Susceptibility to Gully Erosion: Applying Random Forest (RF) and Frequency Ratio (FR) Approaches to a Small Catchment in Ethiopia

Soil erosion by gullies in Ethiopia is causing environmental and socioeconomic problems. A sound soil and water management plan requires accurately predicted gully erosion hotspot areas. Hence, this study develops a gully erosion susceptibility map (GESM) using frequency ratio (FR) and random forest (RF) algorithms. A total of 56 gullies were surveyed, and their extents were derived by digitizing Google Earth imagery. Literature review and a multicollinearity test resulted in 14 environmental variables for the final analysis. Model prediction potential was evaluated using the area under the curve (AUC) method. Results showed that the best prediction accuracy using the FR and RF models was obtained by using the top four most important gully predictor factors: drainage density, elevation, land use, and groundwater table. The notion that the groundwater table is one of the most important gully predictor factors in Ethiopia is a novel and significant quantifiable finding and is critical to the design of effective watershed management plans. Results from separate variable importance analyses showed land cover for Nitisols and drainage density for Vertisols as leading factors determining gully locations. Factors such as texture, stream power index, convergence index, slope length, and plan and profile curvatures were found to have little significance for gully formation in the studied catchment. View Full-Text

Saved in:
Bibliographic Details
Main Authors: Amare, Selamawit, Langendoen, Eddy, Keesstra, Saskia, Ploeg, Martine Van Der, Gelagay, Habtamu, Lemma, Hanibal, van der Zee, Sjoerd E.A.T.M.
Format: Article/Letter to editor biblioteca
Language:English
Subjects:Ethiopian highlands, Groundwater table, Gully erosion mapping, Nitisols, Soil type, Vertisols,
Online Access:https://research.wur.nl/en/publications/susceptibility-to-gully-erosion-applying-random-forest-rf-and-fre
Tags: Add Tag
No Tags, Be the first to tag this record!
id dig-wur-nl-wurpubs-577535
record_format koha
spelling dig-wur-nl-wurpubs-5775352024-12-04 Amare, Selamawit Langendoen, Eddy Keesstra, Saskia Ploeg, Martine Van Der Gelagay, Habtamu Lemma, Hanibal van der Zee, Sjoerd E.A.T.M. Article/Letter to editor Water 13 (2021) 2 ISSN: 2073-4441 Susceptibility to Gully Erosion: Applying Random Forest (RF) and Frequency Ratio (FR) Approaches to a Small Catchment in Ethiopia 2021 Soil erosion by gullies in Ethiopia is causing environmental and socioeconomic problems. A sound soil and water management plan requires accurately predicted gully erosion hotspot areas. Hence, this study develops a gully erosion susceptibility map (GESM) using frequency ratio (FR) and random forest (RF) algorithms. A total of 56 gullies were surveyed, and their extents were derived by digitizing Google Earth imagery. Literature review and a multicollinearity test resulted in 14 environmental variables for the final analysis. Model prediction potential was evaluated using the area under the curve (AUC) method. Results showed that the best prediction accuracy using the FR and RF models was obtained by using the top four most important gully predictor factors: drainage density, elevation, land use, and groundwater table. The notion that the groundwater table is one of the most important gully predictor factors in Ethiopia is a novel and significant quantifiable finding and is critical to the design of effective watershed management plans. Results from separate variable importance analyses showed land cover for Nitisols and drainage density for Vertisols as leading factors determining gully locations. Factors such as texture, stream power index, convergence index, slope length, and plan and profile curvatures were found to have little significance for gully formation in the studied catchment. View Full-Text en application/pdf https://research.wur.nl/en/publications/susceptibility-to-gully-erosion-applying-random-forest-rf-and-fre 10.3390/w13020216 https://edepot.wur.nl/540038 Ethiopian highlands Groundwater table Gully erosion mapping Nitisols Soil type Vertisols https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0/ Wageningen University & Research
institution WUR NL
collection DSpace
country Países bajos
countrycode NL
component Bibliográfico
access En linea
databasecode dig-wur-nl
tag biblioteca
region Europa del Oeste
libraryname WUR Library Netherlands
language English
topic Ethiopian highlands
Groundwater table
Gully erosion mapping
Nitisols
Soil type
Vertisols
Ethiopian highlands
Groundwater table
Gully erosion mapping
Nitisols
Soil type
Vertisols
spellingShingle Ethiopian highlands
Groundwater table
Gully erosion mapping
Nitisols
Soil type
Vertisols
Ethiopian highlands
Groundwater table
Gully erosion mapping
Nitisols
Soil type
Vertisols
Amare, Selamawit
Langendoen, Eddy
Keesstra, Saskia
Ploeg, Martine Van Der
Gelagay, Habtamu
Lemma, Hanibal
van der Zee, Sjoerd E.A.T.M.
