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The form and function of freshwater mussel shell rings in the Yazoo Basin was examined in this thesis. General and controlled surface collections, excavations, a seriation, and documentary research on flooding in the Yazoo Basin were completed. Four sites were investigated, including 22YZ513 (Rugby Farm), 22YZ605 (Light Capp), 22QU562 (Devil’s Race Track), and 22QU569 (Drew Smith), in an attempt to address whether shell rings were a functional byproduct of flood-prone environments. Results indicated that the two Quitman County sites were not shell rings, even though they appeared as such from aerial photographs, and that they represent a different ceramic cultural lineage than the two shell ring sites in Yazoo County. The two shell ring sites support hypothesis 1: that a functional relationship existed between shell rings and flood-prone environments during the Middle to Late Woodland periods in the Yazoo Basin.

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Forested watersheds have often been managed for flood mitigation. Studies have shown that forests have the potential to minimize peak flows during storm events, yet the relationship between forests and flooding is inexact. Forest roads, usually found in managed systems, can potentially magnify the effects of forest harvesting on water yields. A distributed hydrologic model (DHSVM) was calibrated for a 760 ha watershed in the Blue Ridge Mountains of North Carolina. The impacts of forest road density were evaluated by running the model using uniform input parameters but changing road densities. Road densities tested were 0.5, 1.0, 3.0, 4.3, 6.0 and 12.0 km km-2. Results indicate that increases in road density increased average streamflows at densities ≥ 4.3 km km-2. During small storm events, discharge was impacted at densities ≥ 6.0 km km-2 and streamflows were impacted during large rainfall events ≥ 3.0 km km-2 road densities. These findings indicate that forest roads can influence water yields and additional management efforts may be needed that can slow the water yield from forest roads. / Master of Science

In the past thirty years, the development of compositional reservoir simulators using various equations of state (EOS) has been addressed in the literature. However, the development of compositional thermal simulators in conjunction with EOS formulation has been ignored, in particular. Therefore in this work, a fully implicit, parallel, compositional EOS-based simulator has been developed. In this model, an equation of state is used for equilibrium calculations among all phases (oil, gas, and aqueous). Also, the physical properties are calculated based on an equation of state, hence obviating the need for using steam tables for calculation of water/steam properties. The governing equations for the model comprise fugacity equations between the three phases, material balance, pore volume constraint and energy equations. The governing partial differential equations are solved using finite difference approximations. In the steam injection process, the solubility of oil in water-rich phase and the solubility of water in oil phase can be high. This model takes into account the solubility of water in oil phase and the solubility of hydrocarbon components in water-rich phase, using three-phase flash calculations. This simulator can be used in various thermal flooding processes (i.e. hot water or steam injections). Since the simulator was implemented for parallel computers, it is capable of solving large-scale thermal flooding problems. The simulator is successfully validated using analytical solutions. Also, simulations are carried out to compare this model with commercial simulators. The use of an EOS for calculation of various properties for each phase automatically satisfies the thermodynamic consistency requirements. On the other hand, using the K-value approach, which is not thermodynamically robust, may lead to results that are thermodynamically inconsistent. This simulator accurately tracks all components and mass transfer between phases using an EOS; hence, it will produce thermodynamically consistent results and project accurate prediction of thermal recovery processes. Electrical heating model, Joule heating and in-situ thermal desorption methods, and hot-chemical flooding model have also been implemented in the simulator. In the electrical heating model, electrical current equation is solved along with other governing equations by considering electrical heat generation. For implementation of the hot-chemical heating model, first the effect of temperature on the phase behavior model and other properties of the chemical flooding model is considered. Next, the material and energy balance and volume constraints equations are solved with a fully implicit method. The models are validated with other solutions and different cases are tested with the implemented models. / text

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The severity and frequency of flooding-related catastrophes are increasing, and lands adjacent to rivers that were formerly the hub for city growth and commerce now face constant threats of flooding. As flood risks have become more at the forefront of legislative consciousness, with governments increasing flood-protection and mitigation measures for flood-prone areas, landowners within such areas are left with little support and direction for their lands. In exploring the issues facing landowners within flood-prone lands, this practicum focuses on whether governments should be directly involved in finding solutions for landowners to ensure a situation where both private landowners and governments benefit. The research concludes that development within flood-prone areas should be avoided, and that municipalities should, given adequate capacity and ability, relocate existing residents from flood-prone areas to repurpose the area for flood-mitigation measures. The research recommends that the City of Brandon become a member, and participate in the Red River Basin Commission, while also exploring opportunities to play a leadership role in the implementation of a similar commission for the Assiniboine River Basin. / February 2017

