Special Issue "Heterogeneous Aquifer Modeling: Closing the Gap"

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrology".

Deadline for manuscript submissions: closed (3 December 2018).

Special Issue Editor

Prof. Dr. J. Jaime Gómez-Hernández
E-Mail Website
Guest Editor
Group of Hydrogeology, Institute for Water and Environmental Engineering, Universitat Politècnica de València, Spain
Interests: geostatistics; hydrogeology; inverse modeling; stochastic groundwater modeling

Special Issue Information

Dear Colleagues,

Aquifer heterogeneity has been a major topic of research in the last few decades, with many theoretical analyses on how to characterize it, about its impact on flow and transport modeling, on its impact in prediction uncertainty, or on how to use inverse approaches to improve heterogeneous models; however, there is still a large gap between theoretical findings and practical applications. This Special Issue seeks papers proposing or demonstrating readily-applicable approaches to treat heterogeneity in real practice. Successful case studies proving the importance of taking heterogeneity into account are welcome.

Prof. Dr. J. Jaime Gómez-Hernández
Guest Editor

Manuscript Submission Information

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Keywords

  • stochastic groundwater modeling
  • geostatistics
  • inverse modeling
  • uncertainty
  • spatial variability
  • upscaling
  • groundwater flow and mass transport modeling

Published Papers (7 papers)

