ناحیه بندی حوضه‌های آبریز خراسان با استفاده از تحلیل خوشه‌ای هیبرید

نوع مقاله : مقاله پژوهشی

چکیده

به علت کمبود آمار و اطلاعات همیشه امکان استفاده از تحلیل فراوانی مکانی جهت تخمین چندک‌های سیلاب وجود ندارد. از آن‌جاکه استفاده از یک روش واحد برای ناحیه‌ای کردن معمولاً نتایج قابل قبولی را به دست نمی‌دهد، لذا معمولاً چندین روش منطقه‌ای به‌طور توأم مورد استفاده قرار می‌گیرد. در این مطالعه سه الگوریتم خوشه‌ای هیبرید که هر یک به طور جداگانه فرایند خوشه‌ای کردن را برای تعیین نواحی مشابه به کار می‌برند، مورد بررسی قرار گرفت. از الگوریتم‌های خوشه‌ای سلسله مراتبی متراکمی استفاده شد. الگوریتم‌های خوشه‌ای مورد استفاده شامل پیوند تکی، پیوند کامل و Ward، و الگوریتم خوشه‌ای تفکیکی شامل الگوریتم K-means است. تأثیر تحلیل خوشه‌ای هیبرید در ناحیه‌ای کردن با استفاده از آمار و اطلاعات 68 حوضه آبریز استان‌های خراسان مورد بررسی قرار گرفت. همچنین چهار شاخص آزمون خوشه‌ای شامل ضریب کوفنتیک، عرض سیلهوت متوسط، شاخص Dunn و Davies-Bouldin جهت تعیین تعداد بهینه خوشه‌ها مورد استفاده واقع گردید. تحلیل خوشه‌ای هیبرید در حداقل‌سازی تلاش لازم جهت نیل به نواحی همگن مفید و مؤثر بود. نهایتاً هیبرید الگوریتم Ward و  K-means برای استفاده در ناحیه‌ای کردن پیشنهاد گردید. چهار ناحیه همگن تشخیص داده شد.

کلیدواژه‌ها


عنوان مقاله [English]

Regionalization of Khorasan Watersheds by Hybrid-Cluster Analysis

چکیده [English]

Because of the scarcity of flood data, it is not always possible to use at-site frequency analysis for flood quantiles estimations. No single procedure has a global acceptance in regionalization. In this paper, three hybrid-clustering algorithms are investigated. Each of these algorithms use the partitional clustering procedure to identify groups of similar catchments by refining the clusters derived from agglomerative hierarchical clustering algorithms. Their effectiveness in regionalization are then compared. The hierarchical clustering algorithms used are single linkage, complete linkage, and Ward’s algorithms. The partitional clustering algorithm used is the K-means algorithm. The effectiveness of the hybrid-cluster analysis in regionalization is investigated using data from 68 watersheds in former Khorasan Province, IRAN (now separated as three Provinces). Further, four cluster validity indices, namely cophenetic correlation coefficient, average silhouette width, Dunn’s index, and Davies–Bouldin index are tested to determine their effectiveness in identifying optimal partition provided by the clustering algorithms. The hybrid-cluster analysis is found to be useful in minimizing the effort needed to identify homogeneous regions. The hybrid of Ward’s and K-means algorithms is recommended for use. Four homogeneous zones were detected.

کلیدواژه‌ها [English]

  • regionalization
  • flood frequency analysis
  • L-moments
  • Cluster analysis
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