Correlation Analysis of RMR and Q Systems in Himalaya Rock Mass Conditions: A Case Study of Seti-khola Hydropower Project, Nepal

Abstract

Rock mass classification systems such as Q, Rock Mass Rating (RMR), and Geological Strength Index (GSI) are widely applied in Himalayan tunneling to assess excavation and support requirements. This study aims to establish an empirical relationship between RMR and Q values based on 934 field observations collected from the 3.1 km-long headrace tunnel of the Seti Khola Hydropower Project (22 MW) in western Nepal. Multiple regression models—linear, logarithmic, exponential, and power—were applied to the categorical and overall dataset, and their performance was assessed using standard statistical indicators (R², MAE, RMSE, and MAPE). The logarithmic model emerged as the most suitable, revealing a moderate but meaningful correlation that better captures the non-linear scaling behavior between Q and RMR. These findings offer improved compatibility and cross-interpretability between classification systems in Himalayan geological settings.