A Comparison of Six Transport Models of the MADE-1 Experiment Implemented With Different Types of Hydraulic Data.

Six conceptually different transport models were applied to the macrodispersion experiment (MADE)-1 field tracer experiment as a first major attempt for model comparison. The objective was to show that complex mass distributions in heterogeneous aquifers can be predicted without calibration of transport parameters, solely making use of structural and flow data. The models differ in their conceptualization of the heterogeneous aquifer structure, computational complexity, and use of conductivity data obtained from various observation methods (direct push injection logging, DPIL, grain size analysis, pumping tests and flowmeter). They share the same underlying physical transport process of advection by the velocity field solely. Predictive capability is assessed by comparing results to observed longitudinal mass distributions of the MADE-1 experiment. The decreasing mass recovery of the observed plume is attributed to sampling and no physical process like mass transfer is invoked by the models. Measures like peak location and strength are used in comparing the modeled and measured plume mass distribution. Comparison of models reveals that the predictions of the solute plume agree reasonably well with observations, if the models are underlain by a few parameters of close values: mean velocity, a parameter reflecting log-conductivity variability, and a horizontal length scale related to conductivity spatial correlation. The robustness of the results implies that conservative transport models with appropriate conductivity upscaling strategies of various observation data provide reasonable predictions of plumes longitudinal mass distribution, as long as key features are taken into account.

Transport-limited kinetics of phosphate retention on iron-coated sand and practical implications.

Iron-coated sand (ICS) is a by-product from drinking water treatment made of sand coated with ferric iron (hydr)oxides. It is considered a suitable material for large-scale measures for phosphate removal from natural and agricultural waters to prevent eutrophication. Previous studies demonstrated that the residence time of water must be very long to reach equilibrium partitioning between phosphate and ICS but specifics for application are missing. First, SEM-EDX images were used to support the conceptual assumption that P adsorption inside the coating is a transport-limited process. Second, a conceptual model of phosphate adsorption was proposed considering two types of sites: one type with fast adsorption kinetics and reaching equilibrium with the percolating solution, and another type for which adsorption is also reversible but described by pseudo-first-order kinetics. The latter is conceived to account for transport-limited adsorption in the interior of the coating while the former fraction of sites is assumed to be easily accessible and located close to the grain surface. Third, the kinetics of phosphate adsorption on ICS were quantitatively determined to describe and predict phosphate retention in filters under various flow conditions. The model was calibrated and validated with long-term column experiments, which lasted for 3500 h to approach equilibrium on the slowly reacting sites. The model reproduced the outflowing phosphate concentrations: the pronounced increase after a few pore volumes and the slow increase over the remaining part of the experiment. The parameterized model was also able to predict the time evolution of phosphate concentrations in the outflow of column experiments with different flow velocities, flow interruption, and in desorption experiments. The equilibrium partition coefficient for the experimental conditions was identified as 28.1 L/g-Fe at pH 6.8 and a phosphate concentration of 1.7 mg-P / L. The optimized first-order mass transfer coefficient for the slow adsorption process was 1.56 10-4 h-1, implying that the slow adsorption process has a time scale of several months. However, based on the parameterized model, the slow adsorption process accounted for 95.5% of the equilibrium adsorption capacity, emphasizing the potential relevance of this process for practical applications. The implications for the design, operation, and lifespan of ICS filters are exemplarily illustrated for different scenarios.

Evidence Based Estimation of Macrodispersivity for Groundwater Transport Applications.

The scope of this work is to discuss the proper choice of macrodispersion coefficients in modeling contaminant transport through the advection dispersion equation (ADE). It is common to model solute concentrations in transport by groundwater with the aid of the ADE. Spreading is quantified by macrodispersivity coefficients, which are much larger than the laboratory observed pore-scale dispersivities. In the frame of stochastic theory, longitudinal macrodispersivity is related to the hydraulic conductivity spatial variability via its statistical moments (mean, variance, integral scales), which are generally determined by geostatistical analysis of field measurements. In many cases, especially for preliminary assessment of contaminant spreading, these data are not available and ad hoc values are adopted by practitioners. The present study aims at recommending dispersivity values based on a thorough analysis of tens of field experiments. Aquifers are classified as of weak, medium, and high heterogeneity and for each class a range of macrodispersivity values is recommended. Much less data are available for the transverse macrodispersivities, which are significantly smaller than the longitudinal one. Nevertheless, a few realistic values based on field data, are recommended for applications. Transport models using macrodispersivities can predict mean concentrations, different from the local ones. They can be used for estimation of robust measures, like plumes spatial moments, longitudinal mass distribution and breakthrough curves at control planes.

