce soil salinity (<1.7 dS m−1) and enhance soil moisture under climate change by 2050. These findings will be useful for preventing soil salinity in rainfed maize fields. HIGHLIGHTS We propose a methodological framework to identify the temporal trend of soil salinity and formulate optimal irrigation plans under climate change.; Future soil salinity could be predicted via Global Climate Models and HYDRUS-1D model.; Supplying limited supplemental irrigation amount is highly needed to reduce soil salinity in rainfed maize fields under climate change.;
Climate change effects on soil salinity in rainfed maize areas: a case study from South Africa
In maize fields, few studies have been conducted to identify the temporal trend of soil salinity and formulate optimal irrigation plans under climate change. Therefore, the main goals of this study were to predict changes in soil salinity over 2022–2050 and to formulate an optimal supplemental irrigation plan preventing soil salinity in a South African rainfed maize field. The study used the Global Climate Model (GCM) MPI-ESM1-2-LR to obtain future climate data for the study area from 2022 to 2050 and applied the HYDRUS-1D model to project the effects of these future climate data on soil salinity over the same period and to identify the best irrigation plan under climate change. Two key findings were revealed: first, the combined use of GCMs (i.e., MPI-ESM1-2-LR model) and soil-water models (i.e., HYDRUS-1D) was a powerful tool to identify soil salinity trends and formulate optimal irrigation plan under climate change. Second, in addition to rainfall amount, supplying a limited supplemental irrigation amount equal to 8% of the actual evapotranspiration of maize at the mid-season stage of maize growth can significantly reduce soil salinity (<1.7 dS m−1) and enhance soil moisture under climate change by 2050. These findings will be useful for preventing soil salinity in rainfed maize fields. HIGHLIGHTS We propose a methodological framework to identify the temporal trend of soil salinity and formulate optimal irrigation plans under climate change.; Future soil salinity could be predicted via Global Climate Models and HYDRUS-1D model.; Supplying limited supplemental irrigation amount is highly needed to reduce soil salinity in rainfed maize fields under climate change.;
Climate change effects on soil salinity in rainfed maize areas: a case study from South Africa
Zied Haj-Amor (author) / Tesfay Araya (author) / Dong-Gill Kim (author) / Salem Bouri (author)
2023
Article (Journal)
Electronic Resource
Unknown
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