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GIS Based Assessment of Climate-induced Landslide Susceptibility of Sensitive Marine Clays in the Ottawa Region, Canada

Landslides are relatively frequent in Ottawa due to the presence of sensitive marine clays (Leda clay or Champlain Sea clay), and the presence of natural or climatic triggers such as rainfall or snowmelt. A geographic information system (GIS) based modeling tool has been developed to assess and predict climate (rainfall and snowmelt)-induced landslides in the sensitive marine clays of the Ottawa region. The Transient Rainfall Infiltration and Grid-based Regional Slope-Stability (TRIGRS) model is used in a GIS framework to investigate the influence of rainfall and snowmelt on shallow landslides through the Ottawa region, with respect to time and location.
First, the GIS and TRIGRS models are combined to assess landslide susceptibility with respect to rainfall. The GIS-TRIGRS approach requires topographic, geologic, hydrologic, and geotechnical information of the study area. In addition to this technical information (input data), rainfall intensity data for different durations (5 minutes, and 6, 12, 18, and 24 hours), and historical data of the regional landslides is required. This data is used to verify the locations of predicted landslide-susceptible areas with respect to historical landslide maps in the area. The generated results from the GIS-TRIGRS model were verified by comparing the predicted and historical locations of shallow landslides induced by rainfall throughout the Ottawa region. The comparison results showed a high correlation between the predicted areas of landslides and the previously reported landslides. In addition, the results also indicated that not all previous landslides in Leda clays were triggered by rainfall.
The second application of the developed GIS-TRIGRS approach was used to assess and predict snowmelt-induced landslides in areas of sensitive marine clay in the Ottawa region. Similar to the first analysis, the approach requires the following input data: topographic, geologic, hydrologic, geotechnical, snowmelt intensity data for various periods (6–48 hours, 3–15 days, 25 days, and 30 days), This approach also requires data indicating the location of historical landslides in the study area. Using this data, we examine both the timing and location of shallow landslides due to snowmelt in a GIS-based framework. The developed model was validated by comparing the predicted landslide-susceptible areas to historical landslide maps in the study area. A high correlation between predicted and historical landslide location trends was obtained, confirming that the developed GIS-TRIGRS model can predict the snowmelt-induced landslide susceptibility in the sensitive marine clays relatively well. The model results reinforced the conclusion that areas with high slopes and sensitive marine clays were more prone to snowmelt-induced landslides.
Finally, in a Geographic Information System (GIS) the landslide occurrence susceptibility in the Ottawa area was modeled. Results of such models are presented as maps showing landslide susceptibility in Champlain Sea clays (Leda clays) in the Ottawa area due to both rainfall and snowmelt. Various input data was collected and entered into a GIS and TRIGRS model. The main categories of such inputs are climate, topography, geology, hydrology, and geotechnical data. The rainfall and snowmelt intensity data was extracted for 24 to 48 hour periods from Environment and Climate Change Canada historical climate records. Thereafter, the factor of safety was calculated in order to determine the stability of slopes across the study area. The model assesses the effects of rainfall and snowmelt on landslide occurrence, and based on the calculated factor of safety at each pixel of the study area, the model calculates the landslide susceptibility.
The results presented in this thesis will provide a geotechnical basis for making appropriate engineering decisions during slope management and land use planning in the Ottawa region.

Identiferoai:union.ndltd.org:uottawa.ca/oai:ruor.uottawa.ca:10393/37218
Date January 2018
CreatorsAl-Umar, Mohammad
ContributorsFall, Mamadou, Daneshfar, Bahram
PublisherUniversité d'Ottawa / University of Ottawa
Source SetsUniversité d’Ottawa
LanguageEnglish
Detected LanguageEnglish
TypeThesis

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