Heat transfer in moist porous media has been given extensive theoretical consideration. In attempting to define the problem mathematically, either one of two approaches has been followed. There is the mechanistic approach which is based upon the diffusion of vapor and the capillary movement of liquids, and there is the approach which applies the theory of the thermodynamics of irreversible processes. The latter is the more general but both approaches give rise to simultaneous equations for the steady-state flow of matter and energy. These equations contain coefficients which are measures of physical properties of the particular medium under study. In this dissertation two heat transfer coefficients are evaluated: "real" thermal conductivity and "real" thermal diffusivity. Real thermal conductivity is one of the coefficients referred to above and real thermal diffusivity is a coefficient that appears in the equations for the transient flow of heat in moist porous media. Both thermal constants are those that would be obtained if measurements could be made without the interference of moisture transfer. A large-diameter, cylindrical thermal probe was designed and used for evaluation of these real thermal constants. The probe is heated uniformly at a constant rate and as the heat is dissipated in the surrounding medium, the probe temperature is recorded as a function of time. Thermal constants are obtained by comparing a theoretical expression with the experimental data. The theoretical expression includes the probe diameter, the heat capacity per unit length of the probe, and the thermal contact "resistance" between the probe and the surrounding medium. The analysis requires evaluation of the thermal contact resistance from the experimental data and independent determination of the volumetric heat capacity of the surrounding medium. Thermal constants close to real values but which include effects of distillation are obtained from the initial portion of the experimental record. These are then corrected for distillation by subtracting out a small quantity which can be evaluated theoretically. Values of real thermal conductivity and diffusivity were obtained at different moisture contents for 20/30 mesh Ottawa sand and for a sandy loam soil. Real thermal conductivity of the Ottawa sand (with a dry bulk density of approximately 1,7 gms/cm³) increases rapidly from a value of 0.000870 cal/°C/cm/sec when dry to 0.00Lt4 cal/°C/cm/sec at about 15% of saturation. Thereafter it apparently increases at a rate equal to the rate of increase of the volumetric heat capacity of the sand-water system to a value of 0.00755 cal/°C/cm/sec at saturation. Real thermal diffusivity of this material increases from 0.00275 cm²/sec when dry to 0,012 cm²/sec at about 15% of saturation. It remains nearly constant with further increase in water content. In a similar manner, real thermal conductivity of the sandy loam soil (with a dry bulk density of approximately 1.5 gms/cm³) increases rapidly from a value of 0,000605 cal/°C/cm/sec when dry to 0.0036 cal/°C/cm/sec at about 30% of saturation. It then increases at a rate approximately equal to the rate of increase of the volumetric heat capacity of the soil-water system to 0.00595 cal/°C/cm/ sec at saturation. Real thermal diffusivity for this material increases from 0.00223 cm²/sec when dry to 0.0090 cm²/sec at about 30% of saturation. Thereafter it remains essentially constant with further increase in water content. Thus, a single measurement of thermal diffusivity in the saturated sand and soil is sufficient to define real thermal diffusivity over a wide range of moisture contents.

This dissertation examines three different aspects of groundwater contamination by immiscible liquids, both at laboratory and field scale. The first component incorporates a study of denser than water immiscible-liquid dissolution at the laboratory scale that aims to describe the effects of immiscible liquid source-zone saturation, distribution, and length on dissolution rates. It was observed that overall immiscible-liquid saturation, distribution, and source zone length did not influence initial dissolution rates under the condition of the experiments. However, transient phase dissolution behavior, primarily observed by the heterogeneously packed columns, was significantly different to that of the homogeneously packed columns. This indicates that initial dissolution rates are comparable for these different systems, however it is demonstrated that immiscible liquid distributions (e.g., heterogeneity) can significantly effect transient dissolution rates. The second component investigates the effectiveness of a field-scale partitioning tracer test (PTT) for the measurement of the amount of denser than water immiscible liquid in the subsurface. It was demonstrated that the effectiveness of partitioning tracer test may be significantly limited by factors contributing to nonideal transport such as sorption, tracer mass, and immiscible liquid distribution. The third component examines the effectiveness of a field-scale remediation technology for the enhanced removal of denser than water immiscible liquid in the subsurface. An important component of this project was the implementation of reagent recovery and reuse, which improved the efficiency of the technology. It was demonstrated that the effectiveness of enhanced solubilization technologies for groundwater remediation may be significantly limited by the distribution of immiscible liquid in the subsurface. However, the nature of cyclodextrin (enhanced-solubilization agent) makes it an attractive option for subsurface remediation of immiscible-liquid contaminants, especially for situations where mobilization is undesirable and where the use of higher-toxicity agents is not possible.

