Evaluating the usefulness of soil moisture (forecasts) in streamflow prediction for central Texas

The past decade has brought significant advancements in seasonal climate forecasting. However, water resources decision support and management continues to be based almost entirely on historical observations and does not take advantage of climate forecasts. This study builds on previous work that conditioned streamflow ensemble forecasts on observable climate indicators, such as the El Niño-Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO) for use in a decision support model for the Highland Lakes multi-reservoir system in central Texas operated by the Lower Colorado River Authority (LCRA). In the current study, seasonal soil moisture is explored as a climate indicator and predictor of annual streamflow for the LCRA region. The main purpose of this study is to evaluate the correlation of fractional soil moisture with streamflow using the 1950-2000 Variable Infiltration Capacity (VIC) Retrospective Land Surface Data Set over the LCRA region. Correlations were determined by examining different annual and seasonal combinations of VIC modeled fractional soil moisture and observed streamflow. The applicability of the VIC Retrospective Land Surface Data Set as a data source for this study is tested along with establishing and analyzing patterns of climatology for the watershed study area using the selected data source (VIC model) and historical data. Correlation results showed potential for the use of soil moisture as a predictor of streamflow over the LCRA region. This was evident by the good correlations found between seasonal soil moisture and seasonal streamflow during coincident seasons as well as between seasonal and annual soil moisture with annual streamflow during coincident years. With the findings of good correlation between seasonal soil moisture from the VIC Retrospective Land Surface Data Set with observed annual streamflow presented in this study, future research would evaluate the application of NOAA Climate Prediction Center (CPC) forecasts of soil moisture in predicting annual streamflow for use in the decision support model for the LCRA.

Engineering design motivations : a qualitative and quantitative analysis of university students

What motivates students to perform and pursue engineering design tasks? This study examines this question by way of three Learning Through Service (LTS) programs: 1) an on-going longitudinal study examining the impacts of service on engineering students, 2) an on-going analysis of an international senior design capstone program, and 3) an on-going evaluation of an international graduate-level research program. The evaluation of these programs incorporates both qualitative and quantitative methods, utilizing surveys, questionnaires, and interviews, which help to provide insight on what motivates students to do engineering design work. The quantitative methods were utilized in analyzing various instruments including: a Readiness assessment inventory, Intercultural Development Inventory, Sustainable Engineering through Service Learning survey, the Impacts of Service on Engineering Students’ survey, Motivational narratives, as well as some analysis for interview text. The results of these instruments help to provide some much needed insight on how prepared students are to participate in engineering programs. Additional qualitative methods include: Word clouds, Motivational narratives, as well as interview analysis. This thesis focused on how these instruments help to determine what motivates engineering students to pursue engineering design tasks. These instruments aim to collect some more in-depth information than the quantitative instruments will allow. Preliminary results suggest that of the 120 interviews analyzed Interest/Enjoyment, Application of knowledge and skills, as well as gaining knowledge are key motivating factors regardless of gender or academic level. Together these findings begin to shed light on what motivates students to perform engineering design tasks, which can be applied for better recruitment and retention in university programs.

Assessment of soil erosion vulnerability in rural communities in the vicinity of Motozintla de Mendoza, Chiapas, Mexico : a physical and sociological approach

Soil erosion is a natural geological phenomenon resulting from removal and transportation of soil particles by water, wind, ice and gravity. As soil erosion may be affected from cultural factors as well. The physical and social phenomena of soil erosion are researched in six communities in the upper part of Rio Grijalva Basin in the vicinity of Motozintla de Mendoza, Chiapas, Mexico. For this study, the USDA RUSLE model was applied to estimate soil erosion rates in the six communities based on the available data. The RUSLE model is based on soil properties, topography, and land cover and management factors. These results showed that estimated soil erosion rates ranged from a high of 2,050 metric ton ha-1 yr-1 to a low of 100 metric ton ha-1 yr-1. A survey concerning knowledge, attitudes and practices (KAP) related to soil erosion was also conducted in all 236 households in the six communities. The main findings of the KAP survey were: 69% of respondents did not know what soil erosion was, while over 40% of the population perceived that hurricanes are the biggest factors that cause soil erosion, and about 20 % of the interviewees said that the landslides are the consequences of the soil erosion. People in communities did not perceive cultural factors as important in conservation efforts for reduce vulnerability to erosion; therefore, the results obtained are suggested to be useful for informing efforts to educate stakeholders.

