Hardness, defined as resistance to surface deformation, is an intrinsic property of all materials including sedimentary rocks. The variables responsible for a sedimentary rock’s hardness are not completely understood. By understanding which variables control hardness, we may gain a better understanding of related rock strength. Rock strength, defined as a rock’s resistance to plastic deformation under loading, is an important parameter for many industries such as mining, civil engineering, and hydrocarbon exploration.
Numerous tests such as triaxial tests or uniaxial tests are used to quantify rock strength, but are often expensive, time consuming, or require substantial investment in laboratory setup. To circumvent these issues, other devices have been employed to determine rock strength. For example, the Proceq Equotip Bambino micro-rebound hammer (Bambino) has been used for decades to test the hardness of materials such as concrete, steel, and ceramics. These hardness values have been used to determine material strength. Selected studies on rocks empirically correlate between Bambino-derived hardness value (called Leeb hardness) and uniaxial compressive strength (UCS). However, significant scatter in the data suggest that certain intrinsic (e.g., density, bulk mineralogy, etc.) or extrinsic factors (e.g., sample volume, surface the sample rests on) need to be considered for a better correlation.
In this study, I examined the relations between Leeb hardness and UCS values, while examining lithologic variations and other properties such as bulk mineralogy, water loss, volume, density, and effective porosity. I found that bulk mineralogy, density, effective porosity, and water content correlated with a sample’s mechanical hardness. Also, a sample’s UCS is related to its density, effective porosity, and mechanical hardness. Ultimately, these data validated previous studies and shed new insight on the controlling properties of a rock’s hardness and strength.

The Kittanning coal seams run underneath West Virginia, southeast Ohio, and southwestern Pennsylvania. It is part of a sequence that underlies the Freeport and Pittsburgh coals. All three seams are of Pennsylvanian Age. Of the seams in the Northern Appalachian Basin, the Kittanning has the among the largest extents. For that reason, it will most likely be the greatest influencer on population patterns. Since the early 1800s, the people of the region mined and used coal to produce their energy. As such, it is the goal of this research is to determine the spatial relationship between the economic coal sources and population centers.

Anxiety related to academics, especially with regards to testing, is a rapidly growing mental health issue impacting all undergraduates at TCU. High levels of test anxiety have been shown to inhibit memory recall, reduce exam scores, and promote poor study habits. Expressive writing is a form of test anxiety intervention consisting of a type of free response developed to allow students to release their minds of anxious thoughts and emotions related to exams. Expressive writing has been shown to reduce test anxiety and improve exam performance. However, the effectiveness of expressive writing may be mitigated by a students’ level of emotional intelligence. Emotional intelligence is defined as the capacity to be aware of, control, and express one’s emotions. In order to better understand the connection between emotional intelligence and expressive writing, I conducted an exploratory mixed-methods study using quantitative survey data to inform our selection of interview participants and the initial development of my interview protocol. Initially, to gain insight into students’ responses to the expressive writing prompt, I collected and coded expressive writing samples from GEOL 10113 students during the Fall of 2020. Prior to the beginning of the semester, I asked the students to complete a Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF) to assign a numerical value to their approximate emotional intelligence levels. Next, I stratified students by quartiles into high (Q3), medium (Q2), and low (Q1) emotionally intelligent groups. Then, GEOL 10113 students were asked to participate in focus group interviews, and volunteers were subsequently grouped by their TEIQue-SF score into three focus groups relating to the high, medium, and low emotional intelligence bins. Finally, using the focus group interview data and the selected student’s responses from the initial expressive writing exercise, I found that all of the student responses showed consistent differences between the three focus groups. Highly emotionally intelligent students had more positive experiences with the expressive writing exercise while lower emotionally intelligent students tended to have neutral or negative experiences with the activity. Overall, these data suggest that the level of emotional intelligence relates to how willing students were to convey their thoughts and emotions during the activity, which helped the higher emotionally intelligent students to have positive experiences with the writing exercise. The implications of my study are that while the efficacy of the expressive writing exercise is assumed, emotional intelligence is a confounding variable. Students must engage with it in some sort of authentic manner if they are to benefit from the exercise.

Solar energy is a significant contributor to the renewable energy mix. Many urban developments are making investments to install solar systems across feasible areas. The allocation of solar systems relies on the land’s geography and the amount of solar radiation received. The purpose of this study is to apply to determine the best sites for solar installations in urban areas. Using the TCU area of Fort Worth, Texas as a case study, this study will use ESRI’s ArcMap and ArcGIS Pro to estimate the solar power potential of different residential rooftops. The results will be useful in showing what households are most suitable for solar installation based on their expected energy yield.

