World Library  


Add to Book Shelf
Flag as Inappropriate
Email this Book

Coupled Hydrogeophysical Parameter Estimation Using a Sequential Bayesian Approach : Volume 14, Issue 3 (18/03/2010)

By Rings, J.

Click here to view

Book Id: WPLBN0003982148
Format Type: PDF Article :
File Size: Pages 12
Reproduction Date: 2015

Title: Coupled Hydrogeophysical Parameter Estimation Using a Sequential Bayesian Approach : Volume 14, Issue 3 (18/03/2010)  
Author: Rings, J.
Volume: Vol. 14, Issue 3
Language: English
Subject: Science, Hydrology, Earth
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Historic
Publication Date:
2010
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications

Citation

APA MLA Chicago

Vereecken, H., Huisman, J. A., & Rings, J. (2010). Coupled Hydrogeophysical Parameter Estimation Using a Sequential Bayesian Approach : Volume 14, Issue 3 (18/03/2010). Retrieved from http://hawaiilibrary.net/


Description
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.

Summary
Coupled hydrogeophysical parameter estimation using a sequential Bayesian approach

Excerpt
Archie, G. E.: The electrical resitivity log as an aid in determining some reservoir characteristics, American Institute of Mining and Metallurgical Engineers, 55–62, 1942.; Arulampalam, M. S., Maskell, S., Gordon, N., and Clapp, T.: A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking, IEEE T. Signal Proces., 50, 174–188, 2002.; Binley, A., Winship, P., West, L. J., Pokar, M., and Middleton, R.: Seasonal variation of moisture content in unsaturated sandstone inferred from borehole radar and resistivity profiles, J. Hydrol., 267, 160–172, 2002.; Cappe, O., Godsill, S. J., and Moulines, E.: An overview of existing methods and recent advances in sequential Monte Carlo, Proc. IEEE, 95, 899–924, doi:10.1109/JPROC.2007.893250, 2007.; Cassiani, G. and Binley, A.: Modeling unsaturated flow in a layered formation under quasi-steady state conditions using geophysical data constraints, Adv. Water Resour., 28, 467–477, 2005.; Chen, J. S., Hubbard, S. S., Rubin, Y., Murray, C., Roden, E., and Majer, E.: Geochemical characterization using geophysical data and Markov Chain Monte Carlo methods: a case study at the South Oyster bacterial transport site in Virginia, Water Resour. Res., 40, W12412, doi:10.1029/2003WR002883, 2004.; Chen, Z.: Bayesian filtering: From Kalman filters to particle filters, and beyond, Tech. rep., McMaster University, 2003.; Day-Lewis, F. D., Singha, K., and Binley, A. M.: Applying petrophysical models to radar travel time and electrical resistivity tomograms: resolution-dependent limitations, J. Geophys. Res., 110, B08206, doi:10.1029/2004JB003569, 2005.; Deiana, R., Cassiani, G., Villa, A., Bagliani, A., and Bruno, V.: Calibration of a vadose zone model using water injection monitored by GPR and electrical resistiance tomography, Vadose Zone J., 7, 215–266, 2008.; Douc, R., Cappe, O., and Moulines, E.: Comparison of Resampling Schemes for Particle Filtering, Image and Signal Processing and Analysis, 2005, 64, http://www.citebase.org/abstract?id=oai:arXiv.org:cs/0507025, 2005.; Doucet, A. and de Freitas, N.: Sequential Monte Carlo Methods in Practice, Statistics for Engineering and Information Science, Springer, 2001.; Evensen, G.: Sequential data assimilation with a nonlinear quasigeostrophic model using Monte Carlo methods to forecast error statistics, J. Geophys. Res., 99, 10143–10162, 1994.; Gordon, N. J., Salmond, D. J., and Smith, A. F. M.: Novel approach to nonlinear/non-Gaussian Bayesian state estimation, IEE Proc.-F, 140, 107–113, 1993.; Hardelauf, H., Javaux, M., Herbst, M., Gottschalk, S., Kasteel, R., Vanderborght, J., and Vereecken, H.: PARSWMS: a parallelized model for simulating three-dimensional water flow and solute transport in variably saturated soils, Vadose Zone J., 6, 255–259, 2007.; Hendricks Franssen, H. J. and Kinzelbach, W.: Real-time groundwater flow modeling with the ensemble Kalman filter: joint estimation of states and parameters and the filter inbreeding problem, Water Resour. Res., 44, W09408, doi:10.1029/2007WR006505, 2008.; Hinnell, A. C., Ferre, T. P. A., Vrugt, J. A., Huisman, J. A., Moysey, S., Rings, J., and Kowalsky, M. B.:

 

Click To View

Additional Books


  • Potential and Limitations of Multidecada... (by )
  • Using 14C and 3H to Understand Groundwat... (by )
  • A Physically Based Approach for the Esti... (by )
  • Uncertainty Analysis of a Spatially-expl... (by )
  • A Statistical Post-processor for Account... (by )
  • Forward Modeling and Validation of a New... (by )
  • A Global Water Cycle Reanalysis (2003–20... (by )
  • Regional Climate Model Data Used Within ... (by )
  • Effect of Spatial Distribution of Daily ... (by )
  • Adaptation of the Integrated Nitrogen Mo... (by )
  • Generalisation for Neural Networks Throu... (by )
  • Indirect Downscaling of Global Circulati... (by )
Scroll Left
Scroll Right

 



Copyright © World Library Foundation. All rights reserved. eBooks from Hawaii eBook Library are sponsored by the World Library Foundation,
a 501c(4) Member's Support Non-Profit Organization, and is NOT affiliated with any governmental agency or department.