Chaney Lake is a temporary karst wetland located in southern Warren County, Kentucky. Because of an impermeable chert layer between the surface and the porous limestone, Chaney Lake fills with water over the winter and spring and then gradually drains over the summer. Three experiments were conducted over the course of the 1998 flooding season to assess the effects of phosphorus addition on the phytoplankton community in Chaney Lake. Ten plastic-sided mesocosms were constructed and placed in the marsh area of the wetland at three different periods: early spring, early summer, and late summer. Phosphorus in the form of K2HPO4 was added by volume to five of the enclosures, with five remaining as controls. The water chemistry parameters measured included soluble reactive phosphate, nitrates, ammonia, and ammonium. Physical parameters such as depth, temperature, dissolved oxygen, dissolved oxygen %, specific conductivity, pH, and turbidity were measured. Chlorophyll a and phytoplankton community structure were also assessed for all three of the experiments. The various parameters were analyzed with Discriminate Function Analysis, ANOVAs, and Pearson Correlations to determine whether there were significant differences between the treated and control enclosures. The results indicate significant differences (P<0.05) between the treated and control enclosures with respect to nitrates, turbidity, and ammonia. There were no significant differences in SRP, chlorophyll a, DO, DO%, SPC, pH, temperature, depth, and phytoplankton composition. It was concluded that phytoplankton in Chaney Lake may not be limited by phosphorus. However, phosphorus may limit bacterioplankton, periphyton, or both. The high nutrient concentrations with low elemental ratios indicate that bacterioplankton may be more efficient in phosphorus utilization and possibly play an important role in nutrient availability for phytoplankton in the marsh area of Chaney Lake.

The Matozinhos-Pedro Leopoldo limestone area is a tropical karst located near the metropolis of Belo Horizonte, East Central Brazil, in an area undergoing rapid urbanization and land degradation. Qualitative dye tracing experiments have determined the groundwater routes and catchment areas in the two major drainage basins in the area, Samambaia Basin and Palmeiras-Mocambo Basin. Other drainage basins were identified, but not traced due to the absence of related swallets. Fluorescein and optical brightener had a poor performance as tracers under tropical climate. Dilution due to the existance of lakes at some swallets prevented some dye traces. The water that flows through this karst area is almost entirely autogenic, having a small external contribution from some phyllite areas. About 88% of the total water discharge of identified springs drains directly toward Velhas River, the regional base level. The remaining 12% drains toward Mata Creek, a tributary of the Velhas River. Hydrochemical monitoring in four of the major springs showed that groundwater quality for the measured parameters in the discharge zone is generally good, despite the heavy industrialization and occupation in some of the recharge areas. Conduit flow predominates in Samambaia and Palmeiras- Mocambo Basins. The outlets for these basins show a marked seasonal variation in the physical and chemical parameters monitored. Some of the other springs such as Moinho Velho Spring and Jaguara Spring show little variation in temperature, suggesting a diffuse flow component. All springs are characterized by hardness dilution during the wet season, suggesting a small residence time during the wet season, not allowing the water to achieve saturation. Seasonal variation in runoff is the most important control on the hydrochemical pattern of the area. It determines the marked dilution of major ions in both conduit-flow and diffuse-flow springs. Variation in soil C02 due to the rainfall pattern may also play an important role in the water chemistry. Observation of paleoflow indicators made in several dry caves showed that the past flow pattern at Palmeiras-Mocambo Basin agrees with the present groundwater routes. At Samambaia Basin, however, the lower reaches of the basin show paleoflow directions pointing toward other active base levels such as Mocambeiro Depression or Velhas River, suggesting that Samambaia Basin may have developed its present morphology in a later stage.

