Centennial Scale Spatio-Temporal Analysis of Meteorological Drought in the State of Himachal Pradesh Using Standardised Precipitation Index and Copula-Based Return Period

Abstract

The heavy reliance on agriculture, horticulture and forests in Himachal Pradesh underscores the need to understand the dynamics of dry conditions and meteorological droughts in the region. Meteorological droughts, marked by prolonged low precipitation, are especially critical in mountainous regions like Himachal Pradesh, affecting soil moisture, runoff and water availability, often leading to other drought types. Despite existing precipitation trend analyses, the region remains underexplored in terms of the frequency, duration, severity, return period and elevation-dependent variation of dry conditions and meteorological droughts. The present study fills these gaps by utilising the widely used gridded (0.25° × 0.25°) India Meteorological Department (IMD) rainfall data to understand centennial-scale drought spatial characteristics across the varying altitude region of Himachal Pradesh. The Standardised Precipitation Index (SPI) is utilised to identify drought events, while ‘Run Theory’ is applied to analyse their characteristics across various time scales. Droughts were categorised as moderate, very dry and extreme based on SPI values, and their duration, severity and frequency were subsequently calculated for each category. The average drought duration in the state at the SPI-12 time scale was 6.5 months, and Kangra, Chamba, Lahaul and Spiti at the same time scale have witnessed more prolonged droughts at this time scale. Comparatively, more severe droughts have occurred in parts of Kangra, Chamba, Mandi, Kullu and Sirmaur districts (SPI-12), and the average severity at the same time scale was found to be 4.02. The influence of topography on drought frequency and future drought risk was also evaluated. Results revealed that the number of droughts decreased as we moved from a time scale of 1–48 months, but the maximum and average duration kept on increasing. The correlation coefficient (ρ) of moderate and extreme drought frequency with elevation at SPI-12 was estimated to be 0.11 and −0.33, respectively. The correlation analysis revealed that lower elevations experience more frequent extreme droughts as compared to higher elevations, whereas higher elevations experience more frequent moderate droughts. Similarly, elevation-dependent variation was observed for maximum drought duration, average drought duration and maximum drought severity, showing a negative correlation with elevation. However, the average duration of droughts showed an inconsistent correlation with elevation, displaying positive correlations at certain scales and negative ones at others (ρ = −0.15, 0.18, 0.26, −0.02, 0.05 and −0.09 for SPI-1, 3, 6, 12, 24 and 48, respectively). While drought characterisation has been studied, there is a significant lack of research on future predictions of meteorological drought in the study area. The study extends beyond regional drought characterisation by addressing a gap in predicting future meteorological droughts, using probabilistic models to estimate return periods and levels for drought duration and severity in the study area. The results indicate that, at the SPI-12 time scale, the average return levels for drought duration were estimated at 7.83, 12.35, 18.01, 27.56 and 36.64 months, while those for drought severity were 0.57, 3.02, 7.17, 14.70, 33.23 and 57.58 for return periods of 2, 5, 10, 20, 50 and 100 years, respectively. For shorter return periods (like 2 and 5 years), all the districts are expected to encounter comparable return levels of drought duration and severity. However, at longer return periods (10 years and longer), large variations have been observed for both duration and severity return levels, according to which Hamirpur district has been observed to experience the longest and most severe droughts in the state (at SPI-12). Minimum return levels for the same have been envisaged for the district of Kullu. As meteorological droughts can impact soil moisture, crop yields, and surface/subsurface water levels, these findings can aid policymakers in future agricultural planning and water conservation strategies. However, properly understanding drought propagation dynamics will be pivotal for bringing these future predictions to practical use.