Landslides may be caused naturally or triggered by human activities and have enormous societal and economic impacts. Detecting and mapping landslides through the generation of landslide susceptibility maps (LSM) and understanding the factors that trigger these processes will be helpful in land use planning and risk assessments. Moreover, it will also assist landslide mitigation efforts by controlling anthropogenic-led processes that induce landslides. This study deals with the analysis to identify slow-moving landslides in Travis County, Texas. It combines geographic information systems(GIS) and remote sensing datasets and techniques to generate an LSM of the study area and identify ground displacements. Remote sensing data provide key information about the topography and land uses, combined with controlling factors for a landslide occurrence such as slope, geology/soil and geological structures, and vegetation/land uses to perform an empirical approximation to map and assess landslide susceptibility. Once the susceptible areas are identified, analysis for ground displacement is applied using a Synthetic Aperture Radar Interferometric (InSAR) technique referred to as the Small Baseline Subset (SBAS) and field-based multitemporal Real-Time Kinematic (RTK) GPS measurements.

The Ouachita Trough is a basin that formed along a passive margin on the southern border of Laurentia caused by the Precambrian–Cambrian rifting of Rodinia and the opening of the Iapetus Ocean. The collision of Laurentia and Gondwana and the closing of the Iapetus Ocean thrust sediments from the Ouachita Trough onto the southern portion of the North American craton to form the Ouachita Mountains. The Ouachita Trough transitioned from a sediment-starved basin into an area of rapid sediment accumulation during the Mississippian. The Stanley Group, of interest in this study, was deposited prior to the collision of the encroaching Gondwana continent to the south. Although there have been many previous studies aiming to determine the provenance history of the Stanley Group, the results are inconclusive. In this study, nine samples from turbidite deposits of the Stanley Group were processed using both U-Pb age dating and core rim analysis. Laurentia and Gondwana have similar aged terranes that are difficult to differentiate. Using core rim analysis allowed us to date both the age of the core and rim of individual zircon grains. We were then able to correlate zircon grains of similar ages to their sources. By analyzing a large area of the Ouachita Mountains, this study shows that the Stanley Group consists of sediments sourced from both Laurentia and Gondwana terranes to the south.

Rapid industrialization and global population growth have increased the number of people living in urban areas worldwide. Developing countries, have seen tremendous increases in their industries over the past decades, which generated both positives and negative effects on their people, environment, and economy. One of the negative impacts of industrialization is industrial pollution and the increase in the number of pollutants released into the environment_ in this case, heavy metals. Heavy metal contamination is an alarming problem that many Developing countries are becoming aware of and trying to address. Heavy metal direct or indirect consumption may result in several health effects in the body, including damage and alteration of normal functioning of organs such as the brain, kidney, lungs, liver, and blood, which later result into acute or chronic diseases. This case study will look at heavy metal contamination cases in Rwanda in different drinking water sources. The focus of this case study will be on some common heavy metals released from industrial waste: Lead, Manganese, Iron, Cadmium, Zinc, and Chromium.

Teachers have experimented with the idea of virtual learning and its’ effects on student achievement. Due to the coronavirus pandemic, many schools and universities transitioned from traditional classroom-focused learning to asynchronous online learning. Asynchronous online learning is a type of instruction where online learning is not happening at the same time or place. Consequently, TCU made the abrupt transition in the Spring of 2021 to fully online asynchronous courses. To understand the magnitude of how remote learning can effect students’ academic success, my research project looks at what factors, including remote learning, can predict final grade utilizing GEOL 10113 student performance data and survey data from the spring semester of 2020 surveys. To investigate the impact of online learning, I tested several linear models to determine what confounders have a significant role in predicting students’ success in online and in remote learning. These models investigated which factors, ranging from demographic information to GPA, are significant predictors of both final grade and remote grade. I started the linear model selection process by testing a complex linear model, which had all the possible factors including interactions that can impact final grade or remote grade from the surveys. Once I knew which factors were significant from the complex model, I eliminated non-significant variables and created new models, comparing each model by their AIC values until I found the best-fit linear model for final grade and remote grade. AIC is a measurement of how well a linear model fits and the lower the AIC value the better fit the linear model has. After testing each linear model: GPA, students’ lecture section, remote grade, and exam average were significant to final grade. These models suggest that while remote grade is a significant predictor of final grade, no variable measured in this study is significant enough to impact remote grade. Differing from previous research, my results showed that there were no gaps in achievement amongst gender and underrepresented minority students. Although statistically no variable significantly impacted remote grade, there are trends amongst demographic variables and remote grade, suggesting some potential relationships that could be explored in future studies.

