Theses and Dissertations

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Open Access
Chloride binding and desorption mechanism in blended cement containing supplementary cementitious materials exposed to de-icing brine solutions
(Colorado State University. Libraries, 2024) Teymouri Moogooee, Mohammad, author; Atadero, Rebecca, advisor; Fantz, Todd, advisor; Jia, Gaofeng, committee member; Bailey, Travis, committee member
Concrete, the most widely used construction material globally, faces significant challenges due to its porous nature, particularly from chloride-induced corrosion. This corrosion, primarily caused by chloride ions penetrating concrete, affects over 7.5% of U.S. concrete bridges, incurring annual costs ranging from $5.9 to $9.7 billion. Chlorides enter concrete from various sources, including de-icing salts. Maritime infrastructures also suffer from severe chloride-induced corrosion because seawater contains a high concentration of chloride ions. Irrespective of how chlorides enter the concrete, chlorides can exist in concrete in two forms: free and bound chlorides. While bound chlorides are beneficial, they can be released due to environmental factors like carbonation and chemical attacks, exacerbating corrosion rates. These attacks cause pH reduction in concrete and subsequently can result in the release of bound chlorides (chloride desorption).This dissertation aims to address three main objectives: (1) investigate factors influencing chloride binding measurements due to lack of a standardized method for chloride binding measurements, (2) study chloride desorption mechanisms in different cementitious systems exposed to de-icing brines, and (3) analyze pH and compositional changes in blended pastes under chloride contamination and carbonation. First, factors impacting chloride binding measurements were identified, such as sample form and saturation level, solution composition, and solution volume. Vacuum-saturated samples exhibited higher chloride binding than partially saturated or dried samples, with powdered samples showing the highest binding. Secondly, chloride desorption mechanisms were investigated in both Ordinary Portland Cement (OPC) pastes and pastes containing supplementary cementitious materials (SCMs) like fly ash, slag, and silica fume. Results indicated that the type of cation in the brine solution influenced bound chloride levels, with SCMs improving chloride binding capacity. Slag inclusion was effective in promoting chloride binding, while silica fume showed the least effect. The degree of chloride desorption under acid attack depended on the acid-to-paste mass ratio. The results reveal that inclusion of fly ash and slag is favorable in terms of chloride desorption, and silica fume is not recommended for use when chloride-induced corrosion is a concern. MgCl2 and CaCl2 de-icers demonstrated a lower chloride desorption compared to NaCl. Finally, the synergistic effects of chloride contamination and carbonation were examined in OPC and fly ash-containing pastes. Carbonation led to over 95% chloride desorption after two weeks, with fly ash-containing pastes exhibiting lower pH levels due to reduced portlandite content. Incorporation of fly ash is not recommended when carbonation is a concern. Therefore, caution should be exercised when considering fly ash inclusion in mixtures where both chloride contamination and carbonation are simultaneous concerns. This dissertation contributes to understanding chloride desorption in cementitious systems, essential for enhancing the durability and service life of concrete structures. This dissertation shed lights on primary factors influencing chloride binding measurements, enhancing the accuracy and comparability of chloride binding results. The results reveal that type of cation present in the solution and type of SCMs have significant influences on the pH, chloride binding capacity, and chloride desorption rates.
Embargo
Integrated assessment of water shortage under climate, land use, and adaptation changes in the contiguous United States
(Colorado State University. Libraries, 2024) Gharib, Ahmed AbdelTawab Fahmy AbdelMeged, author; Arabi, Mazdak, advisor; Goemans, Christopher, committee member; Sharvelle, Sybil, committee member; Warziniack, Travis, committee member
Water scarcity is a critical global challenge. Water managers pursue water supply- and demand-side strategies, including construction or enhancement of water supply systems, conservation, and water reuse, to address water security driven by changes in climate, population, and land use. However, the effects of these strategies to mitigate future water shortages under dynamic climate and socioeconomic conditions at various spatial and temporal scales remain unclear. The overarching goal of this dissertation is to (1) improve understanding of the interconnections and interactions between climate, socioeconomic, hydrological, and institutional factors that influence water shortage at the river basin level, and (2) conduct an integrated assessment of water and land use management strategies. The dissertation is organized into three research studies. The first study explores water shortages in the South Platte River Basin (SPRB) and the potential benefits of investing in storage infrastructure and demand management strategies. The second study develops a methodology to understand the interactions between land use planning, water demands, shortage vulnerability, and effects on associated economic value. The third study expands the integrative assessment framework to assess changes in water demand, supply, and withdrawals, and identify effective mitigation strategies across river basins in the Contiguous United States over a range of climatic and socioeconomic pathways that are forecasted for the coming decades. In the first study, we develop data analysis and modeling tools to project water demands, supply, and shortages in the SPRB by the mid and end of the 21st century, examine the efficacy of adaptation strategies to reduce water shortages, and explore conditions under which reservoir storage and demand management would serve benefits for reduction of the vulnerability of economic sectors to water shortages. We implement two demand modeling tools to simulate the current and future urban and agricultural water demand in the river basin. Water yield is simulated using calibrated and tested Variable Infiltration Capacity (VIC) model. The estimated water demands and supplies are integrated using the Water Evaluation and Planning (WEAP) model to simulate water allocation with a half-monthly timestep to 70 aggregate users in the basin. Population growth, climate change, reservoir operations, and institutional agreements were considered during the modeling. The study reveals that the vulnerability to water shortages across sectors would increase without adaptation strategies. Population growth tends to be the primary driver of water shortages in the river basin. Reservoirs in the basin can relieve the sequences of the earlier seasonal shift of the water supply by capturing water during the high flow to be used in the high-demand seasons. However, additional storage is only beneficial up to a threshold of storage capacity to the water supply mean ratio of 0.64. The second study focuses on integrating the effects of land use planning and water rights institutions into the shortage analysis of the SPRB. The goal is to build a framework to understand the complex interactions between climate change, water rights institutions, urban land use planning, and population growth, and how they collectively impact the water shortage and economic analysis. We apply this framework to the SPRB simulate three water institutions, update the urban demand modeling to be a function of the population density, and test different scenarios of population locations throughout the basin. Results show that changing water rights institutions has a small impact on total shortages compared to climate change, but substantially impacts which users experience shortages. Land use policies influencing population locations have larger impacts on shortage and economic value compared to water rights. Finally, distributing the population more evenly between upstream and downstream regions reduces water shortages and increases associated economic value regardless of water rights institutions and climate conditions. The third study employs an integrative modeling assessment framework to assess water shortage and effective mitigation strategies in river basins across the Contiguous United States. The goals are to improve the methodologies for estimation of water withdrawals, consumptive use, and water shortage, and explore the effectiveness of supply- and demand-side adaptation strategies. The simulated demands are integrated with the water supply components (groundwater, interbasin transfers, water yield, and reservoirs) into a water allocation model for simulating shortage under different scenarios. Results reveal that irrigation has the highest historical and future consumptive use, over 75% of the total consumptive use. Although the consumptive use ratio receives little attention in the literature, it appears to be the most significant parameter for shortage calculations. The allocation model provides comprehensive shortage analysis considering shortage volume, ratio, and frequency across multiple scenarios for the 204 sub-regions –Hydrologic Unit Code 4 watersheds– of the Contiguous United States. Water shortages concentrate between the boundaries of the West Region with both the Midwest and the South regions, in addition to Arizona, Florida, and the center valley of California. Relying only on sustainable groundwater pumping rates is essential to stop the ongoing groundwater depletion, but adds more pressure on demand reduction strategies. The ongoing research examining water demand, supply, and shortage is important and requires further integration of the key influencing variables. This dissertation demonstrates the necessity of an integrated approach to fully understand the relative impacts of the main drivers of water allocation and shortage. We highlight that reservoirs play a vital role in balancing seasonal fluctuations in the water supply. However, their effect on the 30-year mean annual shortage is effective until the storage volume ratio to mean water supply exceeds 64%. Additionally, land use policies carry higher direct significance on water shortages compared to water rights. We find that distributing the population more evenly throughout the river basin provides the lowest shortage. Lastly, the approaches targeting shortage calculation and mitigation should analyze both regional and national scenarios under integrated frameworks comparing demand- and supply-side options.
