A new framework for experimental design using Bayesian Evidential Learning: the case of wellhead protection area (2021-05-12T00:00:00.000000Z)

TL;DR

This work aims to make stochastic predictions of the WHPA within the Bayesian Evidential Learning (BEL) framework, which aims to find a direct relationship between predictor and target using machine learning.

Authors

Robin Thibaut

2 papers

E. Laloy

2 papers

T. Hermans

2 papers

TL;DR

Authors

References69 items

Deep generative models in inversion: The impact of the generator's nonlinearity and development of a new approach based on a variational autoencoder

Direct forecasting of global and spatial model parameters from dynamic data

Improving BEL1D accuracy for geophysical imaging of the subsurface

Optimal Bayesian experimental design for subsurface flow problems

Bayesian Model Averaging With Fixed and Flexible Priors: Theory, Concepts, and Calibration Experiments for Rainfall‐Runoff Modeling

Improving the accuracy of 1D surface nuclear magnetic resonance surveys using the multi-central-loop configuration

A Monte Carlo-based framework for assessing the value of information and development risk in geothermal exploration

Automated Monte Carlo-based quantification and updating of geological uncertainty with borehole data (AutoBEL v1.0)

Seismic Bayesian evidential learning: estimation and uncertainty quantification of sub-resolution reservoir properties

1D geological modeling of the subsurface from geophysical data with Bayesian Evidential Learning

Bayesian evidential learning: a field validation using push-pull tests

Hydrogeology: Groundwater Science and Engineering

Surrogate‐Based Bayesian Inverse Modeling of the Hydrological System: An Adaptive Approach Considering Surrogate Approximation Error

Quantifying Uncertainty in Subsurface Systems

Uncertainty Quantification of Medium‐Term Heat Storage From Short‐Term Geophysical Experiments Using Bayesian Evidential Learning

FloPy: Python Package for Creating, Running, and Post-Processing MODFLOW-Based Models

On uncertainty quantification in hydrogeology and hydrogeophysics

Prediction‐Focused Approaches: An Opportunity for Hydrology

Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

Direct prediction of spatially and temporally varying physical properties from time‐lapse electrical resistance data

Optimal observation network design for conceptual model discrimination and uncertainty reduction

Advances in Combinatorial Optimization - Linear Programming Formulations of the Traveling Salesman and Other Hard Combinatorial Optimization Problems

Robust optimization of well location to enhance hysteretical trapping of CO2: Assessment of various uncertainty quantification methods and utilization of mixed response surface surrogates

A review of surrogate models and their application to groundwater modeling

On the optimal design of experiments for conceptual and predictive discrimination of hydrologic system models

Pyrcca: Regularized Kernel Canonical Correlation Analysis in Python and Its Applications to Neuroimaging

Prediction-Focused Subsurface Modeling: Investigating the Need for Accuracy in Flow-Based Inverse Modeling

Efficient Bayesian experimental design for contaminant source identification

Multiple-point Geostatistics: Stochastic Modeling with Training Images

Uncertainty in training image‐based inversion of hydraulic head data constrained to ERT data: Workflow and case study

Direct forecasting of subsurface flow response from non-linear dynamic data by linear least-squares in canonical functional principal component space

Efficient posterior exploration of a high‐dimensional groundwater model from two‐stage Markov chain Monte Carlo simulation and polynomial chaos expansion

Multiscale-finite-element-based ensemble Kalman filter for large-scale groundwater flow

On Tools

Review of surrogate modeling in water resources

Bayesian analysis of data-worth considering model and parameter uncertainties

Bayesian assessment of the expected data impact on prediction confidence in optimal sampling design

Impact of hydrogeological data on measures of uncertainty, site characterization and environmental performance metrics

High‐dimensional posterior exploration of hydrologic models using multiple‐try DREAM(ZS) and high‐performance computing

Statistical Data Analysis: A Practical Guide

Pumping optimization of coastal aquifers based on evolutionary algorithms and surrogate modular neural network models

Applied Geostatistics with SGeMS: A User's Guide

Combining multiobjective optimization and Bayesian model averaging to calibrate forecast ensembles of soil hydraulic models

Inverse groundwater modeling for hydraulic conductivity estimation using Bayesian model averaging and variance window

Treatment of uncertainty using ensemble methods: Comparison of sequential data assimilation and Bayesian model averaging

Stochastic management of pump-and-treat strategies using surrogate functions

Optimal groundwater remediation design using an Adaptive Neural Network Genetic Algorithm

Metamodelling: Theory, concepts and application to nitrate leaching modelling

Using Bayesian Model Averaging to Calibrate Forecast Ensembles

Inverse problem theory - and methods for model parameter estimation

Image quality assessment: from error visibility to structural similarity

Level set methods and dynamic implicit surfaces

Gradual Deformation and Iterative Calibration of Sequential Stochastic Simulations

A new family of power transformations to improve normality or symmetry

A fast marching level set method for monotonically advancing fronts.

A modified Hausdorff distance for object matching

SKBEL – Bayesian Evidential Learning framework built on top of scikit-learn

MODFLOW-2005: USGS three-dimensional finite-difference groundwater model

Markov chain Monte Carlo simulation using the DREAM software package: Theory, concepts, and MATLAB implementation

MT3D-USGS: Groundwater Solute Transport Simulator for MODFLOW

MODPATH: A particle-tracking model for MODFLOW. U.S. Geological Survey

Inverse methods in hydrogeology: Evolution and recent trends

Machine learning: a probabilistic perspective, Adaptive computation and machine learning series

Multimodel Bayesian analysis of data-worth applied to unsaturated fractured tuffs

Delineation of spring protection zones

The traveling salesman problem and its variations, Combinatorial optimization

Constrained Global Optimization of Expensive Black Box Functions Using Radial Basis Functions

Geostatistics for natural resources evaluation, Applied geostatistics series

well number 6, constantly showing low-bounds and narrow IQR

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