Evaluation of Gully Erosion Susceptibility Using a Maximum Entropy Model in the Upper Mkhomazi River Basin in South Africa

Abstract

Soil erosion is one of the most challenging environmental issues in the world, causing unsustainable soil loss every year. In South Africa, several episodes of gully erosion have been documented and clearly linked to the presence of Quaternary colluvial deposits on the Drakensberg Mountain footslopes. The aim of this study was to identify and assess the triggering factors of gully erosion in the upper Mkhomazi River basin in KwaZulu-Natal, South Africa. We compiled a gully inventory map and applied remote sensing techniques as well as field surveys to validate the gully inventory. The gullies were subdivided into slope gullies and fluvial gullies. We derived susceptibility maps based on the spatial distribution of gully types to assess the most important driving factors. A stochastic modeling approach (MaxEnt) was applied, and the results showed two susceptibility maps within the spatial distribution of the gully erosion probability. To validate the MaxEnt model results, a subset of the existing inventory map was used. Additionally, by using areas with high susceptibilities, we were able to delineate previously unmapped colluvial deposits in the region. This predictive mapping tool can be applied to provide a theoretical basis for highlighting erosion-sensitive substrates to reduce the risk of expanding gully erosion.

Intersecting views of gully erosion in South Africa

“…As a result, spatial coverage increased compared to aerial imagery, albeit at medium spatial resolution only. More recently, the advancements in geographic information system (GIS) environments allowed the integration of several remotely sensed datasets in a singular environment (Bernini et al, 2021; Grellier et al, 2012; Kakembo et al, 2009; Le Roux & Van der Waal, 2020; Makaya, Mutanga, et al, 2019; Mararakanye & Sumner, 2017; Olivier, 2013; Olivier et al, 2018; Seutloali et al, 2016). Introducing more variables restricted the studies to shorter temporal scales but allowed more complex efforts to understand gully occurrence (Bernini et al, 2021; Le Roux & Sumner, 2012; Mararakanye & Le Roux, 2012; Mararakanye & Nethengwe, 2012; Olivier et al, 2016; Seutloali et al, 2016).…”

“…Topographic variables are frequently combined with imagery in a GIS environment (Grellier et al, 2012; Kakembo et al, 2009; Makaya, Mutanga, et al, 2019; Mararakanye & Sumner, 2017; Olivier, 2013; Olivier et al, 2018; Seutloali et al, 2016). Although other physiographic factors were used less often initially, more recently, they have been used more prominently, for example, geological (Bernini et al, 2021; Le Roux & Sumner, 2012; Mararakanye & Sumner, 2017), soil (Mararakanye & Sumner, 2017; Seutloali et al, 2016), land‐use/cover (Bernini et al, 2021; Du Plessis et al, 2020; Le Roux & Sumner, 2013), climate (Mararakanye & Sumner, 2017), and vegetation data (Bernini et al, 2021; Mararakanye, 2015). Topographic variables were mainly derived from single‐date DEMs and applied as a general exploratory measure to derive causes of gully occurrence.…”

“…Slope gradient was widely used (Kakembo et al, 2009; Olivier et al, 2016; Seutloali et al, 2016), primarily as classes to determine where gully features were located, and were not specifically related to gully morphology features (e.g., gully head, floor, or outlet). Other commonly used topographic indices include contributing catchment area above gully heads (Grellier et al, 2012; Mararakanye & Sumner, 2017), curvature (Bernini et al, 2021; Chaplot, 2013), stream power index (Chaplot, 2013; Kakembo et al, 2009; Mararakanye, 2015; Mararakanye & Sumner, 2017), and topographic wetness index (Chaplot, 2013; Mararakanye, 2015; Mararakanye & Sumner, 2017). More specific uses of DEMs and topographic variables, such as soil loss quantification from DEM‐of‐difference (Flügel et al, 1999) or investigating gully wall retreat (Chaplot, 2013; Podwojewski et al, 2020), were rare.…”

Impact of Overgrazing on Diffuse and Concentrated Erosion: Case Study in the Sloping Lands of South Africa

“…Linear erosion and especially deep gullies, locally termed 'dongas', are a main concern in South Africa because of their number [17][18][19][20][21] and because they pose severe constraints on the agricultural use of land by rendering much of the farmland inaccessible. Dongas mainly affect steep slope areas dedicated to rangeland [22].…”

“…Dongas mainly affect steep slope areas dedicated to rangeland [22]. Despite there being numerous studies on gully erosion that have provided information on gully occurrence (e.g., [21]), there is limited quantitative information on the amount of erosion involved. Dongas are associated with the presence of certain parent materials [19], such as unconsolidated colluvions associated with high sodium contents [23,24], and erode easily [20].…”