<p>This doctoral dissertation presents the derivation and application of a series of water quality models and modeling strategies which provide critical guidance to water quality-based management decisions. Each model focuses on identifying and explicitly acknowledging uncertainty and variability in terrestrial and aquatic environments, and in water quality sampling and analysis procedures. While the modeling tools I have developed can be used to assist management decisions in waters with a wide range of designated uses, my research focuses on developing tools which can be integrated into a probabilistic or Bayesian network model supporting total maximum daily load (TMDL) assessments of impaired shellfish harvesting waters. Notable products of my research include a novel approach to assessing fecal indicator bacteria (FIB)-based water quality standards for impaired resource waters and new standards based on distributional parameters of the in situ FIB concentration probability distribution (as opposed to the current approach of using most probable number (MPN) or colony-forming unit (CFU) values). In addition, I develop a model explicitly acknowledging the probabilistic basis for calculating MPN and CFU values to determine whether a change in North Carolina Department of Environment and Natural Resources Shellfish Sanitation Section (NCDENR-SSS) standard operating procedure from a multiple tube fermentation (MTF)-based procedure to a membrane filtration (MF) procedure might cause a change in the observed frequency of water quality standard violations. This comparison is based on an innovative theoretical model of the MPN probability distribution for any observed CFU estimate from the same water quality sample, and is applied to recent water quality samples collected and analyzed by NCDENR-SSS for fecal coliform concentration using both MTF and MF analysis tests. I also develop the graphical model structure for a Bayesian network model relating FIB fate and transport processes with water quality-based management decisions, and encode a simplified version of the model in commercially available Bayesian network software. Finally, I present a Bayesian strategy for calibrating bacterial water quality models which improves model performance by explicitly acknowledging the probabilistic relationship between in situ FIB concentrations and common concentration estimating procedures.</p> / Dissertation

<p> Erosion along shorelines in open water bodies and waterways is a major cause in conversion of wetlands and uplands to an open water environment. Conventional shoreline protective structures are expensive to construct in these environments, and they may impede environmental exchanges that are essential for connectivity and functionality. The Wave Suppression and Sediment Collection (WSSC) System (Wave Robber&trade;) could become an alternative Device in shoreline protection. The primary goals of this study are to evaluate its performance in both wave reductions and sediment collection in the lab, and to optimize the design and to compare the efficiency of the Device in different conditions. This study showed that the WSSC can collect and retain sediment while reducing about 84 to 90% wave height. A new mass balance model was developed to evaluate its performance in sediment collection. A variable &agr;, ranging from 0 to 1, represents the sediment collection efficiency of the Devices, was introduced into this model. The sediment data fitted the model reasonably well, yielding the correlation coefficients of about 0.87. Modeling results show that the sediment collection efficiency of WSSC for silt-clay soil was about 14%. The model used could become useful for not only evaluating this Device, but even using it to evaluate existing Devices. The sensitivity study showed that the wave height and the initial concentration were the most important factors effecting sediment collection. Water depth also plays an important role in that it reduces the sediment collection as the water depth increases. The preliminary field study showed some elevation changes behind the WSSC due to sediment accumulation.</p>

Nonlocal moment equations allow one to render optimum predictions of flow in randomly heterogeneous media deterministically conditional on measured values of medium properties and to assess the corresponding predictive uncertainty. I present a geostatistical inverse algorithm for steady-state flow that makes it possible to further condition such predictions and assessments on measured values of hydraulic head and (or) flux. My algorithm is based on recursive finite-element approximations of exact first and second conditional moment equations. Computational efficiency is enhanced through the use of a direct sparse matrix solver. Hydraulic conductivity is parameterized via universal kriging based on unknown values at pilot points and (optionally) measured values at other discrete locations. Correlation among parameter estimates (or priors) is considered in the universal kriging equations. Optimum unbiased inverse estimates of natural log hydraulic conductivity, head and flux are obtained by minimizing a calibration criterion, composed of residuals of head or (and) flux and (possibly) log conductivity, using the Levenberg-Marquardt algorithm. Statistical parameters characterizing the natural variability of hydraulic conductivity can also be estimated using this algorithm. I illustrate the method for superimposed mean uniform and convergent flows in a bounded two-dimensional domain under various conditions for a range of parameters. My examples illustrate how conductivity and head data act separately or jointly to reduce parameter estimation errors and model predictive uncertainty. Over-parameterization is seen to create zones of high mean conductivity, in which flux prediction is more uncertain than is in other regions. It is found that a regular distribution of pilot points works better than does an irregular layout and that the number of pilot points should be as close as possible to the number of head data while maintaining parameters reasonably uncorrelated. Head and flux predictions are very satisfactory for cases with either log conductivity variance or integral scale between one and four, though prediction quality deteriorates with either larger variances or shorter integral scales. The method may perform satisfactorily in cases with no conductivity measurements and only a few head data.

