Comment on “Advective transport in heterogeneous aquifers: Are proxy models predictive?” by A. Fiori, A. Zarlenga, H. Gotovac, I. Jankovic, E. Volpi, V. Cvetkovic, and G. Dagan

Research output: Contribution to journalComment/debate

3 Citations (Scopus)

Abstract

Fiori et al. (2015) examine the predictive capabilities of (among others) two “proxy” non-Fickian transport models, MRMT (Multi-Rate Mass Transfer) and CTRW (Continuous-Time Random Walk). In particular, they compare proxy model predictions of mean breakthrough curves (BTCs) at a sequence of control planes with near-ergodic BTCs generated through two- and three-dimensional simulations of nonreactive, mean-uniform advective transport in single realizations of stationary, randomly heterogeneous porous media. The authors find fitted proxy model parameters to be nonunique and devoid of clear physical meaning. This notwithstanding, they conclude optimistically that “i. Fitting the proxy models to match the BTC at [one control plane] automatically ensures prediction at downstream control planes [and thus] ii. … the measured BTC can be used directly for prediction, with no need to use models underlain by fitting.” I show that (a) the authors' findings follow directly from (and thus confirm) theoretical considerations discussed earlier by Neuman and Tartakovsky (2009), which (b) additionally demonstrate that proxy models will lack similar predictive capabilities under more realistic, non-Markovian flow and transport conditions that prevail under flow through nonstationary (e.g., multiscale) media in the presence of boundaries and/or nonuniformly distributed sources, and/or when flow/transport are conditioned on measurements.

Original languageEnglish (US)
Pages (from-to)5701-5702
Number of pages2
JournalWater Resources Research
Volume52
Issue number7
DOIs
StatePublished - Jul 1 2016

Fingerprint

advection
breakthrough curve
aquifer
prediction
porous medium
mass transfer
simulation

Keywords

  • advection
  • convolution
  • CTRW
  • Markovian
  • nonlocality
  • transport

ASJC Scopus subject areas

  • Water Science and Technology

Cite this

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title = "Comment on “Advective transport in heterogeneous aquifers: Are proxy models predictive?” by A. Fiori, A. Zarlenga, H. Gotovac, I. Jankovic, E. Volpi, V. Cvetkovic, and G. Dagan",
abstract = "Fiori et al. (2015) examine the predictive capabilities of (among others) two “proxy” non-Fickian transport models, MRMT (Multi-Rate Mass Transfer) and CTRW (Continuous-Time Random Walk). In particular, they compare proxy model predictions of mean breakthrough curves (BTCs) at a sequence of control planes with near-ergodic BTCs generated through two- and three-dimensional simulations of nonreactive, mean-uniform advective transport in single realizations of stationary, randomly heterogeneous porous media. The authors find fitted proxy model parameters to be nonunique and devoid of clear physical meaning. This notwithstanding, they conclude optimistically that “i. Fitting the proxy models to match the BTC at [one control plane] automatically ensures prediction at downstream control planes [and thus] ii. … the measured BTC can be used directly for prediction, with no need to use models underlain by fitting.” I show that (a) the authors' findings follow directly from (and thus confirm) theoretical considerations discussed earlier by Neuman and Tartakovsky (2009), which (b) additionally demonstrate that proxy models will lack similar predictive capabilities under more realistic, non-Markovian flow and transport conditions that prevail under flow through nonstationary (e.g., multiscale) media in the presence of boundaries and/or nonuniformly distributed sources, and/or when flow/transport are conditioned on measurements.",
keywords = "advection, convolution, CTRW, Markovian, nonlocality, transport",
author = "Neuman, {Shlomo P}",
year = "2016",
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T2 - Are proxy models predictive?” by A. Fiori, A. Zarlenga, H. Gotovac, I. Jankovic, E. Volpi, V. Cvetkovic, and G. Dagan

AU - Neuman, Shlomo P

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N2 - Fiori et al. (2015) examine the predictive capabilities of (among others) two “proxy” non-Fickian transport models, MRMT (Multi-Rate Mass Transfer) and CTRW (Continuous-Time Random Walk). In particular, they compare proxy model predictions of mean breakthrough curves (BTCs) at a sequence of control planes with near-ergodic BTCs generated through two- and three-dimensional simulations of nonreactive, mean-uniform advective transport in single realizations of stationary, randomly heterogeneous porous media. The authors find fitted proxy model parameters to be nonunique and devoid of clear physical meaning. This notwithstanding, they conclude optimistically that “i. Fitting the proxy models to match the BTC at [one control plane] automatically ensures prediction at downstream control planes [and thus] ii. … the measured BTC can be used directly for prediction, with no need to use models underlain by fitting.” I show that (a) the authors' findings follow directly from (and thus confirm) theoretical considerations discussed earlier by Neuman and Tartakovsky (2009), which (b) additionally demonstrate that proxy models will lack similar predictive capabilities under more realistic, non-Markovian flow and transport conditions that prevail under flow through nonstationary (e.g., multiscale) media in the presence of boundaries and/or nonuniformly distributed sources, and/or when flow/transport are conditioned on measurements.

AB - Fiori et al. (2015) examine the predictive capabilities of (among others) two “proxy” non-Fickian transport models, MRMT (Multi-Rate Mass Transfer) and CTRW (Continuous-Time Random Walk). In particular, they compare proxy model predictions of mean breakthrough curves (BTCs) at a sequence of control planes with near-ergodic BTCs generated through two- and three-dimensional simulations of nonreactive, mean-uniform advective transport in single realizations of stationary, randomly heterogeneous porous media. The authors find fitted proxy model parameters to be nonunique and devoid of clear physical meaning. This notwithstanding, they conclude optimistically that “i. Fitting the proxy models to match the BTC at [one control plane] automatically ensures prediction at downstream control planes [and thus] ii. … the measured BTC can be used directly for prediction, with no need to use models underlain by fitting.” I show that (a) the authors' findings follow directly from (and thus confirm) theoretical considerations discussed earlier by Neuman and Tartakovsky (2009), which (b) additionally demonstrate that proxy models will lack similar predictive capabilities under more realistic, non-Markovian flow and transport conditions that prevail under flow through nonstationary (e.g., multiscale) media in the presence of boundaries and/or nonuniformly distributed sources, and/or when flow/transport are conditioned on measurements.

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