A coupled simulation-optimization approach for groundwater remediation design under uncertainty: An application to a petroleum-contaminated site

This study provides a coupled simulation–optimization approach for optimal design of petroleum-contaminated groundwater remediation under uncertainty. Compared to the previous approaches, it has the advantages of: (1) addressing the stochasticity of the modeling parameters in simulating the flow and transport of NAPLs in groundwater, (2) providing a direct and response-rapid bridge between remediation strategies (pumping rates) and remediation performance (contaminant concentrations) through the created proxy models, (3) alleviating the computational cost in searching for optimal solutions, and (4) giving confidence levels for the obtained optimal remediation strategies. The approach is applied to a practical site in Canada for demonstrating its performance. The results show that mitigating the effects of uncertainty on optimal remediation strategies (through enhancing the confidence level) would lead to the rise of remediation cost due to the increase in the total pumping rate.     

A comparison of numerical solutions of partial differential equations with probabilistic and possibilistic parameters for the quantification of uncertainty in subsurface solute transport

Traditionally, uncertainty in parameters are represented as probabilistic distributions and incorporated into groundwater flow and contaminant transport models. With the advent of newer uncertainty theories, it is now understood that stochastic methods cannot properly represent non random uncertainties. In the groundwater flow and contaminant transport equations, uncertainty in some parameters may be random, whereas those of others may be non random. The objective of this paper is to develop a fuzzy-stochastic partial differential equation (FSPDE) model to simulate conditions where both random and non random uncertainties are involved in groundwater flow and solute transport. Three potential solution techniques namely, (a) transforming a probability distribution to a possibility distribution (Method I) then a FSPDE becomes a fuzzy partial differential equation (FPDE), (b) transforming a possibility distribution to a probability distribution (Method II) and then a FSPDE becomes a stochastic partial differential equation (SPDE), and (c) the combination of Monte Carlo methods and FPDE solution techniques (Method III) are proposed and compared. The effects of these three methods on the predictive results are investigated by using two case studies. The results show that the predictions obtained from Method II is a specific case of that got from Method I. When an exact probabilistic result is needed, Method II is suggested. As the loss or gain of information during a probability–possibility (or vice versa) transformation cannot be quantified, their influences on the predictive results is not known. Thus, Method III should probably be preferred for risk assessments.     

Monitoring groundwater contamination and delineating source zones at industrial sites: uncertainty analyses using integral pumping tests

Field-scale characterisations of contaminant plumes in groundwater, as well as source zone delineations, are associated with uncertainties that can be considerable. A major source of uncertainty in environmental datasets is due to variability of sampling results, as a direct consequence of the heterogeneity of environmental matrices. We develop a methodology for quantifying uncertainties in field-scale mass flow and average concentration estimations, using integral pumping tests (IPTs), where the contaminant concentration is measured as a function of time in a pumping well. This procedure increases the sampling volume and reduces the effect of small-scale variability that may bias point-scale measurements. In particular, using IPTs, the interpolation uncertainty of conventional point-scale measurements is transformed to a quantifiable uncertainty related to the (unknown) plume position relative to the pumping well. We show that this plume position uncertainty generally influenced the predicted mass flows and average concentrations (of acenapthene, benzene and CHCs) to a greater extent than a boundary condition uncertainty related to the local water balance, considering 19 control planes at a highly heterogeneous industrial site in southwest Germany. Furthermore, large (order of magnitude) uncertainties only occurred if the conditions were strongly heterogeneous in the nearest vicinity of the well. We also develop a consistent methodology for an assessment of the combined effect of uncertainty in hydraulic conditions and uncertainty in reactive transport parameters for delimiting of both contaminant source zones and zones absent of source, based on (downgradient) IPTs.     

Assessing the natural attenuation of organic contaminants in aquifers using plume-scale electron and carbon balances: model development with analysis of uncertainty and parameter sensitivity

