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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
Author(s) -
Neuman Shlomo P.
Publication year - 2016
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1002/2016wr019093
Subject(s) - proxy (statistics) , advection , continuous time random walk , porous medium , random walk , statistical physics , mathematics , aquifer , mechanics , geology , thermodynamics , statistics , porosity , physics , geotechnical engineering , groundwater
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.