Probabilistic assessment of spatial heterogeneity of natural background concentrations in large-scale groundwater bodies through Functional Geostatistics.

We propose and exemplify a framework to assess Natural Background Levels (NBLs) of target chemical species in large-scale groundwater bodies based on the context of Object Oriented Spatial Statistics. The approach enables one to fully exploit the richness of the information content embedded in the probability density function (PDF) of the variables of interest, as estimated from historical records of chemical observations. As such, the population of the entire distribution functions of NBL concentrations monitored across a network of monitoring boreholes across a given aquifer is considered as the object of the spatial analysis. Our approach starkly differs from previous studies which are mainly focused on the estimation of NBLs on the basis of the median or selected quantiles of chemical concentrations, thus resulting in information loss and limitations related to the need to invoke parametric assumptions to obtain further summary statistics in addition to those considered for the spatial analysis. Our work enables one to (i) assess spatial dependencies among observed PDFs of natural background concentrations, (ii) provide spatially distributed kriging predictions of NBLs, as well as (iii) yield a robust quantification of the ensuing uncertainty and probability of exceeding given threshold concentration values via stochastic simulation. We illustrate the approach by considering the (probabilistic) characterization of spatially variable NBLs of ammonium and arsenic detected at a monitoring network across a large scale confined groundwater body in Northern Italy.

Modeling the fate of UV filters in subsurface: Co-metabolic degradation and the role of biomass in sorption processes.

Ultraviolet filters (UVFs) are emerging organic compounds found in most water systems. They are constituents of personal care products, as well as industrial ones. The concentration of UVFs in the water bodies in space and time is mostly determined by degradation and sorption, both processes being determinant of their bioavailability and toxicity to ecosystems and humans. UVFs are a wide group of compounds, with different sorption behavior expected depending on the individual chemical properties (pKa,Koc,Kow). The goal of this work is framed in the context of improving our understanding of the sorption processes of UVFs occurring in the aquifer; that is, to evaluate the role of biomass growth, solid organic matter (SOM) and redox conditions in the characterization of sorption of a set of UVFs. We constructed a conceptual and a numerical model to evaluate the fate of selected UV filters, focused on both sorption and degradation. The models were validated with published data by Liu et al. (2013), consisting in a suite of batch experiments evaluating the fate of a cocktail of UVs under different redox conditions. The compounds evaluated included ionic UV filters (Benzophenone-3; 2-(3-t-butyl-2-hydroxy-5-methylphenyl)5-chloro-benzotriazole; 2-(2'-hydroxy-5'-octylphenyl)-benzotriazole) and neutral ones (octyl 4-methoxycinnamatte; and octocrylene).

A bilayer coarse-fine infiltration system minimizes bioclogging: The relevance of depth-dynamics.

Bioclogging is a main concern in infiltration systems as it may significantly shorten the service life of these low-technology water treatment methods. In porous media, biofilms grow to clog partially or totally the pore network. Dynamics of biofilm accumulation (e.g., by attachment, detachment, advective transport in depth) and their impact on both surface and deep bioclogging are still not yet fully understood. To address this concern, a 104 day-long outdoor infiltration experiment in sand tanks was performed, using secondary treated wastewater and two grain size distributions (GSDs): a monolayer system filled with fine sand, and a bilayer one composed by a layer of coarse sand placed on top of a layer of fine sand. Biofilm dynamics as a function of GSD and depth were studied through cross-correlations and multivariate statistical analyses using different parameters from biofilm biomass and activity indices, plus hydraulic parameters measured at different depths. Bioclogging (both surface and deep) was found more significant in the monolayer fine system than in the bilayer coarse-fine one, possibly due to an early low-cohesive biofilm formation in the former, driven by lower porosity and lower fluxes; under such conditions biomass is favorably detached from the top layer, transported and accumulated in depth, so that new biomass might colonize the surface. On the other hand, in the bilayer system, fluxes are highest, and the biofilm is still in a growing phase, with low biofilm detachment capability from the top sand layer and high microbial activity in depth, resulting in low bioclogging. Overall, the bilayer coarse-fine system allows infiltrating higher volume of water per unit of surface area than the monolayer fine one, minimizing surface and deep bioclogging, and thus increasing the longevity and efficiency of infiltration systems.

