Reactive Transport Parameters Research Articles

Effect of particle size on the transport of polystyrene micro- and nanoplastic particles through quartz sand under unsaturated conditions

Micro- and nanoplastics (MNPs) are contaminants of emerging concern recently found in soil ecosystems. Their presence in terrestrial environments and their migration to aquatic environments may become a risk for the health of ecosystems and, through them, of humans. Understanding the interaction between particle properties and physicochemical and hydrodynamic factors is crucial to evaluate their fate and their potential infiltration towards groundwater. This study investigates the impact of particle size on MNPs transport through sand under unsaturated conditions. Infiltration column experiments with polystyrene MNPs ranging from 120 to 10,000 nm were conducted and supported by numerical modelling to derive reactive transport parameters. Results show a significant effect of particle size on the transport of MNPs, with higher recovery values observed for smaller particles (120 nm; 95.11%) compared to larger particles (1,000 nm; 71.44%). No breakthrough was observed for 10,000 nm particles, indicating a complete retention within the quartz sand matrix. DLVO theory confirmed the dominance of electrostatic repulsive forces between MNPs and sand grains, suggesting an unfavourable environment for MNPs to adhere to quartz sand. Consequently, particle retention in the sand matrix occurs predominantly by physical processes. Equilibrium sorption modelling reveals that larger particles (1,000 nm) tend to be immobilized in small pores throats due to straining, resulting in lower recoveries. When they are not trapped, particles tend to travel faster through preferential flows due to a size exclusion effect, evidenced by shorter arrival times at the column outlet compared to tracers. These findings highlight the influence of particle size on the transport and retention of MNPs in quartz sand under unsaturated conditions and contribute to a better understanding of their transport dynamics and environmental fate.

A 3D convolutional neural network model with multiple outputs for simultaneously estimating the reactive transport parameters of sandstone from its CT images

Porosity, tortuosity, specific surface area (SSA), and permeability are four key parameters of reactive transport modeling in sandstone, which are important for understanding solute transport and geochemical reaction processes in sandstone aquifers. These four parameters reflect the characteristics of pore structure of sandstone from different perspectives, and the traditional empirical formulas cannot make accurate predictions of them due to their complexity and heterogeneity. In this paper, eleven types of sandstone CT images were firstly segmented into numerous subsample images, the porosity, tortuosity, SSA, and permeability of the subsamples were calculated, and the dataset was established. The 3D convolutional neural network (CNN) models were subsequently established and trained to predict the key reactive transport parameters based on subsample CT images of sandstones. The results demonstrated that the 3D CNN model with multiple outputs exhibited excellent prediction ability for the four parameters compared to the traditional empirical formulas. In particular, for the prediction of tortuosity and permeability, the 3D CNN model with multiple outputs even showed slightly better prediction ability than its single-output variant model. Additionally, it demonstrated good generalization performance on sandstone CT images not included in the training dataset. The study showed that the 3D CNN model with multiple outputs has the advantages of simplifying operation and saving computational resources, which has the prospect of popularization and application.

Characterization of evolution of reactive transport parameters during leaching process of sandstone uranium ore by combining porosity and lacunarity

During the in-situ leaching process of sandstone uranium ore deposits, the dynamic evolution of reactive transport parameters, including permeability, tortuosity, and specific surface area (SSA), plays a crucial role in solution flow and solute transport. Characterizing the evolution of these parameters is essential for understanding the leaching process. However, the heterogeneous pore structure of sandstone renders porosity alone insufficient to capture changes in these parameters. This study combines porosity and lacunarity to comprehensively characterize these parameters. For this purpose, leaching experiments were conducted on sandstone uranium ore samples, and CT imaging was performed at different leaching time points. The evolution of reactive transport parameters was analyzed by studying cubic subsamples from the images. The results indicate that both porosity and lacunarity are significant factors influencing the reactive transport parameters. However, neither parameter alone adequately characterizes their evolution. In contrast, combining them accurately characterizes the evolution of reactive transport parameters. Porosity reflects pore quantity, while lacunarity represents pore heterogeneity. Combining these measures facilitates a comprehensive understanding of the evolution of reactive transport parameters and the influence of pore microstructure on macroscopic reactive transport parameters. This research provides valuable insights for optimizing the leaching process in sandstone uranium ore deposits.

