Scale dependence of the hydraulic properties of a fractured aquifer estimated using transfer functions

We present an investigation of the scale dependence of hydraulic parameters in fractured media based on the concept of transfer functions (TF). TF methods provide an inexpensive way to perform aquifer parameter estimation, as they relate the fluctuations of an observation time series (hydraulic head fluctuations) to an input function (aquifer recharge) in frequency domain. Fractured media are specially sensitive to this approach as hydraulic parameters are strongly scale-dependent, involving nonstationary statistical distributions. Our study is based on an extensive data set, involving up to 130 measurement points with periodic head measurements that in some cases extend for more than 30 years. For each point, we use a single-porosity and dual-continuum TF formulation to obtain a distribution of transmissivities and storativities in both mobile and immobile domains. Single-porosity TF estimates are compared with data obtained from the interpretation of over 60 hydraulic tests (slug and pumping tests). Results show that the TF is able to estimate the scale dependence of the hydraulic parameters, and it is consistent with the behavior of estimates from traditional hydraulic tests. In addition, the TF approach seems to provide an estimation of the system variance and the extension of the ergodic behavior of the aquifer (estimated in approximately 500 m in the analyzed aquifer). The scale dependence of transmissivity seems to be independent from the adopted formulation (single or dual-continuum), while storativity is more sensitive to the presence of multiple continua

Some Insights in Superdiffusive Transport

In this paper we deal with high-order corrections for the Fractional Derivative approach to anomalous diffusion, in super-diffusive regime, which become relevand whenever one attempts to describe the behavior of particles close to normal diffusion.Comment: 14 pages, 7 figure

Child maltreatment and NR3C1 exon 1F methylation, link with deregulated hypothalamus-pituitary-adrenal axis and psychopathology: A systematic review

Background Epigenetics offers one promising method for assessing the psychobiological response to stressful experiences during childhood. In particular, deoxyribonucleic acid (DNA) methylation has been associated with an altered hypothalamus–pituitary–adrenal (HPA) axis and the onset of mental disorders. Equally, there are promising leads regarding the association between the methylation of the glucocorticoid receptor gene (NR3C1-1F) and child maltreatment and its link with HPA axis and psychopathology. Objective The current study aimed to assess the evidence of a link among child maltreatment, NR3C1-1F methylation, HPA axis deregulation, and symptoms of psychopathology. Methods We followed the Prisma guidelines and identified 11 articles that met our inclusion criteria. Results We found that eight studies (72.72%) reported increased NR3C1-1F methylation associated with child maltreatment, specifically physical abuse, emotional abuse, sexual abuse, neglect, and exposure to intimate partner violence, while three studies (27.27%) found no significant association. Furthermore, a minority of studies (36.36%) provided additional measures of symptoms of psychopathology or cortisol in order to examine the link among NR3C1-1F methylation, HPA axis deregulation, and psychopathology in a situation of child maltreatment. These results suggest that NR3C1-1F hypermethylation is positively associated with higher HPA axis activity, i.e. increased production of cortisol, as well as symptoms of psychopathology, including emotional lability-negativity, externalizing behavior symptoms, and depressive symptoms. Conclusion NR3C1-1F methylation could be one mechanism that links altered HPA axis activity with the development of psychopathology

Non-Markovian diffusion equations and processes: analysis and simulations

In this paper we introduce and analyze a class of diffusion type equations related to certain non-Markovian stochastic processes. We start from the forward drift equation which is made non-local in time by the introduction of a suitable chosen memory kernel K(t). The resulting non-Markovian equation can be interpreted in a natural way as the evolution equation of the marginal density function of a random time process l(t). We then consider the subordinated process Y(t)=X(l(t)) where X(t) is a Markovian diffusion. The corresponding time evolution of the marginal density function of Y(t) is governed by a non-Markovian Fokker-Planck equation which involves the memory kernel K(t). We develop several applications and derive the exact solutions. We consider different stochastic models for the given equations providing path simulations.Comment: 43 pages, 19 figures, in press on Physica A (2008

Effect of spatial concentration fluctuations on effective kinetics in diffusion-reaction systems

