Date of Graduation
5-2025
Document Type
Dissertation
Degree Name
Doctor of Philosophy in Geosciences (PhD)
Degree Level
Graduate
Department
Geosciences
Advisor/Mentor
Aly, Mohamed H.
Committee Member
Tullis, Jason A.
Second Committee Member
Cothren, Jackson D.
Third Committee Member
Dumond, Gregory
Keywords
Colorado; Colorado Springs; Electrical Resistivity; Garfield; Landslides Susceptibility; Random Forest
Abstract
Landslides are among the highly damaging natural hazards worldwide. In the USA, active landslides cause damage to homes and infrastructures as well as around 25-50 deaths per year. Colorado is one of the states most highly affected by landslides. According to the most recent Colorado Hazard Mitigation Plan (CHMP), landslides are one of the main hazards that affect Colorado State. For this research, El Paso and Garfield Counties have been selected to be studied because they have an extreme landslide growth risk. Due to the high activity of landslides in El Paso County according to the 2018 CHMP, Colorado Springs City has been selected for this research. In this dissertation, Geographic Information System (GIS), remote sensing, and Electrical Resistivity (ER) have been used to conduct three independent studies focusing on assessing landslides in Colorado. Each independent study has been presented in a separate chapter in a paper format as the paper is either published or being considered for publication in peer-reviewed journals.
The first study addresses the recent zones of landslides in Colorado Springs. Colorado Springs has been experiencing increased landslide activity for 4 decades due to developing new communities on unstable ground. Colorado Springs has developed hillslope areas on its western side; these areas are dominated by unstable shale and landslide deposits. This development decreased the stability of hillslope areas and created vulnerability to landslides. In this study, ER has been used to study Skyway landslides and the Broadmoor Bluffs landslides in Colorado Springs. ER has provided valuable information about the location of the failure surface, the geometry of the landslide surface, the moisture content, and the interface between rock types. This information has not been obtained on this large scale for Colorado Springs before using ER. The produced ER models will guide to future land use and mitigate landslides hazards in the developed areas in the landslide’s areas.
The second study has been dedicated to creating landslide susceptibility maps for Colorado Springs. In this study, the Regression Analysis (RA), Random Forest (RF), and the Analytical Hierarchy Process (AHP) have been integrated into a GIS to establish different GIS-based models. This research has extended the work that has been done before on Colorado Springs. An updated susceptibility map has been created to overcome the limitations of the susceptibility map created by the Colorado Geological Survey (CGS). In addition, the whole city has been considered in this study and several landslide-influencing factors have been investigated. The highest precipitation rates, the presence of shale units, and the high slope values are found to be the main trigger of landslides in Colorado Springs. Most landslides occur in the western, southwestern, and northwestern parts of the city. The landslide susceptibility map produced can help with landslide management, hazard mitigation, and future land use planning in Colorado Springs.
The third study has been focused on evaluating landslides in Garfield County. According to the 2018 CHMP, Garfield County is one of the counties that has been assigned the highest growth risk ratings based on the high risk noted in its local hazard mitigation plan as well as large projected percentages of population growth (ranging from 35% to 42%). The previous landslide hazard mapping is limited to the studied areas, while landslides investigation for the entire Garfield County has not been conducted before. RF has been used to investigate the relationship between landslides events and the significant influencing factors in the entire Garfield County. Five main factors, including precipitation, topographic factors, lithological types, landuse/cover (LuLc) types, and soil types have been investigated. Precipitation showed higher importance than other variables (21%). If the current climate trends continue, the frequency of landslide events will increase. Also, due to the high population growth, development and construction will increase the probability of landslides occurrences in the future. The landslide susceptibility map will help in hazard mitigation and future landuse planning in Garfield County.
Citation
Ahmed, M. (2025). Investigating Landslides in Colorado Using GIS-based Methods, Remote Sensing & Electrical Resistivity. Graduate Theses and Dissertations Retrieved from https://scholarworks.uark.edu/etd/5682