Evolution of pore structure and reactive transport parameters during acid leaching of sandstone uranium ore

The changes in the micro-scale pore structure during the acid leaching of sandstone uranium ore significantly affect its reactive transport parameters, which, in turn, directly influence the leaching efficiency of uranium. Consequently, understanding and managing the dynamic evolution of the pore structure of sandstone at micro-scale during acid leaching is beneficial for enhancing the leaching efficiency of uranium. This paper employs a dynamic continuous water-rock reaction experiment on sandstone uranium ore to simulate the in-situ acid leaching process. Additionally, X-ray micro-computed tomography (μCT) scanning was utilized to produce three-dimensional (3D) images at various leaching stages. Subsequently, image processing techniques were employed to characterize and parameterize the pore structure within these images. The results revealed that, during the leaching process, mineral dissolution led to an increase in the interconnected pores, while there was a decrease in the isolated pores. Nonetheless, at the leading edge of the sandstone uranium ore, detachment of mineral grains occurred during the leaching process along the direction of fluid flow. The migration of mineral grains resulted in a reduction of interconnected pores and an increase in the isolated pores. The analysis of 3D images indicated that porosity, permeability, the percentage of connected pore area and the reactive surface area exhibited similar variation trends throughout the leaching process. Furthermore, the permeability, the percentage of connected pore area and the reactive surface area displayed a positive correlation with porosity. The study holds valuable insights to develop a deeper understanding of the evolutionary patterns regarding the pore structure during the in-situ acid leaching of sandstone uranium ore.

Various Bacterial Attachment Functions and Modeling of Biomass Distribution in MICP Implementations

Microbial induced calcium carbonate precipitation (MICP) offers a robust technique to improve strength and stiffness properties of subsurface soils supporting infrastructures. Several unknown factors, including the MICP reactive transport parameters, however, limit the ability to predict spatial distribution of calcium carbonate (CaCO3) precipitation within a subsurface area and with depth. As it was shown that calcium carbonate distribution is highly affected by biomass profiles in subdomains, five bacteria attachment models (constant-rate, power-law, exponential, gamma distribution, and “cstr based on colloid attachment theory”) were calibrated here using data from both small- and large-scale testing programs. Out of the five models, colloid attachment theory with modified velocity and straining terms was shown to be the most promising approach in yielding the most fitted CaCO3 distribution compared with the experimental data. A new parameter, cstr, was incorporated to modify straining and the constraint peak value of biomass attachment due to straining at distances larger than a 0.14×sample size. Using the results from the numerical simulations, relationships were developed for velocity and straining coefficients of “the cstr based on colloid attachment theory” (hereafter “colloid attachment cstr”) as a function of bacteria size, soil particle size, sample size, volume of injected bacteria, and soil pore volume.

Column-Test Data Analyses and Geochemical Modeling to Determine Uranium Reactive Transport Parameters at a Former Uranium Mill Site (Grand Junction, Colorado)

The long-term release of uranium from residual sources at former uranium mill sites was often not considered in prior conceptual and numerical models, as contaminant removal focused on meeting radiological standards. To determine the reactive transport parameters, column tests were completed with various influent waters (deionized water, site groundwater, and local river water) on sediment from identified areas with elevated uranium on the solid phase in (1) vadose-zone (VZ) sediments, (2) saturated-zone sediments with higher organic carbon content, and (3) both vadose- and saturated-zone sediments with additional gypsum content. The gypsum was precipitated when low-pH, high-sulfate, tailings fluids or acidic waste disposal water were buffered by natural aquifer calcite dissolution. In general, the resulting uranium release was higher in the sediments with greater uranium concentrations. However, the addition of deionized water (DI) to the VZ sediments delayed the uranium release until higher-alkalinity groundwater was added. Higher-alkalinity river water continued to remove uranium from the VZ sediments for an extended number of pore volumes, with the uranium being above typical standards. Thus, river flooding is more efficient at removing uranium from VZ sediments than precipitation events (DI water in column tests). Organic carbon provides a stronger uranium sorption surface, which can be explained with geochemical modeling or a larger constant sorption coefficient (Kd). Without organic carbon, the typical sorption in sands and gravels is easily measurable, but sorption is stronger at lower, water-phase uranium concentrations. This effect can be simulated with geochemical modeling, but not with a constant Kd. Areas with gypsum create situations in which geochemical sorption is more difficult to simulate, which is likely due to the presence of uranium within mineral coatings. All the above mechanisms for uranium release must be considered when evaluating remedial strategies. Column testing provides initial input parameters that can be used in future reactive transport modeling to evaluate long-term uranium release rates and concentrations.

