Traditionally civil infrastructure designs were rendered using rainfall data from dated historical records. However, recent studies have shown that the magnitude and intensity of historical precipitation events do not exhibit the extreme nature of precipitation events that are projected to occur in the future. Increasing extreme rainfall trends have already been documented in Canada. Therefore there are growing concerns that the aging infrastructure in southern Ontario will be unable to function effectively and as a result the frequency of floods is expected to increase. Updating intensity-duration-frequency (IDF) curves to account for extreme precipitation events is vital to ensure that the consequences of floods are mitigated. This study first reviewed the most robust techniques for updating IDF curves, and applied a select set of approaches to create IDF curves for stations within southern Ontario. Three robust techniques – the at-site method, the regional frequency analysis method, and a future IDF curve development technique – were compared with one another to determine which technique was most suitable for updating IDF curves in southern Ontario. Results showed that the difference between the at-site method and the regional frequency analysis method was marginal for short return periods, however for larger return periods larger differences were observed. Future IDF statistic results showed that for the 2050s there were minor differences in the increases in rainfall intensities when comparing with the at-site and the regional frequency analysis method. For the 2100s there were larger increases in rainfall intensities compared to the at-site and the regional frequency analysis method, especially for larger return periods. These results suggest that it is worthwhile for regions within southern Ontario to update their IDF curves using the future IDF curve technique, however it is recommended that additional climate models, emission scenarios and downscaling techniques involved in future IDF curve construction are explored. / Thesis / Master of Science (MSc)

Tennessee has a long history of floods that have caused property damage and loss of life. In the face of climate change and variability, it is imperative to look at trends to ascertain if there is a significant change in current flood regimes versus past flood events. Trend Analysis and Emerging Hotspot Analysis are useful geospatial tools that can effectively display changes over time and space. This study aims to evaluate the history of flood events in Tennessee to identify spatiotemporal trends and hot spots. A total of 902 flood events from 1996-2021 recorded in the National Oceanic Atmospheric Agency (NOAA) storm events database were analyzed using the number of events per county and the total damages per county at an annual time step. Two 26-year space-time cubes were built in ArcGIS Pro (version 3.0) for flood events and damages using an annual time step, with counties as the spatial unit. GeoGa software (version 1.20.0.22) was used to weight the distance between Tennessee counties to define a statistically significant neighborhood distance at 37km fixed distance. Trend Analysis and Emerging Hotspot Analysis was conducted to assess spatiotemporal trends in flooding events and damages (in dollars). Trend analysis revealed an increasing trend of flood events in eleven counties in middle Tennessee (Davidson, Wilson, Rutherford, Coffee, Marion, Putnam, Overton, Maury, Lawrence and Dickson counties) and Carter county in east Tennessee. Decreasing trends were observed in two counties (Lake and Bradley), all at a 90% or greater confidence level. Increasing trends in flood damages were identified in Cumberland, Putnam, Lawrence, Blount, Sullivan and Green counties, all in east and middle Tennessee. Decreasing trends were identified in Lake, Obion, Dyer, and Tipton, all in west Tennessee. East Tennessee was identified as a sporadic flooding hot spot (Hawkins, Green and Washington counties) with no significant hot spots in middle and west Tennessee. There were no hot spots nor cold spots in flood-related damages across Tennessee. The results indicate that flood events and related damages are decreasing in west Tennessee while parts of middle Tennessee and east Tennessee are experiencing increased flood events. This study is an important step to better understand spatiotemporal trends in flooding and flooding damages and will be useful in hazard mitigation planning in Tennessee at both state and county levels.

Recently, oil prices and oil demand are rising and are projected to continue to rise over the long term. These trends create great potential for enhanced oil recovery methods that could improve the recovery efficiency of reservoirs all over the world. The greatest challenges for enhanced oil recovery involve the technical uncertainty with design and performance, and the high financial risk. Pilot tests can help mitigate the risk associated with such projects; however, there is a question about the value of information from the tests. Decision support can provide information about the value of an enhanced oil recovery project, which can assist with alleviating financial risk and create more potential opportunities for the technology. The first objective of this study is to create a new simplified method for modeling oil production histories of enhanced oil recovery methods. The method is designed to satisfy three criteria: 1) it allows for quick simulations based on only a few physically meaningful input parameters; 2) it can create almost any potential type of realistic production history that may be realized during a project; and 3) it applies to all nonthermal enhanced oil recovery methods, including surfactant-polymer, alkali-surfactant polymer, and CO₂ floods. The developed method is capable of creating realistic curves with only four unique parameters. The second objective is to evaluate the predictive method against data from pilot and field scale projects. The evaluations demonstrate that the method can fit most realistic production histories as well as provided ranges for the input parameters. A sensitivity analysis is also performed to assist with determining how all of the parameters involved with the predictive method and the economic model influence the forecasted value for a project. The analysis suggests that the price of oil, change in oil saturation, and the size of the reservoir are the most influential parameters. The final objective is to establish a method for a decision analysis that determines the value of information of a pilot for enhanced oil recovery. The analysis uses the predictive method and economic model for determining economic utilities for every potential outcome. It uses a decision-based method to ensure that the non-informative prior probability distributions have an unbiased, consistent, and rational starting point. A simple example demonstrating the process is discussed and it is used to show that a pilot test provides some valuable information when there is minimal prior information. For future work it is recommended that more evaluations are performed, the decision analysis is expanded to include more input parameters, and a rational and logical method is developed for determining likelihood functions from existing information. / text