A quantitative methodology is described for the field-scale performance assessment of natural attenuation using plume-scale electron and carbon balances. This provides a practical framework for the calculation of global mass balances for contaminant plumes, using mass inputs from the plume source, background groundwater and plume residuals in a simplified box model. Biodegradation processes and reactions included in the analysis are identified from electron acceptors, electron donors and degradation products present in these inputs. Parameter values used in the model are obtained from data acquired during typical site investigation and groundwater monitoring studies for natural attenuation schemes. The approach is evaluated for a UK Permo-Triassic Sandstone aquifer contaminated with a plume of phenolic compounds. Uncertainty in the model predictions and sensitivity to parameter values was assessed by probabilistic modelling using Monte Carlo methods. Sensitivity analyses were compared for different input parameter probability distributions and a base case using fixed parameter values, using an identical conceptual model and data set. Results show that consumption of oxidants by biodegradation is approximately balanced by the production of CH4 and total dissolved inorganic carbon (TDIC) which is conserved in the plume. Under this condition, either the plume electron or carbon balance can be used to determine contaminant mass loss, which is equivalent to only 4% of the estimated source term. This corresponds to a first order, plume-averaged, half-life of > 800 years. The electron balance is particularly sensitive to uncertainty in the source term and dispersive inputs. Reliable historical information on contaminant spillages and detailed site investigation are necessary to accurately characterise the source term. The dispersive influx is sensitive to variability in the plume mixing zone width. Consumption of aqueous oxidants greatly exceeds that of mineral oxidants in the plume, but electron acceptor supply is insufficient to meet the electron donor demand and the plume will grow. The aquifer potential for degradation of these contaminants is limited by high contaminant concentrations and the supply of bioavailable electron acceptors. Natural attenuation will increase only after increased transport and dilution.     

A field comparison of BTEX mass flow rates based on integral pumping tests and point scale measurements

Measuring contaminant flow rates at control cross sections is the most accurate method to evaluate natural attenuation processes in the saturated subsurface. In most instances, point scale measurement is the method of choice due to practical reasons and cost factors. However, at many field sites, the monitoring network is too sparse for a reliable estimation of contaminant and groundwater flow rates. Therefore, integral pumping tests have been developed as an alternative. In this study, we compare mass flow rates obtained by integral pumping test results and point scale data. We compare results of both methods with regard to uncertainties due to estimation errors and mass flow estimations based on two different point scale networks. The differences between benzene and groundwater flow rate estimates resulting from point scale samples and integral pumping tests were 6.44% and 6.97%, respectively, demonstrating the applicability of both methods at the site. Point scale-based data, especially with use of cost efficient Direct-Push technique, can be applied to show the contaminant distribution at a site and may be followed by a denser point scale network or an integral method. Nevertheless, a combination of both methods decreases uncertainties.     

Groundwater flow and contaminant transport modeling applications in urban area: scopes and limitations

Background

A three-dimensional groundwater flow model was used to evaluate the groundwater potential and assess the effects of groundwater withdrawal on the regional water level and flow direction in the central Beijing area. A program of groundwater modeling aimed at estimating current contaminant fluxes to the central area and site streams via groundwater was developed.

Results and discussion

The conceptual model developed for the site attempted to incorporate a complex stratigraphic profile in which groundwater flow and contaminant transport is strongly controlled by a shallow aquifer. Here, a conceptual model for groundwater flow and contaminant transport in central Beijing is presented.

Conclusion

Model simulations indicated that a sharp drop in the hydraulic head occurs at the center of the model area, which generates a cone of depression and a continuous decline of head with respect to time as a result of heavy groundwater abstraction.     

Data fusion modeling for groundwater systems

Engineering projects involving hydrogeology are faced with uncertainties because the earth is heterogeneous, and typical data sets are fragmented and disparate. In theory, predictions provided by computer simulations using calibrated models constrained by geological boundaries provide answers to support management decisions, and geostatistical methods quantify safety margins. In practice, current methods are limited by the data types and models that can be included, computational demands, or simplifying assumptions. Data Fusion Modeling (DFM) removes many of the limitations and is capable of providing data integration and model calibration with quantified uncertainty for a variety of hydrological, geological, and geophysical data types and models. The benefits of DFM for waste management, water supply, and geotechnical applications are savings in time and cost through the ability to produce visual models that fill in missing data and predictive numerical models to aid management optimization. DFM has the ability to update field-scale models in real time using PC or workstation systems and is ideally suited for parallel processing implementation. DFM is a spatial state estimation and system identification methodology that uses three sources of information: measured data, physical laws, and statistical models for uncertainty in spatial heterogeneities. What is new in DFM is the solution of the causality problem in the data assimilation Kalman filter methods to achieve computational practicality. The Kalman filter is generalized by introducing information filter methods due to Bierman coupled with a Markov random field representation for spatial variation. A Bayesian penalty function is implemented with Gauss–Newton methods. This leads to a computational problem similar to numerical simulation of the partial differential equations (PDEs) of groundwater. In fact, extensions of PDE solver ideas to break down computations over space form the computational heart of DFM. State estimates and uncertainties can be computed for heterogeneous hydraulic conductivity fields in multiple geological layers from the usually sparse hydraulic conductivity data and the often more plentiful head data. Further, a system identification theory has been derived based on statistical likelihood principles. A maximum likelihood theory is provided to estimate statistical parameters such as Markov model parameters that determine the geostatistical variogram. Field-scale application of DFM at the DOE Savannah River Site is presented and compared with manual calibration. DFM calibration runs converge in less than 1 h on a Pentium Pro PC for a 3D model with more than 15,000 nodes. Run time is approximately linear with the number of nodes. Furthermore, conditional simulation is used to quantify the statistical variability in model predictions such as contaminant breakthrough curves.     