Asymptotic behavior of a random oscillating nonlinear reactive transport in thin turbulent layers

We consider a nonlinear reactive transport of a scalar field in a domain composed of a bounded region lined by turbulent thin layers. We suppose that these layers display a cellular microstructure with thin varying thickness. We suppose that, within the layers, the diffusion, reaction, and velocity coefficients admit random large‐scale structures. Under mixing properties of the diffusion, reaction, and velocity processes, we study the asymptotic behavior of the problem with respect to a vanishing parameter describing the thickness of the layers. We derive the effective flux boundary condition on the surface of the fixed region which coincides with the lower surface of the layers. This flux boundary condition consists in a generalized nonlinear Robin condition involving some nonlocal random effects which emerge asymptotically due to the random fluctuations of the reactive transport parameters in the layers.

Multiscale modeling of CO2-induced carbonate dissolution: From core to meter scale

Reactive transport models can be used to predict the long-term storage capacity of CO2 in carbonate formations if the parameters that couple physical and chemical interactions can be calibrated from centimeters (laboratory-scale) to kilometers (field-scale). However, calibration across length scales is challenging in highly reactive and heterogeneous carbonate reservoirs. In this study we translated simulations of CO2-induced carbonate dissolution and transport processes of centimeter-sized cores to meter-sized rock blocks. The meter-sized rocks represent an intermediate scale between laboratory experiments and field demonstrations.We conducted brute-force, meter-sized simulations maintaining the same grid resolution used to successfully model rock heterogeneities and physical behaviors observed in laboratory experiments. To do this, we applied multi-point statistics to generate rock heterogeneity that honors characterization data, and adopted the reaction and transport parameters (e.g., reaction rate kinetics, porosity-permeability relationship) from models calibrated by core-flood experiments.We used the high-resolution simulation data sets to understand the interplay between carbonate reactivity, flow velocity, and rock heterogeneity on the development and consequences of dissolution fronts at a meter scale, and in particular how parameters that couple chemistry and transport change at variable length scales. The modeling results reveal scale dependence of porosity-permeability relationship and carbonate reactivity. We found that upscaling reactive transport processes from centimeters to meters requires: (1) Effective representation of initial rock heterogeneity and related preferential flow field. In more permeable rocks, several dissolution fingers or wormholes form and grow along the flow direction, competing for reactive solution and leading to fast breakthrough. In less permeable rocks, a single dissolution channel forms with a dramatic increase in lateral branching due to the resistance from low-permeability regions along the flow path. (2) Higher exponential values for porosity-permeability power-law correlations. The value of the power parameter n increases by about two times as we scale the dissolution process from centimeters to meters. (3) Lower carbonate reaction rates. Carbonate reaction rates obtained for meter-sized models are about ten times slower than those for the smaller core-flood experiments. We also used the high-resolution meter-sized simulations to upscale carbonate dissolution by coarsening the representative elementary volumes (or grids). The calibrated reactive transport parameters are consistent with those derived from scaling analysis.The upscaling analysis developed in this study improves our understanding of carbonate dissolution (especially wormhole development) and associated reactive transport across time and length scales, providing a useful basis for establishing a direct relationship between core-scale and field-scale models. Additional work is needed to see if relationships developed from single-phase reactive transport processes shown in this work are directly applicable to in-situ reservoir multiphase flow conditions arising from geological storage of CO2.