How to Find Aquifer Statistics Utilizing Pumping Tests? Two Field Studies Using welltestpy.

We present a workflow to estimate geostatistical aquifer parameters from pumping test data using the Python package welltestpy. The procedure of pumping test analysis is exemplified for two data sets from the Horkheimer Insel site and from the Lauswiesen site, Germany. The analysis is based on a semi-analytical drawdown solution from the upscaling approach Radial Coarse Graining, which enables to infer log-transmissivity variance and horizontal correlation length, beside mean transmissivity, and storativity, from pumping test data. We estimate these parameters of aquifer heterogeneity from type-curve analysis and determine their sensitivity. This procedure, implemented in welltestpy, is a template for analyzing any pumping test. It goes beyond the possibilities of standard methods, for example, based on Theis' equation, which are limited to mean transmissivity and storativity. A sensitivity study showed the impact of observation well positions on the parameter estimation quality. The insights of this study help to optimize future test setups for geostatistical aquifer analysis and provides guidance for investigating pumping tests with regard to aquifer statistics using the open-source software package welltestpy.

ogs5py: A Python-API for the OpenGeoSys 5 Scientific Modeling Package.

High-performance numerical codes are an indispensable tool for hydrogeologists when modeling subsurface flow and transport systems. But as they are written in compiled languages, like C/C++ or Fortran, established software packages are rarely user-friendly, limiting a wider adoption of such tools. OpenGeoSys (OGS), an open-source, finite-element solver for thermo-hydro-mechanical-chemical processes in porous and fractured media, is no exception. Graphical user interfaces may increase usability, but do so at a dramatic reduction of flexibility and are difficult or impossible to integrate into a larger workflow. Python offers an optimal trade-off between these goals by providing a highly flexible, yet comparatively user-friendly environment for software applications. Hence, we introduce ogs5py, a Python-API for the OpenGeoSys 5 scientific modeling package. It provides a fully Python-based representation of an OGS project, a large array of convenience functions for users to interact with OGS and connects OGS to the scientific and computational environment of Python.

Transition state theory with Tsallis statistics.

We discuss the rate of an elementary chemical reaction. We use the reaction path and especially its saddle point on the potential energy surface. The reaction path connects reactant and product of a reaction over the transition state (TS). Usually, the TS is assumed near or at the single saddle point of the reaction path. By means of comparison of the statistics of states at the reactant and at the TS, one can estimate the reaction rate by the Eyring theory. We propose to use the Tsallis statistics at the TS, a statistics of seldom accidents. Thus, we propose to generalize the well-known Boltzmann-Gibbs statistics, which is the limiting case of the Tsallis statistics. We use features of this nonextensive thermostatistics. The basic properties of the statistics are used to derive (approximated) partition functions, and they are applied on reaction rates. The approximation includes a factorization of the partition functions. The theory is applied to HCN isomerization to HNC, and to the reaction H(2) + CN --> H + HCN. It allows an accordance with experimental estimations of the reaction rates.

A Critical Analysis of Transverse Dispersivity Field Data.

Transverse dispersion, or tracer spreading orthogonal to the mean flow direction, which is relevant e.g, for quantifying bio-degradation of contaminant plumes or mixing of reactive solutes, has been studied in the literature less than the longitudinal one. Inferring transverse dispersion coefficients from field experiments is a difficult and error-prone task, requiring a spatial resolution of solute plumes which is not easily achievable in applications. In absence of field data, it is a questionable common practice to set transverse dispersivities as a fraction of the longitudinal one, with the ratio 1/10 being the most prevalent. We collected estimates of field-scale transverse dispersivities from existing publications and explored possible scale relationships as guidance criteria for applications. Our investigation showed that a large number of estimates available in the literature are of low reliability and should be discarded from further analysis. The remaining reliable estimates are formation-specific, span three orders of magnitude and do not show any clear scale-dependence on the plume traveled distance. The ratios with the longitudinal dispersivity are also site specific and vary widely. The reliability of transverse dispersivities depends significantly on the type of field experiment and method of data analysis. In applications where transverse dispersion plays a significant role, inference of transverse dispersivities should be part of site characterization with the transverse dispersivity estimated as an independent parameter rather than related heuristically to longitudinal dispersivity.