Embargo
Tools for characterizing and monitoring natural source zone depletion
(Colorado State University. Libraries, 2024) Irianni Renno, Maria, author; De Long, Susan K., advisor; Sale, Thomas C., advisor; Key, Trent A., committee member; Scalia, Joseph, committee member; Stromberger, Mary, committee member
Although natural source zone depletion (NSZD) has gained acceptance by practitioners as a remediation technology for mid- to late-stage sites containing light non-aqueous phase liquids (LNAPL), challenges remain for broader regulatory adoption of NSZD as the sole remedy. Adoption of NSZD as a remedy requires verifying that it is occurring. NSZD can be an efficient and cost-effective solution for LNAPL zones, but acceptance of this bioremediation technology relies on a multiple-lines-of-evidence approach that requires a solid understanding of baseline conditions and effective monitoring. Emerging use of in situ oxidation-reduction potential (ORP) sensors shows promise to resolve spatial and temporal redox dynamics during NSZD processes. Further, next generation sequencing (NGS) of present and active microbial communities can provide insights regarding subsurface biogeochemistry, associated elemental cycling utilized in electron transport (e.g., N, Mn, Fe, S), and the potential for biodegradation. Microbially-mediated hydrocarbon degradation is well documented. However, how these microbial processes occur in complex subsurface petroleum impacted systems remains unclear, and this knowledge is needed to guide technologies to enhance biodegradation effectively. Analysis of RNA derived from soils impacted by petroleum liquids allows for analysis of active microbial communities, and a deeper understanding of the dynamic biochemistry occurring during site remediation. However, RNA analysis in soils impacted with petroleum liquids is challenging due to: 1) RNA being inherently unstable, and 2) petroleum impacted soils containing problematic levels of polymerase chain reaction (PCR) inhibitors (e.g., aqueous phase metals and humic acids) that must be removed to yield high-purity RNA for downstream analysis. Herein, a new RNA purification method that allows for extracting RNA from petroleum impacted soils was developed and successfully implemented to discriminate between active (RNA) and present (DNA) microbes in soils containing LNAPL. A key modification involved reformulation of the sample pretreatment solution by replacing water as the diluent with a commercially available RNA preservation solution consisting of LifeGuard™ (Qiagen) Methods were developed and demonstrated using cryogenically preserved soils from three former petroleum refineries. Results showed the new soil washing approach had no adverse effects on RNA recovery but did improve RNA quality by removing PCR inhibitors, which in turn allows for characterization of active microbial communities present in petroleum impacted soils. To optimally employ NSZD and enhanced NSZD (ENSZD) at sites impacted by LNAPL, monitoring strategies are required. Emerging use of subsurface Soil redox sensors shows promise for tracking redox evolution, which reflects ongoing biogeochemical processes. However, further understanding of how soil redox dynamics relate to subsurface microbial activity and LNAPL biodegradation pathways is needed. In this work, soil redox sensors and DNA and RNA sequencing-based microbiome analysis were combined to elucidate NSZD and ENSZD (biostimulation via periodic sulfate addition and air sparging) processes in columns containing LNAPL impacted soils from a former petroleum refinery. Herein, microbial activity was directly correlated to continuous soil-ORP readings. Results show expected relationships between continuous soil redox and active microbial communities. Continuous data revealed spatial and temporal detail that informed interpretation of the hydrocarbon biodegradation data. Redox increases were transient for sulfate addition, and DNA and RNA sequencing revealed how hydrocarbon concentration and composition impacted microbiome structure and naphthalene biodegradation. When alkanes were present, naphthalene degradation was not observed, likely because naphthalene degraders were outcompeted. Further, the results of the sulfate addition experiment indicated a direct correlation of Desulfovibrio spp. with naphthalene biodegradation and showed that Smithella spp. were enriched in sulfate enhanced soils containing alkanes. Periodic air sparging did not result in fully aerobic conditions suggesting observed increased rates of biodegradation could be explained by stimulating alternative anaerobic metabolisms that were more energetically favorable compared to baseline/control conditions (e.g., iron reduction due to air oxidizing reduced iron). Methods developed and emerging continuous monitoring tools that were tested in lab soil columns were also applied to a mid- and late-stage LNAPL site. Herein, a case study is presented that advances integration of multiple nascent technologies for characterizing mid- and late-stage LNAPL sites including: 1) cryogenic coring, 2) multiple level internet of things (IoT) soil redox and temperature sensors in soil, and 3) application of RNA- and DNA-based molecular biological tools (MBTs) for site characterization. The integration of the data sets produced by these tools allowed for progress of NSZD to be evaluated in parallel under LNAPL site-relevant biogeochemical conditions. Collectively, the research presented in this dissertation support combining cryogenic coring sampling, continuous redox and temperature sensing and microbiome analysis to provide insights beyond those possible with each monitoring tool alone. The synergy achieved between microbiome characterization and soil continuous sensing illustrates how the integration of new characterization tools can provide insight into complex biogeochemical systems. Further understanding of these technologies will lead to improved predictions on remediation outcomes. The modern tools tested for middle- and late-stage LNAPL sites offer opportunities to more effectively and efficiently manage legacy LNAPL sites.
