Delimitation of groundwater zones under contamination risk using a bagged ensemble of optimized DRASTIC frameworks

被引:0
|
作者
Rahim Barzegar
Asghar Asghari Moghaddam
Jan Adamowski
Amir Hossein Nazemi
机构
[1] University of Tabriz,Department of Earth Sciences, Faculty of Natural Sciences
[2] McGill University,Department of Bioresource Engineering
[3] University of Tabriz,Department of Water Engineering, Faculty of Agriculture
关键词
Groundwater risk map; DRASTIC method; Optimization; Bagging ensemble; Iran;
D O I
暂无
中图分类号
学科分类号
摘要
Developing a reliable groundwater vulnerability and contamination risk map is very important for groundwater management and protection. This study aims to compare various modified DRASTIC vulnerability frameworks based on rate calibration using the Wilcoxon rank-sum test (WRST), frequency ratio (FR) and weight optimization using the correlation coefficient (CC), the analytic hierarchy process (AHP), and genetic algorithms (GA), as well as to introduce, for the first time, an aggregated approach based on a bagging ensemble to develop a combined modified DRASTIC model. This research was conducted in the Khoy plain, NW Iran. To develop a typical DRASTIC map, seven DRASTIC data layers were generated, weighted, and then overlaid in ArcGIS. The nitrate (NO3) concentrations at 54 sites in the study area were used to validate the models by calculating the correlation coefficient (r) between the vulnerability/risk indices and NO3 concentrations. The calculated r value for the typical DRASTIC was 0.12. A sensitivity analysis reveals that the impact of the vadose zone and conductivity parameters with mean variation indices of 22.2 and 7.5%, respectively, have the highest and lowest influence on aquifer vulnerability. The r values increased for all the optimized frameworks. The results show that the WRST and GA methods are the most effective methods for calibration and optimization of DRASTIC rates and weights, with the WRST-GA-DRASTIC model obtaining an r value of 0.64. A bagging ensemble model was employed to combine the advantages of each standalone model. The bagging ensemble model yields an r value of 0.67. The ensemble model has the potential to increase the r value further than both the standalone optimized frameworks and the typical DRASTIC approach. In terms of spatial distribution class area (%), the bagging ensemble-DRASTIC model demonstrates that the moderate and low contamination risk classes with 16.4 and 23.1% of the total area cover the lowest and highest parts of the plain.
引用
收藏
页码:8325 / 8339
页数:14
相关论文
共 50 条
  • [41] Mapping groundwater nitrate contaminant risk using the modified DRASTIC model: a case study in Ethiopia
    Alamne, Samuel B.
    Assefa, Tewodros T.
    Belay, Sisay A.
    Hussein, Misbah A.
    ENVIRONMENTAL SYSTEMS RESEARCH, 2022, 11 (01)
  • [42] Groundwater pollution risk assessment using the DRASTIC model at San Menxia Basin, Henan Province
    Lu, Xiaohui
    Zhao, Deshan
    2010 4TH INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICAL ENGINEERING (ICBBE 2010), 2010,
  • [43] Using VES and GIS-Based DRASTIC Analysis to Evaluate Groundwater Aquifer Contamination Vulnerability in Owerri, Southeastern Nigeria
    Okoli, Emeka Austin
    Akaolisa, Casmir Chukwuemeka Zanders
    Ubechu, Bridget Odochi
    Agbasi, Okechukwu Ebuka
    Szafarczyk, Anna
    ECOLOGICAL QUESTIONS, 2024, 35 (03)
  • [44] Assessing groundwater contamination risk in industrial zone of Ranipet district, Southern India: A modified DRASTIC and Fuzzy-AHP approach
    Loganathan, Sankar
    Sathiyamoorthy, Mahenthiran
    RESULTS IN ENGINEERING, 2024, 23
  • [45] Evaluation of groundwater pollution risk (GPR) from agricultural activities using DRASTIC model and GIS
    Ariffin, Sabrina Mohd
    Zawawi, Mohamed Azwan Mohamed
    Man, Hasfalina Che
    8TH IGRSM INTERNATIONAL CONFERENCE AND EXHIBITION ON GEOSPATIAL & REMOTE SENSING (IGRSM 2016), 2016, 37
  • [46] Groundwater vulnerability and contamination risk mapping of semi-arid Totko river basin, India using GIS-based DRASTIC model and AHP techniques
    Bera, Amit
    Mukhopadhyay, Bhabani Prasad
    Das, Shubhamita
    CHEMOSPHERE, 2022, 307
  • [47] Quantitative Risk Management of Groundwater Contamination by Nitrates Using Indicator Geostatistics
    Chica-Olmo, Mario
    Pardo-Iguzquiza, Eulogio
    Luque-Espinar, Antonio
    Rodriguez-Galiano, Victor
    Chica-Rivas, Lucia
    MATHEMATICS OF PLANET EARTH, 2014, : 533 - 536
  • [48] Assessing Aquifer Vulnerability Towards Contamination of Groundwater Using a New Model (DRASTIC-LU) in Parts of Ramganga Basin, India
    Fakhre Alam
    S. K. Swaroop
    S. G. Bhartariya
    Water Conservation Science and Engineering, 2025, 10 (1)
  • [49] Groundwater vulnerability and risk mapping of the Angad transboundary aquifer using DRASTIC index method in GIS environment
    Boughriba, Mimoun
    Barkaoui, Alae-eddine
    Zarhloule, Yassine
    Lahmer, Zakariae
    El Houadi, Boubker
    Verdoya, Massimo
    ARABIAN JOURNAL OF GEOSCIENCES, 2010, 3 (02) : 207 - 220
  • [50] Groundwater pollution risk mapping using modified DRASTIC model in parts of Hail region of Saudi Arabia
    Ahmed, Izrar
    Nazzal, Yousef
    Zaidi, Faisal
    ENVIRONMENTAL ENGINEERING RESEARCH, 2018, 23 (01) : 84 - 91