Fingerprinting and Groundwater Model Application to Evaluate Hydraulic Barrier Efficiency (Italy)

Remediation actions at contaminated sites are based on multiple numerical model scenarios considering different parameter distributions, source positions and contaminant transport paths. In some cases the excess of scenarios is due to uncertainties in the conceptual model as a result of the spread of contamination through heterogeneities in the physical system. Reduction of project hypotheses and conceptual model uncertainty is therefore needed. This result can be achieved by coupling hydrogeological investigations with environmental forensic techniques, better localization of the source and understanding of contamination history. In this respect, in the present study, compositional fingerprinting and groundwater flow modeling were applied to a former oil storage facility where, even though a hydraulic barrier had been built to stop the hydrocarbon plume, the presence of some hydrocarbons was still found in downgradient monitoring wells. The final aim was to evaluate the efficacy of the hydraulic barrier and identify of the source of pollution. Fingerprinting results indicated pollution with a gasoline-diesel mixture much altered by water washing and/or biodegradation. Comparison of seven groundwater samples collected in wells and monitoring wells was performed by analyzing the volatile fraction (BTEX) and the total ion chromatogram (TIC), focusing attention on: n-alkanes (m/z 85), alkylcyclohexanes (m/z 83), isoprenoids (m/z 113), C4-alkylbenzenes (m/z 134), C3-C6 alkylbenzenes and polycyclic aromatic hydrocarbons (PAHs). The most probable scenario was then identified by combining the results of fingerprinting with different contaminant paths obtained using the numerical model.     

A fuzzy composting process model

Composting processes are normally complicated with a variety of uncertainties arising from incomplete or imprecise information obtained in real-world systems. Previously, there has been a lack of studies that focused on developing effective approaches to incorporate such uncertainties within composting process models. To fill this gap, a fuzzy composting process model (FCPM) for simulating composting process under uncertainty was developed. This model was mainly based on integration of a fractional fuzzy vertex method and a comprehensive composting model. Degrees of influence by projected uncertain factors were also examined. Two scenarios were investigated in applying the FCPM method. In the first scenario, model simulation under deterministic conditions was conducted. A pilot-scale experiment was provided for verifications. The result indicated that the proposed composting model could provide an excellent vehicle for demonstrating the complex interactions that occurred in the composting process. In the second scenario, application of the proposed FCPM was conducted under uncertainties. Six input parameters were considered to be of uncertain features that were reflected as fuzzy membership functions. The results indicated that the uncertainties projected in input parameters will result in significant derivations on system predictions; the proposed FCPM can generate satisfactory system outputs, with less computational efforts being required. Analyses on degree of influence of system inputs were also provided to describe the impacts of uncertainties on system responses. Thus, suitable measures can be adopted either to reduce system uncertainty by well-directed reduction of uncertainties of those high-influencing parameters or to reduce the computational requirement by neglecting those negligible factors.     

Uncertainty Analysis of Ozone Formation and Response to Emission Controls Using Higher-Order Sensitivities

Abstract

Understanding ozone response to its precursor emissions is crucial for effective air quality management practices. This nonlinear response is usually simulated using chemical transport models, and the modeling results are affected by uncertainties in emissions inputs. In this study, a high ozone episode in the southeastern United States is simulated using the Community Multiscale Air Quality (CMAQ) model. Uncertainties in ozone formation and response to emissions controls due to uncertainties in emission rates are quantified using the Monte Carlo method. Instead of propagating emissions uncertainties through the original CMAQ, a reduced form of CMAQ is formulated using directly calculated first- and second-order sensitivities that capture the nonlinear ozone concentration-emission responses. This modification greatly reduces the associated computational cost. Quantified uncertainties in modeled ozone concentrations and responses to various emissions controls are much less than the uncertainties in emissions inputs. Average uncertainties in modeled ozone concentrations for the Atlanta area are less than 10% (as measured by the inferred coefficient of variance [ICOV]) even when emissions uncertainties are assumed to vary between a factor of 1.5 and 2. Uncertainties in the ozone responses generally decrease with increased emission controls. Average uncertainties (ICOV) in emission-normalized ozone responses range from 4 to 22%, with the smaller being associated with controlling of the relatively certain point nitrogen oxide (NO_x) emissions and the larger resulting from controlling of the less certain mobile NO_x emissions. These small uncertainties provide confidence in the model applications, such as in performance evaluation, attainment demonstration, and control strategy development.     