Atmospheric rivers (ARs) are long, narrow plumes of concentrated water vapor that are a critical factor in the transport of moisture from oceans to continents in the mid-latitudes. Much of the existing research on the impact of ARs on the United States focuses on the Pacific Coastal states and their importance as contributors to precipitation, their impact on water resources, and their role as flood producers. The objective of this study is to determine the importance of Pacific Ocean ARs penetrating further inland and affecting flooding in the state of Arizona. The following questions were addressed: (1) Are certain regions in Arizona more susceptible to AR-related flooding? (2) Do ARs produce flooding events of greater magnitude in Arizona than floods produced by other mechanisms? (3) Are there identifiable variables or conditions that influence the frequency, magnitude, and location of AR-related flooding in the state? Based on a study of selected watersheds throughout Arizona, results showed that the most active region of AR-related flooding in Arizona is associated with the abrupt increase of elevation along the Mogollon Rim of the state's Central Highlands Transition Zone physiographic region. The percentage of AR-related flooding events in this region can reach over 50% for some watersheds, such as the Verde and the Salt. The influence of ARs on flooding is weaker to the north, in the Colorado Plateau region, and to the south, where summer convective storm activity in southeastern Arizona's Basin and Range physiographic region is a more common flood producer, and where the most extreme floods are associated with late-summer tropical cyclones. When ARs did affect northern or southern Arizona, they did not have the same degree of influence on flood magnitude and frequency as in the Mogollon Rim/Central Highlands watersheds, which implies that watersheds in the Mogollon Rim/Central Highlands have characteristics that are favorable for AR-related flooding. Lastly, in addition to the importance of the Central Highlands' orography on AR flooding, another finding of this study points to the importance of the trajectory of the inland-penetrating AR as a factor. The corridor along which the AR enters the region can strongly affect which ARs will produce floods and which ARs will not, with a south/southwesterly trajectory across Baja California producing the largest percentage of AR floods in Arizona in this study.

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This study examines the relationship between the developing landscape and the water flowing through it. The study area was an 86 sq. mi. watershed located in the coastal plains in Harris County, Texas. Daily streamflow data for 52 years was obtained from USGS and coincident precipitation data was obtained from NOAA. Georeferenced parcel-level data was obtained from the Harris County Appraisal District with sufficient detail to determine year of development, parcel area, and impervious cover. Watershed boundaries were obtained from the Harris County Flood Control District. After controlling for daily precipitation, streamflow exhibited significant increases at all levels over time. Increasing streamflow was not associated with climate change. FRAGSTATS was used to quantify spatial patterns in the developed landscape on an annual basis. Regression analysis was used to determine the relationship between spatial and non-spatial measures of development and streamflow. It was found that models based on the spatial configuration of the developed landscape predict streamflow better than non-spatial measures such as total impervious cover. Several metrics were identified for their potential use as guidelines for urban planning.

Increasing the catalyst utilization is one way to improve the performance of a fuel cell. In this study, the hydrophobic pillared micro structures (HPMS) is used to increase the oxygen/ catalyst layer interface and thereby raise the performance by about 40%. By using the HPMS of a large size, the performance is improved by around 20%, which is just the same as the increment of the contact surface between oxygen and catalyst layer. By halving the loading of the small HPMS and thus increasing the contact surface between oxygen and the catalyst layer by half of the previous amount, the performance increase is also halved. These experimental results indicate that the main reaction zone is near the surface between oxygen and the catalyst layer. Consequently, there is no obvious decrement in the performance when the Pt loading of cathode is halved, just as the experimental results indicated. As a result, the utilization of catalyst is raised substantially.

This study examines the relationship between the developing landscape and the water flowing through it. The study area was an 86 sq. mi. watershed located in the coastal plains in Harris County, Texas. Daily streamflow data for 52 years was obtained from USGS and coincident precipitation data was obtained from NOAA. Georeferenced parcel-level data was obtained from the Harris County Appraisal District with sufficient detail to determine year of development, parcel area, and impervious cover. Watershed boundaries were obtained from the Harris County Flood Control District. After controlling for daily precipitation, streamflow exhibited significant increases at all levels over time. Increasing streamflow was not associated with climate change. FRAGSTATS was used to quantify spatial patterns in the developed landscape on an annual basis. Regression analysis was used to determine the relationship between spatial and non-spatial measures of development and streamflow. It was found that models based on the spatial configuration of the developed landscape predict streamflow better than non-spatial measures such as total impervious cover. Several metrics were identified for their potential use as guidelines for urban planning.