Calibration and Reliability in Groundwater Modelling:
Credibility of Modelling
Edited by J. C. Refsgaard, K. Kovar, E. Haarder & E. Nygaard
IAHS Publ. 320(2008)ISBN978-1-901502-49-7, 358 + x pp. Price £67.00
ModelCARE 2007 (Copenhagen, September 2007) was the sixth in the international conference series on Calibration and Reliability in Groundwater Modelling, which provides a forum for state-of-the-art presentations on methodologies and techniques, and the identification of needs for further development.
The theme, Credibility of Modelling, also attracted papers illustrating the applicability of various techniques through advanced case studies on calibration and reliability techniques. This book comprises 57 peer-reviewed papers selected from the conference and is organised in the following themes:
1)Development in modelling and uncertainty assessment
2)Credibility in modelling for practical approaches
3)New data types and monitoring systems
4)Integrated hydrological modelling
5)Reactive and density affected transport
6)Parameter estimation and model calibration
7)Geological models and conceptual model uncertainty
Contents
Preface by J. C. Refsgaard, K. Kovar, E. Haarder & E. Nygaard
/ v1 / Development in modelling and uncertainty assessment
On the geostatistical characterization of hierarchical media Shlomo P. Neuman, Monica Riva& Alberto Guadagnini / 3
Evaluation of Fickian and non-Fickian models for solute transport in porous media containing decimetre-scale preferential flow paths Marco Bianchi, Chunmiao Zheng, Geoffrey R. Tick & Steven M. Gorelick / 9
Bias-corrected groundwater model prediction uncertainty analysis
Yonas Demissie, Albert Valocchi, Barbara Minsker & Barbara Bailey / 15
Solving computationally demanding reliability based design problems in hydrogeology P. Bayer, C. M. Bürger & M. Finkel / 22
Uncertainty assessment for contaminant leaching from flood water retention areas E. Bethge & U. Mohrlok / 27
Application of stochastic modelling to numerical solution of groundwater flow: transmissivity upscaling G. Dagan & S. C. Lessoff / 34
Characterizing the spatial variability of transmissivity using stochastic type-curve and numerical inverse analyses of data from a sequence of pumping tests
Monica Riva, Alberto Guadagnini & Shlomo P. Neuman / 39
The potential of data assimilation methods for modelling groundwater flow systems: review and synthetic examples Harrie-Jan Hendricks Franssen / 45
Simulation of fractured rock solute transport with a multidimensional dual-porosity model Jiří Havlíček & Milan Hokr / 52
Credibility evaluation of numerically estimated heterogeneous hydraulic property by eigenvalues of Hessian of Lagrange function for constrained groundwater problem K. Masumoto / 58
Application of maximum likelihood Bayesian model averaging to groundwater flow and transport at the Hanford Site 300 area Philip D. Meyer, Ming Ye, Shlomo P. Neuman & Mark L. Rockhold / 64
Maximum likelihood Bayesian averaging of air flow models in unsaturated fractured tuff Eric Morales-Casique, Shlomo P. Neuman &
Velimir V. Vesselinov / 70
An efficient calibration-constrained Monte Carlo technique for evaluating model predictive error Matthew Tonkin & John Doherty / 76
2 / Credibility in modelling for practical approaches
Groundwater vulnerability assessment using physically-based modelling: from challenges to pragmatic solutions I. C. Popescu, N. Gardin, S. Brouyère &
A. Dassargues / 83
Real time control of a well field Gero Bauser, Harrie-Jan Hendricks Franssen, Wolfgang Kinzelbach & Hans-Peter Kaiser / 89
The National Groundwater Modelling System for England and Wales
Rolf Farrell, Mark Whiteman & Peter Gijsbers / 95
Model peer reviews and modeller–manager dialogues as an avenue to improved model credibility H. J. Henriksen & A. L. Højberg / 101
MIPWA: Water managers develop their own high-resolution groundwater model tools Judith Snepvangers, Bennie Minnema, Wilbert Berendrecht,
Peter Vermeulen, Aris Lourens, Wim van der Linden, Mike Duijn,
Jan van Bakel, Willem-Jan Zaadnoordijk, Marcel Boerefijn,
Margo Meeuwissen & Vera Lagendijk / 108
Auditing as a necessary step for gaining credibility in groundwater modelling Adolfo Chávez, Adán Pinales, Ricardo Ducoing & José L. Cruz / 114
Real-time optimisation of groundwater management H. Madsen, A. K. Falk,
D. Rosbjerg, H. Madsen, N. Schrøder, J. Mortensen, B. Mortensen,
