Preliminary Findings of Potential Increased Flood Risk near Aging Dams in Kansas, USA

Authors: Christy Jean*, Kansas State University
Topics: Human-Environment Geography, Rural Geography, Water Resources and Hydrology
Keywords: Human-Environment Geography, Flood Risk, Risk Perception, Natural Hazards, Rural Geography
Session Type: Poster
Day: 4/5/2019
Start / End Time: 1:10 PM / 2:50 PM
Room: Lincoln 2, Marriott, Exhibition Level
Presentation File: No File Uploaded


Kansas ranks second in the largest number of dams in the United States, behind Texas (FEMA 2015). By 2020, Kansas dams will be at an average age of 52 years old, with many exceeding their designed life expectancy or in need of rehabilitation. The life span of a dam is generally affected by the aging of components and materials used during construction and any changes in the physical environment including chemical, physical, mechanical and/or biological processes (Wieland and Mueller 2010). Additionally, climate change and increased urbanization projections suggest more frequent and extreme flooding requiring greater demands on current infrastructure (O’Neill et al. 2016). Currently, there is a lack of accessible information on the remaining storage capacity of most intermediate sized dams across the state, which disservices unknowing rural populations. The purpose of this study is to identify the risks associated with aging dams in conjunction with nearby vulnerable populations and a changing physical environment by examining decreased storage capacity (United States Geological Survey), current inundation maps (FEMA, local agencies), and demographic data (2011-2015 American Community Survey). This study specifically focuses on intermediate sized dams which are less likely to receive attention due to their size and remoteness but are often more susceptible to failures because of their construction type and design, lack of knowledge and/or awareness by private owners, and irregular maintenance. This initial analysis is intended to inform further research, which will determine how flood risk perception varies among these locations.

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