Geospatial-based analysis for soil erosion susceptibility evaluation: application of a hybrid decision model

被引:1
|
作者
Okonkwo, Chris C. [1 ]
Chukwuma, Emmanuel C. [1 ,3 ]
Orakwe, Louis C. [1 ]
Okafor, Gloria C. [2 ]
机构
[1] Nnamdi Azikiwe Univ, Fac Engn, Dept Agr & Bioresources Engn, Awka, Nigeria
[2] Nigeria Maritime Univ, Dept Meteorol & Climate Change, Okerenkoko Warri, Delta State, Nigeria
[3] Univ Pretoria, Future Africa Inst, Pretoria, South Africa
关键词
Erosion hazard; Vulnerability assessment; Geospatial analysis; Decision model; Anambra State of Nigeria; DEMATEL; LAND;
D O I
10.1007/s40808-022-01527-y
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Erosion hazard is a major environmental change in developing countries and therefore necessitates investigations for effective erosion control measures. This study is hinged on the numerous advantages of a hybrid Multi-Criteria Decision Model (MCDM) to assess erosion vulnerability using remote-sensed data and the application of Geographical Information System (GIS). Nine risk factors of erosion were selected for this study and their thematic maps were utilized to produce a spatial distribution of erosion hazard in the state. An integrated IVFRN-DEMATEL-ANP model was used to investigate the interrelationships between the risk factors and also obtain their final weights. The assessment model identified Rainfall, Erosivity Index, Stream Power Index, Sediment Transport Index, Topographic Wetness Index, and Soil as the most influential factors of erosion in the study area. The weighted linear combination method was used to integrate the risk factors to produce the spatial distribution of erosion vulnerability model. The method was validated using Anambra State of Nigeria. The findings from the study revealed that Anambra State is vulnerable to erosion hazard with 45% of the state lying between Very High and Medium vulnerable zones. A good predictive model performance of 89.7% was obtained using the AUC-ROC method. The feasibility of integrating the IVFRN, DEMATEL, and ANP models as an assessment model for mapping erosion vulnerability has been determined in this study, and this is vital in managing the impact of erosion hazards globally. The model's identification of hydrological and topographical factors as major causes of erosion hazard emphasizes the importance of critical analysis of risk factors as done in this study for effective management of erosion. This study is a veritable tool for implementation of erosion mitigation measures.
引用
收藏
页码:987 / 1007
页数:21
相关论文
共 50 条
  • [31] Evaluation of the gully erosion susceptibility by using UAV and hybrid models based on machine learning
    Wang, Qian
    Tang, Bohui
    Wang, Kailin
    Shi, Jiannan
    Li, Meiling
    SOIL & TILLAGE RESEARCH, 2024, 244
  • [32] Soil erosion assessment in Rangit catchment, India through a process-based model in the geospatial environment
    Korada, Hari Venkata Durga Rao
    Vala, Venkateshwar Rao
    GEOCARTO INTERNATIONAL, 2014, 29 (05) : 507 - 519
  • [33] Application of a Hybrid Model in Landslide Susceptibility Evaluation of the Western Tibet Plateau
    Yang, Yongpeng
    Guo, Ya
    Chen, Hao
    Tang, Hao
    Li, Meng
    Sun, Ang
    Bian, Yu
    APPLIED SCIENCES-BASEL, 2024, 14 (02):
  • [34] Spatial Decision Analysis on Soil Erosion Control Measures Research Based on GIS
    Sui, Xueyan
    Lin, Chen
    Zhou, Shenglu
    PROCEEDINGS OF THE 2012 THIRD WORLD CONGRESS ON SOFTWARE ENGINEERING (WCSE 2012), 2012, : 119 - 122
  • [35] Hillslope and point based soil erosion - an evaluation of a Landscape Evolution Model
    Hancock, G. R.
    Wells, T.
    Dever, C.
    Braggins, M.
    EARTH SURFACE PROCESSES AND LANDFORMS, 2019, 44 (05) : 1163 - 1177
  • [36] Integrating RUSLE Model with Cloud-Based Geospatial Analysis: A Google Earth Engine Approach for Soil Erosion Assessment in the Satluj Watershed
    Sud, Anshul
    Sajan, Bhartendu
    Kanga, Shruti
    Singh, Suraj Kumar
    Singh, Saurabh
    Durin, Bojan
    Kumar, Pankaj
    Meraj, Gowhar
    Sahariah, Dhrubajyoti
    Debnath, Jatan
    Chand, Kesar
    WATER, 2024, 16 (08)
  • [37] Soil erosion susceptibility prediction using ensemble hybrid models with multicriteria decision-making analysis: Case study of the Medjerda basin, northern Africa
    Bouamrane, Asma
    Boutaghane, Hamouda
    Bouamrane, Ali
    Dahri, Noura
    Abida, Habib
    Saber, Mohamed
    Kantoush, Sameh A.
    Sumi, Tetsuya
    INTERNATIONAL JOURNAL OF SEDIMENT RESEARCH, 2024, 39 (06) : 998 - 1014
  • [38] Modelling water erosion in the Sahel: application of a physically based soil erosion model in a gentle sloping environment
    Visser, SM
    Sterk, G
    Karssenberg, D
    EARTH SURFACE PROCESSES AND LANDFORMS, 2005, 30 (12) : 1547 - 1566
  • [39] An evaluation of the pesera soil erosion model and its application to a case study in Zakynthos, Greece
    Tsara, M
    Kosmas, C
    Kirkby, MJ
    Kosma, D
    Yassoglou, N
    SOIL USE AND MANAGEMENT, 2005, 21 (04) : 377 - 385
  • [40] Assessing soil erosion risk through geospatial analysis and magnetic susceptibility: A study in the Oued Ghiss dam watershed, Central Rif, Morocco
    Ed-Dakiri, Soukaina
    Etebaai, Issam
    El Moussaoui, Said
    Tawfik, Abdelhamid
    Lamgharbaj, Mustapha
    El Talibi, Hajar
    Dekkaki, Hinde Cherkaoui
    Taher, Morad
    SCIENTIFIC AFRICAN, 2024, 26