International audienceThe effect of spatial concentration fluctuations on the reaction of two solutes, A þ B* C, is considered. In the absence of fluctuations, the concentration of solutes decays as Adet ¼ Bdet t 1. Contrary to this, experimental and numerical studies suggest that concentrations decay significantly slower. Existing theory suggests a t d/4 scaling in the asymptotic regime (d is the dimensionality of the problem). Here we study the effect of fluctuations using the classical diffusion-reaction equation with random initial conditions. Initial concentrations of the reactants are treated as correlated random fields.We use the method of moment equations to solve the resulting stochastic diffusion-reaction equation and obtain a solution for the average concentrations that deviates from t 1 to t d/4 behavior at characteristic transition time t . We also derive analytical expressions for t as a function of Damköhler number and the coefficient of variation of the initial concentration

Effects of Single and Integrated Water, Sanitation, Handwashing, and Nutrition Interventions on Child Soil-Transmitted Helminth and Giardia infections: A Cluster-Randomized Controlled Trial in Rural Kenya

Helminth and protozoan infections affect more than 1 billion children globally. Improving water quality, sanitation, handwashing, and nutrition could be more sustainable control strategies for parasite infections than mass drug administration, while providing other quality of life benefits

Gas injection in a liquid saturated porous medium. Influence of pressurization effects and liquid films

We study numerically and experimentally the displacement of a liquid by a gas in a two-dimensional model porous medium. In contrast with previous pore-network studies on drainage in porous media, the gas compressibility is fully taken account. The influence of the gas injection rate on the displacement pattern, breakthrough time and the evolution of the pressure in the gas phase due in part to gas compressibility are investigated. A good agreement is found between the simulations and the experiments as regards the invasion patterns. The agreement is also good on the drainage kinetics when the dynamic liquid films are taken into account

Experimental saltwater intrusion in coastal aquifers using automated image analysis: Applications to homogeneous aquifers

This paper presents the applications of a novel methodology to quantify saltwater intrusion parameters in laboratory-scale experiments. The methodology uses an automated image analysis procedure, minimizing manual inputs and the subsequent systematic errors that can be introduced. This allowed the quantification of the width of the mixing zone which is difficult to measure in experimental methods that are based on visual observations. Glass beads of different grain sizes were tested for both steady-state and transient conditions. The transient results showed good correlation between experimental and numerical intrusion rates. The experimental intrusion rates revealed that the saltwater wedge reached a steady state condition sooner while receding than advancing. The hydrodynamics of the experimental mixing zone exhibited similar traits; a greater increase in the width of the mixing zone was observed in the receding saltwater wedge, which indicates faster fluid velocities and higher dispersion. The angle of intrusion analysis revealed the formation of a volume of diluted saltwater at the toe position when the saltwater wedge is prompted to recede. In addition, results of different physical repeats of the experiment produced an average coefficient of variation less than 0.18 of the measured toe length and width of the mixing zone.Department of Employment and Learning (DEL) in Northern Ireland and Queen’s University Belfas

Numerical assessment of 3D macrodispersion in heterogeneous porous media

Hydrodynamic dispersion is a key controlling factor of solute transport in heterogeneous porous media that critically depends on dimensionality. It has been shown that the transverse macrodispersion (asymptotic dispersion transverse to the mean velocity direction) vanishes only in 2D and not in 3D. Using classical Gaussian correlated permeability fields with a lognormal distribution of variance σ²y, we determine numerically the longitudinal and transverse dispersivities as functions of heterogeneity and dimensionality. We show that the transverse macrodispersion steeply increases with σ²y underlying the essential role of flow lines braiding, a mechanism specific to 3D systems. The transverse macrodispersion remains however at least two orders of magnitude smaller than the longitudinal macrodispersion, which increases even more steeply with σ²y. At moderate to high levels of heterogeneity, the transverse dispersion also converges much faster to its asymptotic regime than do the longitudinal dispersion. Braiding cannot be thus taken as the sole mechanism responsible for the high longitudinal macrodispersions. It could be either supplemented or superseded by stronger velocity correlations in 3D than in 2D. This assumption is supported by the much larger longitudinal macrodispersions obtained in 3D than in 2D, up to a factor of 7 for σ²y = 7.56