An estimation of regional and at-site quantiles of extreme winds under flood index procedure

Abstract Daily annual maximum wind speed values are among environmental events with the most catastrophic consequences for society. A comprehensive understanding of the magnitudes and frequency of extreme winds is essential for ensuring sustainably managed wind energy, planning for emergency weather situations, and designing different building structures. This study investigated regional frequency analysis of daily annual maximum winds for Baluchistan and Sindh provinces of Pakistan. We intended to find the regional frequency distribution for maximum winds and predict the returns for extreme winds events in the future. L-moments regionalization techniques along with flood index procedure were applied to maximum wind speed records of 21 stations across the study area. Only one station namely Lasbella was found to be discordant. With the help of cluster analysis, the remaining twenty stations were further divided into two homogeneous. Heterogeneity measures validate that both regions are homogenous with allotted stations. Regional quantiles for both regions are estimated through best-fit probability distribution among Generalized Normal (GNO), Generalized Logistic (GLO), Pearson Type 3 (P3), Generalized Pareto (GPA), and Generalized Extreme Value (GEV). Robustness of GLO distribution compared to GEV distribution is assessed through Monte Carlo simulations of relative bias and relative root mean square error. Findings clearly show that GLO distribution is best for the regional modeling. Furthermore, at-site quantiles are estimated by multiplying quantities of regional quantiles using the sample mean and median as scaling factors. Estimated quantiles can be helpful for future planning concerning wind energy and the codification of structural designs and policy implications.