A Data Integration Approach for Assessment of Rainfall-Induced Slope Failure Susceptibility

Roadside clayey slopes are prone to rainfall-induced instabilities due to clay’s high swelling and shrinkage potential. These shallow slope failures damage bridges, road surfaces, shoulders, guardrails, and roadside drains severely restricting the movement of commodities, workforce, and resources. Each year highway agencies spend millions of dollars on restoring services disrupted by slope failures. Identifying the critical segments in roadside slopes can facilitate proactive maintenance decisions, thereby reducing the need for emergency repair and minimizing the impact on flowing traffic. This research aims to explore the possibility of integrating publicly available data to identify segments of clayey soil slopes that are susceptible to rainfall-induced slope failure. A combination of hydrological and geotechnical models is used to integrate data on slope stability variables, such as soil properties, slope angles, and rainfall. The data integration approach helps assess the least duration of rainfall corresponding to 10-years return period rainfall event initiating failure in roadside slopes. The proposed data integration approach is demonstrated along the 308 miles of highway corridors in Texas, where roadside slopes are made of highly plastic clayey soils. Historic slope failures were used to validate the result of the proposed approach. The result showed that ninety percent of past roadside slope failures were in the areas that are susceptible to failure from a 10-year rainfall event with the duration of three days or less. The proposed approach for appraising failure susceptibility of roadside slope can help highway agencies to develop slope hazard maps, identify critical slopes, and perform proactive rehabilitation.