Assessment of Meteorological Drought using Long-Term Satellite Precipitation Estimates over Ganga River basin, India

Drought monitoring and its trend assessment has become crucial due to its aggravated impact in the era of climate change. The spatio-temporal coverage of precipitation data is constrained by sparse observing networks with little maintenance, which has been a significant barrier to effective drought monitoring. In this study, the performance and utility of three popular long-term satellite-based precipitation estimates (SPEs) were evaluated with the observed precipitation for drought monitoring. The SPEs which were considered in this study are Multi-Source Weighted-Ensemble Precipitation (MSWEP), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) and Climate Hazards group Infrared Precipitation with Stations (CHIRPS). The study was carried out for the Ganga River Basin, known for its alluvial soil providing livelihood to millions of people living in India, and among the worst water-stressed river basins in the world with substantial drought occurrences. In this region, very few studies have been conducted to assess the spatio-temporal drought using SPEs. This study aims to assess the meteorological drought using Standardized Precipitation Index (SPI) at 1-, 3-, 6-, and 12-months timescale for the period of 1983 to 2017. Based on SPI, probability of drought occurrence was estimated, and its trend was assessed using the modified Mann-Kendall test. From the results, it was observed that drought occurs frequently over the basin and its trend is increasing for the selected period. The findings also imply that MSWEP-based SPI series could be used as a substitute precipitation source for drought monitoring because it was able to capture the occurrence and attributes of drought events.