Flash flooding kills more people in the United States than any other severe weather phenomenon. One of the most vulnerable areas for flooding is the southern Appalachians. These mountains lie in a geographical location that places them near the Atlantic Ocean and the Gulf of Mexico, two major moisture source regions. This ample supply of moisture, mid-latitude circulation patterns, and orographic lifting leads to annual precipitation totals in the southern Appalachians that are comparable to locations along the Gulf coast. The present study investigates eight non-tropical flash flood events. Four of the events occurred in the cool season and four occurred in the warm season. Several meteorological parameters were analyzed using NARR data and synoptic soundings for the pre-storm and storm environments of eight flash flood events. The results show significant differences in the role of moisture advection and wind profiles between the cool and warm season events. In addition, the cool season events were rather widespread in aerial coverage, while the warm season events were typically quite isolated in nature. For example, a large mid-latitude cyclone resulted in up to four inches of rain on large portions of the southern Appalachians on January 26, 1996. On the other hand, during the afternoon of June 22, 2001, slow-moving thunderstorms produced as much as four inches of rain on Skyland, North Carolina. This research shows the role of synoptic and mesoscale settings and their forcings on the evolution of these extreme hydrometeorological events.

Investigation of infiltration provides insights about the flow of water and transport of contaminants through the vadose zone. Infiltration is governed by prevailing environmental conditions like soil characteristics, plant cover and geologic settings. The main objective was to study preferential flow dominated infiltration at two contrasting hydrologic settings in Texas. For the first study, artificial rainfall was simulated within a plot covered with juniper trees at a karst region of the Edwards Plateau and sub-surface flow was monitored using TDR probes. Sub-surface flow was simulated using HYDRUS-2D. Results demonstrated that sub-surface flow occurred in a tri-modal manner, consisting of flow in karst conduits, planar fractures in the limestone, and soil matrix. Both fracture and matrix flow responses increased with increase in rainfall intensity. During large rainfall events, water exchange was observed between the fractures and matrix. Dye studies indicated that fractures and juniper roots were primary pathways for preferential flow occurring within the plot. The model simulated flow characteristics like exchange processes and differentiated between preferential and conduit flow besides determining approximate van Genuchten parameters for each geologic unit.For the second study, tension infiltrometers were used to conduct infiltration experiments at six soil water pressures (?? = -0.2 to 0 m) in an agricultural field near College Station over a 21 month period. The aim was to determine steady infiltration rate, if, saturated hydraulic conductivity, Ksat, unsaturated hydraulic conductivity, K(??) and unsaturated flux density ??(??). Moreover, the effect of varying disc diameters on steady state infiltration rates (if) was also studied. Results demonstrated that infiltration occurred in a bi-modal fashion consisting of preferential flow and matrix flow. Macropores and roots present in the soil resulted in gravity dominated flow at ?? = -0.05 to 0 m for all experiments. Statistical analysis suggested that the soil did not exhibit spatial variability within the plot and the five different disc diameters had no effect on if. Statistically significant differences in if were observed between 0.2 and 0.24 m disc diameters at saturation over the 21 month period. The if values illustrated strong temporal variations based on natural conditions over the 21 month period.

This dissertation summarizes actualistic research in the intertidal environments of northeastern Baja California, Mexico. The first project is a taphofacies analysis of three generations of cheniers that differ in age and taphonomic history. The study shows that the shells that accumulated in the cheniers are slightly affected by biological processes and moderately affected by physical processes. Only the luster features of shells vary substantially and consistently with chenier age -- a result of subaerial weathering. Taphofacies analysis successfully discriminates the three chenier generations. Chenier assemblages are distinct from assemblages formed in other marine environments by a lower frequency of bioerosion and encrustation. Taphonomic differences between the cheniers that differ in age suggest that fossil cheniers may be useful in detecting incompleteness gradients along stratigraphic boundaries (i.e., taphofacies with shells of poorer-than-average preservation indicate a longer subaerial exposure and thus a larger stratigraphic hiatus). The second project investigates the taphonomy of a Recent lingulide brachiopod Glottidia palmeri Dall. Live lingulides occur in patches across the intertidal zone. Dead specimens include in situ shells, surface shells (found on intertidal flats), and beach shells (found on the shoreface). Recent lingulides have a very low fossilization potential. Consequently, large-scale aspects of their history are poorly recorded in the fossil record, but the outcrop-scale aspects may be recorded with high fidelity. The literature survey suggests that Paleozoic lingulides had a higher fossilization potential than their post-Paleozoic relatives. The decrease in diversity and ecologic importance of lingulides after the Paleozoic may be due to a taphonomic megabias. The third project proposes a comparative use of size-frequency distributions derived from trace fossil assemblages for interpretation of ancient populations. Two examples illustrate the approach: Recent lingulide burrows (Baja California) and Cambrian Diplocraterion burrows (Arizona). They show that the approach can provide accurate data useful for paleoecology, sedimentary facies analysis and even local stratigraphic correlations. The fourth project is a theoretical essay on the concept of time-averaging and the concluding part of the dissertation discusses the pitfalls and premises of the actualistic approach in the context of my research in Baja California.