The adaptation of the electrical resistivity tomography (ERT) for monitoring of subsurface hydrological processes is the focus of this research. Specifically, the increase in the method's accuracy, expressed by its spatial and temporal resolution, is sought. A spatial sensitivity analysis of the ERT method is presented. This sensitivity analysis is conducted by a perturbation approach, and is making extensive use of the analytic element method (AEM) to compute potentials in the subsurface. Presented are sensitivity maps for individual typical and atypical arrays. Also presented are sensitivity maps for surveys comprised of a single array type and for mixed surveys, and guidelines for array selection for the detection of a localized target. Results indicate superiority of wide arrays over small arrays, and the relatively poor performance of the double dipole array type. Several optimality criteria are discussed for the selection of an optimal survey, including optimality of individual arrays to individual subsurface targets (locally optimal), and global optimality, achieved through the use of genetic algorithms. In both cases results show superiority of mixed surveys. The method presented here, for optimal ERT configuration, opens the way for implementation of the method for a wide variety of hydrological applications. In addition to the main focus of this dissertation, a complementary work was completed to extend the AEM to compute transient processes. This unique solution uses the Laplace transform to bring the flow equation to a linear, time independent form. The resultant modified Helmholtz equation is then solved using the AEM, and the result is numerically transformed to the time domain.

A numerical first order approach is proposed to conduct stochastic analyses of head and concentration under variably saturated conditions. The approach is based on a first-order Taylor series expansion and an adjoint state method. To implement the approach in different flow and transport regimes, numerical models are adopted to evaluate sensitivities of head and concentration with respect to hydrological parameters. This provides the possibility of conducting stochastic analyses of flow and transport problems with any kind of boundary and initial conditions. As a result, limitations of analytical approaches such as the spectral/perturbation approach can be avoided. In addition, the use of adjoint state method also alleviates the computational burden encountered in Monte Carlo simulation by allowing us to evaluate the sensitivities of head and concentration only at interesting/measurement locations. Several numerical simulations are performed to examine the sensitivities and moments of head and concentration under different flow conditions. The results show that the existence of water tables in the simulation domain can have a significant impact on the moment calculation of head and concentration. The calculated statistical moments are used to estimate log-conductivity by cokriging. The conditioning effect of head, concentration, and arrival time in estimating log-conductivity is investigated under different flow conditions. The results show steady state head is the best secondary information compared to solute concentration and arrival time in estimating conductivity by providing stable and consistent results. Estimates can be error prone when concentration measurements are used to estimate LnKs because of the nonlinear relationship between concentration and LnKs and the large variability in the simulated solute plumes. A sequential estimating technique is shown to be able to overcome some of these inadequacies of using concentration measurements. Arrival time, requiring a large amount of CPU time, does not show any advantage over concentration and head in estimating conductivity.