Bilayer Infiltration System Combines Benefits from Both Coarse and Fine Sands Promoting Nutrient Accumulation in Sediments and Increasing Removal Rates.

Infiltration systems are treatment technologies based on water percolation through porous media where biogeochemical processes take place. Grain size distribution (GSD) acts as a driver of these processes and their rates and influences nutrient accumulation in sediments. Coarse sands inhibit anaerobic reactions such as denitrification and could constrain nutrient accumulation in sediments due to smaller specific surface area. Alternatively, fine sands provide higher nutrient accumulation but need a larger area available to treat the same volume of water; furthermore, they are more susceptible to bioclogging. Combining both sand sizes in a bilayer system would allow infiltrating a greater volume of water and the occurrence of aerobic/anaerobic processes. We studied the performance of a bilayer coarse-fine system compared to a monolayer fine one-by triplicate-in an outdoor infiltration experiment to close the C-N-P cycles simultaneously in terms of mass balances. Our results confirm that the bilayer coarse-fine GSD promotes nutrient removal by physical adsorption and biological assimilation in sediments, and further it enhances biogeochemical process rates (2-fold higher than the monolayer system). Overall, the bilayer coarse-fine system allows treating a larger volume of water per surface unit achieving similar removal efficiencies as the fine system.

Linking biofilm spatial structure to real-time microscopic oxygen decay imaging.

Two non-destructive techniques, confocal laser scanning microscopy (CLSM) and planar optode (VisiSens imaging), were combined to relate the fine-scale spatial structure of biofilm components to real-time images of oxygen decay in aquatic biofilms. Both techniques were applied to biofilms grown for seven days at contrasting light and temperature (10/20°C) conditions. The geo-statistical analyses of CLSM images indicated that biofilm structures consisted of small (~100 µm) and middle sized (~101 µm) irregular aggregates. Cyanobacteria and EPS (extracellular polymeric substances) showed larger aggregate sizes in dark grown biofilms while, for algae, aggregates were larger in light-20°C conditions. Light-20°C biofilms were most dense while 10°C biofilms showed a sparser structure and lower respiration rates. There was a positive relationship between the number of pixels occupied and the oxygen decay rate. The combination of optodes and CLMS, taking advantage of geo-statistics, is a promising way to relate biofilm architecture and metabolism at the micrometric scale.

Interaction between Physical Heterogeneity and Microbial Processes in Subsurface Sediments: A Laboratory-Scale Column Experiment.

Physical heterogeneity determines interstitial fluxes in porous media. Nutrients and organic matter distribution in depth influence physicochemical and microbial processes occurring in subsurface. Columns 50 cm long were filled with sterile silica sand following five different setups combining fine and coarse sands or a mixture of both mimicking potential water treatment barriers. Water was supplied continuously to all columns during 33 days. Hydraulic conductivity, nutrients and organic matter, biofilm biomass, and activity were analyzed in order to study the effect of spatial grain size heterogeneity on physicochemical and microbial processes and their mutual interaction. Coarse sediments showed higher biomass and activity in deeper areas compared to the others; however, they resulted in incomplete denitrification, large proportion of dead bacteria in depth, and low functional diversity. Treatments with fine sediment in the upper 20 cm of the columns showed high phosphorus retention. However, low hydraulic conductivity values reported in these sediments seemed to constraint biofilm activity and biomass. On the other hand, sudden transition from coarse-to-fine grain sizes promoted a hot-spot of organic matter degradation and biomass growth at the interface. Our results reinforce the idea that grain-size disposition in subsurface sandy sediments drives the interstitial fluxes, influencing microbial processes.

The effects of sediment depth and oxygen concentration on the use of organic matter: An experimental study using an infiltration sediment tank.

