Application of hierarchical cluster analysis to spatiotemporal variability of monthly precipitation over Khyber Pakhtunkhwa, Pakistan

Tajbar, Sapna; Tajbar, Asfandiyar; Pashaie, Zahra; Khorshiddoust, Ali Mohammad; Rafiq, Lubna

doi:10.1007/s11600-023-01161-x

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Artykuł - szczegóły

Czasopismo

Acta Geophysica

2024 | Vol. 72, no. 2 | 1159--1174

Tytuł artykułu

Application of hierarchical cluster analysis to spatiotemporal variability of monthly precipitation over Khyber Pakhtunkhwa, Pakistan

Autorzy

Tajbar, Sapna , Tajbar, Asfandiyar , Pashaie, Zahra , Khorshiddoust, Ali Mohammad , Rafiq, Lubna

Wybrane pełne teksty z tego czasopisma

https://www.springer.com/journal/11600

Warianty tytułu

Języki publikacji

Abstrakty

Understanding the long-term spatiotemporal variability of precipitation at the regional scale is critical for developing flood and drought control strategies and water resource management. This study assessed the spatiotemporal variability of monthly precipitation over the Khyber Pakhtunkhwa province of Pakistan for 1998-2019 using hierarchical cluster analysis to cluster 156 Tropical Rainfall Measuring Mission grids. Statistical properties of clusters were calculated and the relationship of geographical features such as latitude, longitude, and altitude and statistical variables including standard deviation, maximum and minimum precipitation, and coefficient of variation (CV) with average precipitation was assessed. Findings showed that northeast parts received maximum precipitation while north and southern regions received less precipitation. Temporal analysis showed two clusters of rainy months (February, March, April, May, July, and August) and dry months (January, June, September, October, November, and December). The region was divided into two homogeneous precipitation regions. From January to April and November to December, cluster 1 occupied northern parts with maximum average precipitation while cluster 2 southern parts. From June to September, cluster 2 covered the northeast and southern parts with the highest average precipitation. During May, cluster 2 received the highest average precipitation in the northeast and southeast parts, whereas cluster 1 covered the northwest and southwest. In October, cluster 2 received maximum average precipitation covering the northeast. CV suggested higher temporal variability in cluster 2 (67.75-102.36)% than cluster 1 (65.82-99.55)%. Precipitation correlation showed that CV opposed the longitude and averages, whereas latitude and altitude demonstrated minimal correlations. These insights can assist decision-makers in devising suitable strategies to plan and control unexpected volumes of precipitation.

Słowa kluczowe

opady zmienność czasowo-przestrzenna hierarchiczna analiza skupień cechy geograficzne zmienne statystyczne Chajber-Pasztunchwa Pakistan

precipitation spatio-temporal variability hierarchical cluster analysis geographical features statistical variables Khyber-Pakhtunkhwa Pakistan

Wydawca

Czasopismo

Acta Geophysica

Rocznik

2024

Tom

Vol. 72, no. 2

Strony

1159--1174

Opis fizyczny

Bibliogr. 55 poz.

Twórcy

autor

Tajbar, Sapna

Department of Climatology, University of Tabriz, Tabriz, East Azerbaijan 51664, Iran, sapnatajbar@gmail.com

autor

Tajbar, Asfandiyar

Department of Electrical Engineering, International Islamic University, Islamabad, Pakistan

autor

Pashaie, Zahra

Department of Climatology, University of Tabriz, Tabriz, East Azerbaijan 51664, Iran

autor

Khorshiddoust, Ali Mohammad

Department of Climatology, University of Tabriz, Tabriz, East Azerbaijan 51664, Iran

autor

Rafiq, Lubna

Department of Geoinformatics, University of Salzburg, Salzburg, Austria

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Typ dokumentu

Bibliografia

Identyfikatory

DOI

10.1007/s11600-023-01161-x

Identyfikator YADDA

bwmeta1.element.baztech-a18b07f4-500c-4c8e-b593-0e8a14c35da0