Solute Transport Dynamics Research Articles

Effect of biochar application on physiochemical properties and nitrate degradation rate in a Siliciclastic Riverine Sandy soil

This study investigated the efficacy of biochar as a soil amendment for enhancing soil physicochemical properties and solute transport dynamics, with implications for agricultural sustainability and environmental stewardship. Batch laboratory experiments and column studies were conducted to assess the effects of biochar application on soil parameters and solute transport under saturated conditions. The saturation soil extraction approach was employed in batch leaching tests, while column experiments replicated subsurface conditions. Transport modeling using CXTFIT 2.1 elucidated solute dispersion dynamics in biochar-amended soils. Batch experiments revealed significant alterations in soil pH, electrical conductivity, and nutrient release following biochar addition. Biochar exhibited adsorption capacity for fluoride ions and released dissolved organic carbon, highlighting its potential for soil carbon sequestration and microbial activity. Column studies demonstrated enhanced solute dispersion and increased microbial activity in biochar-amended soils, as evidenced by changes in breakthrough curves and degradation rates of nitrate. Indeed, nitrate first-order degradation coefficients were 9.08E-06 for the column with only sandy soil, 3.09E-05 and 1.47E-04 for the columns with minimum and maximum doses of biochar respectively. Biochar application significantly influenced soil physicochemical properties and solute transport dynamics, with potential implications for nutrient management and contaminant attenuation in agricultural systems. Despite limitations in laboratory-scale experiments, this research provides valuable insights into biochar-soil interactions. It underscores the need for further investigation under field conditions to validate findings and optimize biochar management practices for sustainable soil and environmental management.

Ensemble surrogate modeling of advective-dispersive transport with intraparticle diffusion model for column-leaching test

Column-leaching tests are a common approach for assessing the leaching behavior and resulting environmental risks of contaminated soils and waste materials, which are frequently reused for various construction purposes. The observed breakthrough curves of the contaminants are influenced by the complex dynamics of solute transport and kinetic inter-phase mass transfer. Disentangling these interactions necessitates numerical models. However, inverse modeling and sensitivity analysis can be time-consuming, especially when sorption kinetics are explicitly described by intraparticle diffusion, which requires discretizing the domain both in the flow direction along the column axis and inside the grains. To circumvent the need for such computationally intensive models, we have developed two different ensemble surrogate models. These models employ two separate ensemble methods: random forest stacking and inverse-distance weighted interpolation. Each method is applied to base surrogate models that cover different parts of the parameter space. The base surrogate models use the method of Extremely randomized Trees (ExtraTrees). The defined parameter range is based on the German standard for column-leaching tests. To optimize the base surrogate models, we utilized adaptive-sampling methods based on three distinct infill criteria: maximizing the expected improvement, staying within a certain Mahalanobis distance to the best estimate (both for exploitation), and maximizing the standard deviation (for exploration). The ensemble surrogate model demonstrates excellent performance in emulating the behavior of the original numerical model, with a relative root mean squared error of 0.09. We applied our proposed ensemble surrogate model to estimate the complete posterior parameter distribution using Simulation-Based Inference, specifically Neural Posterior Estimation, to determine the full parameter distribution conditioned on copper-leaching data from two different soils. Samples drawn from the posterior distribution align perfectly with the observed data for both the surrogate and original models.

Hydrologic connectivity and dynamics of solute transport in a mountain stream: Insights from a long-term tracer test and multiscale transport modeling informed by machine learning

The movement of solutes in a watershed is a complex process with multiple interactions and feedbacks across spatial and temporal scales. Modeling the dynamics of solute transport along diverse hydrologic pathways within watersheds – from hillslopes to stream channels and in and out of the hyporheic zones – is challenging but critically important, as these processes integrate and contribute to the biogeochemical functioning of the river corridor up to the river network scale. Here we use results from a long-term network-scale tracer test at the H.J. Andrews experimental forest in western Cascade Mountains, Oregon, USA to inform a multiscale framework for transport in stream corridors. The framework uses a Lagrangian-based subgrid model to represent the effects of hyporheic exchange flow and advective transport at stream network scales. The spatially and temporally resolved stream discharge needed for the transport model is imputed across the river system by an entity-aware long short-term memory network. Modeled concentrations show good agreements with the observations and exhibit power scaling laws indicative of a very wide range of timescales over which hyporheic exchange flow occurs. Our results demonstrate a data-informed modeling framework that links dynamical processes occurring at small scales to a network context to help understand how changes at reach scale cascade into network-scale effects, providing a useful tool for sustainable river basin management.

