GSA Connects 2024 Meeting in Anaheim, California

Paper No. 209-5
Presentation Time: 2:40 PM

DEVELOPMENT OF CORRELATIONS BETWEEN VARIOUS ROCK MASS CLASSIFICATION SYSTEM IN THE NEPAL HIMALAYA


CHAULAGAI, Kanchan, Central Department of Geology, Tribhuvan University, Kathmandu, Kathmandu, Bagmati +977, Nepal and DAHAL, Ranjan Kumar, Central Department of geology, Tribhuvan University, Kathmandu, Bagmati +977, Nepal

Detailed evaluation of geological and geotechnical is prerequisite for any design in Underground excavation works. The rock mass classification system has serve as a key role for designing of rock engineering projects. It has function as a crucial tool for characterizing the rock masses. Various classification systems are in practice and are still evolving. As different rock mass classifications system were established in different era in different region with different purposes, it is imperative to establish inter-correlatability between them. These inter- correlatability is very necessary in the Nepal Himalaya, as the development in the underground excavation work is going rapidly in these decades. RMR, Q and GSI system are the most accepted and implemented system for characterizing the rock mass of the Nepal Himalaya. The correlation between theses classification system has been provided by different researcher in the past and is continuous with specific to the region. Hence this research is carried out to provide a novel relationship between RMR, Q and GSI in the Nepal Himalayan Terrain. For the purpose of the study, the data obtained from Headrace tunnel of Eight hydropower projects i.e. Upper Chaku A Hydroelectric Project (UCAHEP), Upper Balephi A Hydroelectric Project (UBAHEP), United Mewa Khola Hydroelectric Project (UMKHEP), Kapadi Gad Hydroelectric Project (KGHEP), Maya Khola Hydropower Project (MKHPP), Upper Mai Hydroelectric Project (UMHEP), Lower Erkhuwa Khola Hydropower Project (LEKHPP) and Tungun-Thosne Small Hydropower Project (TTSHP) have been selected. The RMR, Q and GSI values were calculated along the 20 km tunnel excavation. The simple regression statistical analysis were carried out to determine the correlation between RMR, Q and GSI.