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Research

Open AccessArticle
Three-Dimensional Modelling of Heterogeneous Coastal Aquifer: Upscaling from Local Scale
Water 2019, 11(3), 421; https://doi.org/10.3390/w11030421 - 27 Feb 2019
Abstract
The aquifer heterogeneity is often simplified while conceptualizing numerical model due to lack of field data. Conducting field measurements to estimate all the parameters at the aquifer scale may not be feasible. Therefore, it is essential to determine the most significant parameters which [...] Read more.
The aquifer heterogeneity is often simplified while conceptualizing numerical model due to lack of field data. Conducting field measurements to estimate all the parameters at the aquifer scale may not be feasible. Therefore, it is essential to determine the most significant parameters which require field characterization. For this purpose, the sensitivity analysis is performed on aquifer parameters, viz., anisotropic hydraulic conductivity, effective porosity and longitudinal dispersivity. The results of the sensitivity index and root mean square deviation indicated, that the longitudinal dispersivity and anisotropic hydraulic conductivity are the sensitive aquifer parameters to evaluate seawater intrusion in the study area. The sensitive parameters are further characterized at discrete points or at local scale by using regression analysis. The longitudinal dispersivity is estimated at discrete well points based on Xu and Eckstein regression formula. The anisotropic hydraulic conductivity is estimated based on established regression relationship between hydraulic conductivity and electrical resistivity with R2 of 0.924. The estimated hydraulic conductivity in x and y-direction are upscaled by considering the heterogeneous medium as statistically homogeneous at each layer. The upscaled model output is compared with the transversely isotropic model output. The bias error and root mean square error indicated that the upscaled model performed better than the transversely isotropic model. Thus, this investigation demonstrates the necessity of considering spatial heterogeneous parameters for effective modelling of the seawater intrusion in a layered coastal aquifer. Full article
(This article belongs to the Special Issue Heterogeneous Aquifer Modeling: Closing the Gap)
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Open AccessArticle
Spectral Decomposition and a Waveform Cluster to Characterize Strongly Heterogeneous Paleokarst Reservoirs in the Tarim Basin, China
Water 2019, 11(2), 256; https://doi.org/10.3390/w11020256 - 01 Feb 2019
Cited by 1
Abstract
The main components of the Ordovician carbonate reservoirs in the Tahe Oilfield are paleokarst fracture-cavity paleo-channel systems formed by karstification. Detailed characterization of these paleokarst reservoirs is challenging because of heterogeneities in characteristics and strong vertical and lateral non-uniformities. Traditional seismic analysis methods [...] Read more.
The main components of the Ordovician carbonate reservoirs in the Tahe Oilfield are paleokarst fracture-cavity paleo-channel systems formed by karstification. Detailed characterization of these paleokarst reservoirs is challenging because of heterogeneities in characteristics and strong vertical and lateral non-uniformities. Traditional seismic analysis methods are not able to solve the identification problem of such strongly heterogeneous reservoirs. Recent developments in seismic interpretation have heightened the need to describe the fracture-cavity structure of a paleo-channel with more accuracy. We propose a new prediction model for fracture-cavity carbonate reservoirs based on spectral decomposition and a waveform cluster. By the Matching Pursuit decomposition algorithm, the single-frequency data volumes are obtained. The specific frequency data volume that is the most sensitive to the reservoir is chosen based on seismic synthesis traces of well-logging data and geological interpretability. The waveform cluster is then applied to delineate the complex paleokarst systems, particularly the fracture-caves in the runoff zone. This method was applied to the area around Well T615 in the Tahe oilfield, and a paleokarst fracture-cavity system with strong heterogeneity in the runoff zone was delineated and characterized. The findings of this research provide insights for predicting other similar karst systems, such as karstic groundwater and karst hydrogeological systems. Full article
(This article belongs to the Special Issue Heterogeneous Aquifer Modeling: Closing the Gap)
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Open AccessArticle
Characterization of Hydraulic Heterogeneity of Alluvial Aquifer Using Natural Stimuli: A Field Experience of Northern Italy
Water 2019, 11(1), 176; https://doi.org/10.3390/w11010176 - 20 Jan 2019
Cited by 1
Abstract
This study investigates the hydraulic heterogeneity of the alluvial aquifer underneath the dam and the stilling basin of a flood protection structure in Northern Italy. The knowledge of the interactions between the water in the reservoir upstream of the dam and the groundwater [...] Read more.
This study investigates the hydraulic heterogeneity of the alluvial aquifer underneath the dam and the stilling basin of a flood protection structure in Northern Italy. The knowledge of the interactions between the water in the reservoir upstream of the dam and the groundwater levels is relevant for the stability of the structure. A Bayesian Geostatistical Approach (BGA) combined with a groundwater flow model developed in MODFLOW 2005 has been used to estimate the hydraulic conductivity (HK) field in a context of a highly parameterized inversion. The transient hydraulic heads collected in 14 monitoring points represent the calibration dataset; these observations are the results of the hydraulic stresses induced by the variations of the lake stage upstream of the dam (natural stimuli). The geostatistical inversion was performed by means of a computer code, bgaPEST, developed according to the free PEST software concept. The results of the inversion show a moderate degree of heterogeneity of the estimated HK field, consistent with the alluvial nature of the aquifer and the other information available. The calibrated groundwater model is useful for simulating the interactions between the reservoir and the studied aquifer under different flood scenarios and for forecasting the hydraulic head levels due to strong flood events. The use of natural stimuli is useful for obtaining information for aquifer heterogeneity characterization. Full article
(This article belongs to the Special Issue Heterogeneous Aquifer Modeling: Closing the Gap)
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Open AccessArticle
Upscaling Mixing in Highly Heterogeneous Porous Media via a Spatial Markov Model
Water 2019, 11(1), 53; https://doi.org/10.3390/w11010053 - 29 Dec 2018
Cited by 2
Abstract
In this work, we develop a novel Lagrangian model able to predict solute mixing in heterogeneous porous media. The Spatial Markov model has previously been used to predict effective mean conservative transport in flows through heterogeneous porous media. In predicting effective measures of [...] Read more.