The Urban Heat Island (UHI) effect is characterized by the differential heating of densely populated urban areas in comparison to surrounding areas. Increased temperatures caused by buildings and other man-made infrastructure have a wide range of human and ecological impacts. One emerging methodology to combat UHI effects is the implementation of urban green spaces and trees. Trees can provide two main functions that aid in cooling; shade from the sun provided by the canopy and cooling through the process of evapotranspiration. This project aims to identify which species of tree best suits the ecoregion of Fort Worth, how much feasible green space Fort Worth can provide, and project the cooling the green spaces could provide if they are planted with trees.

The use of Interferometric Synthetic Aperture Radar (InSAR) to analyze the deformation of the Earth's surface has become an increasingly important tool for monitoring earthquakes, volcanic activity, landslides, and land subsidence. This process works by calculating the phase differences of radar signals reflected from the Earth's surface over a period of time. If the land has uplifted or subsided, the phase of the two radar signals will interfere. The image this phase difference produces is known as an interferogram, which shows the ground-surface displacement of the target area across the two time periods. This technique has been used extensively to survey Mexico City, which has been an area of concern since the beginning of the 20th century due to its dramatic rate of ground subsidence.

The reusing, recycling, and reduction of waste streams is seen as a viable sustainability strategy. One major waste stream is coffee grounds with about 11.5 million kilograms being generated per day in America of which 90% is landfilled. This waste stream can be repurposed into usable carbon-based materials to address issues of climate, pollution, or engineering applications. For my research, I am converting spent (used) coffee grounds into biochars, a type of carbon-based material, with different charring (burning) temperature to measure the removal of lead (Pb2+) from contaminated water. The charring temperature was changed in order to determine the optimal charring temperature for water treatment. This presentation will go into the maximum amount of lead the biochars can remove, how fast the biochars can remove the lead and the properties of biochars that allow for such removal. Further results, methodology, and modeling applications will be discussed in the presentation.

Nanomaterials are the new technologies reforming industrial activities. They are used to improve energy efficiency and storage, to cheaply store and process information in every internet server and personal computer, to facilitate bio-imaging and drug delivery, and in environmental remediation. These materials’ nanometric dimension, 1/100000 the width of a human hair, allows them to have novel characteristics such as strength, electrical resistivity, and conductivity, and optical absorption compared to the same materials in bigger sizes. Due to their widespread and incorporation into consumer products, it is important to understand their interactions with other elements in the environment. I used flow experiments, to understand the effects of the core and terminal groups chemistries of 3 sets of nanomaterials on their interaction with ferrihydrite, a very common and reactive mineral in the environment. The nanomaterials used in this study, namely Graphene Quantum Dot (GQD), PAMAM G4-OH, and PAMAM G3.5-COOH, have comparable sizes, 6nm, 4.5 nm, and 3.5 nm, respectively. When the experiments were conducted under acidic and circumneutral pH, the quantities of GQD and PAMAM G4-OH sorbed were equivalent and less than the quantity of PAMAM G3.5-COOH sorbed. In my presentation, I will go over the quantities and kinetics results from the interactions of the 3 sets of nanomaterials onto ferrihydrite over environmentally significant pH values (range 3-10).

Land surface temperature is a major factor used in the assessment and understanding of several processes including global climate, hydrological, geo-/biophysical, urban land use/land cover (Avdan and Jovanovska, 2016). Since the Soviet Union launched the world's first artificial satellite, Sputnik 1, in 1957 there have been about 8,900 satellites from more than 40 countries launched in space that have opened possibilities to understand the earth using remote sensing. Specifically, LANDSAT 8’s thermal infrared sensor Band 10 data has been successfully used to map land surface temperature. The specific algorithm used to derive land surface temperature from LANDSAT 8’s thermal infrared sensor Band 10 showed standard deviations of 2.4°C and 2.7°C on the first trial and second trial respectively (Avdan and Jovanovska, 2016). In my project, I used land surface temperature in addition to secondary data (geologic features, volcanoes, faults, change in cities' extents) to locate and deduce the potential geothermal plays in Rwanda. I also compared the potential geothermal plays obtained using remote sensing to those obtained using ground measurements to assess how accurate remote sensing tools are in determining geothermal plays.

