Next Article in Journal
Fuzzy Solution to the Unconfined Aquifer Problem
Next Article in Special Issue
Characterization of Hydraulic Heterogeneity of Alluvial Aquifer Using Natural Stimuli: A Field Experience of Northern Italy
Previous Article in Journal
The Impact of Training Data Sequence on the Performance of Neuro-Fuzzy Rainfall-Runoff Models with Online Learning
Previous Article in Special Issue
Applying 3D Geostatistical Simulation to Improve the Groundwater Management Modelling of Sedimentary Aquifers: The Case of Doñana (Southwest Spain)
Article Menu
Issue 1 (January) cover image

Export Article

Open AccessArticle
Water 2019, 11(1), 53; https://doi.org/10.3390/w11010053

Upscaling Mixing in Highly Heterogeneous Porous Media via a Spatial Markov Model

1
Department of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, IN 46556, USA
2
Division of Hydrologic Sciences, Desert Research Institute, Reno, NV 89512, USA
3
Dipartimento Ingegneria Civile ed Ambientale Politecnico di Milano, Piazza L. Da Vinci, 32, 20133 Milano, Italy
*
Author to whom correspondence should be addressed.
Received: 1 December 2018 / Revised: 19 December 2018 / Accepted: 24 December 2018 / Published: 29 December 2018
(This article belongs to the Special Issue Heterogeneous Aquifer Modeling: Closing the Gap)
  |  
PDF [13267 KB, uploaded 30 December 2018]
  |     |  

Abstract

In this work, we develop a novel Lagrangian model able to predict solute mixing in heterogeneous porous media. The Spatial Markov model has previously been used to predict effective mean conservative transport in flows through heterogeneous porous media. In predicting effective measures of mixing on larger scales, knowledge of only the mean transport is insufficient. Mixing is a small scale process driven by diffusion and the deformation of a plume by a non-uniform flow. In order to capture these small scale processes that are associated with mixing, the upscaled Spatial Markov model must be extended in such a way that it can adequately represent fluctuations in concentration. To address this problem, we develop downscaling procedures within the upscaled model to predict measures of mixing and dilution of a solute moving through an idealized heterogeneous porous medium. The upscaled model results are compared to measurements from a fully resolved simulation and found to be in good agreement. View Full-Text
Keywords: heterogeneous porous media; upscaling; mixing; dilution heterogeneous porous media; upscaling; mixing; dilution
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Wright, E.E.; Sund, N.L.; Richter, D.H.; Porta, G.M.; Bolster, D. Upscaling Mixing in Highly Heterogeneous Porous Media via a Spatial Markov Model. Water 2019, 11, 53.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Water EISSN 2073-4441 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top