2009
DOI: 10.5194/hess-13-1399-2009
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A general real-time formulation for multi-rate mass transfer problems

Abstract: Abstract. Many flow and transport phenomena, ranging from delayed storage in pumping tests to tailing in river or aquifer tracer breakthrough curves or slow kinetics in reactive transport, display non-equilibrium (NE) behavior. These phenomena are usually modeled by non-local in time formulations, such as multi-porosity, multiple processes non equilibrium, continuous time random walk, memory functions, integro-differential equations, fractional derivatives or multirate mass transfer (MRMT), among others. We pr… Show more

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Cited by 63 publications
(53 citation statements)
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References 70 publications
(135 reference statements)
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“…Other equivalent formulations exist (Silva et al, 2009) such the fractional ADE (Benson et al, 2000;Berkowitz et al, 2002;Schumer et al, 2003), Continuous Time Random…”
Section: Non-fickian Solutions For Rtdsmentioning
confidence: 99%
See 1 more Smart Citation
“…Other equivalent formulations exist (Silva et al, 2009) such the fractional ADE (Benson et al, 2000;Berkowitz et al, 2002;Schumer et al, 2003), Continuous Time Random…”
Section: Non-fickian Solutions For Rtdsmentioning
confidence: 99%
“…Walk, Multi-Rate Mass Transfer Gouze et al, 2008;Haggerty and Gorelick, 1995), and generalized memory function approaches (Cvetkovic, 2012;Silva et al, 2009). The solution presented here is a general non-local in time formulation.…”
Section: Non-fickian Solutions For Rtdsmentioning
confidence: 99%
“…One might be tempted to use multirate models (Haggerty and Gorelick, 1995), which reproduce the effect of heterogeneity (Silva et al, 2009;Dentz et al, 2011). In fact, such models would probably capture the fast rebound of the TCA concentration when the recharge stopped, as observed in Fig.…”
Section: Tca and Ec Validationmentioning
confidence: 99%
“…MRMT models differ by the distributions of characteristic rates α i and immobile porosities ϕ i . Among the available models (Cvetkovic, 2012;Haggerty et al, 2000), we choose a uniform distribution for characteristic times (1/α i ) bounded by the two extreme rates α 1 = 1/t 1 and α N = 1/t N (t 1 < t N ) and a power-law distribution for ϕ i : The power-law distribution is consistent with observed breakthrough curves in HPM, which often display long tails that appear linear in log(c) versus log(t) Haggerty et al, 2004;Li et al, 2011;Silva et al, 2009;Willmann et al, 2008). This tailing is well modeled by a power law, such that the breakthrough concentration c evolves as c ∼ t −m .…”
Section: Multi-rate Mass Transfer Model (Mrmt)mentioning
confidence: 97%