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GIS-Based Data Integration Approach for Rainfall-Induced Slope Failure Susceptibility Mapping in Clayey Soils
Roadside slopes in clayey soils with high swelling and shrinkage potential are prone to rainfall-induced shallow slope failures. Identification of slope segments susceptible to rainfall-induced failures helps transportation agencies minimize the impact of slope failures on highway transportation systems. Publicly available datasets on slope stability variables provide an unprecedented opportunity to assess the condition of the slopes along highway corridors. However, these datasets are mostly underutilized with respect to highway slope susceptibility analysis. The objective of this research is to develop a GIS-based data integration approach to take advantage of publicly available data sources for mapping rainfall-induced shallow slope failure susceptibilities in slopes constructed of clayey soils. The methodology is comprised of integrating the slope stability variables with a combination of geotechnical and hydrological models to determine minimum durations for different return period rainfall events triggering slope instability in clayey slopes. The approach was implemented along approximately 308 mi (496 km) of highway corridors in the Texas Department of Transportation (TxDOT) Paris district. Slope susceptibility maps were developed using the minimum duration of a 10-year return period of rainfall required to trigger slope instability. The slope failure susceptibility maps developed using the proposed approach were validated with a dataset of 10 recent slope failures. Nine out of 10 recent slope failures were in the region that required less than three days of 10-year return period rainfall to trigger the shallow slope instability. The proposed data integration approach helps transportation agencies proactively identify and maintain roadside slopes susceptible to rainfall-induced failures.
GIS-Based Data Integration Approach for Rainfall-Induced Slope Failure Susceptibility Mapping in Clayey Soils
Roadside slopes in clayey soils with high swelling and shrinkage potential are prone to rainfall-induced shallow slope failures. Identification of slope segments susceptible to rainfall-induced failures helps transportation agencies minimize the impact of slope failures on highway transportation systems. Publicly available datasets on slope stability variables provide an unprecedented opportunity to assess the condition of the slopes along highway corridors. However, these datasets are mostly underutilized with respect to highway slope susceptibility analysis. The objective of this research is to develop a GIS-based data integration approach to take advantage of publicly available data sources for mapping rainfall-induced shallow slope failure susceptibilities in slopes constructed of clayey soils. The methodology is comprised of integrating the slope stability variables with a combination of geotechnical and hydrological models to determine minimum durations for different return period rainfall events triggering slope instability in clayey slopes. The approach was implemented along approximately 308 mi (496 km) of highway corridors in the Texas Department of Transportation (TxDOT) Paris district. Slope susceptibility maps were developed using the minimum duration of a 10-year return period of rainfall required to trigger slope instability. The slope failure susceptibility maps developed using the proposed approach were validated with a dataset of 10 recent slope failures. Nine out of 10 recent slope failures were in the region that required less than three days of 10-year return period rainfall to trigger the shallow slope instability. The proposed data integration approach helps transportation agencies proactively identify and maintain roadside slopes susceptible to rainfall-induced failures.
GIS-Based Data Integration Approach for Rainfall-Induced Slope Failure Susceptibility Mapping in Clayey Soils
Baral, A. (author) / Poumand, P. (author) / Adhikari, I. (author) / Abediniangerabi, B. (author) / Shahandashti, M. (author)
2021-05-12
Article (Journal)
Electronic Resource
Unknown
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