This document describes a study that uses a multivariate non-homogenous Hidden Markov model to analyze rainfall data over the Bhakra region of northwest India from 1984-2004. The model classifies daily rainfall into three hidden states (dry, somewhat dry/wet, wet) and examines how factors like seasonal cycle, ENSO, and IOD affect transitions between these states. The results show the seasonal cycle significantly impacts summer rainfall through emission distributions, while ENSO and IOD effects are insignificant. For winter, the region is mainly dry with some intense storm events, and transition probabilities between states are not significantly impacted by ENSO or IOD either. Understanding rainfall dynamics in this region can help water management and agriculture.