Upscaling of a dual-permeability Monte Carlo simulation model for contaminant transport in fractured networks by genetic algorithm parameter identification

Cadini, Francesco; Sanctis, J. De; Bertoli, I.; Zio, Enrico

doi:10.1007/s00477-012-0595-8

Cited by 11 publications

(8 citation statements)

References 32 publications

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“…Our study is one among several that has successfully applied the dual‐permeability approach for simulating plot‐scale observations of solute transport (e.g., Roulier et al, 2006; Arora et al, 2011; Cadini et al, 2013; Wang et al, 2014). The dual‐permeability approach allowed us to simulate the Br − depth profiles for the three different irrigation experiments, whereas a single‐domain approach did not reproduce the Br − peak observed in deeper soil layers.…”

Section: Discussionmentioning

confidence: 99%

“…A promising approach for identifying an observation‐based parameterization of preferential flow for catchment simulations is to derive parameters in simulations of detailed plot‐scale observations and to then use these parameters for informing catchment‐scale simulations (e.g., Vogel and Roth, 2003; Beven and Germann, 2013; Cadini et al, 2013). Previous studies have realized such an upscaling of preferential flow simulations from plot to hillslope or catchment scale but have lacked validation of the plot‐ and catchment‐scale simulations against field data (Cadini et al, 2013; Wang et al, 2014). Van Schaik et al (2010) used data from plot‐scale irrigation experiments to parameterize three soil profile models.…”

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confidence: 99%

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How Meaningful are Plot‐Scale Observations and Simulations of Preferential Flow for Catchment Models?

Glaser

Jackisch

Hopp

et al. 2019

Vadose Zone Journal

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Core Ideas We tested a range of dual‐permeability parameterizations at plot and catchment scale. Well‐performing parameters at plot scale did not clearly improve catchment simulation. Vertical preferential flow was important for simulating plot‐scale observations. At catchment scale, it appeared more important to consider fast lateral subsurface flow. This showed that different nonuniform flow processes are critical at different scales. Despite ubiquitous field observations of nonuniform flow processes, preferential flow paths are rarely considered in hydrological models, especially at catchment scale. In this study, we investigated the extent to which plot‐scale observations of preferential flow paths are informative for rainfall–runoff simulations at larger scales. We used data from three plot‐scale irrigation experiments in the Weierbach catchment (Luxembourg) to identify preferential flow parameterizations via a Monte Carlo simulation with HydroGeoSphere. Subsequently, we tested whether these parameter sets could be used directly to simulate the hydrological response of the Weierbach headwater with a HydroGeoSphere catchment model. The Monte Carlo simulations showed that the different depth profiles of Br− tracer observed in irrigation experiments could be reproduced when vertical preferential flow was simulated with a dual‐permeability approach. However, it was not possible to identify unique parameter values for preferential flow. The direct transfer of a range of different dual‐permeability parameter sets to the catchment model revealed that the variability of simulated hydrometric catchment responses (discharge and soil moisture over 18 mo) was independent of the variability among the three irrigation experiments. More importantly, the dual‐permeability approach did not improve the match between simulated and observed discharge and soil moisture responses compared with the single‐domain reference model, where multiple soil layers with differing hydraulic conductivities had already been implemented. This suggests that including structures that allow nonuniform lateral flow was more important for reproducing the hydrological response in the Weierbach catchment than the vertical preferential flow observed at plot scale.

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Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

How Meaningful are Plot‐Scale Observations and Simulations of Preferential Flow for Catchment Models?

Glaser

Jackisch

Hopp

et al. 2019

Vadose Zone Journal

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“…The idea was to include those structures that could lead to short‐distance subplot nonequilibrium and lateral flow processes into lumped 1D plot‐scale models with effective parameters. Further upscaling to obtain field‐scale information could be performed with these effective plot‐scale models (e.g., Cadini et al, 2012) by using Monte Carlo type simulations (e.g., Arora et al, 2015) assuming an ensemble of parallel and statistically independent plots (e.g., Mallants et al, 1996) that could additionally have different hydraulic and effective parameters across the field (e.g., the distribution of compacted clods, among other properties). An additional benefit of our approach is the possibility of including local‐scale heterogeneities induced by tillage and other similar soil structural features considered in the model subdomain (through MIM model addition).…”