Assessment of Seismic Damage of Buildings and Related Environmental Impacts

Sustainable development has only recently started examining the existing infrastructure, and a key aspect of this is hazard mitigation. To examine buildings under a sustainable perspective requires an understanding of a building's life-cycle environmental costs, including the consideration of associated environmental impacts induced by earthquake damage. Damage repair costs lead to additional material and energy consumption, leading to harmful environmental impacts. Merging results obtained from a seismic evaluation and life-cycle analysis for buildings will give a novel outlook on sustainable design decisions. To evaluate the environmental impacts caused by buildings, long-term impacts accrued throughout a building's lifetime and impacts associated with damage repair need to be quantified. A method and literature review for completing this examination has been developed and is discussed. Using software Athena and HAZUS-MH, this study evaluated the performance of steel and concrete buildings considering their life-cycle assessments and earthquake resistance. It was determined that code design-level greatly effects a building repair and damage estimations. This study presented two case study buildings and found specific results that were obtained using several premade assumptions. Future research recommendations were provided to make this methodology more useful in real-world applications. Examining cost and environmental impacts that a building has through, a cradle-to-grave analysis and seismic damage assessment will help reduce material consumption and construction activities from taking place before and after an earthquake event happens.

Performance characteristics and design recommendations for biomass-burning stoves using earthen construction materials

This report provides an analysis of the thermal performance and emissions characteristics of improved biomass stoves constructed using earthen materials. Commonly referred to as mud stoves, this type of improved stove incorporates high clay content soil with an organic binder in the construction of its combustion chamber and body. When large quantities of the mud material are used to construct the stove body, the stove does not offer significant improvements in fuel economy or air quality relative to traditional open fire cooking. This is partly because a significant amount of heat is absorbed by the mass of the stove reducing combustion efficiency and heat transfer to the cook pot. An analysis of the thermal and mechanical properties of stove materials was also performed. A material mixture containing a one‐to‐one ratio by volume of high content clay soil and straw was found to have thermal properties comparable to fired ceramics used in more advanced improved stove designs. Feedback from mud stove users in Mauritania and Mali, West Africa was also collected during implementation. Suggestions for stove design improvements were developed based on this information and the data collected in the performance, emissions, and material properties analysis. Design suggestions include reducing stove height to accommodate user cooking preferences and limiting overall stove mass to reduce heat loss to the stove body.

Structural capacity of steel tubular cast-in-place piling

Steel tubular cast-in-place pilings are used throughout the country for many different project types. These piles are a closed-end pipe with varying wall thicknesses and outer diameters, that are driven to depth and then the core is filled with concrete. These piles are typically used for smaller bridges, or secondary structures. Mostly the piling is designed based on a resistance based method which is a function of the soil properties of which the pile is driven through, however there is a structural capacity of these members that is considered to be the upper bound on the loading of the member. This structural capacity is given by the AASHTO LRFD (2010), with two methods. These two methods are based on a composite or non-composite section. Many state agencies and corporations use the non-composite equation because it is requires much less computation and is known to be conservative. However with the trends of the time, more and more structural elements are being investigated to determine ways to better understand the mechanics of the members, which could lead to more efficient and safer designs. In this project, a set of these piling are investigated. The way the cross section reacts to several different loading conditions, along with a more detailed observation of the material properties is considered as part of this research. The evaluation consisted of testing stub sections of pile with varying sizes (10-¾”, 12-¾”), wall thicknesses (0.375”, 0.5”), and testing methods (whole compression, composite compression, push through, core sampling). These stub sections were chosen as they would represent a similar bracing length to many different soils. In addition, a finite element model was developed using ANSYS to predict the strains from the testing of the pile cross sections. This model was able to simulate the strains from most of the loading conditions and sizes that were tested. The bond between the steel shell and the concrete core, along with the concrete strength through the depth of the cross section were some of the material properties of these sections that were investigated.