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.

The objective of this study is to develop a practical mathematical model to determine optimal operating rules for the reservoir system of the West Branch Penobscot River in the State of Maine of the US. This system is composed of five major lakes and it has three objectives. The hydrological data are not available in winter in the upstream four lakes due to freeze and the length of flow data is less than 25 years. Dynamic programming (DP) has been used extensively for solving reservoir operation problems. One major drawback of DP for multiple reservoir operation is the "curse of dimensionality". Many variations of the original DP have been proposed to ease this problem, for example, incremental DP, discrete differential DP, differential DP, gradient DP, and spline DP. Instead of a DP approach, this study proposes using a nonlinear programming (NLP) approach to solve the multi-reservoir system. NLP has been developed extensively in the field of operations research but not yet widely used in reservoir operations. A distinct advantage of using an NLP model is that it can avoid the dimensionality problem because it solves directly the problem without discretizing the decision variables. To use the NLP approach, a real time operation model is specified at first. Then, a multivariate first-order autoregressive model is used to generate a large number of future inflow sequences. The MINOS software package is then used to optimize the problem with each inflow sequence. MINOS can be implemented seemly in the simulation process and can solve the problems without starting values of variables. The number of runs in a simulation is determined by a statistical model, which shows that 500 runs are sufficient. Finally, the expected values and standard deviations of decision variables are tabulated and the distributions of decision variables are plotted. The proposed real time operation model runs once every month. An information-updating scheme is embedded into the simulation and optimization models. For each month, the synthetic streamflows are updated to reflect the most recent hydrological conditions. Besides, the objective function and constraints can be modified if the situation of the system changes.

This dissertation documents research results from a series of field experiments and analyses used to test interpretive models for investigating the role of fractures in fluid flow through unsaturated, fractured tuffs. It summarizes the experimental design of single- and cross-hole pneumatic injection tests, including borehole configuration and testing schedules, data collection system, interpretive models developed and tested, data, and conclusions. Single-hole tests were interpreted by Guzman et al. (1996) by means of steady-state analysis to obtain permeability values based solely on late pressure data. This dissertation and Illman et al. (1998) employ pressure and pressure-derivative type-curves to analyze transient data. Air permeabilities determined from transient analyses agree well with those derived from steady-state analyses. Cross-hole pneumatic tests were analyzed by means of a graphical matching procedure using newly-developed pressure and pressure-derivative type-curves. Analyses of pressure data from individual monitoring intervals using these new type-curves, under the assumption that the rock acts as a uniform and isotropic fractured porous continuum, yield results that are comparable with parameters obtained from a numerical inverse procedure described in Illman et al. (1998). The results include information about pneumatic connections between the injection and monitoring intervals, corresponding directional air permeabilities, and air-filled porosities. Together with the results of earlier site investigations, single- and cross-hole test analyses reveal that at the Apache Leap Research Site in central Arizona: (1) the pneumatic pressure behavior of fractured tuff is amenable to analysis by methods that treat the rock as a continuum on scales ranging from meters to tens of meters; (2) this continuum is representative primarily, but not exclusively, of interconnected fractures; (3) its pneumatic properties vary strongly with location, direction and scale, in particular, the mean of pneumatic permeabilities increases, and their variance decreases with scale; (4) this scale effect is most probably due to the presence in the rock of various size fractures that are interconnected on a variety of scales; and (5) given a sufficiently large sample of spatially varying pneumatic rock properties on a given scale of measurement, these properties are amenable to analysis by geostatistical methods, which treat them as correlated random fields defined over a continuum.