Susceptibility to Gully Erosion: Applying Random Forest (RF) and Frequency Ratio (FR) Approaches to a Small Catchment in Ethiopia
description Soil erosion by gullies in Ethiopia is causing environmental and socioeconomic problems. A sound soil and water management plan requires accurately predicted gully erosion hotspot areas. Hence, this study develops a gully erosion susceptibility map (GESM) using frequency ratio (FR) and random forest (RF) algorithms. A total of 56 gullies were surveyed, and their extents were derived by digitizing Google Earth imagery. Literature review and a multicollinearity test resulted in 14 environmental variables for the final analysis. Model prediction potential was evaluated using the area under the curve (AUC) method. Results showed that the best prediction accuracy using the FR and RF models was obtained by using the top four most important gully predictor factors: drainage density, elevation, land use, and groundwater table. The notion that the groundwater table is one of the most important gully predictor factors in Ethiopia is a novel and significant quantifiable finding and is critical to the design of effective watershed management plans. Results from separate variable importance analyses showed land cover for Nitisols and drainage density for Vertisols as leading factors determining gully locations. Factors such as texture, stream power index, convergence index, slope length, and plan and profile curvatures were found to have little significance for gully formation in the studied catchment. View Full-Text
format Article/Letter to editor
topic_facet Ethiopian highlands
Groundwater table
Gully erosion mapping
Nitisols
Soil type
Vertisols
author Amare, Selamawit
Langendoen, Eddy
Keesstra, Saskia
Ploeg, Martine Van Der
Gelagay, Habtamu
Lemma, Hanibal
van der Zee, Sjoerd E.A.T.M.
author_facet Amare, Selamawit
Langendoen, Eddy
Keesstra, Saskia
Ploeg, Martine Van Der
Gelagay, Habtamu
Lemma, Hanibal
van der Zee, Sjoerd E.A.T.M.
author_sort Amare, Selamawit
title Susceptibility to Gully Erosion: Applying Random Forest (RF) and Frequency Ratio (FR) Approaches to a Small Catchment in Ethiopia
title_short Susceptibility to Gully Erosion: Applying Random Forest (RF) and Frequency Ratio (FR) Approaches to a Small Catchment in Ethiopia
title_full Susceptibility to Gully Erosion: Applying Random Forest (RF) and Frequency Ratio (FR) Approaches to a Small Catchment in Ethiopia
title_fullStr Susceptibility to Gully Erosion: Applying Random Forest (RF) and Frequency Ratio (FR) Approaches to a Small Catchment in Ethiopia
title_full_unstemmed Susceptibility to Gully Erosion: Applying Random Forest (RF) and Frequency Ratio (FR) Approaches to a Small Catchment in Ethiopia
title_sort susceptibility to gully erosion: applying random forest (rf) and frequency ratio (fr) approaches to a small catchment in ethiopia
url https://research.wur.nl/en/publications/susceptibility-to-gully-erosion-applying-random-forest-rf-and-fre
work_keys_str_mv AT amareselamawit susceptibilitytogullyerosionapplyingrandomforestrfandfrequencyratiofrapproachestoasmallcatchmentinethiopia
AT langendoeneddy susceptibilitytogullyerosionapplyingrandomforestrfandfrequencyratiofrapproachestoasmallcatchmentinethiopia
AT keesstrasaskia susceptibilitytogullyerosionapplyingrandomforestrfandfrequencyratiofrapproachestoasmallcatchmentinethiopia
AT ploegmartinevander susceptibilitytogullyerosionapplyingrandomforestrfandfrequencyratiofrapproachestoasmallcatchmentinethiopia
AT gelagayhabtamu susceptibilitytogullyerosionapplyingrandomforestrfandfrequencyratiofrapproachestoasmallcatchmentinethiopia
AT lemmahanibal susceptibilitytogullyerosionapplyingrandomforestrfandfrequencyratiofrapproachestoasmallcatchmentinethiopia
AT vanderzeesjoerdeatm susceptibilitytogullyerosionapplyingrandomforestrfandfrequencyratiofrapproachestoasmallcatchmentinethiopia
_version_ 1819144391502069760