(untitled) (MAUSAM, 2024)
Region wetness variability was assessed across the Tripura state of North east India (1971 to 2016). Multiple Change point detection tests confirmed the high degree of spatiotemporal variability for the identified shifts in wetness pattern over study period. The periodicity of different wetness time-series varied between 2-128 months for the calculated SPI time scales over variable time series for the selected rain gauge stations. The periodicity pattern became more prominent with an increasing temporal domain of calculated SPI time series. Hierarchical clustering and Principle component analysis (PCA) accounted for the variability in randomness, trend and periodicity of all the SPI time series. Our present study identified the homogeneous clusters of raingauge stations suitable for real-time drought monitoring and reversible use of missing dataset on rainfall in near future across the Tripura state.