Embargo
A data-driven characterization of municipal water uses in the contiguous United States of America
(Colorado State University. Libraries, 2024) Chinnasamy, Cibi Vishnu, author; Arabi, Mazdak, advisor; Sharvelle, Sybil, committee member; Warziniack, Travis, committee member; Goemans, Christopher, committee member
Municipal water systems in the United States (U.S.) are facing increasing challenges due to changing urban population dynamics and socio-economic conditions as well as from the impacts of weather extremities on water availability and quality. These challenges pose a serious risk to the municipal water providers by hindering their ability to continue providing safe drinking water to residents while also securing adequate supply for economic growth. A data-driven approach has been developed in this study to characterize the trends, patterns, and urban scaling relationships in municipal water consumption across the Contiguous United States. Then using sophisticated and robust statistical methods, water consumption patterns are modeled, identifying key climatic, socio-economic, and regional factors. The first chapter of this data-driven study looked at municipal water uses of 126 cities and towns across the U.S. from 2005 to 2017, analyzing the temporal trends and spatial patterns in water consumption and identifying the influencing factors. Water usage in gallons per person per day, ratio of commercial, industrial, and institutional (CII) to Residential water use, and percent outdoor water consumption were statistically calculated using aggregated monthly and annual water use data. The end goal was to statistically relate the variations in CII to Residential water use ratio across the municipalities with their local climatic, socio-economic, and regional factors. The results indicate an overall decreasing trend in municipal water use, 2.6 gallons per person annually, with greater reductions achieved in the residential sector. Both Residential and CII water use exhibit significant seasonality over an average year. Large cities, particularly in the southern and western parts of the U.S. with arid climates, had the highest demand for water but also showed the largest annual reductions in their per capita water consumption. This study also revealed that outdoor water use varied significantly from 3 to 64 percent of the Total water consumption across the U.S., and it was highest in smaller cities in the western and arid regions. Factors such as April precipitation, annual vapor pressure deficit, number of employees in the manufacturing sector, total percentage of houses built before 1950, and total percentage of single-family houses explain much of the variation in CII to Residential water use ratio across the CONUS. The second chapter leverages high-resolution, smart-metered water use data from over 900 single-family households in Arizona for the water year 2021. This part of the study characterizes the determinants or drivers of water consumption patterns, specifically in single-family households, and presents a framework of statistical methods for analyzing smart-metered water consumption data in future research. A novel approach was developed to characterize household appliance efficiency levels using clustering techniques on 5-second interval data. Integrating water consumption data with detailed spatial information of the household and building characteristics, along with local climatic factors, yielded a robust mixed-effects model that captured the variations in household water uses with high accuracy at a monthly time-step. Local air temperature, household occupancy level, presence of a swimming pool, the year the household was built, and the efficiency of indoor appliances and irrigation systems were exhibited to be the key factors influencing variations in household water use. The third and fourth chapter of this study reanalyzed the water consumption data of those 126 municipalities. The third chapter dwelled into the estimation of the state of water consumption efficiencies or economics of scale in the municipal water systems using an econometrics framework called urban scaling theory. A parsimonious mixed-effects model that combined the effects of socio-economic, built environment, and regional factors, such as climate zones and water use type, was developed to model annual water uses. The results confirm efficiencies in water systems as cities grow and become denser, with CII water use category showing the highest efficiency gains followed by the Residential and Total water use categories. A key finding is the estimation of the unique variations in water use efficiency patterns across the U.S. These variations are influenced by factors such as population, housing characteristics, the combined effects of climate type and geographical location of the cities, and the type of water use category (Residential or CII) that dominates in each city. The fourth or the final chapter synthesizes the lessons learned previously about the drivers of municipal water uses and explores the development of a model for predicting monthly water consumption patterns using machine learning algorithms. These algorithms demonstrated improved capabilities in predicting the Total monthly water use more accurately than the previous modeling efforts, also controlling for factors with multi-collinearity. Climatic variables (like precipitation and vapor pressure deficit), socio-economic and built environment variables (such as income level and housing characteristics), and regional factors (including climate type and water use type dominance in a city), were confirmed by the machine learning algorithms to strongly influence and cause variations in the municipal water consumption patterns. Overall, this study showcases the power of data-driven approaches to effectively understand the nuances in municipal water uses. Integration of the lessons learned and the statistical frameworks used in this study can empower water utilities and city planners to manage municipal water demands with greater resiliency and efficiency.
Embargo
Long-term analysis of groundwater depletion in the High Plains Aquifer: historical, predictive, and solutions
(Colorado State University. Libraries, 2024) Nozari, Soheil, author; Bailey, Ryan, advisor; Niemann, Jeffrey, committee member; Ronayne, Michael, committee member; Suter, Jordan, committee member
Semi-arid agricultural regions worldwide are heavily dependent on groundwater storage in a handful of large and over-exploited aquifers, such as the High Plains Aquifer (HPA) in the U.S. High Plains Region. The HPA, one of the world's largest freshwater aquifers, serves as the primary source of irrigation water in the High Plains Region. The socioeconomic development in the High Plains Region has come at the expense of significant groundwater depletion in the HPA. The ongoing depletion of the HPA poses risks to livelihoods of rural communities, local ecosystems, and national food security. Addressing this issue necessitates the formulation of groundwater management policies that aim to reduce groundwater extraction, while minimizing associated economic costs over a multi-generational timeframe, all in the context of climate change. To inform the formulation of effective policies, it is crucial to develop a suite of decision support tools that empower local managers and planners to assess the outcomes of various groundwater management policies amidst climate change. The primary goal of this dissertation is to enhance the capacity to project the future of groundwater systems in semi-arid agricultural areas, particularly within the High Plains Region, as a coupled human-natural system, under various groundwater management schemes in the face of climate change. To achieve this goal, a number of tools were developed that incorporate a spectrum of modeling approaches, from the increasingly popular data-driven models to the state-of-the-art hydro-economic models. First, a data-driven modeling framework was developed and tested that is fast to employ and yet provides reliable long-term groundwater level (GWL) forecasts as a function of climatic and anthropogenic factors. The modeling framework utilizes the random forests (RF) technique in combination with ordinary kriging and was tested for the HPA in Finney County, southwest Kansas. The introduction of groundwater withdrawal potential as a new surrogate for pumping intensity empowers the RF model to capture decline in groundwater depletion rate as the system progresses towards aquifer depletion and/or as a result of well retirement policies. The RF model was