An evaluation of contaminant migration patterns at two waste disposal sites on fractured porous media in terms of the equivalent porous medium (EPM) model

Contamination has occurred many non-indurated and bedrock systems wherein the groundwater flows almost exclusively through a network of connected, open fractures. The matrix surrounding the fractures often possesses porosity which allows contaminant diffusion into the matrix. If the diffusion rates are fast relative to the fracture groundwater velocity, transport effects may be predicted by considering the system to be an equivalent porous medium (EPM). The rapidity with which fracture/immobile-matrix equilibrium is established will be determined in part by the: fracture aperture (2b); interfracture spacing (2B); porosity in the immobile matrix (θ_im); and the matrix diffusion coefficient (D′). Two systems which are characterized by very different values of the above parameters have been studied by our laboratories. At Alkali Lake, Oregon, the EPM approach describes contaminant transport well. At Bayview Park, Ontario, the EPM approach is not appropriate. Several features of the two sites are compared to illustrate the different nature of these two sites. These features include: (1) natural characteristics of the groundwater systems; (2) contaminant distributions; (3) observed transport; and (4) computed fracture/immobile-matrix diffusion times.     

Applied tracer tests in fractured rock: Can we predict natural gradient solute transport more accurately than fracture and matrix parameters?

Applied tracer tests provide a means to estimate aquifer parameters in fractured rock. The traditional approach to analysing these tests has been using a single fracture model to find the parameter values that generate the best fit to the measured breakthrough curve. In many cases, the ultimate aim is to predict solute transport under the natural gradient. Usually, no confidence limits are placed on parameter values and the impact of parameter errors on predictions of solute transport is not discussed. The assumption inherent in this approach is that the parameters determined under forced conditions will enable prediction of solute transport under the natural gradient. This paper considers the parameter and prediction uncertainty that might arise from analysis of breakthrough curves obtained from forced gradient applied tracer tests. By adding noise to an exact solution for transport in a single fracture in a porous matrix we create multiple realisations of an initial breakthrough curve. A least squares fitting routine is used to obtain a fit to each realisation, yielding a range of parameter values rather than a single set of absolute values. The suite of parameters is then used to make predictions of solute transport under lower hydraulic gradients and the uncertainty of estimated parameters and subsequent predictions of solute transport is compared. The results of this study show that predictions of breakthrough curve characteristics (first inflection point time, peak arrival time and peak concentration) for groundwater flow speeds with orders of magnitude smaller than that at which a test is conducted can sometimes be determined even more accurately than the fracture and matrix parameters.     

MTBE Transport Screening Analysis in Vadose Zone Risk and Liability Apportionment Assessment

The problem of allocating liability cleanup costs is an arduous task when more than one potentially responsible party has contributed to the groundwater plume. This problem is most likely to be encountered when dealing with methyl-tert -butyl-ether (MTBE) contamination, as MTBE is seen to travel large distances in underlying aquifers. There has been a significant effort in the recent past to develop liability allocation methodologies that incorporate fate and transport behavior and toxicological characteristics of the contaminants. The application of such methods often requires estimation of contaminant input from the vadose zone into the underlying aquifer. A screening level analysis is presented here to develop preliminary insights on relative mass contributions arising from different source types. The analysis illustrates how different vadose zone conceptualizations lead to vastly different contaminant loadings. Parametric studies indicate that the contaminant flux into the aquifer is very sensitive to changes in water infiltration rates. Hence, a reliable estimate of this parameter is critical for equitable allocation of remedial costs. Conceptual model formulation, should focus on identifying whether the fuel present in the aquifer can flow as a separate phase. It is also important to obtain reliable estimates for fluid saturations at the site.     