Development of a physically-based method for delineation of hydrologically homogeneous regions and flood quantile estimation in ungauged basins via the index flood method

Regional flood frequency techniques are commonly used to estimate flood quantiles when flood data is unavailable or the record length at an individual gauging station is insufficient for reliable analyses. These methods compensate for limited or unavailable data by pooling data from nearby gauged sites. This requires the delineation of hydrologically homogeneous regions in which the flood regime is sufficiently similar to allow the spatial transfer of information. It is generally accepted that hydrologic similarity results from similar physiographic characteristics, and thus these characteristics can be used to delineate regions and classify ungauged sites. However, as currently practiced, the delineation is highly subjective and dependent on the similarity measures and classification techniques employed. A standardized procedure for delineation of hydrologically homogeneous regions is presented herein. Key aspects are a new statistical metric to identify physically discordant sites, and the identification of an appropriate set of physically based measures of extreme hydrological similarity. A combination of multivariate statistical techniques applied to multiple flood statistics and basin characteristics for gauging stations in the Southeastern U.S. revealed that basin slope, elevation, and soil drainage largely determine the extreme hydrological behavior of a watershed. Use of these characteristics as similarity measures in the standardized approach for region delineation yields regions which are more homogeneous and more efficient for quantile estimation at ungauged sites than those delineated using alternative physically-based procedures typically employed in practice. The proposed methods and key physical characteristics are also shown to be efficient for region delineation and quantile development in alternative areas composed of watersheds with statistically different physical composition. In addition, the use of aggregated values of key watershed characteristics was found to be sufficient for the regionalization of flood data; the added time and computational effort required to derive spatially distributed watershed variables does not increase the accuracy of quantile estimators for ungauged sites. This dissertation also presents a methodology by which flood quantile estimates in Haiti can be derived using relationships developed for data rich regions of the U.S. As currently practiced, regional flood frequency techniques can only be applied within the predefined area used for model development. However, results presented herein demonstrate that the regional flood distribution can successfully be extrapolated to areas of similar physical composition located beyond the extent of that used for model development provided differences in precipitation are accounted for and the site in question can be appropriately classified within a delineated region.

Quickbird satellite imagery for riparian management : characterizing riparian filter strips and detecting concentrated flow in an agricultural watershed

Riparian ecology plays an important part in the filtration of sediments from upland agricultural lands. The focus of this work makes use of multispectral high spatial resolution remote sensing imagery (Quickbird by Digital Globe) and geographic information systems (GIS) to characterize significant riparian attributes in the USDA’s experimental watershed, Goodwin Creek, located in northern Mississippi. Significant riparian filter characteristics include the width of the strip, vegetation properties, soil properties, topography, and upland land use practices. The land use and vegetation classes are extracted from the remotely sensed image with a supervised maximum likelihood classification algorithm. Accuracy assessments resulted in an acceptable overall accuracy of 84 percent. In addition to sensing riparian vegetation characteristics, this work addresses the issue of concentrated flow bypassing a riparian filter. Results indicate that Quickbird multispectral remote sensing and GIS data are capable of determining riparian impact on filtering sediment. Quickbird imagery is a practical solution for land managers to monitor the effectiveness of riparian filtration in an agricultural watershed.

Analysis of spring break-up and its effects on a biomass feedstock supply chain in northern Michigan

Demand for bio-fuels is expected to increase, due to rising prices of fossil fuels and concerns over greenhouse gas emissions and energy security. The overall cost of biomass energy generation is primarily related to biomass harvesting activity, transportation, and storage. With a commercial-scale cellulosic ethanol processing facility in Kinross Township of Chippewa County, Michigan about to be built, models including a simulation model and an optimization model have been developed to provide decision support for the facility. Both models track cost, emissions and energy consumption. While the optimization model provides guidance for a long-term strategic plan, the simulation model aims to present detailed output for specified operational scenarios over an annual period. Most importantly, the simulation model considers the uncertainty of spring break-up timing, i.e., seasonal road restrictions. Spring break-up timing is important because it will impact the feasibility of harvesting activity and the time duration of transportation restrictions, which significantly changes the availability of feedstock for the processing facility. This thesis focuses on the statistical model of spring break-up used in the simulation model. Spring break-up timing depends on various factors, including temperature, road conditions and soil type, as well as individual decision making processes at the county level. The spring break-up model, based on the historical spring break-up data from 27 counties over the period of 2002-2010, starts by specifying the probability distribution of a particular county’s spring break-up start day and end day, and then relates the spring break-up timing of the other counties in the harvesting zone to the first county. In order to estimate the dependence relationship between counties, regression analyses, including standard linear regression and reduced major axis regression, are conducted. Using realizations (scenarios) of spring break-up generated by the statistical spring breakup model, the simulation model is able to probabilistically evaluate different harvesting and transportation plans to help the bio-fuel facility select the most effective strategy. For early spring break-up, which usually indicates a longer than average break-up period, more log storage is required, total cost increases, and the probability of plant closure increases. The risk of plant closure may be partially offset through increased use of rail transportation, which is not subject to spring break-up restrictions. However, rail availability and rail yard storage may then become limiting factors in the supply chain. Rail use will impact total cost, energy consumption, system-wide CO2 emissions, and the reliability of providing feedstock to the bio-fuel processing facility.