applied over the period from 2017 to 2099 using 20 downscaled global climate models (GCMs) for two representative concentration pathways (RCPs), RCP4.5 and RCP8.5. The findings indicate that, under status quo management and average climate conditions, the aquifer will no longer be able to sustain irrigated agriculture in most of the county by 2060. Additionally, the difference in climate scenarios will likely shift the aquifer's depletion time frame by up to 15 years in most of the study area. The long-term combined impact of well retirement plans and climate conditions on groundwater depletion trends imply well retirement policies do not lead to sustained groundwater savings. In the next step, an agent-based hydro-economic model (ABM-MODFLOW) was developed for a portion of the HPA in eastern Colorado and northwest Kansas, with the aim of addressing the current limitations of hydro-economic models. Through interdisciplinary collaboration, each component of the ABM-MODFLOW was particularly designed to meet specific research objectives. Planting and irrigation decisions were simulated in the ABM-MODFLOW using a detailed representation of real-world farmers. Additionally, well capacity was incorporated as a constraint on irrigation duration. A subsequent thorough validation of the ABM-MODFLOW was conducted to establish its credibility. The validation results indicate satisfactory performance in reproducing historical data and trends. They also reveal the ABM-MODFLOW's superiority over the standalone groundwater model in simulating the groundwater system. The historical simulation outcomes also underscore the impact of soil type on agents' profitability, especially for those with limited irrigation capacities. Overall, the highest profits are earned by agents with high irrigation capacities and fine soils, while the lowest are achieved by those with low irrigation capacities and coarse soils. Lastly, the ABM-MODFLOW was employed to project the coevolution of human activities, crops, and the groundwater system amidst climate change, both with and without policy interventions. The ABM-MODFLOW simulations involved 32 climate scenarios from 16 downscaled GCMs for two RCPs, RCP4.5 and RCP8.5. Additionally, three groundwater management policy instruments were explored: irrigated land retirement, irrigation well retirement, and authorized pump rate reduction. The simulation outcomes reveal that the groundwater depletion rate decreases over time, primarily due to rising summer temperatures from climate change that limit corn production, a water-intensive crop, in the region. Moreover, these rising temperatures hamper the economic benefits of policies, since the early conserved groundwater is predominantly used for winter wheat irrigation in the later years, a crop with substantially lower irrigation value than corn.
Open Access
Incorporating vehicle trails in soil moisture downscaling for mobility assessments in coarse grained soils
(Colorado State University. Libraries, 2024) Proulx, Holly E., author; Niemann, Jeffrey D., advisor; Scalia, Joseph, advisor; Lynn, Stacy, committee member
Fine resolution (10-30 m) soil moisture maps are critical for determining vehicle mobility in agricultural, forestry, recreational, and military applications. Microwave satellites provide soil moisture products, but the spatial resolutions of these products are too coarse for such applications. Soil moisture downscaling methods, such as the Equilibrium Moisture from Topography Plus Vegetation and Soil (EMT+VS) model, can downscale soil moisture to fine resolutions. However, the EMT+VS model (like most other downscaling models) does not explicitly consider vehicle trails, which may have different soil moisture than undisturbed landscape locations. The objective of this study is to generalize the EMT+VS model to explicitly estimate the soil moisture of trails. The generalized model incorporates two hypothesized effects of vehicle traffic on trails (reduced vegetation cover and reduced porosity). To evaluate the generalized model, porosity and soil moisture observations were collected across a study region in the foothills of the Colorado Front Range. Data were collected at paired trail and landscape locations as well as unpaired landscape locations on six dates in Summer 2023. On average, the porosity of the trail locations was 86% of the paired landscape locations. Soil moisture on trails was on average 73% to 88% of the moisture of the paired landscape locations. Including the vegetation and porosity adjustments in the EMT+VS model reduced the tendency of the model to overestimate the moisture on trails and improved the root mean squared errors.
Open Access
Flow resistance corrections for physical models using unit flowrates
(Colorado State University. Libraries, 2024) Cote, Cassidy B., author; Thornton, Christopher, advisor; Ettema, Robert, committee member; Rathburn, Sara, committee member
Flow resistance is an essential aspect of evaluating flow behavior in open-channel hydraulic models. Flow resistance in open channels is commonly characterized by Manning's resistance equation, where a value of Manning's roughness coefficient n, indicates the magnitude of flow resistance. Physical hydraulic models are one method to estimate Manning's n values for prototype channel reaches. A physical hydraulic model evaluates prototype channel characteristics at the model scale. The scale for a given physical model may be characterized by length-scale factor, given by the relationship of prototype to model geometry. Models that have a large length-scale factor are known to introduce errors associated with instrumentation, measurement, and scale effects, therefore minimization of the length-scale factor is an important consideration in the development of hydraulic models. Evaluating physical models using a scaled unit flowrate provides a method by which the length-scale factor may be minimized. In this way, a scaled design discharge per unit width of channel is applied to a channel that is less wide than the prototype design. Using this approach greatly improves the ability of laboratories to utilize available facilities, without being constrained by prototype design width, which can otherwise be a driving factor increasing the length-scale factor for a given model. This thesis documents the construction and analysis of two physical models of a proposed rectangular canal along Rio Puerto Nuevo in San Juan, Puerto Rico. One model used a scaled unit flowrate and a reduced channel width at a lesser length-scale factor, and the other model accommodated the total scaled design flowrate and design channel width at a larger-scale factor. Tests were conducted for three sidewall conditions to identify the impact associated with applying a unit flowrate physical modeling approach for models with different Manning's n values specific to the sidewalls. The unit flowrate approach was found to result in larger estimates of flow depth and composite Manning's n compared to the model that accommodated the full prototype channel width. Insights regarding the variability of Manning's n as a function of channel width for each sidewall condition were identified by comparing results from the two models. A correction method was proposed for improving estimates of Manning's n derived from scaled unit flowrate models. Correction factors were identified as a function of two dimensionless parameters, relative prototype channel width (defined as the ratio of the width evaluated using a unit flowrate model to the design width of the channel), and relative flow resistance exerted by the individual boundary elements as determined from the unit flow rate model (defined as the ratio of Manning's n values between the sidewall and channel bed boundary elements). Findings indicate that it becomes increasingly important to apply correction factors to flow resistance estimates on unit flowrate models when wall boundary elements exert a larger contribution to flow resistance than that of the channel bed (large relative roughness), and when the scaled unit flowrate approach results in a prototype channel width that is significantly smaller than the proposed design channel width (small relative channel width). Correction factors were developed for a range of relative channel width values from approximately 0.4 to 1.0, and a range of relative roughness values from approximately 0.5 to 3.0. Future physical models using unit flowrates with relative channel widths and relative flow resistance within the range evaluated may use the presented correction methods to improve estimates of flow resistance.