J. Kristensen, G. Brandt / 120
Modelling to support the assessment of interlinkages between groundwater and surface water in the context of the EU Water Framework Directive
D.-I. Müller-Wohlfeil1& S. Mielby / 124
3 /
New data types and monitoring systems
Using stable isotope data to characterise flow systems in the Pannonian Basin, Hungary T. Szocs, Gy. Toth & I. Horvath / 131Quantifying the economic benefit of groundwater monitoring: a pilot study
Frans Van Geer, Annemieke Marsman & Gijs M. C. M. Janssen / 137
Meeting the future demands for borehole data and hydraulic heads Susie Mielby & Claus Ditlefsen / 142
Calibrating unsaturated model parameters using electrical resistivity tomography imaging F. Slama, E. P. Milnes & R. Bouhlila / 148
Grouping of soils according to their soil water retention characteristics B. Tóth, A. Makó, L. Guadagnini, A. Azzellino & A. Guadagnini / 154
4 /
Integrated hydrological modelling
How successful are standard models of groundwater–river interactionsFritz Stauffer, Tobias Doppler & Harrie-Jan Hendricks Franssen / 163
Set-up and calibration of a distributed hydrological model of the Okavango Delta using remote sensing data C. Milzow, L. Kgotlhang, V. Burg & W. Kinzelbach / 169
An efficient variable storage coefficient (VSC) approach for 3-D groundwater modelling of wetlands E. -R. Trübger, H.-J. G. Diersch, Th. Salzmann &
K. Miegel / 176
Evaluation of the hillslope-storage Boussinesq model with leakage S. Broda,
C. Paniconi & M. Larocque / 182
5 /
Reactive and density affected transport
Geochemical processes and their modelling at the fresh and salt water mixing zone K. Jinno, T. Hosokawa, K. Akagi,Y. Hiroshiro & J. Yasumoto / 191Modelling the source zone depletion and plume development of a coal-tar contaminated site Fernando Mazo D’Affonseca, Philipp Blum, Michael Finkel, Reiner Melzer & Peter Grathwohl / 197
A module for the MT3DMS solute transport model for simulating redox processes M. Van Camp & K. Walraevens / 203
Upscaling of solute transport based on the concept of the memory function
G. Llerar-Meza, D. Fernàndez-Garcia & J. J. Gómez-Hernández / 210
Saltwater dynamics due to cut-off wall installation in coastal unconfined aquifers: experimental and numerical studies R. Luyun, Jr, K. Momii, K. Nakagawa &
S. Fujiyama / 214
Impacts of calcite dissolution on seawater intrusion processes in coastal aquifers: density dependent flow and multi species reactive transport modelling
Rachida Bouhlila & Ezzeddine Laabidi / 220
Modelling two-phase transport of 3H/3He Ate Visser, JorisD.Schaap,
Toon Leijnse, Hans Peter Broers & Marc F. P. Bierkens / 226
6 /
Parameter estimation and model calibration
Using many pilot points and singular value decomposition in groundwater model calibration Steen Christensen & John Doherty / 235A critical review of the properties of forward and inverse problems in groundwater hydrology Mauro Giudici, Timothy R. Ginn, Chiara Vassena,
Hanieh Haeri & Laura Foglia / 240
wwhypda: A worldwide hydrogeological parameters database A. Comunian,
P. Renard & M. Kisanga / 245
The use of groundwater age as a calibration target Leonard F. Konikow,
George Z. Hornberger, Larry D. Putnam, Allen M. Shapiro & Brendan A. Zinn / 250
Heat transport in a push–pull test: parameter identification and sensitivity analyses A. Vandenbohede, A. Louwyck & L. Lebbe / 257
A new approach for the stochastic inversion of flow and transport data: application to the macrodispersion experiment (MADE-2) site C. Llopis-Albert & J. E. Capilla / 262
Model predictive error: how it arises and how it can be accommodated
John Doherty / 267
Inverse modelling of aquitard structures using pilot points and regularisation
B. Wiese & G. Nützmann / 272
The influence of the experimental set-up and the model approach on the determination of diffusion coefficients for radionuclides in laboratory column experiments Wilfried Pfingsten / 278
Global upscaling of hydraulic conductivity for modelling contaminant transport in groundwater Ne-Zheng Sun & William W.-G. Yeh / 284
Recent advances in parameter estimation and uncertainty assessment in integrated hydrological modelling H. Madsen, R. -S. Blasone & D. Rosbjerg / 289
Transient calibration of flow to ditches with entry resistance using measured moments of response functions Mark Bakker, Kees Maas & Jos Von Asmuth / 295
Can conditioning to transmissivity data worsen model predictions?