As land-surface modeling moves from the off-line mode to the coupled mode, it is also highly desirable to extend the off-line calibration of land-surface models to coupled applications. Using the NCAR SCCM as an example, this study proposed and implemented some effective schemes for the application of automatic parameter estimation procedures in a locally coupled environment, where other relevant issues such as parameterization tests, sensitivity analyses, and off-line calibrations were also involved. A parameterization deficiency having serious negative impacts on the performance of the NCAR SCCM was identified and rectified in this work, which led to significantly improved model performances and formed the basis for the subsequent sensitivity analysis and calibration experiments. To facilitate the calibration studies, an independent sensitivity analysis was conducted to identify some sensitive model parameters, followed by a multi-objective sensitivity analysis using the MOGSA algorithm to obtain better understanding of the model. Some off-line calibrations using the NCAR LSM were also conducted for comparison purposes. In the locally coupled environment, both land-surface and atmospheric variables/parameters were involved in the calibration processes of 14 different predesigned calibration cases. In brief, the results show that atmospheric parameters are of critical importance for the calibration of a coupled land surface-atmosphere model, and atmospheric forcing variables generally contain more useful information for calibration than land-surface fluxes/variables. In the coupled environment, step-wise calibration schemes, with land-surface and atmospheric parameters optimized successively in the off-line and coupled modes, respectively, appear to be superior to the single-step calibration schemes which optimize land-surface and atmospheric parameters simultaneously in the coupled environment, in that the former can provide better converged optimal solutions with less uncertainties. In addition, the results also show that better optimization effects can be achieved in the partially decoupled environment by replacing the model-generated precipitation and net radiation with the corresponding observations to drive the land-surface part of the model, indicating the dominant importance of precipitation and radiation in a coupled land surface-atmosphere model.

There are three components of error in the ability of land-atmosphere models (e.g., BATS, SiB, etc.) to simulate/predict observed land-surface state variables and output fluxes (e.g. lambdaE, H, Tg, Q, etc.). The first is caused by model structural error associated with simplifications and/or inadequacies in the functional representations of underlying physical processes. The second component is measurement error associated with the input and output data. The third is caused by error in specification of the values of the model parameters. Automatic parameter tuning (model calibration) methods allow minimizing of the parameter error, thereby obtaining an estimate of the remaining error components. This work describes an automatic multi-criteria approach and its use to tune all 27 parameters of the BATS model using data measured in the field. The parameters were adjusted to simultaneously optimize the ability of the model to reproduce observed values of several output fluxes and/or state variables (e.g., latent heat flux, sensible heat flux, ground temperature, etc.). The results indicate that not only does the procedure result in conceptually reasonable and consistent parameter estimates, but the calibrated model is able to provide significant improvement in performance (33% or more reduction in error) over the "un-calibrated" model (i.e., using the BATS default parameter values for the associated region). Substantial improvements of this kind can have important implications for studies that seek to evaluate alternative model structures or to regionalize parameters. To reduce the dimensionality of the optimization problem a multi-criteria extension of the Regionalized Sensitivity Analysis (RSA) has been developed.