Embargo
Assessing the triple bottom line co-benefits and life cycle cost tradeoffs of cloudburst infrastructure in New York City
(Colorado State University. Libraries, 2024) Fenn, Abby M., author; Arabi, Mazdak, advisor; Grigg, Neil, committee member; Sharvelle, Sybil, committee member; Conrad, Steve, committee member
Urbanization and climate change have increased the risk of urban flooding. Specifically, more frequent cloudburst events are on the rise in cities across the globe. Cloudbursts are characterized by high intensity rainfall over a short duration, causing unpredictable, localized flooding. Effective stormwater management is essential to manage extreme precipitation and runoff induced by cloudbursts. Stormwater control measures have evolved over time shifting from gray infrastructure to nature-based and green solutions. Recently, cloudburst specific infrastructure has emerged as a stormwater intervention strategy designed to handle larger volumes of water by capturing, storing, or conveying excess water in highly impervious areas. Cloudburst infrastructure systems are inextricably linked with land use in cities and thus, their implementation should incorporate life cycle costs, and social and ecological co-benefits. This study assesses the Triple Bottom Line co-benefits and environmental effects of cloudburst systems for flood control in New York City. Specifically, we explore the tradeoffs between the costs and co-benefits of alternative surface vegetation including grass, diverse vegetation, and trees. The study identifies the Pareto optimal set of solutions and quantifies effects of incorporating vegetation into the urban landscape via cloudburst systems. The results indicate that surface vegetation plays a key role in altering the co-benefits and life cycle costs of cloudburst infrastructure. Trees were the most frequent non-dominated solution and were linearly related to Triple Bottom Line score and exponentially related to Life Cycle Cost. The framework and results of this study provide valuable insight to support informed decision-making.
Open Access
Assessing the influence of model inputs on performance of the EMT+VS soil moisture downscaling model for a large foothills region in northern Colorado
(Colorado State University. Libraries, 2024) Fischer, Samantha C., author; Niemann, Jeffrey D., advisor; Scalia, Joseph, advisor; Stright, Lisa, committee member
Soil moisture is an important driving variable of the hydrologic cycle and a key consideration for decision-making in off-road vehicle mobility, crop modeling, drought forecasting, flood prediction, and a variety of other applications. Soil moisture can be estimated at coarse resolutions (>1 km) using satellite remote sensing or land surface models; however, coarse resolution estimates are unsuitable for many applications. Downscaling these products to finer resolutions (~10 m) creates soil moisture maps that are more useful. This study applies the Equilibrium Moisture from Topography, Vegetation, and Soil (EMT+VS) model to Maxwell Ranch, a 4,000-ha cattle ranch in Northern Colorado that represents a diverse range of topographic, vegetation, and soil characteristics and a wide range of soil moisture conditions. The EMT+VS model is a physically based geo-information method that downscales coarse resolution soil moisture estimates using ancillary fine resolution datasets of topography and vegetation. Input data to the EMT+VS model contain inherent sources of error that can impact the uncertainty of downscaled estimates. The objective of this study is to identify sources of uncertainty in inputs and assess their influence on the error of the EMT+VS model output. The study finds changes in vegetation input or digital elevation model (DEM) resolution introduce substantial errors in the EMT+VS model output; however, these errors can be mostly overcome when recalibration with local in-situ data is possible. The highest errors (RMSE = 0.20 cm3/cm3) tend to occur in locations with thick vegetation and high contributing area, which are difficult to accurately estimate with available remote sensing data sources.
Open Access
Enhancing natural treatment systems by utilizing water treatment residuals
(Colorado State University. Libraries, 2008) Yarkin, Mustafa, author; Carlson, Kenneth H., advisor
The current project envisions the application of riverbank filtration (RBF) and aquifer recharge and recovery (ARR) in series as preliminary treatment steps of a multi-barrier treatment approach for the City of Aurora's Prairie Waters Project. The primary focus of the project is the removal of phosphorus, nitrogen, and carbon from the source water resulting in biologically stable water that can be stored in a terminal reservoir. In addition to nutrients, perchlorate and three commonly used pesticides, atrazine, alachlor, and metolachlor have been studied in terms of removal with the RBF and ARR systems. Aluminum based water treatment residual (WTR) was considered along with other sorbents for enhanced phosphorus removal. The experimental studies include the monitoring of an RBF field site and pilot columns that simulate RBF and ARR systems. Possible benefits of WTR as an amendment were tested by amending a column with 30% WTR under RBF and ARR conditions. Also an application scenario of RBF followed by a WTR amended ARR infiltration basin and ARR was simulated by a column study. Results of the studies indicated that the RBF and ARR systems are insufficient to provide sustainable phosphorus removal. Phosphorus removal mechanism is limited by the sorption capacity of the alluvial sand and minor biological activity. Use of the WTR amendment reduced phosphorus levels to less than the method detection limit of 0.03 mg/L with a high adsorption capacity. The ARR system in sequential RBF-ARR application suffers from the lack of labile organic carbon and therefore microbially mediated treatment processes are limited. Amending the infiltration of the ARR system with organic carbon rich WTR can promote biological activity, thus allowing further biodegradation of contaminants. Results of the study indicated that the RBF system is a sustainable barrier for nitrate removal while labile carbon limited ARR cannot achieve significant nitrate removal. To use the ARR system as a secondary barrier for nitrate, a labile carbon source should be introduced to the system. WTR was used as a supply of organic carbon to the ARR system and the experimental studies indicated that, once optimized, WTR can promote biological denitrification through the ARR system. The field and column studies also showed that both RBF and ARR can achieve perchlorate removal as long as sufficient electron donating compounds (e.g. organic carbon) are present in the environment. It has also been observed that the ability of RBF and ARR systems to remove alachlor and metolachlor is limited by the biodegradation through the alluvial sand while they achieve sustainable atrazine removal. WTR was tested as an amendment alternative the ARR infiltration basin. Concentrations of selected pesticides were reduced to the method detection limit of 0.3 μg/L during 1-foot 30% WTR amended column treatment with the residence time of 1.25 days under both abiotic and biotic conditions. The overall study suggested that once the source and type of the WTR was selected, the optimum amount of WTR can be obtained by adjusting the application ratio and the media depth for the efficient removal of all contaminants of concern.
