Analysing spatiotemporal drought patterns in Punjab Province, Pakistan, utilizing SPI and SPEI

Drought is an extreme phenomenon which occurs due to a prolonged duration of peculiarly low precipitation in a region. This can affect various sectors like agriculture, livestock, and human health among others. Countries like Pakistan which have agriculture-based economy can have severe consequences due to drought. In this study, Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) are applied to examine drought features at different time scales over Punjab Province which is the food basket for Pakistan. The drought occurrence was examined through drought frequency, concentrating on spatial and temporal scales and considering different geomorphologies. A modified Mann-Kendall test and multiple linear regression are used to examine monthly data from 12 weather stations collected between 1980 and 2020. Stations at high elevations have very variable precipitation, which can lead to periodic droughts. Surprisingly, SPEI shows more drought sensitivity than SPI. The severity of the drought has decreased recently, especially after the 1998-2002 peak period. Correlation analysis demonstrates a substantial link between SPI and SPEI at high elevation stations, with Murree displaying the strongest correlation (0.9334) on a one-month time frame, and Bahawalpur exhibiting a comparably lower correlation (0.6824). Positive trends in SPI and SPEI values are revealed by Mann-Kendall trend tests, which are most prominent at higher elevations and on the northern Punjab. On a one-month time scale, the Mianwali station has the strongest trend in SPEI (0.1497), whereas Bahawalnagar has negligible trends in both SPI (0.0214) and SPEI (0.0459). At high elevation sites, the frequency of drought is constantly high, and SPEI routinely detects greater drought at low elevations. Similar drought frequencies are shown by both indices for the northern region of Punjab. The results of a multiple linear regression model demonstrate the significant impact of meteorological variables on monthly mean precipitation, which advances our knowledge of Punjab's spatiotemporal drought dynamics and provides important information for planning for resilience and water resource management.