Jaouher Kerrou, Harrie-Jan Hendricks Franssen, Philippe Renard &
Ivan Lunati / 299
Practical tools for calibration of transient groundwater flow models
Peter F. Andersen& Gregory W. Council / 305
Data-driven reparameterization structure for estimation of fluid conductivity
I. Berre, F. Clément, M. Lien & T. Mannseth / 310
Data error and highly parameterized groundwater models Mary C. Hill / 316
Estimating parameters of groundwater recharge model in frequency domain Damir Jukić & Vesna Denić-Jukić / 322
7 /
Geological models and conceptual model uncertainty
Conceptual uncertainty assessment for a catchment scale model Matej Gedeon & Isabelle Wemaere / 331Impact of geological modelling on groundwater models – a case study from an area with distributed, isolated aquifers F. Jørgensen, J. Damgaard & H. Olesen / 337
Uncertainty assessment of geological models – a qualitative approach
Peter B. E. Sandersen / 345
Key word index / 350
Author index / 355
______Calibration and Reliability in Groundwater Modelling: Credibility of Modelling
(Proceedings of ModelCARE 2007 Conference, held in Denmark, September 2007). IAHS Publ. 320, 2008, 3-8.
On the geostatistical characterization of hierarchical media
SHLOMO P. NEUMAN1, MONICA RIVA2& ALBERTO GUADAGNINI2
1Department of Hydrology and Water Resources, University of Arizona, Tucson, Arizona 85721, USA
2DIIAR, Politecnico di Milano, Piazza L. Da Vinci 32, 20133 Milano, Italy
Abstract The subsurface exhibits hierarchical structures with multiscale hydraulic and transport properties. The structure and properties are often well characterized by stationary variograms. We propose that the latter is an artefact of sampling over finite windows, which disappears when one uses truncated power variograms (TPVs). We cite evidence that parameters of traditional stationary variograms vary with support and window scales; demonstrate the ability of TPVs to capture these scale variations; show that stationary variograms are often difficult to distinguish from TPVs; note that TPVs are unique in their ability to represent multiscale random fields having either Gaussian or heavy-tailed symmetric Levy stable probability distributions; detail the way in which TPVs allow conditioning on multiscale measurements via co-kriging; and illustrate these capabilities on multiscale hydraulic data from Tübingen, Germany.
Key words hierarchy; multiscale; fractal; variogram; exponential; power; cutoff; co-kriging; Gaussian; Levy stable
______Calibration and Reliability in Groundwater Modelling: Credibility of Modelling
(Proceedings of ModelCARE 2007 Conference, held in Denmark, September 2007). IAHS Publ. 320, 2008, 9-14.
