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

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 footslope...

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Autores principales:	Alice Bernini, Alberto Bosino, Greg A. Botha, Michael Maerker
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	gully erosion soil erosion susceptibility maps colluvial deposit Masotcheni Formation MaxEnt Geography (General) G1-922
Acceso en línea:	https://doaj.org/article/3a0479535e7c44b9895ba830e1c71057
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spelling	oai:doaj.org-article:3a0479535e7c44b9895ba830e1c710572021-11-25T17:52:47ZEvaluation of Gully Erosion Susceptibility Using a Maximum Entropy Model in the Upper Mkhomazi River Basin in South Africa10.3390/ijgi101107292220-9964https://doaj.org/article/3a0479535e7c44b9895ba830e1c710572021-10-01T00:00:00Zhttps://www.mdpi.com/2220-9964/10/11/729https://doaj.org/toc/2220-9964Soil 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.Alice BerniniAlberto BosinoGreg A. BothaMichael MaerkerMDPI AGarticlegully erosionsoil erosionsusceptibility mapscolluvial depositMasotcheni FormationMaxEntGeography (General)G1-922ENISPRS International Journal of Geo-Information, Vol 10, Iss 729, p 729 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	gully erosion soil erosion susceptibility maps colluvial deposit Masotcheni Formation MaxEnt Geography (General) G1-922
spellingShingle	gully erosion soil erosion susceptibility maps colluvial deposit Masotcheni Formation MaxEnt Geography (General) G1-922 Alice Bernini Alberto Bosino Greg A. Botha Michael Maerker Evaluation of Gully Erosion Susceptibility Using a Maximum Entropy Model in the Upper Mkhomazi River Basin in South Africa
description	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.
format	article
author	Alice Bernini Alberto Bosino Greg A. Botha Michael Maerker
author_facet	Alice Bernini Alberto Bosino Greg A. Botha Michael Maerker
author_sort	Alice Bernini
title	Evaluation of Gully Erosion Susceptibility Using a Maximum Entropy Model in the Upper Mkhomazi River Basin in South Africa
title_short	Evaluation of Gully Erosion Susceptibility Using a Maximum Entropy Model in the Upper Mkhomazi River Basin in South Africa
title_full	Evaluation of Gully Erosion Susceptibility Using a Maximum Entropy Model in the Upper Mkhomazi River Basin in South Africa
title_fullStr	Evaluation of Gully Erosion Susceptibility Using a Maximum Entropy Model in the Upper Mkhomazi River Basin in South Africa
title_full_unstemmed	Evaluation of Gully Erosion Susceptibility Using a Maximum Entropy Model in the Upper Mkhomazi River Basin in South Africa
title_sort	evaluation of gully erosion susceptibility using a maximum entropy model in the upper mkhomazi river basin in south africa
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/3a0479535e7c44b9895ba830e1c71057
work_keys_str_mv	AT alicebernini evaluationofgullyerosionsusceptibilityusingamaximumentropymodelintheuppermkhomaziriverbasininsouthafrica AT albertobosino evaluationofgullyerosionsusceptibilityusingamaximumentropymodelintheuppermkhomaziriverbasininsouthafrica AT gregabotha evaluationofgullyerosionsusceptibilityusingamaximumentropymodelintheuppermkhomaziriverbasininsouthafrica AT michaelmaerker evaluationofgullyerosionsusceptibilityusingamaximumentropymodelintheuppermkhomaziriverbasininsouthafrica
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Evaluation of Gully Erosion Susceptibility Using a Maximum Entropy Model in the Upper Mkhomazi River Basin in South Africa

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