Executive Summary : | Geologically, the Cachar-Tripura-Mizoram (CTM) fold belt of northeast India is a part of westerly convex arcuate Indo-Myanmar mobile belt. The lithology of this region is relatively young and fragile of alternating shale-mudstone-siltstone-sandstone of Cenozoic Era that continuously suffers natural disasters like hailstorms, cloudbursts, earthquakes (Seismic Zone–V), landslides, cyclones, flood, fire, etc. that invariably affect the failure behavior of rocks by influencing their hydromechanical and geomechanical properties. Due to the alternate wetting and drying of this material throughout the year, there is a continuous variation in moisture content, pore pressure and temperature, which alters the physico-mechanical properties of the rock at various depths, resulting in unpredictable failure. Surprisingly, research on the combined effect of these parameters on rocks is still lacking for this region. Every year, several landslides have been reported from various localities, continuously hampering the trade and development of the region. Also, the study of the mechanical degradation and failure behavior of the CTM rocks in such geo-environmental conditions have wider applications, such as the construction of stable civil structures on slopes, tunnelling, highway, bridge, etc. But, due to the challenges of being remotely located, inadequate infrastructure, landlocked geography and poor connectivity, the region is still scientifically unexplored in terms of failure behavior of these geotechnically ignored litho-units. Therefore, through this proposal, a regional-scale evaluation of the collective impact of these parameters caused by exogenetic processes driven by the climatic forces will be investigated for this region. The physico-mechanical properties of the rocks will be evaluated in the laboratory and the results shall be used for performing probabilistic slope stability analysis by a series of numerical simulations and coupled artificial intelligence tools like Support Vector Machine (SVM), Artificial Neural Network (ANN) and Multivariate Adaptive Regression Spline (MARS) with geo-spatial data considering the combined effect of various climatic and geologic factors. During the field investigation, Electrical Resistivity Tomography (ERT) technique will be applied for near-surface exploration of the critical slopes. The apparent resistivity contrasts obtained from ERT images will be used to identify the detailed lithological variation/thickness, density contrast and water content variations. The results will be greatly helpful in planning safer slopes, highways, tunnels, bridges and other infrastructures. This research would aid India's long-term economic development goals by improving connectivity between the region and neighbouring Southeast Asian countries such as Myanmar and Thailand. It will also open up a new avenue for India to boost its economic growth in order to counter China's growing influence in the region (Southeast Asia). |