Open Access
Characterization of the scale dependence and scale invariance of the spatial organization of snow depth fields, and the corresponding topographic, meteorologic, and canopy controls
(Colorado State University. Libraries, 2009) Trujillo-Gómez, Ernesto, author; Ramírez, Jorge A., advisor
The spatial organization of snow cover properties and its dependence on scale are determined by precipitation patterns and the interaction of the snow pack with topography, winds, vegetation and radiative fluxes, among others factors. The objectives of this research are to characterize the spatial scaling properties and spatial organization of snow depth fields in several environments at scales between 1 m and 1000 m, and to determine how these properties are related to topography, vegetation, and winds. These objectives are accomplished through (a) the analysis of LIDAR elevation contours, and snow depth contours, (b) the analysis of synthetically generated profiles and fields of snow depth, and (c) simulations performed using a new cellular automata model for redistribution of snow by wind. The analyses of the power spectral densities of snow depth show the existence of two distinct scaling regimes separated by a scale break located at scales of the order of meters to tens of meters depending on the environment. The breaks separate a highly variable larger-scales interval from a highly correlated smaller-scales interval. Complementary analyses support the conclusion that the scaling behavior of snow depth is controlled by the scaling characteristics of the spatial distribution of vegetation height when snow redistribution by wind is minimal and canopy interception is dominant, and by the interaction of winds with features such as surface concavities and vegetation when snow redistribution by wind is dominant. Using these observations together with synthetic snow depth profiles and fields, we show that the scale at which the break occurs increases with the separation distance between snow depth maxima. Finally, the cellular automata model developed here is used to show that the correlation structure of the snow depth fields becomes stronger as the amount of snow transported increases, while the probability distributions of the fields progress from a Gaussian distribution for small transport rates to positively skewed probabilities for high transport rates. These simulation results are used to illustrate the controls that topography, vegetation, and winds have on the spatial organization of snow depth in wind-dominanted environments. Implications of the results from the different analysis are discussed.
Open Access
A spatial decision support system for basin scale assessment of improved management of water quantity and quality in stream-aquifer systems
(Colorado State University. Libraries, 2008) Triana, Enrique, author; Labadie, John W., advisor; Gates, Timothy K., advisor
Challenges in river basin management have intensified over the years, with expanding competition among water demands and emerging environmental concerns, increasing the complexity of the decision making framework. A State-of-the-art spatial-decision support system (River GeoDSS) is developed herein to provide assistance in evaluating management alternatives towards optimal utilization of water resources, providing a comprehensive treatment of water quantity and quality objectives based on conjunctive surface and groundwater modeling within the complex administrative and legal framework of river basin management. The River GeoDSS provides sophisticated tools that allow accurate system simulations and evaluation of strategies while minimizing the technological burden on the user. A unique characteristic of the River GeoDSS is the integration of models, tools, user interfaces and modules, all seamlessly incorporated in a geographic information system (GIS) environment that encourages the user to focus on interpreting and understanding system behavior to better design remediation strategies and solutions. The River GeoDSS incorporates Geo-MODSIM, a fully functional implementation of MODSIM within the ArcMap interface (ESRI, Inc.), and Geo-MODFLOW, a new MODFLOW-MT3DMS results analysis tool in the ArcMap interface. The modeling system is complemented with a new artificial neural networks (ANN) module for natural and irrigation return flow quantity and quality evaluation and salt transport through reservoirs, as well as with a new water quality module (WQM) for conservative salt transport modeling of conjunctive use of surface water and groundwater resources in the river basin network. In this research, innovative methodologies are developed for applying ANNs in efficiently coupling surface and groundwater models for basin-scale modeling of stream-aquifer interactions. The core River GeoDSS is customized to provide comprehensive analysis of alternative solutions to achieving agricultural, environmental, and water savings goals in the Lower Arkansas River Basin in Colorado while assuring physical, legal and administrative compliance. The River GeoDSS applied to the Arkansas River Valley allowed comparing benefits and improvements of management strategies, illustrated their potential to reduce waterlogging and soil salinity, salt load to the river, and non-beneficial evapotranspiration in a strategic planning environment.
Open Access
Three-dimensional finite element modeling of time-dependent behavior of wood-concrete composite beams
(Colorado State University. Libraries, 2009) To, Lam Giang, author; Gutkowski, Richard M., advisor
The wood-concrete composite beam structure with notched shear keys has some advantages such as high composite efficiency and ease of construction with low labor cost compared to other wood-concrete composite beam structures. Made up from two rheological materials, wood and concrete, the time-dependent behavior of the wood-concrete composite beam is not only affected by the long-term load but also driven by the variation of the environmental conditions such as temperature and relative humidity. To consider the effects of the environmental conditions, the modeling process must include the moisture diffusion analysis for the wood layer, the heat transfer analysis and the stress/displacement analysis where the first two analyses provide input parameters for the third analysis. This research focused on modeling the time-dependent behavior of the layered wood-concrete composite with notched shear keys by using 3D finite element method. The main goals of the research are to expand available constitutive models of wood and concrete so that they can be used in the 3D FEM. The 3D constitutive models of wood and concrete were then implemented in the commercial software ABAQUS by using the subroutine UMAT for the stress/displacement analysis. To provide data to validate the theoretical model, a long-term creep test on two specimens has been performed. The results of the verification analysis on one test specimen captured closely the time-dependent behavior of the test specimen for the first 123 days of the test. The verification analysis revealed that the heat transfer analysis is not necessary in long-term analysis. The application of the 3D model with solid elements not only predicts the long-term behavior of the wood-concrete composite beam structures better than ID models do, but it can be also applied for wood-concrete composite structures with complex geometry where the 1D model cannot be applied. In addition, the application of the 3D model with solid element can be used to perform parametric studies to address remaining questions about time-dependent of the wood-concrete composites structures.
