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. 2024 Oct 29;14(1):25882.
doi: 10.1038/s41598-024-75248-w.

Regional frequency analysis of extreme wind in Pakistan using robust estimation methods

Ishfaq Ahmad  1 , Muhammad Salman  1 , Ibrahim Mufrah Almanjahie  2 , Fatimah Alshahrani  3 , Muhammad Shafeeq Ul Rehman Khan  4 , Muhammad Fawad  5 , Ehtasham Ul Haq  1
Affiliations

Regional frequency analysis of extreme wind in Pakistan using robust estimation methods

Ishfaq Ahmad et al. Sci Rep. .

Abstract

The quantile estimates of extreme wind speed are needed for various areas of interest using regional frequency analysis (RFA) and extreme value theory. These calculations are crucial for the coding of wind speed. The data was taken from the NASA official website at a 10-meter distance and measured in meters per second (m/s). RFA of annual maximum wind speed (AMWS) using L-moments is performed utilizing annual maximum wind speed data from sixteen sites (16) in Pakistan's Khyber Pakhtunkhwa province. There are no sites that are found to be discordant. The wards method is used to construct a homogenous region and make two homogenous regions from 16 sites. The heterogeneity test justifies that both clusters are homogeneous. The most appropriate probability distribution from the Generalized Normal (GNO), Generalized Logistic (GLO), Pearson Type-3 (P3), Generalized Pareto (GPA), and Generalized Extreme Value (GEV) distributions is chosen to calculate regional quantiles. According to the L-moments diagram and Z statistics, the GEV for Cluster- Ι and GLO for Cluster- ΙΙ are the best suggestions from the others. Both clusters' robustness is measured utilizing relative bias (RB) and relative root mean square error (RRMSE). Overall, GEV distribution is fit for cluster-Ι, and the GLO distribution is fit for cluster-ΙΙ. Utilizing the site mean and median as index parameters, we can also find at-site quantiles from regional quantiles. The study's quantile estimates can be employed in codified structural designs with policy consequences.

Keywords: Linear-moments; Monte Carlo simulation; Quantile estimates; Wind speed.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Geographical locations of the 16 stations of KPK, Pakistan. (The software ArcGIS 10.7 was used to create the map.).
Fig. 2
Fig. 2
Time series plot of annual maximum wind speeds of 16 gauging stations of Khyber Pakhtunkhwa, Pakistan.
Fig. 3
Fig. 3
Dendrogram that represents the division of 16 gauging sites into sub-groups obtained using the Wards clustering method.
Fig. 4
Fig. 4
L-moments ratio diagram for both regions.
See this image and copyright information in PMC

References

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