Model to describe the mode I fracture of steel fiber reinforced ultra-high performance concrete

Ultra-high performance fiber reinforced concrete (UHPFRC) has arisen from the implementation of a variety of concrete engineering and materials science concepts developed over the last century. This material offers superior strength, serviceability, and durability over its conventional counterparts. One of the most important differences for UHPFRC over other concrete materials is its ability to resist fracture through the use of randomly dispersed discontinuous fibers and improvements to the fiber-matrix bond. Of particular interest is the materials ability to achieve higher loads after first crack, as well as its high fracture toughness. In this research, a study of the fracture behavior of UHPFRC with steel fibers was conducted to look at the effect of several parameters related to the fracture behavior and to develop a fracture model based on a non-linear curve fit of the data. To determine this, a series of three-point bending tests were performed on various single edge notched prisms (SENPs). Compression tests were also performed for quality assurance. Testing was conducted on specimens of different cross-sections, span/depth (S/D) ratios, curing regimes, ages, and fiber contents. By comparing the results from prisms of different sizes this study examines the weakening mechanism due to the size effect. Furthermore, by employing the concept of fracture energy it was possible to obtain a comparison of the fracture toughness and ductility. The model was determined based on a fit to P-w fracture curves, which was cross referenced for comparability to the results. Once obtained the model was then compared to the models proposed by the AFGC in the 2003 and to the ACI 544 model for conventional fiber reinforced concretes.

Sediment yield reduction in an agricultural watershed

With proper application of Best Management Practices (BMPs), the impact from the sediment to the water bodies could be minimized. However, finding the optimal allocation of BMP can be difficult, since there are numerous possible options. Also, economics plays an important role in BMP affordability and, therefore, the number of BMPs able to be placed in a given budget year. In this study, two methodologies are presented to determine the optimal cost-effective BMP allocation, by coupling a watershed-level model, Soil and Water Assessment Tool (SWAT), with two different methods, targeting and a multi-objective genetic algorithm (Non-dominated Sorting Genetic Algorithm II, NSGA-II). For demonstration, these two methodologies were applied to an agriculture-dominant watershed located in Lower Michigan to find the optimal allocation of filter strips and grassed waterways. For targeting, three different criteria were investigated for sediment yield minimization, during the process of which it was found that the grassed waterways near the watershed outlet reduced the watershed outlet sediment yield the most under this study condition, and cost minimization was also included as a second objective during the cost-effective BMP allocation selection. NSGA-II was used to find the optimal BMP allocation for both sediment yield reduction and cost minimization. By comparing the results and computational time of both methodologies, targeting was determined to be a better method for finding optimal cost-effective BMP allocation under this study condition, since it provided more than 13 times the amount of solutions with better fitness for the objective functions while using less than one eighth of the SWAT computational time than the NSGA-II with 150 generations did.