Solute band transport in electroosmotic-pressure-driven flow of Carreau–Yasuda fluid over micropillar arrays

In this study, we numerically investigate the transport and dispersion characteristics of a neutral solute band in a fluid following generalized Carreau–Yasuda constitutive equations. The combined action of electroosmotic forcing and pressure gradient drives the flow through a microchannel embedded with micropillars. We analyze the band transport process by altering the flow-controlling parameters and fluid rheology. We observe an enhancement in band dispersion with increasing solute diffusivity. An augmentation in band dispersion is achieved using bluff micropillar designs compared to the streamlined micropillars. We also observe that the dispersion of solute band is less in shear-thickening fluids than in shear-thinning fluids. In a mixed electroosmotic-pressure-driven flow, the favorable pressure gradient conditions enhance the band dispersion phenomenon. Our results may prove valuable in understanding solute transport dynamics in non-Newtonian fluids, which has implications for lab-on-a-chip diagnostics and precise drug delivery.

Mechanisms of Non-Fresh Groundwater Presence at Water Tables in Highly Permeable Coastal Aquifers.

Coastal aquifers with high hydraulic conductivities on the order of 10-2 m s-1 have unconventional salinity distributions with the presence of non-fresh groundwater at the water table over a wide swath near the coast. This study aims to unravel the mechanisms underlying the phenomenon via numerical simulations for variably saturated, density-driven flow and solute transport in porous media. The simulation results indicate that the existence of non-fresh groundwater at the water table is attributed to the upward mass flux in the saturated zone near the coast, which transports solute from deeper groundwater toward the water table. With high hydraulic conductivity, the upward mass flux becomes prominent at shallower elevations because of the high Darcy flux and the shallow saline groundwater. The upward mass flux has two main drivers, upward advection by the upward flow component and transverse dispersion by the seaward flow component. The advective mass flux dominates over the transverse dispersion in the deep part of the saturated zone where only groundwater with sea water salinity exists. In contrast, the transverse dispersion becomes more pronounced than the upward advection in the shallow saturated zone just beneath the water table and in the unsaturated zone immediately above the water table. Our findings help interpret the unconventional salinity distributions observed and elucidate the unique dynamics of groundwater flow and solute transport in highly permeable coastal aquifers.

Time Series of Electrical Conductivity Fluctuations Give Insights Into Long‐Term Solute Transport Dynamics of an Urban Stream

AbstractArtificial tracers are often used for quantitative estimates of solute transport properties in rivers. However, single‐injection tracer tests give insights in transport characteristics limited to the ecohydrological conditions at the testing time. Series of time‐consuming and laborious tracer tests would be required to properly capture seasonal changes. The present study uses intrinsic diurnal fluctuations of electrical conductivity (EC) caused by discharge of treated wastewater as a tracer to evaluate solute transport processes along a 4.7‐km reach of the River Erpe, Germany. By reproducing the fluctuations recorded along the river using the solute transport model one‐dimensional transport with inflow and storage, this study investigated the long‐term dynamics in solute transport properties. Individual 48‐hr curves of EC were used in the steady state configuration of the model to gain 48‐hr‐integrated estimates of selected transport parameters. Using a sliding window approach in 1‐hr steps along the 2,270‐hr time series of EC the temporal variability of solute transport between April and June 2016 was assessed. To test the identifiability of parameters using the proposed method, sensitivity analyses and a breakthrough curve analysis of selected 48‐hr windows were implemented. With time advancing into the summer, a significant rising trend (Mann‐Kendall test p‐value < 0.05) of the cross sectional area of the channel was observed and attributed to the growth of macrophytes and a significant slightly decreasing trend for the storage rate was found. The presented method is of high value for river management, as promoting transient storage enhances biogeochemical cycling and benefits water quality.

