Untitled

Mishra, Aakanksha; Gutjahr, Allan L.

doi:10.1023/a:1007520716287

Mathematical Geology

1999

DOI: 10.1023/a:1007520716287

|View full text |Cite

Untitled

Aakanksha Mishra

Allan L. Gutjahr

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2007

Publication Types

Select...

Other1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Markov models and the ensemble Kalman filter for estimation of sorption rates.

Vugrin¹,

McKenna

Vugrin³

2007

View full text Add to dashboard Cite

Non-equilibrium sorption of contaminants in ground water systems is examined from the perspective of sorption rate estimation. A previously developed Markov tran-3 sition probability model for solute transport is used in conjunction with a new conditional probability-based model of the sorption and desorption rates based on breakthrough curve data. Two models for prediction of spatially varying sorption and desorption rates along a one-dimensional streamline are developed. These models are a Markov model that utilizes conditional probabilities to determine the rates and an ensemble Kalman filter (EnKF) applied to the conditional probability method. Both approaches rely on a previously developed Markov-model of mass transfer, and both models assimilate the observed concentration data into the rate estimation at each observation time. Initial values of the rates are perturbed from the true values to form ensembles of rates and the ability of both estimation approaches to recover the true rates is examined over three different sets of perturbations. The models accurately estimate the rates when the mean of the perturbations are zero, the unbiased case. For the cases containing some bias, addition of the ensemble Kalman filter is shown to improve accuracy of the rate estimation by as much as an order of magnitude.4

show abstract

Markov models and the ensemble Kalman filter for estimation of sorption rates.

Vugrin¹,

McKenna

Vugrin³

2007

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Untitled

Cited by 1 publication

References 12 publications

Markov models and the ensemble Kalman filter for estimation of sorption rates.

Markov models and the ensemble Kalman filter for estimation of sorption rates.

Contact Info

Product

Resources

About