Observations that colloidal natural organic matter (NOM) enhances the migration of pollutants in groundwater have focused scientific interest towards the transport of NOM and its adsorptive properties. A small-scale tracer test was performed at a field site in Georgetown, SC, to investigate the movement of NOM under field conditions. Special emphasis was given to the hydrological heterogeneity of the site,with the idea that the flow field must be accurately known in order to distinguish adsorption from the effects of the hydrological processes. 308 slug tests were performed to characterize the spatial variability of hydraulic conductivity at the site. Using the hydraulic conductivity dataset, a three-dimensional transport model successfully reproduced the migration of a chloride plume. In this way, the uncertainties due to hydrological factors were minimized. NOM was then injected in a second tracer test. A two-site adsorption model was used to describe NOM transport. Adsorption on the first site of the model was described by a linear equilibrium isotherm, with adsorption on the second site being described by a linear time-dependent (first order kinetic) reaction. Modeling results indicated that the time-dependent process dominated the adsorption of NOM, with a fast attachment and slow detachment rates. An approximate retardation factor of 77 was estimated for NOM. Because of the high velocities created by the forced gradient, chemical equilibria was not reached during the test. Spatial variability of the chemical properties of the aquifer was identified at two different depths of aquifer. Furthermore, differences at late times between the observed and simulated NOM breakthrough curves suggested possible changes on the adsorption properties of the soil caused by continuous NOM adsorption.

A finite element numerical model is developed for the modeling of coupled surface-water flow and ground-water flow. The mathematical treatment of subsurface flows follows the confined aquifer theory or the classical Dupuit approximation for unconfined aquifers whereas surface-water flows are treated with the kinematic wave approximation for open channel flow. A detailed discussion of the standard approaches to represent the coupling term is provided. In this work, a mathematical expression similar to Ohm's law is used to simulate the interacting term between the two major hydrological components. Contrary to the standard approach, the coupling term is incorporated through a boundary flux integral that arises naturally in the weak form of the governing equations rather than through a source term. It is found that in some cases, a branch cut needs to be introduced along the internal boundary representing the stream in order to define a simply connected domain, which is an essential requirement in the derivation of the weak form of the ground-water flow equation. The fast time scale characteristic of surface-water flows and the slow time scale characteristic of ground-water flows are clearly established, leading to the definition of three dimensionless parameters, namely, a Peclet number that inherits the disparity between both time scales, a flow number that relates the pumping rate and the streamflow, and a Biot number that relates the conductance at the river-aquifer interface to the aquifer conductance. The model, implemented in the Bill Williams River Basin, reproduces the observed streamflow patterns and the ground-water flow patterns. Fairly good results are obtained using multiple time steps in the simulation process.

Seasonally snow covered alpine areas play a larger role in the hydrologic cycle than their area would indicate. Their ecosystems may be sensitive indicators of climatic and atmospheric change. Assessing the hydrologic and bio-geochemical responses of these areas to changes in inputs of water, chemicals and energy should be based on a detailed understanding of watershed processes. This dissertation discusses the development and testing of a model capable of predicting watershed hydrologic and hydrochemical responses to these changes. The model computes integrated water and chemical balances for watersheds with unlimited numbers of terrestrial, stream, and lake subunits, each of which may have a unique, variable snow-covered area. Model capabilities include (1) tracking of chemical inputs from precipitation, dry deposition, snowmelt, mineral weathering, baseflow or flows from areas external to the modeled watershed, and user-defined sources and sinks, (2) tracking water and chemical movements in the canopy, snowpack, soil litter, multiple soil layers, streamflow, between terrestrial subunits (surface and subsurface movement), and within lakes (2 layers), (3) chemical speciation, including free and total soluble species, precipitates, exchange complexes, and acid-neutralizing capacity, (4) nitrogen reactions, (5) a snowmelt optimization procedure capable of exactly matching observed watershed outflows, and (6) modeling riparian areas. Two years of data were available for fitting and comparing observed and modeled output. To the extent possible, model parameters are set based on physical or chemical measurements, leaving only a few fitted parameters. Thc effects of snowmelt rate, rate of chemical elution from the snowpack, nitrogen reactions, mineral weathering, and flow routing on modeled outputs are examined.