Evaluation of EOC removal processes during artificial recharge through a reactive barrier

A reactive barrier that consisted of vegetable compost, iron oxide and clay was installed in an infiltration basin to enhance the removal of emerging organic compounds (EOCs) in the recharge water. First-order degradation rates and retardation factors were jointly estimated for 10 compounds using a multilayer reactive transport model, whose flow and conservative transport parameters were previously estimated using hydraulic head values and conservative tracer tests. Reactive transport parameters were automatically calibrated against the concentration of EOCs measured at nine monitoring points. The degradation rate of each compound was estimated for three zones defined according to the redox state, and retardation coefficients were estimated in two zones defined according to the organic matter content. The fastest degradation rates were obtained for the reactive barrier, and the estimated values were similar to or higher than those estimated in column and/or field experiments for most of the compounds (8/10). Estimated retardation coefficients in the reactive barrier were higher than in the rest of the aquifer in most cases (8/10) and higher than those values estimated in previous studies. Based on the results obtained in this study the reactive barrier seems to be able to enhance the removal of EOCs.

The fate of organic micropollutants during long-term/long-distance river bank filtration

The fate of organic micropollutants during long-term/long-distance river bank filtration (RBF) at a temporal scale of several years was investigated along a row of monitoring wells perpendicular to the Lek River (the Netherlands). Out of 247 compounds, which were irregularly analyzed in the period 1999–2013, only 15 were detected in both the river and river bank observation wells. Out of these, 10 compounds (1,4-dioxan, 1,5-naphthalene disulfonate (1,5-NDS), 2-amino-1,5-NDS, 3-amino-1,5-NDS, AOX, carbamazepine, EDTA, MTBE, toluene and triphenylphosphine oxide) showed fully persistent behavior (showing no concentration decrease at all), even after 3.6years transit time. The remaining 5 compounds (1,3,5-naphthalene trisulfonate (1,3,5-NTS), 1,3,6-NTS, diglyme, iopamidol, triglyme) were partially removed. Their reactive transport parameters (removal rate constants/half-lives, retardation coefficients) were inferred from numerical modeling. In addition, maximum half-lives for 14 of the fully removed compounds, for which the data availability was sufficient to deduce 100% removal during sub-surface passage, were approximated based on travel times to the nearest well. The study is one of very few reporting on the long-term field-scale behavior of organic micropollutants. It highlights the efficiency of RBF for water quality improvement as a pre-treatment step for drinking water production. However, it also shows the very persistent behavior of various compounds in groundwater.

Sorption and transformation of the reactive tracers resazurin and resorufin in natural river sediments

Abstract. Resazurin (Raz) and its reaction product resorufin (Rru) have increasingly been used as reactive tracers to quantify metabolic activity and hyporheic exchange in streams. Previous work has indicated that these compounds undergo sorption in stream sediments. We present laboratory experiments on Raz and Rru transport, sorption, and transformation, consisting of 4 column and 72 batch tests using 2 sediments with different physicochemical properties under neutral (pH = 7) and alkaline (pH = 9) conditions. The study aimed at identifying the key processes of reactive transport of Raz and Rru in streambed sediments and the experimental setup best suited for their determination. Data from column experiments were simulated by a travel-time-based model accounting for physical transport, equilibrium and kinetic sorption, and three first-order reactions. We derived the travel-time distributions directly from the breakthrough curve (BTC) of the conservative tracer, fluorescein, rather than from fitting an advective-dispersive transport model, and inferred from those distributions the transfer functions of Raz and Rru, which provided conclusive approximations of the measured BTCs. The most likely reactive transport parameters and their uncertainty were determined by a Markov chain–Monte Carlo approach. Sorption isotherms of both compounds were obtained from batch experiments. We found that kinetic sorption dominates sorption of both Raz and Rru, with characteristic timescales of sorption in the order of 12 to 298 min. Linear sorption models for both Raz and Rru appeared adequate for concentrations that are typically applied in field tracer tests. The proposed two-site sorption model helps to interpret transient tracer tests using the Raz–Rru system.

Horizontal spatial correlation of hydraulic and reactive transport parameters as related to hierarchical sedimentary architecture at the Borden research site

Key Points auto and cross correlation have a common correlation structure correlation structure is defined by hierarchical sedimentary architecture stratal lengths at different scales define correlation substructures

Upscaling retardation factor in hierarchical porous media with multimodal reactive mineral facies