We propose a new method for the solution of stochastic unsaturated flow problems in randomly heterogeneous soils which avoids linearizing the governing flow equations or the soil constitutive relations, and places no theoretical limit on the variance of constitutive parameters. The proposed method applies to a broad class of soils with flow properties that scale according to a linearly separable model provided the dimensionless pressure head ψ has a near-Gaussian distribution. Upon treating ψ as a multivariate Gaussian function, we obtain a closed system of coupled nonlinear differential equations for the first and second moments of pressure head. We apply this Gaussian closure to one-dimensional steady state, transient, and two-dimensional unsaturated flow through randomly stratified soils with hydraulic conductivity that varies exponentially with aψ̅ where ψ̅=(¹/α)ψ is dimensional pressure head and α is a random field with given statistical properties. For flow in a one-dimensional steady state medium, we obtain good agreement between Gaussian closure and Monte Carlo results for the mean and variance of ψ over a wide range of parameters provided that the spatial variability of α is small. Our solution provides considerable insight into the analytical behavior of the stochastic flow problem. For transient flow in a one-dimensional unsaturated medium with randomly homogeneous soil, Gaussian closure and Monte Carlo results for mean dimensionless pressure are in excellent agreement. However, Gaussian closure and Monte Carlo results for variance, although qualitatively acceptable, are only quantitatively accurate for large times or for early times when the variance of the log hydraulic conductivity is small. Finally, we develop a finite element framework with which to solve the two-dimensional steady state Gaussian closure moment equations.

A new stochastic inverse algorithm for the inversion of three-dimensional (3-D) electrical resistivity tomography (ERT) data has been developed and tested using both synthetic and field data. My stochastic inverse algorithm produced satisfactory inverse solutions that were very similar to those of the commonly used Occam's inversion. The ill-posed 3-D stochastic inverse problems were stabilized by incorporating a-priori information in the algorithm in the form of an a-priori model, and data and model covariance matrices. There were several novel features in my algorithm. First, a very fast successive over-relaxation (SSOR) preconditioner was implemented in the conjugate-gradient forward solver. Second, a trade-off factor adapted from the Occam's inversion was employed in the algorithm for better control of convergence. Third, the QMRCGSTAB inverse solver, a quasi-minimal residual (QMR) variant of the stabilized bi-conjugate gradient method (Bi-CGSTAB), was used to solve an asymmetric linearized iterative system, so the inversion of a large model covariance matrix was sidestepped. Therefore my algorithm can handle a variable scale of model correlation. Fourth, much better convergence was achieved by using the data standard deviation instead of the data variance as the entries of data covariance matrix. Fifth, a model covariance weighting scheme using the diagonal of the transposed sensitivity matrix times the sensitivity matrix improved the model resolution greatly in the region where is usually poorly resolved. The run-time of stochastic inversion with a biconjugate-gradient inverse solver doubled that of the Occam's inversion with a conjugate-gradient solver. To speed up the stochastic inversion in in-situ monitoring applications, I developed an efficient difference inversion algorithm to invert the difference between the background and subsequent data sets. The new difference inversion can be two to three times faster than the stochastic inversion. I also developed a unique cokriging approach to estimate a 3-D moisture content distribution quantitatively from 3-D ERT data and a limited number of neutron-derived moisture content data for an infiltration experiment in Socorro, New Mexico. I found that one neutron well in the center of ERT mesh, where model parameters are usually poorly resolved in ERT inversion, played an indispensable role in cokriging.

Laboratory methods were used to define matrix hydraulic properties for low-permeability Apache Leap Tuff core segments. Moisture content/matric potential relationships, including hysteresis, and measured hydraulic conductivity data were determined at a constant laboratory temperature of 20°C. To investigate the effects of temperature on those relationships, additional retention data were obtained at 5°C and 45°C. Measured retention data at all temperatures were applied to the van Genuchten model RETC, which performs curve-fitting and calculation of the flow parameter hydraulic conductivity. Although data at 5°C proved to be inconclusive, increasing the temperature from 20 to 45°C produced a shift of the moisture characteristic curve toward a higher potential for a given water saturation. Model-calculated hydraulic conductivity also increased as temperature increased, with respect to water saturation. The temperature-dependent change in the viscosity of water proved inadequate to explain the increases of hydraulic conductivity with temperature.