Open Access
Effects of principal stress rotation and intermediate principal stress changes on the drained monotonic and undrained cyclic behavior of clean and nonplastic silty Ottawa sands formed underwater
(Colorado State University. Libraries, 2009) Tastan, Erdem Onur, author; Carraro, Antonio, advisor
A state-of-the-art dynamic hollow cylinder apparatus was used to systematically study the effect of drained changes in the major principal stress direction (a, taken from the vertical) and intermediate principal stress coefficient (b) on the (1) drained static and (2) undrained cyclic stress-strain responses, and (3) liquefaction resistance of clean and nonplastic (NP) silty Ottawa sands formed underwater. A modified slurry deposition method was developed to reconstitute HC clean and NP silty Ottawa sand specimens in a way that resembles the actual field deposition of these soils underwater. Using a new density gradient mold developed during this study, the maximum local deviations of relative density (D R) and fines content (FC) from their global averages were determined to be as small as (or lower) than the deviations obtained for similar reconstitution methods typically used for solid triaxial specimens. Drained increases in a and/or b at constant mean normal effective stress and octahedral deviator stress were shown to induce strains as large as those induced during anisotropic- K0 consolidation, with the NP silty Ottawa sand typically yielding larger strains than the clean Ottawa sand at similar states. As a increased, the sands exhibited weaker undrained cyclic responses. However, the relative effect of a on soil response appears to be less significant for Ottawa sands with NP silt content between 11% and 15%. Increase in b improved the liquefaction resistance of the sands. However, when both a and b were greater than zero, their combined effect typically decreased the liquefaction resistance of the sand, suggesting that a may play a more dominant role on the undrained response of the sand than b. Undrained instability was observed in many tests carried out on anisotropically consolidated specimens subjected or not to a and/or b changes. Occurrence of undrained instability depends upon the cyclic stress ratio, a, b, DR and FC of the soil. The results of this study indicate that liquefaction analyses based on axisymmetric parameters may be unconservative for most types of geotechnical applications since axisymmetric conditions do not account for the effect of a on the liquefaction resistance of the soil. Appropriate evaluation of the liquefaction potential of a soil requires consideration of both a and b, although the major controlling mechanism might be associated with the mechanical response imparted by drained principal stress rotation. The results obtained in this study may be used to develop new or improve and calibrate current constitutive models that address soil anisotropy and more realistic loading conditions in geotechnical analyses. Typical applications of such advanced models include geotechnical analyses of slope stability, design of foundations, dams, embankments, pavement subgrades, and retaining structures, particularly those involving tailings, hydraulic fills, and alluvial or marine deposits of sands with fines formed underwater.
Open Access
Source-tracking of antibiotic resistance genes in the watershed using molecular profiling and geospatial analyses
(Colorado State University. Libraries, 2009) Storteboom, Heather, author; Arabi, Mazdak, advisor
Antibiotic resistance genes (ARG) have been found in many environmental matrices, including soils, groundwater, surface water, and sediments. Agricultural feeding operations and wastewater treatment plants are potential sources of ARG in rivers, or are sources of antibiotics that may select ARG from native river bacteria. The aim of this research is to identify ARG profiles that can characterize potential sources of ARG as well as native river environments and then use this knowledge to determine the sources and mechanisms involved in the spread of ARG to river environments. Initially, three wastewater treatment plants, six animal feeding operation lagoons, three sites along a pristine region of the Cache la Poudre River (PR), and a wildlife fish hatchery and rearing unit were compared with respect to the distribution, levels, and phylogenetic diversity of their ARG profiles. The tet genes tet(H), tet(Q), tet(S), and tet(T) were found to indicate agricultural influence, while high detection frequencies of tet(C), tet(E), and tet(O) were more typical of WWTP profiles. Sul(I) was detected in 100% of samples from source environments, but just once in the pristine river environment. The ARG profile of the pristine PR was dominated by tet(M) and tet(W), demonstrating their presence in an environment does not indicate anthropogenic disturbance. The tet(W) clone libraries from Pristine PR, WWTPs, and AFO lagoons, are each unique, as determined by both restriction fragment length polymorphism (RFLP) and phylogenetic analysis. Secondly, samples from the PR and South Platte River (SPR) in Northern Colorado were characterized with respect to the distribution, levels, and diversity of their ARG profiles. On the basis of the ARG indicator variables derived in the study of source environments, most river samples were classified as WWTP influenced by discriminant analysis. The relationship between spatial explanatory variables and the ARG response variables was determined with classification and regression tree (CART) analysis. There was good agreement between the classification of river sites according to spatial variables and source indicator variables, demonstrating the effectiveness of these indicators in source-tracking ARG. According to multivariate linear regression, sul(I) was significantly correlated with the inverse-distance weighted (IDW) number of cattle upstream of each river point (R2 = 0.83, p <0.0003), whereas tet(W) was not correlated with any explanatory variable tested. Tet(W) was isolated from two river environments: site PR4, located in Weld County downstream of Fort Collins; and site SPR3, located downstream of the confluence of the PR with the SPR. When compared to an existing clone library of tet(W) genes from animal feeding operations and wastewater treatment plants, PR4 was significantly different from the animal feeding operations (p<0.05); the SPR confluence (SPR3) was not significantly different from either environment. The PR4 environment was most similar to that of wastewater treatment plants, while SPR3 showed equal similarity with both source environments. A link between ARG indicator variables and spatial indicators was established. Furthermore, it was demonstrated that the ARG profiles of river samples were more similar to WWTPs than AFO lagoons or the pristine river. Based on this work, transport of ARG from sources may be a reasonable mechanism for ARG proliferation in riverine environments.
Open Access
Remediation of arsenic and persistent organic contaminants using enhanced in-situ methods
(Colorado State University. Libraries, 2008) Sullivan, Mary Elizabeth, author; Carlson, Kenneth, advisor; Pruden, Amy, advisor
The demand for inexpensive and reliable water treatment technologies continues to increase as the number of contaminants grows and their associated fate and transport mechanisms become more complex. Advances in public health have contributed to the implementation of more stringent drinking water standards for compounds such as arsenic. Furthermore, advances in analytical chemistry have contributed to the detection of previously immeasurable compounds including endocrine-disrupting compounds (EDCs), pharmaceuticals and personal care products (PPCPs), and other bioactive chemicals in wastewater effluents and surface waters around the world. This research examined the use of enhanced in-situ methods for the remediation of arsenic and several persistent organic contaminants. Unamended and amended electrokinetic remediation (ER) column studies conducted to determine the impact on arsenic revealed arsenic removal from the soil column due to the electrolysis of water and electromigration of the charged species. Column studies also examined the impact of amended aquifer recharge and recovery (ARR) treatment on persistent organic compounds. Water treatment residual-amended ARR columns were utilized to promote an environment capable of reducing flame retardants. The results indicated that the presence of water treatment residuals created a reducing environment and provided ideal adsorption sites and sources of organic matter in the form of leached carbon. Unamended and amended ER column studies were completed to examine the impact on two pharmaceuticals (sulfamethoxazole and carbamazepine) and three organophosphorus flame retardants (tris-(2-chloroethyl) phosphate, tris-(2-chloro-, 1-methylethyl)phosphate, and tris-(2-chloro-, 1-chloromethyl-ethylphophate). Results indicated that the highest removal results occurred in the significant redox zones of the ER column. Oxidizing conditions at the anode and reducing conditions at the cathode had significant impacts on the compounds' concentrations in the column's pore water. Lastly, critical characterization of the compounds' affinity for aqueous, colloidal, and solid phases was determined for the five organic compounds. These results, as well as sources of flame retardant contamination in the experimental design, was useful (and necessary) in interpreting the treatment results from the amended ARR and electrokinetic column studies.