Single-Molecule Fluorescence Investigations of Solute Transport Dynamics in Nanostructured Membrane Separation Materials.

Many materials used for membrane separations are composed of nanoscale structures such as pores and domains. Such nanostructures often control the solute permeability and selectivity of the separation membranes. Thus, for future development of highly efficient separation membranes, it is important to understand the structural and chemical properties of these nanostructures and also their influences on solute transport dynamics. For the last two decades, single-molecule fluorescence techniques have been used to measure the detailed dynamics of solute molecules diffusing in various nanostructured materials, giving valuable insights into molecular transport mechanisms influenced by nanoscale material heterogeneity. This Perspective discusses recent single-molecule fluorescence studies on solute diffusion in materials relevant to membrane separations, including dense polymer films and nanoporous materials. These studies have revealed the formation and properties of nanostructures and unique transport dynamics of solute molecules manipulated by their confinement and partitioning to the nanostructures, which play key roles in membrane separations. This Perspective will also point out scientific challenges toward a thorough understanding of molecular-level mechanisms in membrane separations.

A temporally relaxed theory of physically or chemically non-equilibrium solute transport in heterogeneous porous media

Groundwater constitutes a critical component in providing fresh water for various human endeavors. Nevertheless, its susceptibility to contamination by pollutants represents a significant challenge. A comprehensive understanding of the dynamics of solute transport in groundwater and soils is essential for predicting the spatial and temporal distribution of these contaminants. Presently, conventional models such as the mobile–immobile (MIM) model and the rate-limited sorption (RLS) model are widely employed to describe the non-Fickian behavior of solute transport. In this research, we present a novel approach to solute transport that is founded on the temporally relaxed theory of Fick’s Law. Our methodology introduces two relaxation times to account for solute particle collisions and attachment, leading to the derivation of a new advection–dispersion equation. Our findings indicate that the relaxation times possess similar properties to the transport parameters in the MIM and RLS models, and our solution can be applied to accurately predict transport parameters from soil column experiments. Additionally, we discovered that the relaxation times are proportional to the magnitude of Peclet number. This innovative approach provides a deeper insight into solute transport and its impact on groundwater contamination.

Experimental Analysis of Mass Exchange Across a Heterogeneity Interface: Role of Counter‐Current Transport and Non‐Linear Diffusion

AbstractSolute transport in heterogeneous and fractured systems is a complex process given the permeability contrasts and the time scales discrepancies of transport in high‐permeability versus low‐permeability regions. We studied this phenomenon by injecting a solute (dyed water) in a micromodel comprising a single channel in contact with a porous medium and evaluated the mass exchange across the interface between the channel and porous medium (resembling the interface between free flow and porous media regions). Two sets of transport experiments were performed at three injection rates of 0.01, 0.1, and 1 ml/hr. Injection of dyed water into a clean‐water‐filled micromodel (referred to as the loading process hereafter) and injection of clean water into a dyed‐water‐filled micromodel (referred to as the unloading process hereafter). The dynamics of solute transport was recorded using time‐lapse optical imaging. Our experimental results demonstrated the change of the mass exchange rate coefficient with time and a much smaller transfer rate coefficient during the unloading compared to the loading process. It is proposed that concentration‐dependent counter‐current advection‐diffusion cause slow‐down and further delay in the transport. These results may provide further explanation for the observed slow release of contamination in aquifers.

Procena rizika sadržaja pesticida u zemljištu kao funkcija osobina zemljišta, pesticida i padavina (kiše), upotrebom numeričkog modela HYDRUS 1D

It has been observed through experiments that many chemicals especially pesticides found in streams and groundwater bodies are transported through surface runoff and/or preferential flow processes. Researchers have also proved that the timing and nature of rainfall since the last pesticide application are often described as significant controls on pesticide transport through flow processes. Rainfall variability is now considered as the climate drivers on contaminant transport. The amount of pesticides transported through surface runoff and/or preferential flow pathways to streams and groundwater respectively has been shown to be strongly correlated with the concentration of that chemical in a thin near-surface layer of the soil immediately prior to such an event. The thin near-surface layer of a soil is regarded as the source where all the dynamics of solute transport starts. The thin near-surface layer is the store of pesticide from which they are leached by both fast episodic as well as slow steady processes. In this research, we seek to better understand the idea of driver-source-trigger concept of pesticide solute transport in the subsurface. The driver (rainfall variability) triggers (surface runoff and/or preferential flow) from the source (a thin near-surface layer) for pesticides transport to stream and/or groundwater. The methodology for this study is by the use of HYDRUS 1D Numerical Model.