Solute transport in randomly heterogeneous media is described by stochastic transport equations that are typically solved by Monte Carlo simulation. A promising alternative is to solve a corresponding system of statistical moment equations directly. The moment equations are generally integro-differential and include nonlocal parameters depending on more than one point in space-time [Neuman, 1993; Zhang and Neuman, 1996; Guadagnini and Neuman, 2001]. We present recursive approximations, and a numerical algorithm, that allow computing lead ensemble moments of non-reactive solute transport in bounded, randomly heterogeneous media. Our recursive equations are formally valid for mildly heterogeneous aquifers with σ²ᵧ < 1, where σ²ᵧ is a measure of log-hydraulic conductivity variance, or well-conditioned highly heterogeneous aquifers. Our algorithm utilizes a finite element Laplace transform method (FELT) valid for steady state velocity fields. We solved the recursive moment equations up to second order in σᵧ. We also present an iterative improvement of the recursive equations which allows reaching a solution of order higher than two in σᵧ but does not reach third order accuracy because we do not include third order moments in the computations. Computational results in two spatial dimensions conditioned on synthetic measurements of K , hydraulic conductivity, compare well with Monte Carlo results for σ²ᵧ and Peclet number (in terms of the integral scale of K) as high as 0.3 and 100 respectively for the iterative approach. As these parameters increase, the quality of our iterative moment solution deteriorates. Without conditioning the quality of the solution deteriorates more rapidly as dimensionless time increases. The recursive solution without iteration is much less accurate and deteriorates more rapidly as σ²ᵧ , Peclet number, and/or dimensionless time increase. We infer that this loss in accuracy is due to higher order moments which become important as σ²ᵧ , dimensionless time, and/or Pe increase. We also evaluate a space-localized moment equation and show that the quality of its solution is of inferior accuracy than the iterative solution. In terms of computational efficiency, the recursive and iterative methods require less CPU time than Monte Carlo transport simulations using the same numerical solution method (FELT) and without parallelization.

An efficient and simple method has been developed to improve quality and accuracy of satellite-based VIS/IR images through cloud-top relief spatial displacements adjustment. The products of this algorithm, including cloud-top temperatures and heights, atmospheric temperature profiles for cloudy sky, and displacement-adjusted cloud images, can be useful for weather/climate and atmospheric studies, particularly for high-resolution hydrologic applications such as developing IR satellite-based rainfall estimates, which are urgently needed by mesoscale atmospheric modeling and studies, severe weather monitoring, and heavy precipitation and flash flood forecasting. Cloud-top height and displacement are estimated by applying stereoscopic analysis to a pair of corresponding scan-synchronous infrared images from geostationary satellites (GOES-east and GOES-west). A piecewise linear approximation relationship between cloud-top height and temperature, with a few (6 and 8) parameters is developed to simplify and speed-up the retrieval process. Optimal parameters are estimated using the Shuffled Complex Evolution (SCE-UA) algorithm to minimize the discrepancies between the brightness temperatures of the same location as registered by two satellites. The combination of the linear approximation and the fast optimization algorithm simplifies stereoscopic analysis and allows for its implementation on standard desktop computers. When compared to the standard isotherm matching approaches the proposed method yields higher correlation between simultaneous GOES-8 and GOES-9 images after parallax adjustment. The validity of the linear approximation was also tested against temperature profiles obtained from ground sounding measurements of the TRMM-TEFLUN experiments. This comparison demonstrated good fit between the optimized relationship and atmospheric sounding profile. The accuracy of cloud pixel geo-location was demonstrated through a spatial comparison between correlation of ground-based radar rainfall rate and corresponding both adjusted and original satellite IR images. Higher correlation was represented using displacement-adjusted IR images from both geostationary satellites (GOES) with high altitudes and low altitude satellite (TRMM). Higher correlation and lower RMSE between ground-based NEXRAD observations and estimated rainfall rates from spatial adjusted IR images, using an artificial neural networks algorithm (PERSIANN), present the rainfall retrieval improvement. The ability to differentiate ground surface particularly snow-covered areas from clouds in near-real-time is another useful application of estimated cloud-top height.