Climate Change and Drought Drivers: Identification of drought drivers
and climate extreme using regression-based algorithms
Abstract
Droughts are particularly disastrous in South Africa and other arid
regions, that are water-scarce by nature due to low rainfall and water
sources. According to some studies, droughts are not uncommon in
Africa’s drylands and have been rising in dry African terrain. South
Africa’s provinces were severely affected recently by drought events.
This study aimed at evaluating drought disaster and climate trends in
the Free State Province of South Africa and to identify drought drivers
using regression-based algorithms. The study used high-resolution
downscaled climate change projections under three Representative
Concentration Pathways (RCP). Three future periods comprising the short
(the 2030s), medium (2040s) and long term (2050s) compared to the
current period are analysed to understand the potential magnitude of
projected climate change-related drought. The study revealed that the
year 2001 and 2016 witnessed extreme drought conditions where drought
index is between 0 and 20% across the entire province during summer,
while the year 2003, 2004, 2007 and 2015 observed severe drought
conditions across the region with variation from one part to the other.
The result shows that from -24.5 to -25.5 latitude, the area witnessed a
decrease in precipitation (80 to 120mm) across the time slice and an
increase in the latitude -26° to -28° S for summer seasons, which is
more prominent in the year 2041 to 2050. More so, findings from this
study showed that agricultural lands, cultivated grasslands, and barren
surfaces were influenced or impacted by drought disaster, especially in
2015, one of the drought years in Free State Province. From the feature
selection results, the influence of climate proxies and anthropogenic
factors on EVI shows the ecological situation within the study area.