On the relationship between indicators of geostatistical, flow and transport connectivity

Knudby, Christen; Carrera, Jesús

doi:10.1016/j.advwatres.2004.09.001

Cited by 265 publications

(281 citation statements)

References 64 publications

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“…In Case C, the variations are even larger than in Case D, which is a result of a better connectivity between aquifer and streambed. We used the transport connectivity indicator CT 1 by Knudby and Carrera (2005) to analyse the relation between connectivity and discharge variations. CT 1 was defined by Knudby and Carrera (2005) as the ratio between the average arrival time t AVE of a solute travelling through the model domain and the time t 5 at which 5% of the solute has arrived.…”

Section: Resultsmentioning

confidence: 99%

Influence of aquifer and streambed heterogeneity on the distribution of groundwater discharge

Kalbus

Schmidt

Molson

et al. 2009

Hydrol. Earth Syst. Sci.

119

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Abstract. The spatial distribution of groundwater fluxes through a streambed can be highly variable, most often resulting from a heterogeneous distribution of aquifer and streambed permeabilities along the flow pathways. Using a groundwater flow and heat transport model, we defined four scenarios of aquifer and streambed permeability distributions to simulate and assess the impact of subsurface heterogeneity on the distribution of groundwater fluxes through the streambed: (a) a homogeneous low-K streambed within a heterogeneous aquifer; (b) a heterogeneous streambed within a homogeneous aquifer; (c) a well connected heterogeneous low-K streambed within a heterogeneous aquifer; and (d) a poorly connected heterogeneous low-K streambed within a heterogeneous aquifer. The simulation results were compared with a base case scenario, in which the streambed had the same properties as the aquifer, and with observed data. The results indicated that the aquifer has a stronger influence on the distribution of groundwater fluxes through the streambed than the streambed itself. However, a homogeneous low-K streambed, a case often implemented in regional-scale groundwater flow models, resulted in a strong homogenization of fluxes, which may have important implications for the estimation of peak mass flows. The flux distributions simulated with heterogeneous low-K streambeds were similar to the flux distributions of the base case sceCorrespondence to: E. Kalbus (edda.kalbus@web.de) nario, despite the lower permeability. The representation of heterogeneous distributions of aquifer and streambed properties in the model has been proven to be beneficial for the accuracy of flow simulations.

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Section: Resultsmentioning

confidence: 99%

Influence of aquifer and streambed heterogeneity on the distribution of groundwater discharge

Kalbus

Schmidt

Molson

et al. 2009

Hydrol. Earth Syst. Sci.

119

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show abstract

“…To analyze the effect of connectivity on risk, this section categorizes risk simulations in terms of a dynamic connectivity metric. The chosen connectivity metric CI is defined as the ratio of the effective hydraulic conductivity, K eff , to the geometric mean of K, K G [Knudby and Carrera, 2005],…”

Section: Impact Of Connectivitymentioning

confidence: 99%

“…In this context, the variability of the hydraulic properties typically leads to preferential flow channels and lowpermeability areas where contaminants can be temporarily trapped by rate-limited mass transfer [e.g., Gomez-Hernandez and Wen, 1998;Zinn and Harvey, 2003;Bianchi et al, 2011]. The formation of these fast flow channels is typically associated with the presence of well-connected, highly permeable geological bodies or structures that can concentrate flow and solute transport [e.g., Knudby and Carrera, 2005; Incorporating hydrogeological uncertainty in human health predictions has been a topic of intense research in the past [e.g., Andričević and Cvetković, 1996;de Barros and Rubin, 2008;Cvetković and Molin, 2012;Rodak and Silliman, 2011;Andričević et al, 2012;Siirila and Maxwell, 2012;Atchley et al, 2013;de Barros and Fiori, 2014]. Probabilistic risk models allow one to determine the likelihood of risk exceeding a given regulatory threshold value [Tartakovsky, 2007], to delineate the spatial distribution of a plume for monitoring adaptation or intensification [James and Gorelick, 1994;Smalley et al, 2000;Maxwell et al, 2007;Fernandez-Garcia et al, 2012] and to better allocate characterization efforts to reduce the overall uncertainty of a given environmental performance metric [e.g., de Barros et al, 2009].…”

Section: Introductionmentioning

confidence: 99%

Probabilistic human health risk assessment of degradation‐related chemical mixtures in heterogeneous aquifers: Risk statistics, hot spots, and preferential channels

Henri

Fernàndez-García

Barros

2015

Water Resources Research

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The increasing presence of toxic chemicals released in the subsurface has led to a rapid growth of social concerns and the need to develop and employ models that can predict the impact of groundwater contamination on human health risk under uncertainty. Monitored natural attenuation is a common remediation action in many contamination cases. However, natural attenuation can lead to the production of daughter species of distinct toxicity that may pose challenges in pollution management strategies. The actual threat that these contaminants pose to human health depends on the interplay between the complex structure of the geological media and the toxicity of each pollutant byproduct. This work addresses human health risk for chemical mixtures resulting from the sequential degradation of a contaminant (such as a chlorinated solvent) under uncertainty through high-resolution three-dimensional numerical simulations. We systematically investigate the interaction between aquifer heterogeneity, flow connectivity, contaminant injection model, and chemical toxicity in the probabilistic characterization of health risk. We illustrate how chemical-specific travel times control the regime of the expected risk and its corresponding uncertainties. Results indicate conditions where preferential flow paths can favor the reduction of the overall risk of the chemical mixture. The overall human risk response to aquifer connectivity is shown to be nontrivial for multispecies transport. This nontriviality is a result of the interaction between aquifer heterogeneity and chemical toxicity. To quantify the joint effect of connectivity and toxicity in health risk, we propose a toxicity-based Damk€ ohler number. Furthermore, we provide a statistical characterization in terms of low-order moments and the probability density function of the individual and total risks.

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“…Dynamic connectivity metrics involve the physical processes of flow or transport. They are estimated experimentally or with modelling such as effective hydraulic conductivity [7].…”

Section: Introductionmentioning

confidence: 99%

Characterization of microstructures using contour tree connectivity for fluid flow analysis

Aydogan

Hyttinen

2014

J. R. Soc. Interface.

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Quantifying the connectivity of material microstructures is important for a wide range of applications from filters to biomaterials. Currently, the most used measure of connectivity is the Euler number, which is a topological invariant. Topology alone, however, is not sufficient for most practical purposes. In this study, we use our recently introduced connectivity measure, called the contour tree connectivity (CTC), to study microstructures for flow analysis. CTC is a new structural connectivity measure that is based on contour trees and algebraic graph theory. To test CTC, we generated a dataset composed of 120 samples and six different types of artificial microstructures. We compared CTC against the Euler parameter (EP), the parameter for connected pairs, the nominal opening dimension (d nom ) and the permeabilities estimated using direct pore scale modelling. The results show that d nom is highly correlated with permeability (R 2 ¼ 0.91), but cannot separate the structural differences. The groups are best classified with feature combinations that include CTC. CTC provides new information with a different connectivity interpretation that can be used to analyse and design materials with complex microstructures.

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On the relationship between indicators of geostatistical, flow and transport connectivity

Cited by 265 publications

References 64 publications

Influence of aquifer and streambed heterogeneity on the distribution of groundwater discharge

Influence of aquifer and streambed heterogeneity on the distribution of groundwater discharge

Probabilistic human health risk assessment of degradation‐related chemical mixtures in heterogeneous aquifers: Risk statistics, hot spots, and preferential channels

Characterization of microstructures using contour tree connectivity for fluid flow analysis

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