Master of Arts / Department of Geography / Douglas G. Goodin / The Chobe River Basin (CRB) is a flood-dependent ecosystem that relies on seasonal floods from the Zambezi and Linyanti Rivers. These flood pulses provide water for the flood recession agriculture in the region, water for the fishing grounds around Lake Liambezi, and nutrients for the vegetation in the CRB. Recent years have shown an increase in the magnitude of flooding, which could have consequences on the region’s biodiversity and the people living in the CRB. The goal of this study is to develop a classification framework based on a training library and time-windows to use in classifying the extent of flooding in the CRB. MODIS MOD09A1 satellite imagery served as the satellite imagery. Bands one through seven were converted into the tasseled cap transformation to serve as the feature selection. The study period, from February to July, is broken down into three time-windows. The time-windows are used because the land covers in the CRB go through significant spectral changes during the study period and the three time-windows seek to improve the classification accuracy. The classification methods include maximum likelihood classifier (MLC), decision trees (DT), and support vector machines (SVMs). The results show that DT and SVMs provide the highest overall accuracy and kappa values over MLC. Classification using the time-window method was statistically significant when comparing kappa values and visually, images classified using the correct training library for a time-window displayed higher agreement with the reference data. Flooding extent was high for 2014 but low in 2015 and 2016, indicating a decreasing trend. DTs provided better inundation maximums compared to SVMs and therefore is the reason that DT are the best classification technique. The results will provide planners with information regarding the extent of flooding in the CRB and where waterborne diseases occur in the region. A new classification technique is also developed for the remote sensing literature.

The working hypothesis for this study was that small elevation differences in field depressions affect the availability of redox active nutrients because the bottom of the depression remains waterlogged and in reducing conditions longer than the edge of the depression. Mn, Fe, S and P availabilities were investigated in a field depression with a 20 meter radius and 0.5 meter depth on a flood-prone, organic vegetable farm. One depression (Depression 1) was sampled seven times during three field seasons (May 2012-June 2014). The last two dates included sampling in an additional three depressions to allow a comparison among depressions on the same date. Sampling dates were categorized by the severity of flooding into the three following kinds of events: Post-Irene, Peak, and Non-Peak. The Post-Irene category includes sampling dates in the agricultural season following prolonged snow melt and flooding from Tropical Storm Irene in 2011. Sampling dates in the Peak category occurred within 30 days after one of the the top 12 greatest rainfalls, snowfalls, or heights of Winooski River Gage in the 30 month sampling period. Sampling on Non-Peak events occurred at least one month after a preceding Peak event. Repeated waterlogging events can increase redox cycling directly affecting the interchange of Mn, Fe, and S oxides and the soil solution. Indirectly, waterlogging can increase phosphorus release into the soil solution by reduction of iron. The results of this experiment indicate that some redox-sensitive soil nutrients correlated with elevation on some dates regardless of event type. Mn was more consistently affected by waterlogging events than Fe and S. Any relationship between sulfur and elevation may have been obscured by the strong relationship of sulfur with organic matter. This data suggests that phosphorus availability depended to some extent on available iron concentration.

Although literature on flood risk and environmental justice investigates the link between race and ethnicity and vulnerability to floods, few studies examine the distribution of flood mitigation amenities. This study analyzes census tract proximity to flood mitigation projects (FMPs) completed between 2012 and 2016 in Harris County, Texas to determine if a) project location is biased towards economic growth and the urban core; b) areas most impacted by previous floods are prioritized for drainage assistance; and c) if low-income and Latinx populations are being neglected. A spatial error regression analysis indicates that FMPs are significantly proximate to the urban core, net of other factors. Results also indicate no significant relationship between census tract-level Latinx composition, income status, and proximity to FMPs. Finally, built environment characteristics and locations of previous flooding had no significant effect on where projects were placed.