Aquifer heterogeneity controls spatial and temporal variability of reactive transport parameters and has significant impacts on subsurface modeling of flow, transport, and remediation. Upscaling (or homogenization) is a process to replace a heterogeneous domain with a homogeneous one such that both reproduce the same response. To make reliable and accurate predictions of reactive transport for contaminant in chemically and physically heterogeneous porous media, subsurface reactive transport modeling needs upscaled parameters such as effective retardation factor to perform field-scale simulations. This paper develops a conceptual model of multimodal reactive mineral facies for upscaling reactive transport parameters of hierarchical heterogeneous porous media. Based on the conceptual model, covariance of hydraulic conductivity, sorption coefficient, flow velocity, retardation factor, and cross-covariance between flow velocity and retardation factor are derived from geostatistical characterizations of a three-dimensional unbounded aquifer system. Subsequently, using a Lagrangian approach the scale-dependent analytical expressions are derived to describe the scaling effect of effective retardation factors in temporal and spatial domains. When time and space scales become sufficiently large, the effective retardation factors approximate their composite arithmetic mean. Correlation between the hydraulic conductivity and the sorption coefficient can significantly affect the values of the effective retardation factor in temporal and spatial domains. When the temporal and spatial scales are relatively small, scaling effect of the effective retardation factors is relatively large. This study provides a practical methodology to develop effective transport parameters for field-scale modeling at which remediation and risk assessment is actually conducted. It does not only bridge the gap between bench-scale measurements to field-scale modeling, but also provide new insights into the influence of hierarchical mineral distribution on effective retardation factor.

Field leaching of pesticides at five test sites in Hawaii: modeling flow and transport

Physically based tier-II models may serve as possible alternatives to expensive field and laboratory leaching experiments required for pesticide approval and registration. The objective of this study was to predict pesticide fate and transport at five different sites in Hawaii using data from an earlier field leaching experiment and a one-dimensional tier-II model. As the predicted concentration profiles of pesticides did not provide close agreement with data, inverse modeling was used to obtain adequate reactive transport parameters. The estimated transport parameters of pesticides were also utilized in a tier-I model, which is currently used by the state authorities to evaluate the relative leaching potential. Water flow in soil profiles was simulated by the tier-II model with acceptable accuracy at all experimental sites. The observed concentration profiles and center of mass depths predicted by the tier-II simulations based on optimized transport parameters provided better agreements than did the non-optimized parameters. With optimized parameters, the tier-I model also delivered results consistent with observed pesticide center of mass depths. Tier-II numerical modeling helped to identify relevant transport processes in field leaching of pesticides. The process-based modeling of water flow and pesticide transport, coupled with the inverse procedure, can contribute significantly to the evaluation of chemical leaching in Hawaii soils.

Influence of Sedimentary Bedding on Reactive Transport Parameters under Unsaturated Conditions

Moisture and contaminant transport in partially saturated, heterogeneous, layered sediments is typically anisotropic. Solute transport parameters, including dispersivity and the adsorption coefficient, and the modeled concentration of reactive minerals may depend on the direction of flow with respect to sedimentary layering. Reaction rates, in contrast, should be independent of flow direction. We determined the influence of flow direction on transport parameters for nonreactive (Br−) and reactive (cobalt ethylenediaminetetraacetic acid [Co(II)EDTA2−]) solutes under partially saturated conditions by imposing flow either parallel to or across sedimentary bedding in 11 intact sediment cores of various textures. Higher dispersivity of nonreactive tracers in parallel‐bed cores suggested fluid channeling through permeable layers, while low‐conductivity layers dampened channeling in cross‐bed samples. Rates of transformation of Co(II)EDTA2− into Co(III)EDTA− and of disassociation of Co2+ and EDTA4− were modeled assuming that the reaction rates were independent of the flow direction. The concentration of Mn oxides that was responsible for the transformation reaction was dependent on the flow direction, which governed the extent of contact between the solution and the solid phase. Similarly, the adsorption constants of Co(II)EDTA2− and Co(III)EDTA− were dependent on the flow direction but were also unique for each experiment. The modeled concentration of reactive minerals was the most sensitive parameter describing the reaction and transformation of Co(II)EDTA2−