Evaluation of Fickian and non-Fickian models for solute transport in porous media containing decimetre-scale preferential flow paths
MARCO BIANCHI1, CHUNMIAO ZHENG1, GEOFFREY R. TICK1
& STEVEN M. GORELICK2
1Department of Geological Sciences, The University of Alabama, Tuscaloosa, Alabama 35487, USA
2Department of Geological & Environmental Sciences, Stanford University, Stanford, California 94305, USA
Abstract The effectiveness of the classical advection–dispersion model (ADM) to describe solute transport in heterogeneous aquifers has been challenged by many studies.In particular, it has been shown that the dual-domain single-rate mass transfer (DDSR) model is more appropriate than the ADM in characterizing solute transport in flow fields controlled by preferential flowpaths at the decimetre or smaller scales. In such situations the transport patterns, generally referred to as non-Fickian, are characterized by highly asymmetric plumes with early-time high concentration peaks and late-time low concentration tails. A recent development in non-Fickian transport is the continuous time random walk (CTRW) formulation. While this approach has been successfully applied to fit breakthrough curves from laboratory and field experiments, no systematic study has been conducted to test its applicability to simulate solute transport in porous media containing small-scale preferential flowpaths. In this study we conducted a detailed numerical experiment to evaluate the effectiveness of the ADM and two non-Fickian transport models (CTRW and DDSR) in reproducing the transport behaviour when small-scale preferential flowpaths are present in a binary heterogeneous system. Our reference is a 2-D synthetic aquifer characterized by a network of 10-cm wide high hydraulic conductivity channels, embedded in an otherwise homogeneous matrix. The contrast in hydraulic conductivity between the channels and the remaining portion of the aquifer is 100:1. Numerical simulations were used to obtain accurate reference solutions for flow and contaminant transport in the channel-network system. Breakthrough curves and mass profiles from the reference solutions were compared with the results obtained from the ADM, DDSR and CTRW models to determine the most appropriate model for characterizing the transport behaviour in the synthetic aquifer controlled by decimetre-scale preferential flow paths.
Key words advection–dispersion model; continuous time random walk; dual domain model; aquifer heterogeneity; preferential flowpaths
______Calibration and Reliability in Groundwater Modelling: Credibility of Modelling
(Proceedings of ModelCARE 2007 Conference, held in Denmark, September 2007). IAHS Publ. 320, 2008, 15-21.
Bias-corrected groundwater model prediction uncertainty analysis
Yonas Demissie1, Albert Valocchi1, Barbara Minsker1 & Barbara Bailey2
1Department of Civil and Environmental Engineering, University of Illinois Urbana-Champaign, 205 N. Mathews, Urbana, Illinois 61801, USA
2Department of Mathematics and Statistic, San Diego State University, 5500 Campanile Drive, San Diego,
California 92182, USA
Abstract The incomplete description of the subsurface processes by physically-based groundwater models often results in biased and correlated prediction errors, thus suggesting the need for systematic correction of errors before conducting prediction uncertainty analysis. In this work, error-mapping artificial neural networks (ANN) are used to correct the physically-based groundwater model (MODFLOW) prediction errors. The resulting prediction uncertainty of the coupled MODFLOW-ANN model is then assessed using three alternative methods. The first method establishes approximate confidence and prediction intervals using first-order least-squares regression approximation (also called first-order error analysis). The second method employs bootstrap approaches that involve resampling of the uncertain data with replacement and repeated model runs for constructing the confidence and prediction intervals. The third method relies on a Bayesian approach that uses analytical or Monte Carlo methods to derive the posterior distribution. The performance of these approaches is evaluated using a hypothetical case study developed based on a phytoremediation site at the Argonne National Laboratory, USA. The results indicate that the three approaches yield comparable confidence and prediction intervals, thus making the computationally efficient first-order error analysis approach attractive for estimating the coupled model uncertainty. The results also demonstrate that the error-mapping ANN not only captures some of the local biases in the MODFLOW prediction, but also systematically reduces the prediction variance.
Key words calibration; complementary modelling; bias correction; uncertainty analysis
______Calibration and Reliability in Groundwater Modelling: Credibility of Modelling
(Proceedings of ModelCARE 2007 Conference, held in Denmark, September 2007). IAHS Publ. 320, 2008, 22-26.