Mount Rainier is a stratovolcano within the Cascade Arc situated southeast of the cities of Seattle and Tacoma. This region of Washington has undergone substantial population growth while being situated in the shadow of a large stratovolcano. Historically lahar flows, volcanoclastic debris flows, from the volcano have reached as far as Tacoma and could still pose a risk to Seattle and other smaller communities. Seismicity and annual precipitation are large contributors into predicting an eruption event as well as eruption severity. Using ArcGIS Pro and implementing various types of data including historic lahar deposit extent, population growth, seismic activity, and other contributions that can peer into a future volcanic eruption, it can be possible to assess the volcanic hazard Mount Rainier poses on nearby communities.

Anti-inflammatory drugs such as ibuprofen and triclosan are widely used and available in many pharmaceutical and personal care products (PPCP’s). The concentrations of these drugs are increasing in public surface and groundwaters and is often linked to negative impacts on aquatic life. These impacts are due to the fact that PPCP’s bypass water treatment facilities since they are not typically regulated and water treatment methods at the facilities are not designed to remove them. My research focuses on removing PPCP’s using reactive environmental sorbents like nanocrystalline ferrihydrite. Specifically, I examined the interaction of two widely used PPCP’s (Ibuprofen and Triclosan) with nanocrystalline ferrihydrite of varying particle size (<125, 125-250, >250). Results thus far show that when Ibuprofen interacts with nanocrystalline ferrihydrite at pH 4.3-4.8; 28.29% was removed when the particle size was less than 125 microns; 45.89% was removed when the particle size was 125-250 microns; and 49.92% was removed when the particle size was greater than 250. While for Triclosan 40.55%, 54.7%, 23.80% was removed by nanocrystalline ferrihydrite with size <125, 125-250, >250 respectively. My presentation will further cover surface properties of nanocrystalline ferrihydrite controlling the sorption of ibuprofen and triclosan.

The changing climate as well as the cycling of nutrients and contaminants throughout our planet is heavily influenced by interactions involving plant biomass. For example, interactions of plant biomass with soil biota (specifically fungi)regulates climate and pollution by controlling 1) the quantity of CO2 released from the respiration of organic matter and 2) the movement of pollutants on land and in water. This study focused on 1) investigating fungal colonization of coffee grounds, as a model for understanding the fungi-plant biomass interactions in soils, and 2) studying how fungal colonization changes in the physical and chemical properties of coffee grounds after molding them for 0,3,4,5 and 7 months. The objectives of the next phase of this research will be to examine how the fungi-induced changes in physical and chemical properties of coffee grounds impact 1)carbon sequestering potential (i.e. ease of respiration to CO2) of the coffee grounds and 2) the capacity of the coffee grounds to bind Gentian violet dye (as a model for organic/cationic pollutant).

Synthetic nanomaterials continue to revolutionize how we do things industrially, medically and domestically. As we continue to utilize these materials, the inevitability of them entering the environment and the need to understand the associated consequences rises to the forefront. My research focuses on understanding the chemo-dynamics of interactions between polyamidoamine (PAMAM)-based nanomaterials (most commonly in the biomedical field through drug and gene delivery) and reactive minerals in the environment. Specifically, this presentation will cover the size-dependent binding (and debinding) dynamics of carboxyl-terminated PAMAMs (G-COOH) onto (and from) ferrihydrite (FFH), a form of naturally-occurring iron oxide mineral. Early results suggest that at pH 5, the smaller G1.5-COOH PAMAM binds to (and debinds from) FFH in higher quantities but at much slower rates that the larger G3.5-COOH PAMAM. The higher quantities of G1.5-COOH PAMAM being bound to (or debound) from FFH is attributable to its smaller size - facilitating access to internal micropore space in FFH that are inaccessible by the larger G3.5-COOH PAMAM. Difference in the accessibility of internal FFH micropore space by the different sized PAMAMs would also explain observed trends in their rates of binding and debinding. In future research, I will be targeting the confirmation of early results and the expansion of my study to include G-COOH PAMAMs larger than G3.5-COOH.

