A study of uncertainties in groundwater vulnerability modelling using Bayesian model averaging (BMA)-Reference-Cited by-同舟云学术

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A study of uncertainties in groundwater vulnerability modelling using Bayesian model averaging (BMA)

Published:2022-02 Issue: Volume:303 Page:114168
ISSN:0301-4797
Container-title:Journal of Environmental Management
language:en
Short-container-title:Journal of Environmental Management

Author:

Gharekhani Maryam,Nadiri Ata Allah,Khatibi Rahman,Sadeghfam Sina,Asghari Moghaddam Asghar

Funder

Iran National Science Foundation

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Waste Management and Disposal,General Medicine,Environmental Engineering

Reference55 articles.

1. DRASTIC: a Standardized System for Evaluating Ground Water Pollution Potential Using Hydrogeologic Settings;Aller,1987

2. An approach to aquifer vulnerability including uncertainty in a spatial random function framework;Armengol;J. Hydrol.,2014

3. Optimization of DRASTIC method by artificial neural network, nitrate vulnerability index, and composite DRASTIC models to assess groundwater vulnerability for unconfined aquifer of Shiraz Plain, Iran;Baghapour;J. Environ. Health Sci. Eng.,2016

4. A modified SINTACS method for groundwater vulnerability and pollution risk assessment in highly anthropized regions based on NO3- and SO42- concentrations;Busico;Sci. Total Environ.,2017

5. Prediction and structural uncertainty analyses of artificial neural networks using hierarchical Bayesian model averaging;Chitsazan;J. Hydrol.,2015

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