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ارزیابی و تحلیل آماری عوامل مورد استفاده در تحلیل منطقه‌ای سیلاب و روش‌های همگنی حوزه‌های آبخیز در ایران

نوع مقاله : مقاله پژوهشی

نویسندگان

استادیار، پژوهشکده حفاظت خاک و آبخیزداری، سازمان تحقیقات، آموزش و ترویج کشاورزی، تهران، ایران

چکیده

تحلیل فراوانی منطقه‌ای سیلاب ابزار توانمندی در برآورد و تحلیل جریان سیل درحوزه‌های آبخیز می‌باشد. در این پژوهش، روش‌های مختلف تحلیل منطقه‌ای سیلاب و همگن‌بندی هیدرولوژیکی حوضه‌ها  که در کشور انجام شده، بررسی شده است. در میان روش‌های متعدد تعیین همگنی زیرحوضه‌­ها، روش تحلیل خوشه‌ای به‌دلیل قابلیت استفاده از تحلیل عاملی برای انتخاب مهمترین عوامل موثر، سادگی امکان لحاظ کردن عوامل متنوع، استقلال پارامترهای موثر، دقت در تفکیک گروه‌های همگن و مزیت استفاده از توابع تشخیص، مناسب­‌ترین روش است. روش رگرسیون چند متغیره به‌ویژه آنجا که همگنی حوزه‌های آبخیز با دقت لازم تعیین شده باشند، کارایی مناسبی در تحلیل منطقه‌ای سیلاب از خود نشان داده است. روش گشتاورهای خطی به­علت دارا بودن دو ویژگی وجود و یکتایی، از کارایی خوبی در تخمین پارامترها و انتخاب توزیع­های مناسب آماری برخوردار می­‌باشد. به­‌نحوی­‌که در تحلیل فراوانی منطقه‌­ای سیلاب به­‌ویژه در شرایط مواجه با کمبود آماری یا طول دوره کم و داده­های دارای اریب، روش گشتاور خطی نسبت به سایر روش­‌ها عملکرد بهتری دارد. نتایج بررسی و تحلیل نتایج مربوط به روش مدل­های سامانه­های هوشمند نظیر شبکه­های عصبی مصنوعی (ANNS) و منطق فازی، نشان­‌دهنده قابلیت بالا در ایجاد برقراری روابط غیرخطی بین متغیرهای ورودی چندگانه می‌­باشد. نتایج بررسی عوامل مختلف مورد استفاده در روش‌­های تحلیل منطقه­‌ای نشان داد که عوامل فیزیوگرافی بیشترین درصد (72.11) و بعد از آن عوامل اقلیمی با 17.69 و پارامترهای پوشش زمینی با 7.48 درصد مورد استفاده قرار گرفته‌اند. همچنین، کمینه مشارکت مربوط به عامل هیدرولوژیکی با 2.72 درصد است. از میان پارامترهای فیزیوگرافی، عامل مساحت حوضه با 30.19‌ درصد مشارکت، بیشترین تأثیرگذاری را در تحلیل منطقه‌­ای سیلاب داشته است. از میان عوامل اقلیمی، بیشترین درصد کاربرد مربوط به عامل متوسط بارندگی سالیانه با 73.08 درصد به­‌دست آمد.

کلیدواژه‌ها

عنوان مقاله [English]

Statistical evaluation and analysis of methods used in regional flood analysis and homogeneity of watersheds in Iran

نویسندگان [English]

  • Alireza Eslami
  • Rahim Kazemi

Assistant Professor, Soil Conservation and Watershed Management Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran

چکیده [English]

Regional flood frequency analysis is a powerful tool for estimating and analyzing flood flow in watersheds. In this research, different methods of regional flood analysis and hydrological homogeneity of catchments that has been done in the country has been investigated. Among the many methods for determining the homogeneity of sub-catchments, cluster analysis due to the ability of factor analysis to select the most important factors, simplicity of considering various factors, independence of effective factors, accuracy of separation of homogeneous groups, and advantage of using proper diagnostic functions, was the most appropriate method. Multivariate regression method, especially when the homogeneity of catchments have been accurately determined, has shown good performance in regional flood analysis. L-moment method, due to uniqueness and existence has good performance in estimating parameters and selecting appropriate statistical distributions. So that in the regional flood frequency analysis, the L-moment method performs better than other methods, particularly in the case of shortage and skewed data. The analysis of the intelligent models such as artificial neural networks (ANNs) and fuzzy logic, showed the high ability to establish nonlinear relationships between multiple input variables. The results of the Investigation of different factors used in regional analysis methods showed that Physiographic factors were highest (72.11%) followed by climatic factors (17.69%) and land cover parameters (7.48%). Also, the lowest contribution was related to hydrological factor with 2.72%. Among the physiographic parameters, the area factor with 30.19% of the contribution had the most influence on the regional flood analysis. Among the climatic factors, the highest application was related to the average annual rainfall factor with 73.08% contribution.

کلیدواژه‌ها [English]

  • Cluster analysis
  • Hybrid
  • L-Moment
  • Multiple regressions
  • Neural network
  • Regional flood analysis
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مهندسی و مدیریت آبخیز
دوره 12، شماره 4
دی 1399
صفحه 1009-1023
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