Nitrate contamination of groundwater has been a growing problem in Texas and California from increased food demands, requiring growing agricultural inputs of synthetic fertilizer and manure. Pyrolysis of pistachio agro-waste is a promising method for reducing waste products and engineering biochar with the capacity to support zerovalent iron impregnation (ZVI). This study examined the efficiency of pistachio biochar for nitrate (NO₃-N) removal in water with and without ZVI. Pistachio biochar was functionalized through varied temperature pyrolysis (400-600℃) over three heating durations (0 min, 5 min, 10 min). Biochar samples from both 400°C and 600℃ pyrolysis were tested with and without ZVI impregnation over a 5 day period in a 20 ppm solution of NO₃-N. The biochar-nitrate solutions were recorded in intervals (1 hr, 3 hr, 7 hr, 24 hr, 68 hr, 96 hr, 120 hr) and Ultraviolet-Visible Spectroscopy was utilized to measure NO₃-N absorbance of samples at 400nm. The experimental data show that pistachio biochar with and without ZVI decreased nitrate levels from water; presenting a potential low-cost and sustainable option for repurposing agro-waste for water remediation.

Herbicides are chemicals frequently used in agriculture to manage or remove unwanted vegetation (i.e., weeds) that may negatively impact crops through resource competition. Through the elimination of these competitors, losses in crop yield may be reduced thus increasing cropland productivity. Atrazine is an herbicide that is widely used in the United States for the control of weeds that is predominately applied in the agriculture of corn, sorghum, and sugarcane. This is of interest to Illinois agriculture, as according to the United States Department of Agriculture (USDA), Illinois is a major agricultural producer of corn and soybeans with corn accounting for 11 million of Illinois’ 27 million acres of cropland. Further, Illinois possesses an agricultural industry that produces more than $19 billion annually of which corn accounts for more than 50 percent. It is due to the economic importance of corn crops to the state of Illinois and the widespread use of Atrazine in the agriculture of corn, that this project seeks to examine the relationship between Illinois annual corn crop yields and Atrazine application. This relationship will be assessed through analysis of spatial data acquired from the USDA for Illinois Atrazine application and corn crop yield.

Analysis of Deforestation in Nilgiri Biosphere Reserve
This research will focus on Nilgiri Biosphere Reserve, a mountainous region located in the Western Ghats of southern India that encompasses several major national parks. Recent developments have caused mass deforestation in the region for lumber and area for plantations. In addition, more roads are being developed connecting urban centers to Nilgiri, which is only worsening the deforestation issue. In this research, Landsat satellite images will be used to track change over time with regards to deforestation and the development of road networks to see how that impacts wildlife. Geospatial data geoprocessing tools will be used to categorize change in land use over time (the change in some land areas from forest/untouched reserve to agricultural or road). False and true color composites in addition to Normalized Difference Vegetation Index (NDVI) assessments will be undertaken to track the deforestation and differentiate between land types, since vegetation will be in a bright red, soil will be brown, and urban areas will be cyan blue to determine how much live green vegetation there is in the reserve as well.

Assessing Land Use Impact on Urban Heat Island Formation in Fort Worth

This research project will focus on assessing the impacts of human activity on the environment in Fort Worth as urbanization has increasingly taken hold over the years. Specifically, the project focuses on analyzing the change in land use in the city over a span of roughly three decades and its contributions to urban heat island formation. Landsat band data products will be used to estimate variations in land surface temperature (LST). LST calculations will highlight the factors contributing to urban heat island formation in Fort Worth.

Plant biomass represents an important component within the biogeochemical cycling of nutrients and contaminants. Transformation of this plant biomass in the environment to organic residuals is dictated primarily by interactions with micro-organisms specifically fungi. My research investigates the effects of fungal colonization of spent coffee grounds as a model for plant biomass to organic matter transformation and how this transformation impacts environmental stability and its ability to bind to contaminants. This presentation will cover; 1) physical and chemical changes in the spent coffee grounds after molding for 0,3,4,5 and 7 months, 2) how these physical changes impact the environmental degradability, and 3) how these physical and chemical changes impact the capacity to bind Gentian violet dye (as a model for organic cations).