Section: Discussionmentioning

confidence: 99%

Representation of Plot‐Scale Soil Heterogeneity in Dual‐Domain Effective Flow and Transport Models with Mass Exchange

Filipović

Coquet

Gerke

2019

Vadose Zone Journal

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Core Ideas The heterogeneity of soil hydraulic properties can be described with effective parameters. Increasing model complexity can be used to represent plot‐scale soil heterogeneity. One‐dimensional dual‐domain flow models are used to reproduce 2D preferential transport. Local subscale variability effects are included as mass transfer in an effective model. Agricultural soils are characterized by a structure that is strongly dependent on farming practices like tillage and trafficking. These practices can create compacted zones in the soil, thus initiating preferential flow. Two‐ or three‐dimensional models can be used to account for the spatial variability of the soil hydraulic and transport properties. Since it is challenging to obtain such data, it is logical to find simpler approaches. Our objective was to design a one‐dimensional (1D) modeling approach that effectively accounts for plot‐scale soil structure variability. A 1D dual‐permeability model was tested in which compacted soil was represented by a matrix domain and uncompacted soil by a fracture domain and eventually by assuming an additional immobile water region (MIM) in the fracture domain representing compacted clods embedded within the uncompacted soil. Models (1D) were compared with two‐dimensional single‐porosity (2D_SP) modeling results for water flow and Br− transport based on a previously performed field tracer experiment. Results indicated good agreement between 1D dual‐domain approaches (1D_DPERM and 1D_DPERM_MIM) and the 2D_SP representative model simulation results with high model efficiency and with respect to the field observations. This implied that a 1D vertical model description was sufficient to represent plot‐scale variability if smaller scale soil structure heterogeneities could be accounted for as effective parameters in dual‐domain models. Variation in the mass transfer term had a large effect on the vertical Br− profile distribution. The parameters describing the sizes and shapes of the domains were most relevant for estimating mass transfer between soil structural features in heterogeneous agricultural fields. Still, the calibration of the upscaling approach of two‐domain interactions in larger scale models remains challenging.

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“…In numerical simulations, fracture networks with randomly distributed fractures are typically established using the Monte Carlo methods, and consequently, random numbers used for network construction would affect the geometry of networks and subsequently influence the mechanical and hydraulic properties of established numerical models (Rouleau and Gale 1987;Xu et al 2013;Cadini et al 2013;Liu et al 2016c). To diminish the effect of random numbers, a large number of DFN realizations are required to determine the REV (Bear 1972;Oda 1988;Khaleel 1989;Kulatilake and Panda 2000;Brown et al 2000;Esmaieli et al 2010).…”

Section: Permeability and Scalementioning

confidence: 99%

Review: Mathematical expressions for estimating equivalent permeability of rock fracture networks

et al. 2016

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Fracture networks play a more significant role in conducting fluid flow and solute transport in fractured rock masses, comparing with that of the rock matrix. Accurate estimation of the permeability of fracture networks would help researchers and engineers better assess the performance of projects associated with fluid flow in fractured rock masses. This study provides a review of previous works that have focused on the estimation of equivalent permeability of twodimensional (2-D) discrete fracture networks (DFNs) considering the influences of geometric properties of fractured rock masses. Mathematical expressions for the effects of nine important parameters that significantly impact on the equivalent permeability of DFNs are summarized, including (1) fracturelength distribution, (2) aperture distribution, (3) fracture surface roughness, (4) fracture dead-end, (5) number of intersections, (6) hydraulic gradient, (7) boundary stress, (8) anisotropy, and (9) scale. Recent developments of 3-D fracture networks are briefly reviewed to underline the importance of utilizing 3-D models in future research.

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Upscaling of a dual-permeability Monte Carlo simulation model for contaminant transport in fractured networks by genetic algorithm parameter identification

Cited by 11 publications

References 32 publications

How Meaningful are Plot‐Scale Observations and Simulations of Preferential Flow for Catchment Models?

How Meaningful are Plot‐Scale Observations and Simulations of Preferential Flow for Catchment Models?

Representation of Plot‐Scale Soil Heterogeneity in Dual‐Domain Effective Flow and Transport Models with Mass Exchange

Review: Mathematical expressions for estimating equivalent permeability of rock fracture networks

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