ارزیابی مدل‌‏‎های محاسبات نرم در همگن‌بندی هیدرولوژیکی سیلاب ناحیه‌ای (مطالعه موردی: حوضه ‏آبریز کرخه)‏

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه مهندسی عمران، دانشکده مهندسی عمران و منابع زمین، دانشگاه آزاد اسلامی، واحد تهران مرکزی، تهران، ایران.

2 گروه مهندسی عمران، دانشکده مهندسی عمران و منابع زمین، دانشگاه آزاد اسلامی واحد تهران مرکزی، تهران، ایران.

10.22059/jwim.2023.354624.1054

چکیده

شناسایی گروه­‌های همگن هیدرولوژیک یکی از مباحث بنیادی هیدرولوژی در دو بعد کاربردی و تحقیقاتی است. یکی از روش­‌های معمول به‌منظور دستیابی به مناطق همگن هیدرولوژیکی برای برآورد منطقه‌­ای سیلاب، استفاده از روش­‌های خوشه­‌بندی است. در این پژوهش استفاده، ارزیابی و مقایسه روش­های آماری و روش‌های مبتنی بر هوش مصنوعی به‌منظور خوشه‌­بندی حوضه آبریز کرخه مورد بررسی قرار گرفته است. از خوشه‌بندی SOM، K-means و سلسله‌مراتبی برای منطقه موردمطالعه استفاده شد. در ادامه نیز بررسی همگنی هیدرولوژیکی مناطق به‌دست‌آمده با استفاده از روش گشتاورهای خطی و تعدیل ناهمگنی با استفاده از روش‌­های پیشنهادی توسط هاسکینگ و والیس ارزیابی شد. نتایج نشان داده که منطقه موردمطالعه قابلیت تبدیل به دو خوشه را دارد. مقادیر آماره همگنی برای خوشه‌­های اول و دوم به‌ترتیب معادل 0/33 و 0/17 محاسبه گردید که نشان‌دهنده همگنی هر یک از مناطق می‌باشد. با توجه به کوتاهی دوره آماری در برخی از ایستگاه‌­ها، نواقص آماری و قابل‌اعتمادبودن نتایج تحلیل فراوانی منطقه­ای، در برآورد سیلاب حوضه­‌های آبریز دیگر از این روش استفاده شود.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Evaluating Soft Computing Models for Hydrologically Homogenizing Regional Floods (Case study: Karkheh river basin)

نویسندگان [English]

  • SAHAR SAFARI 1
  • Mohammad Sadegh Sadeghian 2
  • hooman hajikandi 2
  • S.Sajad mehdizadeh 2
1 Water Resources Engineering and Management, Department of civil Engineering, Faculty of Civil and Earth Resources Engineering, Central Tehran branch, Islamic Azad University, Tehran, Iran.‎
2 Department of civil engineering, Faculty of civil and earth resources engineering, Central Tehran branch, Islamic Azad university, Tehran, Iran.‎
چکیده [English]

Identification of homologous hydrological groups is one of the fundamental topics in hydrology in both applied and research dimensions. One of the common methods to achieve homogeneous hydrological zones for estimating flood zones is the use of clustering methods. In this study, the using, evaluation and comparison of statistical methods and methods based on artificial intelligence for clustering Karkheh catchment have been investigated. SOM, K-meansand hierarchical clustering were used for the study area. In the following, the study of hydrological homogeneity of the obtained areas was evaluated using the linear torque method and the heterogeneity adjustment was evaluated using the methods proposed by Husking and Wallis. The results show that the study area can be converted into two clusters. The values ​​of homogeneity statistics for the first and second clusters were calculated to be 0.33 and 0.17, respectively, which indicates the homogeneity of each region. Due to the short statistical period in some stations, statistical shortcomings and the reliability of the results of regional frequency analysis, this method should be used in estimating floods in other catchments.

کلیدواژه‌ها [English]

  • Clustering
  • Flood
  • Homogeneous areas
  • Karkheh Basin
  • Self-organizing map

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مدیریت آب و آبیاری
دوره 13، شماره 3
مهر 1402
صفحه 817-835

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