Multitracer Test Approach to Characterize Reactive Transport in Karst Aquifers

A method to estimate reactive transport parameters as well as geometric conduit parameters from a multitracer test in a karst aquifer is provided. For this purpose, a calibration strategy was developed applying the two-region nonequilibrium model CXTFIT. The ambiguity of the model calibration was reduced by first calibrating the model with respect to conservative tracer breakthrough and later transferring conservative transport parameters to the reactive model calibration. The reactive transport parameters were only allowed to be within a defined sensible range to get reasonable calibration values. This calibration strategy was applied to breakthrough curves obtained from a large-scale multitracer test, which was performed in a karst aquifer of the Swabian Alb, Germany. The multitracer test was conducted by the simultaneous injection of uranine, sulforhodamine G, and tinopal CBS-X. The model succeeds to represent the tracer breakthrough curves (TBCs) of uranine and sulforhodamine G and verifies that tracer-rock interactions preferably occur in the immobile fluid region, although the fraction of this region amounts to only 3.5% of the total water. However, the model failed to account for the long tailing observed in the TBC of tinopal CBS-X. Sensitivity analyses reveal that model results for the conservative tracer transport are most sensitive to average velocity and volume fraction of the mobile fluid region, while dispersion and mass transfer coefficients are least influential. Consequently, reactive tracer calibration allows the determination of sorption sites in the mobile and immobile fluid region at small retardation coefficients.

Identifying geochemical processes by inverse modeling of multicomponent reactive transport in the Aquia aquifer

Modeling reactive geochemical transport in the subsurface is a powerful tool for understanding and interpreting geochemical processes in aquifer systems. Different conceptual models can include different combinations of geochemical processes. A limitation of current inverse models is that they are based only on one conceptual model, which may lead to statistical bias and underestimation of uncertainty. We present a stepwise inverse modeling methodology that can include any number of conceptual models and thus consider alternate combinations of processes, and it can provide a quantitative basis for selecting the best among them. We applied the inverse methodology to modeling the geochemical evolution in the Aquia aquifer (Maryland, USA) over 105 yr. The inverse model accounts for aqueous complexation, acid-base and redox reactions, cation exchange, proton surface complexation, and mineral dissolution and precipitation; identifies relevant geochemical processes; and estimates key reactive transport parameters from available hydrogeochemical data. Inverse modeling provides optimum estimates of transmissivities, leakage rates, dispersivities, cation exchange capacity (CEC), cation selectivities, and initial and boundary concentrations of selected chemical components. Inverse modeling with multiple conceptual models helps to identify the most likely physical and chemical processes in the paleohydrology and paleogeochemistry of the Aquia aquifer. Identification criteria derived from information theory are used to select the best among ten candidate conceptual models. In the final model, both proton surface complexation and methane oxidation are identified as relevant geochemical processes.

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.

Determination of bacterial and viral transport parameters in a gravel aquifer assuming linear kinetic sorption and desorption

The bacteria Escherichia coli and Pseudomonas putida, and the bacteriophage virus H40/1 are examined both for their transport behaviour relative to inert solute tracers and for their modelability under natural flow conditions in a gravel aquifer. The microbes are attenuated in the following sequence: H40/1≥ P. putida≫ E. coli. The latter is desorbed almost completely within a few days. Breakthrough and recovery curves of the simultaneously injected non-reactive tracers are simulated with the 2D and 1D dispersion equation, in order to ascertain longitudinal dispersivity ( α L) and mean flow time ( T 0). Mathematical modelling is difficult due to the aquifer heterogeneity, which results in preferential flow paths between injection and observation wells. Therefore, any attempt of fitting the dispersion model (DM) to the entire inert-tracer breakthrough curve (BTC) fails. Adequate fitting of the model to measured data only succeeds using a DM consisting of a superposition of several BTCs, each representing another set of flow paths. This gives rise to a multimodal, rather than a Gaussian groundwater velocity distribution. Only hydraulic parameters derived from the fastest partial curve, which is fitted to the rising part of the Uranine BTC, are suitable to model microbial breakthroughs. The hydraulic parameters found using 2D and 1D models were nearly identical. Their values were put into an analytical solution of 1D advective-dispersive transport combined with two-site reaction model introduced by Cameron and Klute [Cameron, D.R., Klute, A., 1977. Convective-dispersive solute transport with a combined equilibrium and kinetic adsorption model. Water Resour. Res. 13, 183–189], in order to identify reactive transport parameters (sorption/desorption) and attenuation mechanisms for the microbes migration. This shows that the microbes are almost entirely transported through preferential flow paths, which are represented by the first partial curve. Inert tracers, however, also spread along less permeable pathways.