Water flowing through hyporheic river sediments or artificial recharge facilities promotes the development of microbial communities with sediment depth. We performed an 83-day mesocosm infiltration experiment, to study how microbial functions (e.g., extracellular enzyme activities and carbon substrate utilization) are affected by sediment depth (up to 50 cm) and different oxygen concentrations. Results indicated that surface sediment layers were mainly colonized by microorganisms capable of using a wide range of substrates (although they preferred to degrade carbon polymeric compounds, as indicated by the higher ß-glucosidase activity). In contrast, at a depth of 50 cm, the microbial community became specialized in using fewer carbon substrates, showing decreased functional richness and diversity. At this depth, microorganisms picked nitrogenous compounds, including amino acids and carboxyl acids. After the 83-day experiment, the sediment at the bottom of the tank became anoxic, inhibiting phosphatase activity. Coexistence of aerobic and anaerobic communities, promoted by greater physicochemical heterogeneity, was also observed in deeper sediments. The presence of specific metabolic fingerprints under oxic and anoxic conditions indicated that the microbial community was adapted to use organic matter under different oxygen conditions. Overall the heterogeneity of oxygen concentrations with depth and in time would influence organic matter metabolism in the sediment tank.

Geochemical modeling of arsenic release from a deep natural solid matrix under alternated redox conditions.

Dissolved arsenic (As) concentrations detected in groundwater bodies of the Emilia-Romagna Region (Italy) exhibit values which are above the regulation limit and could be related to the natural composition of the host porous matrix. To support this hypothesis, we present the results of a geochemical modeling study reproducing the main trends of the dynamics of As, Fe, and Mn concentrations as well as redox potential and pH observed during batch tests performed under alternating redox conditions. The tests were performed on a natural matrix extracted from a deep aquifer located in the Emilia-Romagna Region (Italy). The solid phases implemented in the model were selected from the results of selective sequential extractions performed on the tested matrix. The calibrated model showed that large As concentrations have to be expected in the solution for low crystallinity phases subject to dissolution. The role of Mn oxides on As concentration dynamics appears significant in strongly reducing environments, particularly for large water-solid matrix interaction times. Modeled data evidenced that As is released firstly from the outer surface of Fe oxihydroxides minerals exhibiting large concentrations in water when persistent reducing conditions trigger the dissolution of the crystalline structure of the binding minerals. The presence of organic matter was found to strongly affect pH and redox conditions, thus influencing As mobility.

Arsenic release from deep natural solid matrices under experimentally controlled redox conditions.

We investigated the role of iron (Fe) on arsenic (As) release from two samples of a natural deep soil collected in an aquifer body in the Emilia-Romagna Region, Italy. Each sample is representative of a different solid matrix, i.e., sand and vegetal matter. Batch experiments were performed by applying alternating aerobic/anaerobic conditions to the samples under a range of redox and pH conditions, consistent with the corresponding values measured in the field. Arsenic mobilization was triggered by abrupt and rapid changes in redox conditions and displayed a clear correlation with oxidation/reduction potential for both solid matrices. Vegetal matter showed high binding capacity and large As concentration release. Arsenic release was also correlated with Fe released from the solid matrices. Our results suggest that the environmentally critical As concentrations detected in some aquifers in the Emilia-Romagna Region are consistent with (a) the occurrence of high natural As content in the component of the host porous medium associated with vegetal matter and (b) the effect of possible sharp localized (and temporally oscillating) variations in redox conditions.

Optimal reconstruction of concentrations, gradients and reaction rates from particle distributions.

Random walk particle tracking methodologies to simulate solute transport of conservative species constitute an attractive alternative for their computational efficiency and absence of numerical dispersion. Yet, problems stemming from the reconstruction of concentrations from particle distributions have typically prevented its use in reactive transport problems. The numerical problem mainly arises from the need to first reconstruct the concentrations of species/components from a discrete number of particles, which is an error prone process, and then computing a spatial functional of the concentrations and/or its derivatives (either spatial or temporal). Errors are then propagated, so that common strategies to reconstruct this functional require an unfeasible amount of particles when dealing with nonlinear reactive transport problems. In this context, this article presents a methodology to directly reconstruct this functional based on kernel density estimators. The methodology mitigates the error propagation in the evaluation of the functional by avoiding the prior estimation of the actual concentrations of species. The multivariate kernel associated with the corresponding functional depends on the size of the support volume, which defines the area over which a given particle can influence the functional. The shape of the kernel functions and the size of the support volume determines the degree of smoothing, which is optimized to obtain the best unbiased predictor of the functional using an iterative plug-in support volume selector. We applied the methodology to directly reconstruct the reaction rates of a precipitation/dissolution problem involving the mixing of two different waters carrying two aqueous species in chemical equilibrium and moving through a randomly heterogeneous porous medium.