The southern margin of the North American continent transformed from a passive margin to an
active margin during the Ouachita orogeny. Thick and near–continuous Paleozoic successions in
the Ouachita Mountains provide a unique opportunity to document changes in both
sedimentation and tectonics. In contrast to well-documented Taconic, Acadian, and Alleghenian
orogenic events, limited detrital zircon studies of the Ouachita orogeny and associated
successions have been published, and sediment sources of these deep-water, synorogenic clastics
remain less constrained.
In this study, a total of six outcrop samples (n=617) from the Mississippian Stanley Group and
Lower-Middle Pennsylvanian Jackfork and Johns Valley Groups were collected and processed
for U-Pb detrital zircon geochronologic analyses to depict sediment sources and dispersal
patterns during the Ouachita orogeny. Results show that the age distributions of the
Carboniferous deep-water clastic deposits in the Ouachita Mountains are characterized by major
peaks of the Paleozoic (~350-500 Ma), Grenville (~900-1350 Ma), and Midcontinental GraniteRhyolite (~1350-1500 Ma), minor peaks of Yavapai-Mazatzal (~1600-1800 Ma) and Superior (>
~2500 Ma) provinces. These deep water clastics share great similarities with the Appalachian
sources and are likely derived from similar sources. From the Mississippian Stanley Group to the
Pennsylvanian Jackfork and Johns Valley Groups, the Yavapai-Mazatzal population shows
marked enrichment (up to ~12%), suggesting Precambrian basement uplifts, possibly related to
the Ancestral Rockies to the northwest, might be another potential source. Compilation and
comparison show the Neoproterozoic age population (~550-800 Ma), most likely associated with
the peri-Gondwana terrane to the south, ranges from 3% to 35% within the Mississippian Stanley
Group. The variation indicates that the Stanley Group may have strong but short-lived local
contribution from the Gondwana terrane in addition to the regional Appalachian sources.
Overall, despite its proximal location, these Carboniferous deep-water clastic deposits in the
Ouachita Mountains received limited contribution from the Ouachita orogenic belt itself.

The new world tropics represent an area of unparalleled biodiversity. Unfortunately, it also represents an area of increasing habitat loss and consequently is in dire need of protection and conservation. The TCU San Ramon Tropical Biology Station located on the Caribbean slope of Costa Rica protects 100 hectares of primary and secondary forest and is a unique and ideal location for studying tropical biology. In the summer of 2018, we mapped an updated trail network at the station using a Bad elf sub-meter GNSS receiver in conjunction with Arc Collector. For this project we analyzed the distance each trail traveled through the 3 habitat types found at the station (primary forest, secondary forest, and pasture land), which will be used to aid the sampling efforts of my Master’s thesis project examining how mixed-species foraging flocks utilize the habitat protected by the station.

The Triassic Dockum Group of the western Texas High Plains is studied in depth paleontologically, but until recently lacked a detailed sedimentological evaluation. Recent research of the Dockum Group in Palo Duro Canyon, Texas, provides new interpretations of the complex fluvial lacustrine strata of the comprising formations based on analysis of individual lithofacies. Identified within the lithofacies assemblages are numerous channel belts composed of upper flow regime bedforms. Observed upper flow regime bedforms in outcrop range from upper plane bed, antidunes, breaking antidunes, chutes and pools, and cyclic steps with increasing flow velocity respectively. These channel belts record extreme flow events from repeating massive storms that perpetuated throughout the Texas region of Triassic Pangea. These unique reservoir-quality channels are interpreted to be resultant of a megamonsoonal climate producing massive pulses of rapid flow allowing for the preservation of upper flow regime bedforms. While these channels are identified in outcrop they have not been quantified in distribution, variability in fill, connectivity and formative discharge.
This study aims to test the megamonsoonal hypothesis by quantifying the discharge of these channels and testing if the distribution density and paleodischarge of these channels is consistent with local dominance of megamonsoonal conditions. Upper flow regime structures are rarely preserved in the rock record and extremely difficult to observe directly during natural formation in modern rivers. Most of the equations used to quantify flow conditions for these structures are derived from flume tank experiments. These are applied to the upper flow regime bedforms found in outcrops of the Dockum Group to reconstruct paleohydrology. Current flume tank research reinforces Kennedy’s equations defining relationships between the wavelengths of stable antidune apexes (λ), mean flow depth (hm) and mean flow velocity (U). These equations are modified to account for different upper flow regime structures formed under increasing velocity and discharge identified in outcrop. Bedform distribution, size, and type are variables determined from outcrop measurement. Paleoflow velocities, Froude numbers and relative water depths are determined with an observed margin of error. Scaling relationships and field measurements provide constraints on channel cross sectional area and channel-belt density. This data along with grain size distribution provides tangible numbers for calculating formative discharge. Preliminary results align with data from flume tank experiments and are consistent with major floods produced by substantial storm events verifying the megamonsoonal hypothesis.