The safe disposal of arsenic-containing waste has been a difficult problem for the mining and metallurgical industry. One of the solutions to the arsenic problem is the precipitation of scorodite, an arsenic-containing mineral. Scorodite is reported to be relatively stable over a wide range of pH, and therefore may be a preferred disposal option. The effect of organic complexing agents on scorodite stability, however, is largely unknown. The present study is a phenomenological investigation into the dissolution kinetics of scorodite in the presence of oxalic acid under varying conditions of pH, oxalic acid concentration and temperature. The effect of scorodite particle size was also investigated. The morphological changes accompanying the dissolution process were examined by SEM and TEM analyses. Dissolution curves were divided into a linear induction period and a post-induction period. Activation energies were determined. Complete dissolution data were fit to the Prout-Tompkins/Austin-Rickett model. Dissolution data are indicative of auto-accelerated processes. The rapid increase in dissolution rate following the induction period is believed to be associated with an increase in the effective surface area. Pitting was observed on the surface of scorodite in the early stages of dissolution. In the later stages of dissolution, these pits were observed to grow and coalesce, in many cases resulting in the formation of dissolution holes.

<p> A team at the University of Colorado at Boulder is working with the Bill &amp; Melinda Gates Foundation to develop a novel technical solution for 2.5 billion people in the developing world with no access to basic sanitation. The university's Sol-Char toilet uses concentrated sunlight to convert human fecal sludge into biochar, which has potential as a value-added product. The feasibility of using feces-derived biochar as a solid fuel for heating and cooking is assessed, considering energy content and elemental analysis of biochars made under different reactor conditions, ease of briquetting, and durability of biochar briquettes. Fecal biochars made at 300&deg;C were similar in energy content to wood biochars and bituminous coal, possessing a higher heating value of 25.6 MJ/kg, while fecal chars made at 750&deg;C were significantly lower in energy content at 13.8 MJ/kg. Chars derived from simulant feces favored by other Bill &amp; Melinda Gates Foundation sanitation research projects were found to differ significantly from fecal char in their energy content and briquetting characteristics. A frequently used correlation between elemental composition of chars and their higher heating values was adapted to be more applicable to feces-derived chars based on a review of fecal char literature and experimental results. Fecal chars made at low temperatures and briquetted with molasses and lime binders yielded briquettes of comparable strength and energy content to commercial charcoal briquettes, suggesting that briquettes made from human feces could be a significant contribution to the sanitation value chain.</p>

Recent technological advancements in hydrologic science and geographic information systems (GIS) have permitted the rapid and accurate analysis of flood control options in the Clear Creek watershed. Models were developed using the Hydrologic Engineering Center's latest hydrologic and hydraulic programs, including HEC-HMS, HEC-RAS and HEC-GeoRas. These models were used to develop alternatives to large-scale channelization, including limited channelization, floodplain property buyouts, and a combination approach. NEXRAD radar was used to compliment an inadequate rain gage network. The above tools were coupled with available floodplain data and a GIS program (ArcView) to produce floodplain mapping for each scenario. The effects of six different limited channelization schemes were explored. Cost estimates were calculated for properties within various return frequency floodplains. Results show that the combination of one of the investigated channelization schemes with buyouts of properties in the residual floodplain was the most viable from the perspectives of flood control and economics.

Flood Alert System (FAS2) incorporates adjusted real-time NEXRAD radar data, GIS, hydrologic models and the Internet to provide advanced warning to the Texas Medical Center (TMC) in Houston, Texas. It has been tested during 2006 season with excellent performance and was used as a platform to develop a real-time hydraulic prediction tool---the Floodplain Map Library (FPML) system. FPML provides inundation maps in near real time linking with NEXRAD radar over the watershed. FPML is also compatible with storm surge input in order to predict inundation maps during extreme coastal weather conditions, which will improve emergency personnel's ability to initiate evacuation strategies at many levels.