Travel time and trajectory moments of conservative solutes in two-dimensional convergent flows.

We address advective transport of a solute traveling toward a single pumping well in a two-dimensional randomly heterogeneous aquifer. The two random variables of interest are the trajectory followed by an individual particle from the injection point to the well location and the particle travel time under steady-state conditions. Our main objective is to derive the predictors of trajectory and travel time and the associated uncertainty, in terms of their first two statistical moments (mean and variance). We consider a solute that undergoes mass transfer between a mobile and an immobile zone. Based on Lawrence et al. [Lawrence, A.E., Sánchez-Vila, X., Rubin, Y., 2002. Conditional moments of the breakthrough curves of kinetically sorbing solute in heterogeneous porous media using multirate mass transfer models for sorption and desorption. Water Resour. Res. 38 (11), 1248, doi:10.1029/2001WR001006.], travel time moments can be written in terms of those of a conservative solute times a deterministic quantity. Moreover, the moments of solute particles trajectory do not depend on mass transfer processes. The resulting mean and variance of travel time and trajectory for a conservative species can be written as functions of the first, second moments and cross-moments of trajectory and velocity components. The equations are developed from a consistent second order expansion in sigmaY (standard deviation of the natural logarithm of hydraulic conductivity). Our solution can be completely integrated with the moment equations of groundwater flow of Guadagnini and Neuman [Guadagnini, A., Neuman, S.P., 1999a. Nonlocal and localized analyses of conditional mean steady state flow in bounded, randomly non uniform domains 1. Theory and computational approach. Water Resour. Res. 35(10), 2999-3018.,Guadagnini, A., Neuman, S.P., 1999b. Nonlocal and localized analyses of conditional mean steady state flow in bounded, randomly non uniform domains 2. Computational examples. Water Resour. Res. 35(10), 3019-3039.], it is free of distributional assumptions regarding the log conductivity field, and formally includes conditioning. We present analytical expressions for the unconditional case by making use of the results of Riva et al. [Riva, M., Guadagnini, A., Neuman, S.P., Franzetti, S., 2001. Radial flow in a bounded randomly heterogeneous aquifer. Transport in Porous Media 45, 139-193.]. The quality of the solution is supported by numerical Monte Carlo simulations. Potential uses of this work include the determination of aquifer reclamation time by means of a single pumping well, and the demarcation of the region potentially affected by the presence of a contaminant in the proximity of a well, whenever the aquifer is very thin and Dupuit-Forchheimer assumption holds.

Using Geostatistical Analysis to Evaluate the Presence of Rotylenchulus reniformis in Cotton Crops in Brazil: Economic Implications.

In recent years, the productivity of cotton in Brazil has been progressively decreasing, often the result of the reniform nematode Rotylenchulus reniformis. This species can reduce crop productivity by up to 40%. Nematodes can be controlled by nematicides but, because of expense and toxicity, application of nematicides to large crop areas may be undesirable. In this work, a methodology using geostatistics for quantifying the risk of nematicide application to small crop areas is proposed. This risk, in economic terms, can be compared to nematicide cost to develop an optimal strategy for Precision Farming. Soil (300 cm(3)) was sampled in a regular network from a R. reniformis-infested area that was a cotton monoculture for 20 years. The number of nematodes in each sample was counted. The nematode number per volume of soil was characterized using geostatistics, and 100 conditional simulations were conducted. Based on the simulations, risk maps were plotted showing the areas where nematicide should be applied in a Precision Farming context. The methodology developed can be applied to farming in countries that are highly dependent on agriculture, with useful economic implications.