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The agrarian economy of Bhutan is highly vulnerable to rainfall uncertainties for its typical geographic location and rugged topography. Rainfall time series is also constrained by inadequate rain gauge stations in the country. To complement rainfall data obtained from 12 distinct satellite sources is validated against surface measurements from 12 ground stations. The rainfall obtained from Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System-Climate Data Record (PERSIANN-CCS-CDR) exhibited a strong correlation with the measured rainfall with minimal bias and error. The seasonal mean rainfall is lowest in the winter (3.62%) with high variability (89.18%) and highest in the summer (60.36%) with low variability (33.93%). Using 3- and 12-month accumulation periods, the Standardized Precipitation Index (SPI) was computed to examine the frequency of wetness and drought. In all time frames, the severity of wetness and drought are of the “moderate” type. The majority of the districts witnessed higher levels of wetness in 1987, 1988, 2012, 2015, and 2017, while severe to extreme droughts were found over varying time periods in 1984–86, 1990–93, 1996, 1999, and 2019. In general, the frequency of wetness is 1.17 and 1.33 times higher than drought during June-August and 12-month periods, respectively. A strong positive correlation was observed between the Oceanic Niño Index (ONI) of October-December and the SPI of following June-August as well as the 12-month period. Additionally, the Indian Ocean Dipole Mode Index (DMI) showed a strong positive correlation with SPI, especially during June to August. The low amplitude and rapid fluctuation of DMI implies that the impact of Indian Ocean Dipole may be more seasonal; conversely, ENSO exhibited more noticeable fluctuations on an inter-annual basis. The results also suggests a complex interplay between the East Asian and Indian summer monsoons, the Tibetan plateau, and the local orography of Bhutan, which determines the wetness and drought. A district-level Mann-Kendall test of SPI showed the trends in wetness and dryness in a spatial context. Three districts at the 12-month scales and four districts at the 3-month scale (September-November) exhibited a significant upward trend, indicating increasing wetness. On the other hand, only one district showed a significant downward trend between September and November, suggesting an increasing drought incidence. |
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