Solving computationally-demanding reliability-based design problems in hydrogeology
P. BAyer, C. M. Bürger & M. Finkel
Center for Applied Geosciences (ZAG), University of Tübingen, D-72076 Tübingen, Germany
Abstract The design of technologies used to manage groundwater quality or quantity typically involves the use of groundwater models and an optimisation algorithm. Further, decision makers increasingly request explicit consideration of the uncertainty of model parameters and predictions. Performing Monte Carlo simulations leads to a stack of multiple aquifer realisations, which must then be considered simultaneously during optimisation. The evaluation of the performance of a particular design in every single realisation of the stack provides an estimate of the expected reliability of the design, i.e. its chance to reach a given management target. However, reliability-based optimisation may become computationally impractical if a large number of realisations have to be considered. To substantially reduce the required number of realisations, we propose a new approach that works with small subsets of realisations, which are dynamically drawn from a much larger repository stack. The drawing is controlled by a so-called stack-ordering procedure that ranks the realisations with respect to criticalness. The results of an example application are promising, with computational savings of up to 98.5% and clear improvements as compared to random sampling.
Key words reliability; stochastic processes; heterogeneity; multiple realisations; Monte Carlo; stochastic optimisation; hydraulic capture; stack ordering; computational efficiency; capture zone
______Calibration and Reliability in Groundwater Modelling: Credibility of Modelling
(Proceedings of ModelCARE 2007 Conference, held in Denmark, September 2007). IAHS Publ. 320, 2008, 27-33.
Uncertainty assessment for contaminant leaching from flood water retention areas
E. Bethge & U. Mohrlok
Institute for Hydromechanics, Universität Karlsruhe (TH), Kaiserstraße 12, D-76128 Karlsruhe, Germany
Abstract A probabilistic framework was developed to quantify the risk of groundwater contamination by flood water seepage from retention areas. The involved flow and transport processes have been described and a mass balance model was developed to calculate the contaminant infiltration. During the model application the flood data (flood water depth, flood duration, etc.) were compiled in scenarios and were linked to the soil information in the retention area. The uncertainty of the saturated hydraulic conductivity and of the linear sorption coefficient of the topsoil was described in probability density functions generated from field data and literature values and can be used for Monte Carlo simulations to calculate the risk of groundwater contamination.
Key words flood water retention area; groundwater; contamination; risk assessment; soil; Bayesian update
______Calibration and Reliability in Groundwater Modelling: Credibility of Modelling
(Proceedings of ModelCARE 2007 Conference, held in Denmark, September 2007). IAHS Publ. 320, 2008, 34-38.
Application of stochastic modelling to numerical solution of groundwater flow: transmissivity upscaling
G. DAGAN & S. C. LESSOFF
Department of Fluid Mechanics and Heat Transfer, Faculty of Engineering, Tel Aviv University, Ramat Aviv,
69978 Tel Aviv, Israel
Abstract Stochastic modelling of groundwater flow and transport has undergone a tremendous development in the last 30 years. However, its use in application still lags behind the theoretical developments. Following a strategy outlined in the past (Dagan, 2002), it is suggested that stochastic concepts be applied to numerical solution of groundwater at the regional scale, which is one of the common hydrological modelling activities. The basic approach is to regard the log-transmissivity of the modelled aquifer as random and stationary, characterized by a normal probability distribution function and a two-point covariance (variance, integral scale). Then, the dependent variables to be determined by the numerical solution (head, water flux at grid points) are also random and characterized statistically, in terms of their mean and variance. These values provide measures of uncertainty of the model output as related to the transmissivity spatial variability. Among the various steps required to implement this goal, the one discussed here is that of upscaling, i.e. of attaching values of transmissivity to numerical blocks. Such blocks generally have dimensions of the order of the integral scale of log-transmissivity. The latter was found, by analysing field data, to be of the order of hundreds to thousands of metres. Upscaling procedures are developed in two modes: regarding the upscaled transmissivity as a random field, to be used in Monte Carlo simulations; or determining equivalent transmissivities, that lead directly to the expected value of the dependent variables. Upscaling is carried out for conditions of mean uniform flows, which apply to natural gradients, or to strongly non-uniform but common, well flows. For each case solutions are provided in the unconditional mode (for regions far from measurement points) or the conditional one, near points of transmissivity measurements.By using a first-order approximation in the log-transmissivity variance, simple upscaling rules are provided.