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Modelling climatic trends for the Zambezi and Orange River Basins: implications on water security

Domaine:

climateenvironment and energy
Créateur:
ChaKabHenKaw
Éditeur:
IWA
Hôte:
Abstract Climate change impacts are dependent on changes in air temperature, rainfall (frequency and amount) and climate indices, which are highly certain. Climate extreme indices are important metrics that are used to communicate the impacts of climate change. The CORDEX African-domain RCM (SMHI-RCA4) run by seven CMIP5 (CCCma-CanESM2, IPSL-IPSL-CM5A-MR, MIROC-MIROC5, MPI-M-MPI-ESM-LR, NCC-NorESM1-M, MOHC-HadGEM2-ES and NOAA-GFDL-GFDL-ESM2M) and two representative concentration pathways (RCP4.5 and RCP8.5) were used in this study. The future climate change is analysed relative to 2020–2050/1970–2000 using a multi-model ensemble projection. Selected climate indices were analysed using a multi-model ensemble of CMIP5 GCMs (GFDL-ESM2G, HadGEM2-ES and IPSL-CM5A-MR). The climate data operators (CDOs) were used in merging and manipulating the modelled (RCM) data and ETCCDI climate indices. The Mann–Kendall was used to compute the trends in time-series data at p < 0.05. Results indicate that temperature will increase in the Orange and Zambezi River Basins. Rainfall shows variability in both river basins. The temperature-based indices (tn90pETCCDI, tnnETCCDI, tnxETCCDI, tx90pETCCDI, txnETCCDI and txxETCCDI) were statistically significant with positive linear trends. The dtrETCCDI and wsdiETCCDI were statistically significant with positive linear trends within the Zambezi River Basin. csdiETCCDI and tn10pETCCDI were statistically significant with negative trends in both basins. The change in rainfall, temperature and climate indices will have implications on agricultural production, provisions of various ecosystem services, human health, water resources, hydrology, water security, water quality and quantity. The climate extreme indices can assist in analysing regional and global extremes in meteorological parameters and assist climate, and crop modellers and policymakers in assessing sectoral impacts.

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doi.org

Languages

Tonga

Licenses

http://creativecommons.org/licenses/by/4.0/

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