Soil texture and structure heterogeneity predominantly governs bulk density gradients around roots

AbstractRhizosphere soil is known to differ from the bulk soil due to numerous physicochemical processes induced by root growth. The spatial extent and magnitude of the influence of roots on the surrounding soil is still debated controversially. To date, most studies focused on a limited number of soil types and plant species and were carried out under homogeneous soil structure conditions (i.e., finely sieved and repacked soil). With the help of X‐ray computed tomography (CT), we present the results of an image processing workflow, which enabled to analyze soil structure around roots of maize (Zea mays L.) plants under different degrees of soil structure heterogeneity. We analyzed >400 samples extracted during laboratory and field experiments covering various combinations of texture, bulk density, packing heterogeneity, maize genotype, and soil moisture. We show that soil texture and structure heterogeneity predominantly governs the magnitude of bulk density alteration around roots. In homogeneous soil structure, roots had to create their own pores by pushing away soil particles, which confirms previous findings. Under more heterogeneous conditions, we found that roots predominantly grew in existing pores without inducing compaction. The influence of root hairs, root length density, and plant growth stages had no or little impact on the results. The effect of root diameter was more pronounced in sand than in loam. Fine roots caused sand grains to align along their axis, whereas big roots broke the fragile arrangement of grains. Our findings have implications for water and solute transport dynamics at the root–soil interface, which may affect plant productivity.

Sorption of sulfadiazine and flow modeling in an alluvial deposit of a dry riverbed in the Brazilian semiarid

The Brazilian semiarid region is subjected to irregular rainfall, prolonged droughts, and high temperatures, hampering the surface water accumulation. The water access is restricted to the alluvium in the valleys, which are used for cattle and poultry livestock development. These activities trigger the excessive use of veterinary antibiotics. As a consequence, antibiotics reach sediment surfaces and promote deterioration of groundwater quality. This work aims to evaluate the sorption potential of Sulfadiazine (SDZ) and to understand the dynamics of water transfer and solute transport processes in a typical alluvial deposit of the Capibaribe River, in the Agreste of Pernambuco. The sedimentological characterization was performed by Miall's Code, defining four lithofacies (Scm, Scm,b, Gcm,o, Scm,o). Kinetics and isotherms experiments allowed the analyses of SDZ sorption. Kinetics sorption showed an equilibrium tendency after 40 h and was better described by a second-order model, while isotherm sorption data were better fitted by the Freundlich model. According to the particle size distribution curve, Scm had the highest number of fine particles and organic matter, affecting interaction of SDZ in sediments. Consequently, SDZ sorption was slightly higher in this lithofacies. However, overall, SDZ sorption was low, thereby offering a real risk of groundwater contamination. For further investigation the dynamics of water transfer and solute transport in a heterogeneous alluvial deposit were simulated with the HYDRUS-2D. The structural heterogeneity influenced the spatial distribution of water storage under unsaturated conditions and provided the emergence of preferential flows. The solute dynamic follow a similar behavior of the water flow, due to the low retention of SDZ in the soil. Considering a condition near to saturation, the contrast of hydraulic and transport properties influences simultaneously in the processes of water transfer and solute transport.

