GSA 2020 Connects Online

Paper No. 60-7
Presentation Time: 11:30 AM

MODELING FLOOD POTENTIAL BASED ON LAND USE IN THE GREENBRIER RIVER WATERSHED IN WEST VIRGINIA


LÓPEZ SÁNCHEZ, Manuel E., Voinovich School of Leadership and Public Affairs, Ohio University, Ridges Building 21, Athens, OH 45701, SPRINGER, Gregory, Department of Geological Sciences, Ohio Univ, 316 Clippinger, Athens, OH 45701 and KRUSE, Natalie A., Voinovich School of Leadership and Public Affairs, Ohio University, Athens, OH 45701

In the context of flood statistics, the stationarity assumption refers to independent and equally distributed floods at a given location. While flood analyses have been conducted using the stationarity principle, recent studies question its validity. This research echoes studies challenging stationarity and develops multiple maps to test flood probabilities. West Virginia relates to questioning the stationarity assumption as it has suffered various catastrophic floods in just the past 40 years. As the Greenbrier River (GR) watershed (HUC 05050003) suffered dramatic land use changes in the past 120 years, land use change and historic logging are considered crucial variables for the purposes of this study. A statistical analysis of the hydrological data for the GR is performed to test for stationarity. Watershed land use scenarios are illustrated to compare land use differences in accordance to historic logging data. As stationarity is questioned, new flood statistical analyses are conducted by collecting broad meteorological data. This study also considers the rising costs of floods and consequential disaster risks produced after such events. To understand such risks and how they could be altered with new data, Digital Elevation Models (DEMs) covering the region are used to illustrate topographical maps. Historic runoff, streamflow, logging data and the newly created land use scenarios, will be used to simulate flood distribution based on regional meteorological records. Similarly, as the flood record could be distorted by early logging activities, flood recurrence intervals (RI) are assessed with modern statistical flood probabilities. This study will provide tools to understand the largest floods and will also ensure if previously calculated N-year flood events changed.