Despite a breadth of work investigating the spatiotemporal details of fluid dynamics over bedforms and bedload transport dynamics over flat beds, there remains a relative dearth of investigations into the spatiotemporal details of bedload transport over bedforms and on a sub-bedform scale. To address this, we conducted two sets of flume experiments focused on the two fundamental regions of flow associated with bedforms: flow separation/reattachment on the lee side of the bedform (Chapter 1; backward facing-step) and flow reacceleration up the stoss side of the next bedform (Chapter 2; two-dimensional bedform). Using Laser and Acoustic Doppler Velocimetry to record fluid turbulent events and manual particle tracking of high-speed imagery to record bedload transport dynamics, we identified the existence and importance of “permeable splat events” in the region proximal to flow reattachment.
These coupled turbulent and sediment transport events are integral to the spatiotemporal pattern of bedload transport over bedforms. Splat events are localized, high magnitude, intermittent flow features in which fluid impinges on the bed, infiltrates the top portion of bed, and then exfiltrates in all directions surrounding the point of impingement. This initiates bedload transport in a radial pattern. These turbulent structures are primarily associated with quadrant 1 and 4 turbulent structures (i.e. instantaneous fluid fluctuations in the streamwise direction that bring fluid down into the bed in the case of quadrant 1 events, or up away from the bed in the case of quadrant 4 events) and generate a distinct pattern of bedload transport compared to transport dynamics distal to flow reattachment. Distal to flow reattachment, bedload transport is characterized by relatively unidirectional transport. The dynamics of splat events, specifically their potential for inducing significant magnitudes of cross-stream transport, has important implications for the evolution of bedforms from simple, two dimensional features to complex, three-dimensional features.
New advancements in sonar technology have enabled more detailed quantification of bedload transport on the reach scale, a process paramount to the effective management of rivers with sand or gravel-dominated bed material. However, a practical and scalable field methodology for reliably estimating bedload remains elusive. A popular approach involves calculating transport from the geometry and celerity of migrating bedforms, extracted from time-series of bed elevation profiles (BEPs) acquired using echosounders. Using two sets of repeat multibeam sonar surveys from the Diamond Creek USGS gage station in Grand Canyon National Park with large spatio-temporal resolution and coverage, we compute bedload using three field techniques for acquiring BEPs: repeat multi-, single-, and multiple single-beam sonar. Significant differences in flux arise between repeat multibeam and single beam sonar. Mulitbeam and multiple single beam sonar systems can potentially yield comparable results, but the latter relies on knowledge of bedform geometries and flow that collectively inform optimal beam spacing and sampling rate. These results serve to guide design of optimal sampling, and for comparing transport estimates from different sonar configurations.
Through an investigation of agriculture and cuisine and its consequential influence on culture, education, and design, the following project intends to reconceptualize the learning environment in order facilitate place-based practices. Challenging our cognitive dissonant relationship with food, the design proposal establishes a food identity through an imposition of urban agriculture and culinary design onto the school environment. Working in conjunction with the New American University’s mission, the design serves as a didactic medium between food, education, and architecture in designing the way we eat.
Due to the importance of millennials to cities around the globe, this study uses 2010 ZIP code area data and the Phoenix metropolitan area as a case study to test the relationships between thirteen parameters of livability and the presence of millennials after controlling for other correlates of millennial preference.
The results of a multiple regression model indicated a positive linear association between livability parameters within smart cities and the presence of millennials. Therefore, the selected parameters of livability within smart cities are significant measures in influencing location decisions made by millennials. Urban planners can consequently increase the likelihood in which millennials will choose to live in a given area by improving livability across the parameters exemplified in this study. This mutually beneficial relationship provides added support to the notion that planners should develop solutions to improve livability within smart cities.
In light of climate change and urban sustainability concerns, researchers have been studying how residential landscape vegetation affect household water consumption and heat mitigation. Previous studies have analyzed the correlations among residential landscape practices, household water consumption, and urban heating at aggregate spatial scales to understand complex landscape decision tradeoffs in an urban environment. This research builds upon those studies by using parcel-level variables to explore the implications of vegetation quantity and height on water consumption and summertime surface temperatures in a set of single-family residential homes in Tempe, Arizona. QuickBird and LiDAR vegetation imagery (0.600646m/pixel), MASTER temperature data (approximately 7m/pixel), and household water billing data were analyzed. Findings provide new insights into the distinct variable, vegetation height, thereby contributing to past landscape studies at the parcel-level. We hypothesized that vegetation of different heights significantly impact water demand and summer daytime and nighttime surface temperatures among residential homes. More specifically, we investigated two hypotheses: 1) vegetation greater than 1.5 m in height will decrease daytime surface temperature more than grass coverage, and 2) grass cover will increase household water consumption more than other vegetation classes, particularly vegetation height. Bivariate and stepwise linear regressions were run to determine the predictive capacity of vegetation on surface temperature and on water consumption. Trees of 1.5m-10m height and trees of 5m-10m height lowered daytime surface temperatures. Nighttime surface temperatures were increased by trees of 5m-10m height and decreased by grass. Houses that experienced higher daytime surface temperatures consumed less water than houses with lower daytime surface temperatures, but water consumption was not directly related to vegetation cover or height. Implications of this study support the practical application of tree canopy (vegetation of 5m-10m height) to mitigate extreme surface temperatures. The trade-offs between water and vegetation classes are not yet clear because vegetation classes cannot singularly predict household water consumption.