Temporal flow variations interact with spatial physical heterogeneity to impact solute transport in managed river corridors

The interactions between surface water and groundwater in river corridors lead to temporal fluctuations in subsurface water fluxes which have a critical role on solute transport dynamics. In this work, we develop a framework to analyze the relative impacts of different temporal frequencies of the flow field in a spatially heterogeneous aquifer on solute transport. Our analysis indicates that the advection-dispersion equation behaves as a low-pass filter by wiping out the effect of high-frequency velocity fluctuations on the first two spatial moments of the solute plume, namely its center of mass and spreading. The concepts discussed in the theoretical analysis are then applied to understand solute transport dynamics at the 300 Area of the Hanford site (USA) adjacent to the Columbia River. We examine the temporal behavior of the solute plume's spatial moments for different temporal frequencies utilizing geostatistical parameters estimated in the 300 Area. Due to the proximity to the Columbia river, groundwater fluxes at the Hanford site are highly dynamic resulting in a large range of characteristic temporal frequencies. Nonetheless, similar to the theoretical analysis, our results show that the effect of high-frequency fluctuations is filtered, with most of the solute transport dynamics being controlled by fluctuations characterized by a large characteristic period.

Differential C-Q Analysis: A New Approach to Inferring Lateral Transport and Hydrologic Transients Within Multiple Reaches of a Mountainous Headwater Catchment

Concentration-discharge (C-Q) relationships have been widely used as “hydrochemical tracers” to determine the variability in riverine solute exports across event, seasonal, annual, and decadal time scales. However, these C-Q relationships are limited to investigating solute transport dynamics at individual sampling stations, such that they create an incomplete understanding of the solute behavior upstream or downstream of the sampling station. Therefore, the objective of this study is to develop, apply and assess a differential C-Q approach that can characterize spatial variability in solute behavior across stations, as well as investigate their controls, by following a different spatial scheme and organizing the river into multiple sections. The differential C-Q approach captures the difference in concentration in a river segment over the difference in discharge, thereby accounting for gains, losses or fractional solute turnover between sampling stations. Using water quality data collected over four water years (2014-18) in a mountainous headwater catchment of the East River, Colorado, this study compares traditional and differential C-Q relationships in predicting solute behavior between three sampling stations distributed throughout the river. Results from the differential C-Q analysis demonstrate significant differences in solute behavior within upstream versus downstream reaches of the East River watershed. In particular, the meandering downstream section is marked by significant gains in both groundwater and solute concentrations as opposed to the dilution and the declining trends observed in the high-relief, steep terrain upstream reach. Shale mineralogy was determined to have a major influence on in-stream concentrations pertaining to Ca, DIC, DOC, Mg, Mo, NO3 and SO4. The analyses further revealed that total P concentration in the downstream reach exceeded the U.S. Environmental Protection Agency’s desired goal for control of eutrophication (110 ppb). Overall, differential C-Q metrics yield a better understanding of the lateral storage and interactions within catchments than traditional analyses, and holds potential for aiding water quality managers in the identification of critical stream reaches that assimilate harmful chemicals.

Abstract 4263: Characterization of patient-specific drug delivery for breast cancer using image-guided computational fluid dynamics

Abstract Introduction: A tumor's blood supply and interstitial flow play an essential role in tumor growth, invasion, and treatment response. We have developed a methodology that employs quantitative MRI data to constrain a patient-specific, computational fluid dynamics (CFD) model of blood flow and interstitial transport within breast tumors. The dynamics of solute transport are characterized based on steady state flow fields, so that delivery of oxygen, nutrients, or therapies through the circulation can be estimated. It is a fundamentally new way to characterize breast tumor hemodynamics using MRI. Method: Eleven malignant and five benign lesions from 12 patients were included in this study. Vessel segmentation and tracking were performed to reconstruct the whole breast vasculature and to identify vessels feeding or draining tumors. Ultrafast dynamic contrast-enhanced MRI and diffusion-weighted imaging data were analyzed to estimate the bolus arrival time, Ktrans (volume transfer coefficient), and ADC (apparent diffusion coefficient); these data were used to spatially assign flow direction, local vascular permeability, and tissue density, respectively. The model of steady state flow was described by three components: 1) blood flow following Poiseuille's law, 2) interstitial flow following Darcy's law, and 3) flux transmitted across the vascular walls following Starling's law. The behavior of drug delivery was described by an advection-diffusion equation in the interstitial tissue, with the profile of the vascular bolus as a source term. The whole system was solved with a 1D-3D coupled implementation. At the end of analysis, the tracer's propagation through the tissue-of-interest was visualized and hemodynamic characteristics are derived to compare the malignant and benign lesions. Result: Visualization of the time-resolved distribution and propagation of solute demonstrated the intratumoral heterogeneity of accessibility to drugs. Furthermore, we are currently calculating the spatially-resolved accumulation, wash-in rate, and infiltration duration of different drugs for each lesion, so that a quantitative comparison can be performed between malignant and benign lesions. Conclusion: We have developed a computational model, informed by patient-specific MRI data, to simulate the blood supply, interstitial fluid environment, and intratumorally heterogeneous access to therapies for breast tumors. It represents the first methodology of integrating CFD with patient specific MRI data for quantifying the spatiotemporally resolved drug propagation as well as the entire pressure and flow fields within the breast. NCI U01CA142565, U01CA CA174706, and R01 CA218700. CPRIT RR160005. Citation Format: Chengyue Wu, David A. Hormuth, Federico Pineda, Gregory S. Karczmar, Robert D. Moser, Thomas E. Yankeelov. Characterization of patient-specific drug delivery for breast cancer using image-guided computational fluid dynamics [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4263.