Characterization of a Coal Fly Ash-Cement Slurry by the Absolute Foam Index

This dissertation established a standard foam index: the absolute foam index test. This test characterized a wide range of coal fly ash by the absolute volume of air-entraining admixture (AEA) necessary to produce a 15-second metastable foam in a coal fly ash-cement slurry in a specified time. The absolute foam index test was used to characterize fly ash samples having loss on ignition (LOI) values that ranged from 0.17 to 23.3 %wt. The absolute foam index characterized the fly ash samples by absolute volume of AEA, defined as the amount of undiluted AEA solution added to obtain a 15-minute endpoint signified by 15-second metastable foam. Results were compared from several foam index test time trials that used different initial test concentrations to reach termination at selected times. Based on the coefficient of variation (CV), a 15-minute endpoint, with limits of 12 to 18 minutes was chosen. Various initial test concentrations were used to accomplish consistent contact times and concentration gradients for the 15-minute test endpoint for the fly ash samples. A set of four standard concentrations for the absolute foam index test were defined by regression analyses and a procedure simplifying the test process. The set of standard concentrations for the absolute foam index test was determined by analyzing experimental results of 80 tests on coal fly ashes with loss on ignition (LOI) values ranging from 0.39 to 23.3 wt.%. A regression analysis informed selection of four concentrations (2, 6, 10, and 15 vol.% AEA) that are expected to accommodate fly ashes with 0.39 to 23.3 wt.% LOI, depending on the AEA type. Higher concentrations should be used for high-LOI fly ash when necessary. A procedure developed using these standard concentrations is expected to require only 1-3 trials to meet specified endpoint criteria for most fly ashes. The AEA solution concentration that achieved the metastable foam in the foam index test was compared to the AEA equilibrium concentration obtained from the direct adsorption isotherm test with the same fly ash. The results showed that the AEA concentration that satisfied the absolute foam index test was much less than the equilibrium concentration. This indicated that the absolute foam index test was not at or near equilibrium. Rather, it was a dynamic test where the time of the test played an important role in the results. Even though the absolute foam index was not an equilibrium condition, a correlation was made between the absolute foam index and adsorption isotherms. Equilibrium isotherm equations obtained from direct isotherm tests were used to calculate the equilibrium concentrations and capacities of fly ash from 0.17 to 10.5% LOI. The results showed that the calculated fly ash capacity was much less than capacities obtained from isotherm tests that were conducted with higher initial concentrations. This indicated that the absolute foam index was not equilibrium. Rather, the test is dynamic where the time of the test played an important role in the results. Even though the absolute foam index was not an equilibrium condition, a correlation was made between the absolute foam index and adsorption isotherms for fly ash of 0.17 to 10.5% LOI. Several batches of mortars were mixed for the same fly ash type increasing only the AEA concentration (dosage) in each subsequent batch. Mortar air test results for each batch showed for each increase in AEA concentration, air contents increased until a point where the next increase in AEA concentration resulted in no increase in air content. This was maximum air content that could be achieved by the particular mortar system; the system reached its air capacity at the saturation limit. This concentration of AEA was compared to the critical micelle concentration (CMC) for the AEA and the absolute foam index.

SELECTED CHEMOAUTOTROPHIC PROCESSES IN WASTEWATER TREATMENT: LOW TEMPERATURE NITRIFICATION INHIBITION BY AN AZO DYE AND BIOFILTRATION FOR ODOR CONTROL OF HYDROGEN SULFIDE

Biochemical processes by chemoautotrophs such as nitrifiers and sulfide and iron oxidizers are used extensively in wastewater treatment. The research described in this dissertation involved the study of two selected biological processes utilized in wastewater treatment mediated by chemoautotrophic bacteria: nitrification (biological removal of ammonia and nitrogen) and hydrogen sulfide (H2S) removal from odorous air using biofiltration. A municipal wastewater treatment plant (WWTP) receiving industrial dyeing discharge containing the azo dye, acid black 1 (AB1) failed to meet discharge limits, especially during the winter. Dyeing discharge mixed with domestic sewage was fed to sequencing batch reactors at 22oC and 7oC. Complete nitrification failure occurred at 7oC with more rapid nitrification failure as the dye concentration increased; slight nitrification inhibition occurred at 22oC. Dye-bearing wastewater reduced chemical oxygen demand (COD) removal at 7oC and 22oC, increased i effluent total suspended solids (TSS) at 7oC, and reduced activated sludge quality at 7oC. Decreasing AB1 loading resulted in partial nitrification recovery. Eliminating the dye-bearing discharge to the full-scale WWTP led to improved performance bringing the WWTP into regulatory compliance. BiofilterTM, a dynamic model describing the biofiltration processes for hydrogen sulfide removal from odorous air emissions, was calibrated and validated using pilot- and full-scale biofilter data. In addition, the model predicted the trend of the measured data under field conditions of changing input concentration and low effluent concentrations. The model demonstrated that increasing gas residence time and temperature and decreasing influent concentration decreases effluent concentration. Model simulations also showed that longer residence times are required to treat loading spikes. BiofilterTM was also used in the preliminary design of a full-scale biofilter for the removal of H2S from odorous air. Model simulations illustrated that plots of effluent concentration as a function of residence time or bed area were useful to characterize and design biofilters. Also, decreasing temperature significantly increased the effluent concentration. Model simulations showed that at a given temperature, a biofilter cannot reduce H2S emissions below a minimum value, no matter how large the biofilter.