Open Access
Series expansion of the Modified Einstein Procedure
(Colorado State University. Libraries, 2009) Shah-Fairbank, Seema Chandrakant, author; Julien, Pierre Y., advisor
This study examines calculating total sediment discharge based on the Modified Einstein Procedure (MEP). A new procedure based on the Series Expansion of the Modified Einstein Procedure (SEMEP) has been developed. This procedure contains four main modifications to MEP. First, SEMEP solves the Einstein integrals quickly and accurately based on a series expansion. Next, instead of dividing the suspended sediment and bed material samples into particle size classes, the total sediment discharge calculation is based on a median grain size in suspension (d50ss). Thirdly, for depth-integrated samples the Rouse number (Ro) is determined directly by calculating the fall velocity (ω) based on dsoss, the shear velocity (u. = -√ghS) and assuming the value of the von Karman constant (κ) is 0.4. For point concentration measurements, the Ro is calculated by fitting the concentration profile to the measured points. Lastly, SEMEP uses the measured unit sediment discharge and Ro to determine the unit bed discharge directly. Thus, SEMEP can determine the unit bed discharge (qb), unit suspended sediment discharge (qs), unit total sediment discharge (qt), ratio of measured to total sediment discharge (qm/qt) and ratio of suspended to total sediment discharge (qs/qt).
Open Access
Design and implementation of hydrologic unit watersheds for rainfall-runoff modeling in urban areas
(Colorado State University. Libraries, 2009) Rivas Acosta, Iván, author; Roesner, Larry A., advisor
The calibration of complex hydrology and hydraulics of rainfall-runoff models represents one of the most challenging problems in water resources engineering. Unlike undeveloped watersheds, but specifically urban basins with surface drainage. From the available models, SWMM (Storm Water Management Model) was used as the modeling engine since it was developed for urban watersheds. Calibration procedure used a Multi-Criteria Decision Analysis (MCDA) approach that minimized the RMSE (Root Mean Square Error) between the flow duration curves of the modeled and the observed runoff. The flow duration curve was divided in High and Low Flows using the 1-Yr storm to split the curve, since there is a change in flow regime at this point. Pareto optimal front surfaces were obtained. Two case studies in North Carolina (Pigeon and SW Prong basins) were used to illustrate a proposed methodology for calibration. The methodology simplified the drainage network and irregular sub-catchments shapes were converted to regular shapes using a Kinematic Wave (KW) cascading plane approach. The KW cascading plane approach showed to be effective to convert irregular sub-basins shapes to rectangular features. A discretization analysis was performed where a set of hydrologic experiments using different levels of discretization were used and a threshold discretization value in urban hydrology was investigated. Needed GIS data was extracted through a toolbox. MCDA methodology and numerical simulations showed that Horton's decay coefficient (K, 1/h) and drying time (Tw, days) needed to have different values for the High and Low Flow portions of the flow duration curve to improve performance. Longer drying times were required to improve estimation of High Flows than Low Flows because the soils would take more time to recover their initial infiltration capacity. The Representative Element Area (REA) concept was explored in SWMM and it was found that sub-catchment sizes of 3% of the total basin size were appropriate. This magnitude represents the suggested level of discretization in urban watersheds since the improvement in performance became asymptotic either to 1.00 (Pearson's Moment Correlation Coefficient-PMCC, Nash-Sutcliff Coefficient-NSC and Index of Agreement-IOA) or to zero (RMSE) and therefore, it is not significant to improve the spatial resolution. Coarser resolution levels underestimated peak flow rates and total runoff volumes. Research results are summarized in a proposed protocol to discretisize urban watersheds.
Open Access
High-volume use of self-cementing spray dry absorber material for structural applications
(Colorado State University. Libraries, 2009) Riley, Charles E., author; Heyliger, Paul R., advisor; Atadero, Rebecca A., advisor
Spray dry absorber (SDA) material, or spray dryer ash, is a byproduct of energy generation by coal combustion and sulfur emissions controls. Like any resource, it ought to be used to its fullest potential offsetting as many of the negative environmental impacts of coal combustion as possible throughout its lifecycle. Its cementitious and pozzolanic properties suggest it be used to augment or replace another energy and emissions intensive product: Portland cement. There is excellent potential for spray dryer ash to be used beneficially in structural applications, which will offset CO2 emissions due to Portland cement production, divert landfill waste by further utilizing a plentiful coal combustion by-product, and create more durable and sustainable structures. The research into beneficial use applications for SDA material is relatively undeveloped and the material is highly underutilized. This dissertation explored a specific self-cementing spray dryer ash for use as a binder in structural materials. Strength and stiffness properties of hydrated spray dryer ash mortars were improved by chemical activation with Portland cement and reinforcement with polymer fibers from automobile tire recycling. Portland cement at additions of five percent of the cementitious material was found to function effectively as an activating agent for spray dryer ash and had a significant impact on the hardened properties. The recycled polymer fibers improved the ductility and toughness of the material in all cases and increased the compressive strength of weak matrix materials like the pure hydrated ash. The resulting hardened materials exhibited useful properties that were sufficient to suggest that they be used in structural applications such as concrete, masonry block, or as a hydraulic cement binder. While the long-term performance characteristics remain to be investigated, from an embodied-energy and carbon emissions standpoint the material investigated here is far superior to Portland cement.
Open Access
Performance modeling of stormwater best management practices with uncertainty analysis
(Colorado State University. Libraries, 2009) Park, Daeryong, author; Roesner, Larry A., advisor; Loftis, Jim C., advisor
Best management practices (BMPs) contain many uncertainties that make it difficult to determine their performance with a model. Moreover, predicting BMP performance with existing methods is not easy. The major research objective of this dissertation is to incorporate uncertainty analysis in a BMP performance model to better represent its treatment performance. The k-C* model is used in this study to simulate BMP performance, and the study assumes that the influent event mean concentration (Cin) and aerial removal constant (k) include uncertainty. Both Cin and k represent data and model uncertainty. To evaluate the model, three different uncertainty cases, uncertainty in Cin, k, and both Cin and k, are applied to the total suspended solid (TSS) data of detention basins and retention ponds. To evaluate uncertainty values, three different uncertainty analysis methods, the derived distribution method (DDM), the first-order second-moment method (FOSM), and the latin hypercube sampling (LHS), are applied to each case. TSS, as a representative pollutant, and detention basins and retention ponds, as representative BMPs, are utilized in this study. The observed datasets are selected from the International Stormwater BMP database. By incorporating uncertainty analysis into the k-C* model, the effect of BMP surface area and inflow on the effluent event mean concentration (Cout) of TSS can be quantified for detention basins and retention ponds. These effects are not large in detention basins but are noticeable in retention ponds. In addition, the k-C* model with uncertainty analysis is applied to a hypothetical watershed to show how uncertainty might be used improve the probability of compliance with TMDLs.