Clustering of precipitation features by a new validity index over Iran
Study region: The study domain is Iran, a climatically diverse country. Study focus: Clustering is an effective approach for climate zoning that identifies areas with similar climatic patterns. This study clusters precipitation data over Iran to identify meaningful regional patterns based on six fea...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-06-01
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| Series: | Journal of Hydrology: Regional Studies |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214581825002460 |
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| Summary: | Study region: The study domain is Iran, a climatically diverse country. Study focus: Clustering is an effective approach for climate zoning that identifies areas with similar climatic patterns. This study clusters precipitation data over Iran to identify meaningful regional patterns based on six features, including extreme indices (Rx1day, SDII, R95p, R99p, R10) and monthly average precipitation (Pmon) during 2001–2020. To determine an optimal number of clusters, this study defines a modified validity index, SVM, by refining the separation measure used in the traditional SV index. Four traditional validity indices, including DB, Gap Statistic, Silhouette, and CH, are also used to evaluate the performance of the new index. New hydrological insights for the region: Results indicate that traditional clustering indices tend to either overestimate or underestimate the optimal number of clusters, which can be due to the complex pattern of precipitation clusters with no clearly defined boundaries. However, the developed index outperforms traditional indices on clustering synthetic datasets with varying sizes and shapes, and also on the real precipitation data. Results show that seven, five, seven, four, three, and six clusters of the desired features cover precipitation zones over Iran, which is consistent with the Köppen-Geiger Classification (KGC) and previous studies. In addition, results highlight the main role of the topography, like mountains, that affect air masses and circulation in precipitation zones clustering. The developed validity index can be efficiently used for clustering other hydrometeorological variables and climatic zones, which is valuable in water resources, atmosphere, and climate studies, and hazard assessment. |
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| ISSN: | 2214-5818 |