Impact of fractional probability distributions on statistics of hydraulic conductivity, dynamics of groundwater flow and solute transport at a low‐permeability site

AbstractThe fractional Brownian motion (fBm) and fractional Lévy motion (fLm) can easily describe the geometry and the statistical structure of hydraulic conductivity (K) for real‐world. However, the fBm and fLm models have not been systematically evaluated when building the K field for a low‐permeability site. In this study, both the fBm and fLm are used to simulate the low‐K field at NingCheGu (NCG), Tianjin, China. Groundwater flow and solute transport are then computed using MODFLOW and MT3DMS, respectively, and the influence of the fBm/fLm models for K on groundwater flow and solute transport is discussed. Results show that the fLm fits better the statistics of the low‐K medium than fBm, and the random logarithmic K (LnK) field generated by fLm is more stable because the resultant LnK field captures more of the measured properties at the field site than that generated by fBm. In contrast, the LnK generated by fBm is more likely to form both high‐K channels and low‐K barriers. The fBm therefore predicts more extreme behaviours in flow and transport, including the preferential flow, low‐concentration blocks and solute retention. The overall groundwater renewal period and solute travel time for the fLm simulation are slightly shorter than those for fBm. The impacts of the fLm and fBm models on the statistics of the resultant LnK fields and the dynamics of groundwater flow and solute transport revealed by this study shed light on the selection and evaluation of the fractional probability distribution models in capturing the K fields for low‐K media.

A physiologically-motivated model of cystic fibrosis liquid and solute transport dynamics across primary human nasal epithelia.

Cystic fibrosis (CF) disease is caused by mutations affecting the gene coding for the cystic fibrosis transmembrane conductance regulator (CFTR), an anion channel expressed in the mucosal side of epithelial tissue. In the airway, dysfunctional CFTR results in a transepithelial osmotic imbalance leading to hyperabsorption of airway surface liquid mucostasis, chronic inflammation, and eventual respiratory failure. Human nasal epithelial cell cultures from healthy and CF donors were used to perform studies of liquid and solute transport dynamics at an air/liquid interface in order to emulate the in vivo airway. Then, these results were used to inform a quantitative systems pharmacology model of airway epithelium describing electrically and chemically driven transcellular ionic transport, contributions of both convective and diffusive paracellular solute transport, and osmotically driven transepithelial water dynamics. Model predictions showed CF cultures, relative to non-CF ones, have increased apical and basolateral water permeabilities, and increase paracellular permeability and transepithelial chemical driving force for a radiolabeled tracer used to track small molecule absorption. These results provide a computational platform to better understand and probe the mechanisms behind the liquid hyperabsorption and small molecule retention profiles observed in the CF airway.