Transport of reactive colloids and contaminants in groundwater: effect of nonlinear kinetic interactions

Transport of reactive colloids in groundwater may enhance the transport of contaminants in groundwater. Often, the interpretation of results of transport experiments is not a simple task as both reactions of colloids with the solid matrix and reactions of contaminants with the solid matrix and mobile and immobile colloids may be time dependent and nonlinear. Further colloid transport properties may differ from solute transport properties. In this paper, a one-dimensional model for coupled and contaminant in a porous medium (COLTRAP) is presented together with simulation results. Calculated breakthrough curves (BTC's) during contamination and decontamination show systematically the effect of nonlinear and kinetic interactions on contaminant transport in the presence of reactive colloids, and the effect of colloid transport properties that differ from solute transport properties. It is shown that in case of linear kinetic reactions, the rate of exchange of mobile and immobile colloids have a large impact on the shape of BTC's even if the solid matrix is saturated with respect to colloids. BTC's during the contamination and decontamination phase have identical shapes in this case. Moreover, the slow reactions of contaminants and colloids may lead to unretarded breakthrough of contaminants. Independent of reaction rates, nonlinear reactions lead to BTC's that are steeper during contamination than in the linear case. A characteristic aspect of nonlinear sorption is that shapes of BTC's differ during the contamination and decontamination phase. It has been observed that shapes of some of the simulated adsorption and desorption curves are similar as shapes found in experiments reported in literature. This stresses the importance of incorporating both kinetics and nonlinearity in models for coupled colloid and contaminant transport and the capability of COLTRAP to interpret experimental results. Finally, to figure out whether nonlinear processes play a role, it is very important to consider both contamination and decontamination in transport experiments.     

An overview of uncertainties in modelling groundwater solute transport

Model predictions are uncertain because of uncertainties on future and/or anthropogenic stresses, parameter values and conceptual models. The first two groups of problems can be addressed through rather systematic methods (scenario analysis, error transmission techniques, automatic calibration algorithms, etc.). However, conceptual uncertainties are rarely given adequate attention. The objective of this paper is to synthesize conceptual difficulties associated with transport. These include: (1) processes that are significant at small scales may not be relevant at large scales; (2) inversely, new processes (e.g., dispersion) emerge in response to increase in scale and the way to represent them may depend on the assumed model structure; (3) the observed shapes of both breakthrough curves and pollutant plumes are not well represented by the classical transport equation; (4) porosities and dispersivities derived from field tracer tests often exhibit a directional dependence; etc. Though not directly related to solute transport, scale effects on hydraulic conductivity may also affect solute transport modelling. When these anomalies are examined, it is concluded that they are directly or indirectly caused by heterogeneity. Current approaches for dealing with heterogeneity can be divided into stochastic and deterministic. Stochastic methods have been successful in explaining qualitatively some anomalies of solute transport, but they appear to be far from reaching a stage at which they can be used routinely for solving realistic field problems. On the other hand, when applied with care, deterministic methods have been successfully used in actual problems. Yet, it can be argued that they fail to account for small-scale variability of concentrations so that they would become ineffective when dealing with nonlinear processes, such as chemical reactions. Relevance of on-going research for overcoming these difficulties is discussed.     

Modelling of an enhanced PAH attenuation experiment and associated biogeochemical changes at a former gasworks site in southern Germany

Former manufactured gas plant sites often form a widespread contaminant source in the subsurface, leading to large plumes that contain a wide variety of tar-oil related compounds. Although most of these compounds eventually degrade naturally, the relevant processes tend to be slow and inefficient, often leaving active remediation as the only viable option to eliminate the risks of toxic substances to reach potential receptors such as surface waters or drinking water wells. In this study we use a reactive transport model to analyse the fate of a contaminant plume containing acenaphthene, methylbenzofurans and dimethylbenzofurans (i) prior to the installation of an active remediation scheme and (ii) for an enhanced remediation experiment during which O(2) and H(2)O(2) were added to the contaminated groundwater through a recirculation well. The numerical model developed for this study considers the primary contaminant degradation reactions (i.e., microbially mediated redox reactions) as well as secondary and competing mineral precipitation/dissolution reactions that affect the site's hydrochemistry and/or contaminant fate. The model was calibrated using a variety of constraints to test the uncertainty on model predictions resulting from the undocumented presence of reductants such as pyrite. The results highlight the important role of reactive transport modelling for the development of a comprehensive process understanding.     

