首页|Gully erosion mapping susceptibility in a Mediterranean environment:A hybrid decision-making model

Gully erosion mapping susceptibility in a Mediterranean environment:A hybrid decision-making model

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Gully erosion is one of the main natural hazards,especially in arid and semi-arid regions,destroying ecosystem service and human well-being.Thus,gully erosion susceptibility maps(GESM)are urgently needed for identifying priority areas on which appropriate measurements should be considered.Here,we proposed four new hybrid Machine learning models,namely weight of evidence-Multilayer Per-ceptron(MLP-WoE),weight of evidence-K Nearest neighbours(KNN-WoE),weight of evidence-Logistic regression(LR-WoE),and weight of evidence-Random Forest(RF-WoE),for mapping gully erosion exploring the opportunities of GIS tools and Remote sensing techniques in the El Ouaar water-shed located in the Souss plain in Morocco.Inputs of the developed models are composed of the dependent(i.e.,gully erosion points)and a set of independent variables.In this study,a total of 314 gully erosion points were randomly split into 70％for the training stage(220 gullies)and 30％for the validation stage(94 gullies)sets were identified in the study area.12 conditioning variables including elevation,slope,plane curvature,rainfall,distance to road,distance to stream,distance to fault,TWI,lithology,NDV1,and LU/LC were used based on their importance for gully erosion susceptibility mapping.We evaluate the performance of the above models based on the following statistical metrics:Accuracy,precision,and Area under curve(AUC)values of receiver operating characteristics(ROC).The results indicate the RF-WoE model showed good accuracy with(AUC=0.8),followed by KNN-WoE(AUC=0.796),then MLP-WoE(AUC=0.729)and LR-WoE(AUC=0.655),respectively.Gully erosion susceptibility maps provide information and valuable tool for decision-makers and planners to identify areas where urgent and appropriate interventions should be applied.

Sliman Hitouri、Mohajane Meriame、Ali Sk Ajim、Quevedo Renata Pacheco、Thong Nguyen-Huy、Pham Quoc Bao、Ismail ElKhrachy、Antonietta Varasano

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Geosciences Laboratory,Department of Geology,Faculty of Sciences,University Ibn Tofail,Kenitra,14000,Morocco

Construction Technologies Institute,National Research Council of Italy,Polo Tecnologico di San Giovanni a Teduccio,80146,Napoli,Italy

Department of Geography,Faculty of Science,Aligarh Muslim University(AMU),Aligarh,UP,202002,India

Earth Observation and Geoinformatics Division,National Institute for Space Research(INPE),Sao Jose dos Campos,Sao Paulo,12227010,Brazil

Centre for Applied Climate Sciences,University of Southern Queensland,Toowoomba,4350,QLD,Australia

Faculty of Natural Sciences,Institute of Earth Sciences,University of Silesia in Katowice,Będzińska street 60,41-200,Sosnowiec,Poland

College of Engineering,Civil Engineering Department,Najran University,Najran,66291,Saudi Arabia

ITC-CNR,Construction Technologies Institute,National Research Council,70124,Bari,Italy

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Deanship of Scientific Research at Najran University for funding this work,under the Research Groups Funding program grant c

NU/RG/SERC/12/21

2024

10.1016/j.iswcr.2023.09.008

国际水土保持研究(英文)

国际水土保持研究(英文)

ISSN：2095-6339
年,卷(期)：2024.12(2)
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