Environmental dynamics of rainfall patterns: a comparative analysis of intensity-duration-frequency curves of metropolitan cities in Pakistan

Abstract

The analysis of extreme rainfall parameters, particularly rainfall intensities, plays a serious role in the protection, productivity, and resilience of hydrological systems against storms and floods. This is especially important in arid and semi-arid regions like Pakistan, where inclusive long-term rainfall data with short aggregation periods is limited. Addressing this need, the current study develops intensity-duration-frequency (IDF) curves using rainfall data from four cities across different elevations and geographical regions within Pakistan. By statistically fitting the Gumbel distribution to observed data at different durations (1 h, 6 h, 12 h, and 24 h), the study originates rainfall intensities for distinct return periods. The analysis discloses an average annual rainfall of 25.42 mm, 9.62 mm, 9.25 mm, and 28.02 mm, with standard deviations of 6.45 mm, 9.67 mm, 7.50 mm, and 11.96 mm for Lahore, Karachi, Quetta, and Peshawar, respectively, based on data from 2001 to 2022. Notably, the assessed rainfall intensities for various return periods (2, 5, 10, and 25 years) are higher in mountainous regions compared to interior and coastal regions. Additionally, the study develops empirical parameters for the IDF formula for each city through a linear regression technique, allowing the prediction of rainfall intensities based on desired return periods. Finally, contour maps for all the parameters were created, which can be used to determine IDF relationships for un-gauged locations. These outcomes underscore the vulnerability of mountainous regions to extreme rainfall events, focus the necessity for updated infrastructure and robust flood management strategies. The derived IDF curves and empirical parameters offer valuable tools for policymakers and urban planners to plan effective interventions aimed at mitigating the adverse impacts of extreme rainfall in Pakistan.