An improved multi-criteria decision analysis approach for watershed soil erosion susceptibility assessment

被引:0
|
作者
Aladejana, Olabanji Odunayo [1 ]
Oraegbu, Ayomide Joshua [1 ]
Fagbohun, Babatunde Joseph [1 ]
机构
[1] Fed Univ Technol Akure, Dept Remote Sensing & Geoscience Informat Syst, Akure, Ondo, Nigeria
关键词
Soil erosion; fuzzy AHP; hydrological response unit (HRU); susceptibility assessment; LOSS EQUATION; TEMPORAL VARIABILITY; WESTERN NIGERIA; SEDIMENT YIELD; RUSLE MODEL; LAND-USE; GIS; MANAGEMENT; RUNOFF; BASIN;
D O I
10.1080/10106049.2022.2136256
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Soil erosion within watersheds is a common phenomenon worldwide, and many scientific efforts have been made to address this problem. The Revised Universal Soil Loss Equation (RUSLE) model has been widely employed in soil erosion estimation. However, several studies have highlighted its limitations and the need to account for some key aspects of soil erosion which are not considered in the model. This study explores the potential of utilizing locally dominant soil erosion driving factors alongside the RUSLE model for soil erosion susceptibility assessment within the OIO watershed. Landsat 8 OLI image for the year 2020, DEM, soil data, Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) datasets coupled with field observed datasets were employed to derive these factors. They include soil loss, sediment yield, sediment transport index, and runoff. Numerical rankings that represent the level of contribution of each factor and their attributes to soil erosion within the watershed were generated using the Fuzzy Analytical Hierarchy Process (FAHP). Each factor was reclassified according to these rankings and overlaid using the GIS-based weighted overlay technique to model soil erosion within the OIO watershed. Finally, we employed a statistical combination of the modelled soil erosion map and Hydrological Response Unit (HRU) to assess erosion susceptibility within the watershed. Initial results from the study highlighted the variabilities in annual soil loss (min: < 6.0 t ha(-1) yr(-1), max: >= 58.0 t ha(-1) yr(-1), mean: 13.55 t ha(-1) yr(-1)) and identified areas with high predispositions to soil loss within the OIO watershed. The annual sediment yield of the entire OIO watershed ranged between <= 14.04 to 715.10 t ha(-1)yr(-1) with an annual average of 14.88 t ha(-1)yr(-1). In addition, the sediment transport index and runoff volume for the OIO watershed range between 0.00-69.07 and 0.00-70.00 mm, respectively. Five erosion susceptibility levels were delineated: very slight, slight, moderate, severe, and severe. They occupied 65.00%, 24.43%, 7.69%, 2.63%, and 0.23% of the watershed, respectively. Accuracy assessment conducted using the Receiver Operating Curve (ROC) showed that the soil erosion susceptibility map has an AUC value of 0.86, indicating acceptable results. Our methodological approach improves the RUSLE model, especially regarding preliminary soil susceptibility assessment for watershed development under typical data-scarce conditions.
引用
收藏
页码:17853 / 17889
页数:37
相关论文
共 50 条
  • [1] Morphometry and land cover based multi-criteria analysis for assessing the soil erosion susceptibility of the western Himalayan watershed
    Altaf, Sadaff
    Meraj, Gowhar
    Romshoo, Shakil Ahmad
    [J]. ENVIRONMENTAL MONITORING AND ASSESSMENT, 2014, 186 (12) : 8391 - 8412
  • [2] Morphometry and land cover based multi-criteria analysis for assessing the soil erosion susceptibility of the western Himalayan watershed
    Sadaff Altaf
    Gowhar Meraj
    Shakil Ahmad Romshoo
    [J]. Environmental Monitoring and Assessment, 2014, 186 : 8391 - 8412
  • [3] Incorporating probabilistic approach into local multi-criteria decision analysis for flood susceptibility assessment
    Tang, Zhongqian
    Yi, Shanzhen
    Wang, Chunhua
    Xiao, Yangfan
    [J]. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2018, 32 (03) : 701 - 714
  • [4] Incorporating probabilistic approach into local multi-criteria decision analysis for flood susceptibility assessment
    Zhongqian Tang
    Shanzhen Yi
    Chunhua Wang
    Yangfan Xiao
    [J]. Stochastic Environmental Research and Risk Assessment, 2018, 32 : 701 - 714
  • [5] A comparative assessment of multi-criteria decision analysis for flood susceptibility modelling
    Shahiri Tabarestani, Ehsan
    Afzalimehr, Hossein
    [J]. GEOCARTO INTERNATIONAL, 2022, 37 (20) : 5851 - 5874
  • [6] Spatial modeling of soil erosion risk: a multi-criteria decision-making (MCDM) approach in the paguyaman watershed, gorontalo, Indonesia
    Muhammad Ramdhan Olii
    Abdul Kadir Zailani Olii
    Aleks Olii
    Ririn Pakaya
    Bambang Agus Kironoto
    [J]. Arabian Journal of Geosciences, 2024, 17 (7)
  • [7] Soil erosion susceptibility mapping using a GIS-based multi-criteria decision approach: Case of district Chitral, Pakistan
    Aslam, Bilal
    Maqsoom, Ahsen
    Alaloul, Wesam Salah
    Musarat, Muhammad Ali
    Jabbar, Talha
    Zafar, Ahmed
    [J]. AIN SHAMS ENGINEERING JOURNAL, 2021, 12 (02) : 1637 - 1649
  • [8] Identification of soil erosion vulnerable areas in Chandrabhaga river basin: a multi-criteria decision approach
    Pal S.
    [J]. Modeling Earth Systems and Environment, 2016, 2 (1)
  • [9] National Risk Assessment in The Netherlands A Multi-Criteria Decision Analysis Approach
    Pruyt, Erik
    Wijnmalen, Diederik
    [J]. MULTIPLE CRITERIA DECISION MAKING FOR SUSTAINABLE ENERGY AND TRANSPORTATION SYSTEMS: PROCEEDINGS OF THE 19TH INTERNATIONAL CONFERENCE ON MULTIPLE CRITERIA DECISION MAKING, 2010, 634 : 133 - 143
  • [10] Flood Susceptibility Assessment in Bangladesh Using Machine Learning and Multi-criteria Decision Analysis
    Rahman, Mahfuzur
    Chen Ningsheng
    Islam, Md Monirul
    Dewan, Ashraf
    Iqbal, Javed
    Washakh, Rana Muhammad Ali
    Tian Shufeng
    [J]. EARTH SYSTEMS AND ENVIRONMENT, 2019, 3 (03) : 585 - 601