Abstract:
Soil erosion is a global challenge that threatens ecological functionality. The need for
better soil conservation practices keeps growing due to the twin challenges of
climate change and population growth. However, effective soil erosion management
solutions remain elusive to practitioners due to the complexity of the soil erosion
process. This is especially true for mountainous tropical regions which experience
rainfall as high intensity thunderstorms accompanied by gusts of wind. Therefore, the
aim of this research was to analyse soil erodibility and rainfall erosivity on the
Soutpansberg range to establish the characteristics of the factors that influence soil
erosion. The specific objectives were to classify geomorphic features of the
Soutpansberg range; to characterise the spatial-temporal aspects of potentially
erosive rainfall; to assess the influence of topography on wind speed and rainfall
erosivity; and to compare rainfall erosivity derived from the USLE and the SLEMSA
incorporating WDR erosivity.
The classification of geomorphic features needed soil, hydrology, slope, geology and
land-use-land-cover data. Soil data were obtained from the Harmonised World Soil
Database (HWSD v 1.21) layer downloaded from The International Institute for
Applied Systems Analysis (IIASA) online database. Additional soil data were
obtained from field samples and splash cups. Hydrological data were downloaded
from Department of Water Affairs, Forestry and Fisheries (DWAFF) website. Slope
data were derived from the 30m pixel size SRTM DEM obtained from National Geo-
Spatial Information (NGI). Geological data were downloaded from South African
Geosciences online database. Land-use-land-cover were extracted from the South
African National Land Cover 2018 dataset accessed online on the Department of
Forestry, Fisheries and Environment website. Rainfall and wind speed data for the
spatial-temporal characterisation of rainfall from 2000 to 2019 were obtained from
the South African Weather Services.
The data analysis followed different tools. Erodibility was assessed using GIS tools
to combine the five factors to create a final soil erodibility map. Potentially erosive
rainfall spatial-temporal characterisation section was done using spatial GIS
interpolation and spatial autocorrelation. Spatial interpolation was achieved through
co-kriging. Spatial autocorrelation was determined by the fusion of the coefficient of
variation and the Moran’s I. The influence of topography on wind speed and rainfall
erosivity was analysed through a Likert scale, simple linear regression and
MANOVA. Finally, simple regression analysis and simple comparison were
employed to establish the influence of wind on rainfall erosivity. This was treated
from the wind free rain (WFR) and wind driven rain (WDR) perspective. The analysis
produced the following results.
The geomorphic classification for erodibility was based on intrinsic erodibility,
landform position, slope position, geological setting as well as rain exposure. The
factors operate on fourteen soil types found on the Soutpansberg range that fall into
five granulometric groups. The erodibility maps for both USLE and SLEMSA, a result
of a weighted sum overlay of all the erodibility factors, show high to very high
erodibility on the south facing slopes of the mountain range. A large part of the range
Analysis of Soil Erodibility and Rainfall Erosivity on the Soutpansberg Range, Limpopo Province, South Africa
on the western part of the mountain range is classified as of very low erodibility in the
SLEMSA method.
The spatial-temporal characterisation indicates that rainfall on the Soutpansberg
Range is very highly variable. The potentially erosive rainfall distribution is spatially
dependent on the mountain range and the spatial variation mostly simple. Most
rainfall is concentrated in the central areas of the south facing slope. The epicentre is
located at elevations above 1200 m.a.s.l. However, rain days are dominated by
medium spatial variability.
The spatio-temporal characterisation mapping indicates that flash flood hotspots are
in low to very low rainfall regions. This implies that high erosion areas are not
defined by total rainfall amounts only because the temporal distribution of the rainfall
is also important. Furthermore, the simple linear regression analysis revealed that
elevation influences erosivity. In addition, hypothesis tests showed that wind speed
and topography increase rainfall erosivity. Empirical data confirm that WFR and
WDR erosivity are different. Wind Driven Rain computations where wind is above 2
m/s1 produce results similar to samples collected from splash cups.
The research concludes that a deep understanding of the factors controlling soil
erodibility is the foundation of effective erosion control. The soils’ intrinsic
characteristics and raindrop exposure (represented by land use and land cover)
explains more of variation in soil loss on the Soutpansberg mountain range.
Furthermore, the mountain setting causes rainfall to be concentrated on the central
south facing slopes at elevations above 1000 m.a.s.l. sending the very low
potentially erosive rain zone to the western region of the mountain range. However,
the highest peak of the mountain is in the western region.
Erosion hazard potential is not confined to high rainfall zones only. Potentially
erosive rainfall hotspots are located in low and very low rainfall zones. Furthermore,
rainfall erosivity is not a function of rainfall amount only because topography
increases both wind speed and rainfall erosivity. However, rainfall amount and wind
speed are not correlated, and wind speed is not implied in rainfall amount.
Nonetheless, wind speed is correlated with rainfall erosivity. Wind speed above
2m/s-1 increases rainfall erosivity. therefore, wind driven rain (WDR) erosivity is a
better representation of rainfall energy than wind free rain (WFR).
The research recommends soil erosion management approaches that also consider
rainfall temporal distribution. In addition, further studies on rainfall spatial distribution
need to be done using satellite-based rainfall data for more accuracy. Additional
research on rainfall erosivity considering rainfall temporal distribution is necessary to
identify erosion hazard zones. Intensive and extensive research on incorporating
wind speed in the computation of rainfall erosivity can improve soil erosion
estimation models.
Analysis of Soil Erodibility and Rainfall Erosivity on the Soutpansberg Range, Limpopo Province, South Africa