Analysis of soil erodability and rainfall erosivity on the Soutpansberg Range, Limpopo Province, South Africa

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