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Coupled Hydrogeophysical Parameter Estimation Using a Sequential Bayesian Approach : Volume 6, Issue 5 (15/10/2009)

By Rings, J.

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Book Id: WPLBN0003989597
Format Type: PDF Article :
File Size: Pages 38
Reproduction Date: 2015

Title: Coupled Hydrogeophysical Parameter Estimation Using a Sequential Bayesian Approach : Volume 6, Issue 5 (15/10/2009)  
Author: Rings, J.
Volume: Vol. 6, Issue 5
Language: English
Subject: Science, Hydrology, Earth
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


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Vereecken, H., Huisman, J. A., & Rings, J. (2009). Coupled Hydrogeophysical Parameter Estimation Using a Sequential Bayesian Approach : Volume 6, Issue 5 (15/10/2009). Retrieved from

Description: ICG 4 – Agrosphere, Forschungszentrum Jülich, Germany. Coupled hydrogeophysical methods infer hydrological and petrophysical parameters directly from geophysical measurements. Widespread methods do not explicitly recognize uncertainty in parameter estimates. Therefore, we apply a sequential Bayesian framework that provides updates of state, parameters and their uncertainty whenever measurements become available. We have coupled a hydrological and an electrical resistivity tomography (ERT) forward code in a particle filtering framework. First, we analyze a synthetic data set of lysimeter infiltration monitored with ERT. In a second step, we apply the approach to field data measured during an infiltration event on a full-scale dike model. For the synthetic data, the water content distribution and the hydraulic conductivity are accurately estimated after a few time steps. For the field data, hydraulic parameters are successfully estimated from water content measurements made with spatial time domain reflectometry and ERT, and the development of their posterior distributions is shown.

Coupled hydrogeophysical parameter estimation using a sequential Bayesian approach

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