In this work, we develop a novel Lagrangian model able to predict solute mixing in heterogeneous porous media. The Spatial Markov model has previously been used to predict effective mean conservative transport in flows through heterogeneous porous media. In predicting effective measures of mixing on larger scales, knowledge of only the mean transport is insufficient. Mixing is a small scale process driven by diffusion and the deformation of a plume by a non-uniform flow. In order to capture these small scale processes that are associated with mixing, the upscaled Spatial Markov model must be extended in such a way that it can adequately represent fluctuations in concentration. To address this problem, we develop downscaling procedures within the upscaled model to predict measures of mixing and dilution of a solute moving through an idealized heterogeneous porous medium. The upscaled model results are compared to measurements from a fully resolved simulation and found to be in good agreement. Full article
(This article belongs to the Special Issue Heterogeneous Aquifer Modeling: Closing the Gap)
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Open AccessArticle
Applying 3D Geostatistical Simulation to Improve the Groundwater Management Modelling of Sedimentary Aquifers: The Case of Doñana (Southwest Spain)
Water 2019, 11(1), 39; https://doi.org/10.3390/w11010039 - 26 Dec 2018
Abstract
Mathematical groundwater modelling with homogeneous permeability zones has been used for decades to manage water resources in the Almonte-Marismas aquifer (southwest Spain). This is a highly heterogeneous detrital aquifer which supports valuable ecological systems in the Doñana National Park. The present study demonstrates [...] Read more.
Mathematical groundwater modelling with homogeneous permeability zones has been used for decades to manage water resources in the Almonte-Marismas aquifer (southwest Spain). This is a highly heterogeneous detrital aquifer which supports valuable ecological systems in the Doñana National Park. The present study demonstrates that it is possible to better characterize this heterogeneity by numerical discretization of the geophysical and lithological data available. We identified six hydrofacies whose spatial characteristics were quantified with indicator variogram modelling. Sequential Indicator Simulation then made it possible to construct a 3D geological model. Finally, this detailed model was included in MODFLOW through the Model Muse interface. This final process is still a challenge due to the difficulty of downscaling to a handy numerical modelling scale. New piezometric surfaces and water budgets were obtained. The classical model with zones and the model with 3D simulation were compared to confirm that, for management purposes, the effort of improving the geological heterogeneities is worthwhile. This paper also highlights the relevance of including subsurface heterogeneities within a real groundwater management model in the present global change scenario. Full article
(This article belongs to the Special Issue Heterogeneous Aquifer Modeling: Closing the Gap)
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Open AccessArticle
An Effective Kalman Filter-Based Method for Groundwater Pollution Source Identification and Plume Morphology Characterization
Water 2018, 10(8), 1063; https://doi.org/10.3390/w10081063 - 10 Aug 2018
Cited by 3
Abstract
The identification of unknown groundwater pollution sources and the characterization of pollution plume remains a challenging problem. In this study, we addressed this problem by a linked simulation-optimization approach. This approach couples a contaminant transport simulation model with a Kalman filter-based method to [...] Read more.
The identification of unknown groundwater pollution sources and the characterization of pollution plume remains a challenging problem. In this study, we addressed this problem by a linked simulation-optimization approach. This approach couples a contaminant transport simulation model with a Kalman filter-based method to identify groundwater pollution source and characterize plume morphology. In the proposed methodology, the concentration field library, the covariance reduction with a Kalman filter, an alpha-cut technique of fuzzy set, and a linear programming model are integrated for solving this inverse problem. The performance of this methodology is evaluated on an illustrative groundwater pollution source identification problem. The evaluation considered the random hydraulic conductivity filed, erroneous monitoring data, a prior information shortage of potential pollution sources, and an unexpected and unknown pumping well. The identified results indicate that, under these conditions, the proposed Kalman filter-based optimization model can give satisfactory estimations to pollution sources and plume morphology for domains with small and moderate heterogeneity but cannot validate the transport in the relatively high heterogeneous field. Full article
(This article belongs to the Special Issue Heterogeneous Aquifer Modeling: Closing the Gap)
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Open AccessArticle
Three Geostatistical Methods for Hydrofacies Simulation Ranked Using a Large Borehole Lithology Dataset from the Venice Hinterland (NE Italy)
Water 2018, 10(7), 844; https://doi.org/10.3390/w10070844 - 25 Jun 2018
Cited by 4
Abstract
A large borehole lithology dataset from the shallowly buried alluvial aquifer of the Brenta River Megafan (NE Italy) is used in this paper to model hydrofacies with three classical geostatistical methods, namely the Object-Based Simulation (OBS), the Sequential Indicator Simulation (SIS), and the [...] Read more.
A large borehole lithology dataset from the shallowly buried alluvial aquifer of the Brenta River Megafan (NE Italy) is used in this paper to model hydrofacies with three classical geostatistical methods, namely the Object-Based Simulation (OBS), the Sequential Indicator Simulation (SIS), and the Truncated Gaussian Simulation (TGS), and rank alternative output models. Results show that, though compromising with geological realism and rendering a noisy picture of subsurface geology, the pixel-based TGS and SIS are better suited than OBS for their ease of conditioning to closely spaced boreholes, especially in fine-scale simulation grids. In turn, SIS appears to provide better prediction and less noisy hydrofacies models than TGS without requiring assumptions about relationship among operative facies, which makes it particularly suited for use with large borehole lithology datasets lacking detail and quality consistency. Flow simulation on a test volume constrained with numerous boreholes indicates the SIS hydrofacies models feature well-connected sands forming relatively fast flow paths as opposed to TGS models, which instead appear to carry a more dispersed flow. It is shown how such a difference primarily relates to ‘noise’, which in TGS models is so widespread to translate into a disordered spatial distribution of K and, consequently, a nearly isotropic simulated flow. Full article
(This article belongs to the Special Issue Heterogeneous Aquifer Modeling: Closing the Gap)
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