Master of Science, Miami University, 2023, Geology and Environmental Earth Science

Fluvial terraces are vital to reconstructing past depositional dynamics within a watershed as well as determining flood and erosion risk. In the midwestern US, detailed mapping of terrace age is necessary to determine if deposition occurred during multiple distinct periods. In this study, changes to soil geochemistry over time were quantified from nine radiocarbon-dated soils spanning ~17,000 years and this relationship was used to infer soil age across a broad fluvial terrace. Regression models quantifying Fe/Ca, Zr/Ca, and Ti/Ca changes at multiple soil depths were created. Fe/Ca models returned R2 values between 0.69 and 0.97 with the lowest uncertainties compared to Zr/Ca and Ti/Ca models. Samples collected at 20-30 cm depth resulted in the highest correlation coefficient compared to samples collected at 0-10 and 60-70 cm. The mean Fe/Ca value of parent material was 0.33 with standard deviation 0.12. The models were subsequently used to infer soil age from Fe/Ca values of 388 locations on the floodplain and overbank deposits were delineated based on inferred soil age. In general, deposit age increases with increasing distance from the modern channel. Results support use of this field-based technique to map fluvial terraces at a high resolution.

Committee: Jason Rech Dr. (Advisor); Maija Sipola Dr. (Committee Member); Claire McLeod Dr. (Committee Member) Subjects: Earth; Geology; Geomorphology; Soil Sciences

Master of Science in Engineering, Youngstown State University, 2016, Department of Civil/Environmental and Chemical Engineering

The flood warning system can be effectively used to reduce the potential property damages and loss of lives. Therefore, a reliable flood warning system is required for the evacuation of people from probable inundation area in sufficient lead time. Hence, this study was commenced to predict the travel time and generate inundation maps along the Grand River, Ohio for various flood stages. A widely accepted hydraulic tool, Hydraulic Engineering Center River Analysis System (HEC-RAS), was used to perform the hydraulic simulation. HEC-GeoRAS, an ArcGIS extension tool, was used to prepare geospatial data and generate flood inundation maps for various flood stages. A topographic survey was conducted to obtain the accurate elevation of river channels. The hydraulic simulations were carried out using six different elevation datasets and various ranges of Manning's roughness to quantify the uncertainties in travel time and inundation area prediction due to the resolutions of the elevation datasets and Manning's roughness. The study showed that the coarse elevation dataset, which was 30m Digital Elevation Model (DEM) without integration of survey data, provided higher travel time and inundation area. It over predicted (11.03%-15.01%) in travel time and inundation area (32.56%-44.52%) for various return period floods when compared with the results of Light Detection and Ranging (LiDAR) integrated with survey data. Moreover, Manning's roughness was found to be more sensitive in channel sections than that of floodplains. The decrease in travel time and inundation area was observed with the decrease in Manning's roughness. The highest decrement of 21.38% and 8.97% in travel time and inundation area was observed when roughness value was decreased in channel sections, while the decrement in travel time and inundation area was 3.45% and 1.49% when roughness value was decreased in floodplains. The difference in predicted travel time and inundation area, while using LiDAR integrated wi (open full item for complete abstract)

Committee: Suresh Sharma PhD (Advisor); Tony Vercellino PhD (Committee Member); Bradley Shellito PhD (Committee Member) Subjects: Civil Engineering; Hydrologic Sciences; Water Resource Management