Identifying Climate Hotspots from Spatiotemporal Variation of Exposure Indicators for Southern Agro-Climatic Zone in Gujarat State, India

Present research identified climate hotspots based on spatiotemporal trends in annual time series of eight exposure indicators which are maximum (Tmax) and minimum (Tmin) temperature, total rainfall (Rain), hot days (HD), rainy days (RD), light rain days (LRD), no rain days (NORD) and one-day extreme rainfall (Maxrain). The southern agro-climatic zone of Gujarat, India, is a heavy rainfall region with mountainous terrain in the east and a long coastline in the west. The Indian Meteorological Department (IMD) gridded dataset for temperature and rainfall of 1951–2020 time period has been used to identify significance and magnitude of trends utilizing Mann–Kendall test (MK) and Sen’s slope method (SEN), respectively. The outcomes of each grid point have been spatially distributed for the whole region in GIS environment using IDW interpolation. The results highlighted positive trends for Tmax in western parts and negative trends in eastern parts. For Tmin, significant positive trends were observed in western parts with trend magnitude up to 0.030 °C/year. The Rain indicator showed significant negative trends in the eastern parts but significant positive trends in the western parts with trend magnitudes in the range of –6.8 mm/year and 6.7 mm/year, respectively. The climate hotspots were identified using Principal Component Analysis (PCA) giving three principal components which explained about 85% of total variation. PC1 consisted of Tmax, Tmin, Rain and Maxrain indicators, PC2 included RD, LRD and NORD indicators, whereas PC3 comprised HD indicator. The composite PC map obtained from factor scores identified hotspots in north-west and south-west showing high exposure to flash floods and in the eastern parts toward water scarcity.