The relation between ozone,NOx and hydrocarbons in urban and polluted rural environments

Research over the past ten years has created a more detailed and coherent view of the relation between O₃ and its major anthropogenic precursors, volatile organic compounds (VOC) and oxides of nitrogen (NO_x). This article presents a review of insights derived from photochemical models and field measurements. The ozone–precursor relationship can be understood in terms of a fundamental split into a NO_x-senstive and VOC-sensitive (or NO_x-saturated) chemical regimes. These regimes are associated with the chemistry of odd hydrogen radicals and appear in different forms in studies of urbanized regions, power plant plumes and the remote troposphere. Factors that affect the split into NO_x-sensitive and VOC-sensitive chemistry include: VOC/NO_x ratios, VOC reactivity, biogenic hydrocarbons, photochemical aging, and rates of meteorological dispersion. Analyses of ozone–NO_x–VOC sensitivity from 3D photochemical models show a consistent pattern, but predictions for the impact of reduced NO_x and VOC in indivdual locations are often very uncertain. This uncertainty can be identified by comparing predictions from different model scenarios that reflect uncertainties in meteorology, anthropogenic and biogenic emissions. Several observation-based approaches have been proposed that seek to evaluate ozone–NO_x–VOC sensitivity directly from ambient measurements (including ambient VOC, reactive nitrogen, and peroxides). Observation-based approaches have also been used to evaluate emission rates, ozone production efficiency, and removal rates of chemically active species. Use of these methods in combination with models can significantly reduce the uncertainty associated with model predictions.     

Contamination potential of nitrogen compounds in the heterogeneous aquifers of the Choushui River alluvial fan, Taiwan

This study aimed to analyze the contamination potential associated with the reactive transport of nitrate-N and ammonium-N in the Choushui River alluvial fan, Taiwan and to evaluate a risk region in developing a groundwater protection policy in 2021. In this area, an aquifer redox sequence provided a good understanding of the spatial distributions of nitrate-N and ammonium-N and of aerobic and anaerobic environments. Equiprobable hydraulic conductivity (K) fields reproduced by geostatistical methods characterized the spatial uncertainty of contaminant transport in the heterogeneous aquifer. Nitrogen contamination potential fronts for high and low threshold concentrations based on a 95% risk probability were used to assess different levels of risk. The simulated result reveals that the spatial uncertainty of highly heterogeneous K fields governs the contamination potential assessment of the nitrogen compounds along the regional flow directions. The contamination potential of nitrate-N is more uncertain than that for ammonium-N. The high nitrate-N concentrations (> or =3 mg/L) are prevalent in the aerobic environment. The low concentration nitrate-N plumes (0.5-3 mg/L) gradually migrate to the mid-fan area and to a maximum distance of 15 km from the aerobic region. The nitrate-N plumes pose a potential human health risk in the aerobic and anaerobic environments. The ammonium-N plumes remain stably confined to the distal-fan and partial mid-fan areas.     

The mathematical modelling of total nitrogen contamination transport via groundwater from a sugar factory in Eskisehir, Turkey

In this study, mathematical modelling of the total nitrogen contamination transport in a porous medium was evaluated in order to determine the potential groundwater pollution caused by a sugar factory in the Eskisehir region of Turkey. Analytical solutions of mathematical modelling were performed to show graphically the distributions of contaminant concentrations. Multiflow computer programming was used to determine the distribution of contaminant concentrations with respect to time and distance. The distribution distance of contaminant concentrations was determined at any time interval. From this study, the potential pollution of groundwater can be effectively estimated. Prediction of pollution by means of the model will help to form the future predictions of water resource management.     

Database uncertainty as a limiting factor in reactive transport prognosis

The effect of uncertainties in thermodynamic databases on prediction performances of reactive transport modeling of uranium (VI) is investigated with a Monte Carlo approach using the transport code TReaC. TReaC couples the transport model to the speciation code PHREEQC by a particle tracking method. A speciation example is given to illustrate the effect of uncertainty in thermodynamic data on the predicted solution composition. The transport calculations consequently show the prediction uncertainty resulting from uncertainty in thermodynamic data. A conceptually simple scenario of elution of uranium from a sand column is used as an illustrating example. Two different cases are investigated: a carbonate-enriched drinking water and an acid mine water associated with uranium mine remediation problems. Due to the uncertainty in the relative amount of positively charged and neutral solution species, the uncertainty in the thermodynamic data also infers uncertainty in the retardation behavior. The carbonated water system shows the largest uncertainties in speciation calculation. Therefore, the model predictions of total uranium solubility have a broad range. The effect of data uncertainty in transport prediction is further illustrated by a prediction of the time when eluted uranium from the column exceeds a threshold value. All of these Monte Carlo transport calculations consume large amounts of computing time.