Active Layer Groundwater Flow: The Interrelated Effects of Stratigraphy, Thaw, and Topography

AbstractThe external drivers and internal controls of groundwater flow in the thawed “active layer” above permafrost are poorly constrained because they are dynamic and spatially variable. Understanding these controls is critical because groundwater can supply solutes such as dissolved organic matter to surface water bodies. We calculated steady‐state three‐dimensional suprapermafrost groundwater flow through the active layer using measurements of aquifer geometry, saturated thickness, and hydraulic properties collected from two major landscape types over time within a first‐order Arctic watershed. The depth position and thickness of the saturated zone is the dominant control of groundwater flow variability between sites and during different times of year. The effect of water table depth on groundwater flow dwarfs the effect of thaw depth. In landscapes with low land‐surface slopes (2–4%), a combination of higher water tables and thicker, permeable peat deposits cause relatively constant groundwater flows between the early and late thawed seasons. Landscapes with larger land‐surface slopes (4–10%) have both deeper water tables and thinner peat deposits; here the commonly observed permeability decrease with depth is more pronounced than in flatter areas, and groundwater flows decrease significantly between early and late summer as the water table drops. Groundwater flows are also affected by microtopographic features that retain groundwater that could otherwise be released as the active layer deepens. The dominant sources of groundwater, and thus dissolved organic matter, are likely wet, flatter regions with thick organic layers. This finding informs fluid flow and solute transport dynamics for the present and future Arctic.

Parameter uncertainty with flow variation of the one-dimensional solute transport model for small streams using Markov chain Monte Carlo

The transient storage model (TSM) is a popular solute transport model among hydrologists and ecologists for characterizing solute retention potential of small headwater streams. TSM parameters are most commonly estimated in an inverse modeling framework using tracer breakthrough data. A key challenge in interpreting TSM parameters is the inherent difficulty in the estimation process and relating these parameters with the physical characteristics of streams. While often recognized that multiple sources of uncertainty impact transient storage modeling, rigorous evaluation of TSM parameter uncertainty is rare. Stream flow magnitude has been identified as a key variable in characterizing stream solute transport dynamics, yet no study has shown the impact of flow magnitude on TSM parameter uncertainty. In this paper we study the impact of flow magnitude on TSM parameter uncertainty by using tracer data from repeated tracer studies with changing stream flow magnitudes, and introduce a software tool to perform Markov chain Monte Carlo based parameter estimation and uncertainty evaluation. The software tool developed is capable of performing thousands of model runs within a few hours, which is necessary for Monte Carlo based parameter estimation, and provides a potentially attractive framework for model testing and improvement. TSM parameters were found to be relatively less important during higher flows with large uncertainty bounds and clear evidence of parameter correlations. The importance of TSM parameters on solute transport seemed to increase as flow decreased with seasonal baseflow recession. Our findings highlight the need for improved field methodologies to reduce parameter uncertainty and the need for further improvement in the model structure for successful stream characterization.

Simple regression models can act as calibration-substitute to approximate transient storage parameters in streams

Transient storage models in combination with tracer tests are widely used to study solute transport dynamics in streams. Storage parameters included in such models are typically calibrated for one or more study reaches by monitoring solute concentrations and fitting breakthrough curve data. Since stream characteristics vary spatially and temporally, it is challenging to generalize these calibrated parameters for another stream reach. This study investigates the ability of simple regression models to predict transient storage parameters such as dispersion coefficient (D), transient storage area (As) and storage exchange coefficient (α). A meta-analysis of 834 tracer studies from 67 published papers was used to develop parsimonious non-linear regression models that relate storage parameters to easily available stream parameters such as discharge, velocity, flow width and flow depth. Correlation analysis showed moderate correlation of D with velocity, depth and width; and high correlation of As with the ratio of discharge to depth. Exchange coefficient (α) did not show significant correlation with available stream parameters. The models were tested using a subset of meta-analysis data and experimental tracer data from Hubbard Brook Experimental Forest located in the US and Kielstau Catchment located in Germany. We predicted storage and breakthrough curves with reasonable accuracy (R2 > 0.5) by using new regression equations and incorporating it into an advection-dispersion-storage model. These equations provide a viable alternative to approximate transient storage parameters in circumstances where time and cost-intensive reach-specific calibration is impossible. Therefore, such regression-based estimates of storage parameters can also form an integral part of larger watershed scale models by predicting solute transport and storage in stream reaches.