تحلیل روند و پهنه‌بندی زمانی-مکانی بارش حوضه دریاچه ارومیه و انتخاب ایستگاه‌های شاخص با روش‌های آماری چند متغیره

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانشیار، گروه آب و هواشناسی، دانشکده انسانی، دانشگاه محقق اردبیلی، اردبیل، ایران

2 دانشجوی دکتری، گروه علوم و مهندسی آب، دانشکده کشاورزی، دانشگاه تبریز، تبریز، ایران

3 دانشیار، گروه علوم و مهندسی آب، دانشکده کشاورزی، دانشگاه تبریز، تبریز، ایران

چکیده

دریاچه ارومیه به عنوان یکی از مهم­ترین دریاچه­های کشور به علت مصرف بیش از حد آب و تغییر اقلیم دارای وضعیت نامناسب زیست­محیطی شده است. بررسی تغییرات اقلیمی و نحوه توزیع بارش در این منطقه می­تواند در جهت مدیریت بهتر این حوضه آبریز به کار رود. در این مطالعه، برای پهنه­بندی نواحی بارش حوضه دریاچه ارومیه از اطلاعات 65 ایستگاه هواشناسی در دوره آماری 1395-1376 استفاده شد. برای این منظور، داده­های هر ماه استاندارد شده است و در ماتریس با ابعاد (n*m) که در آن n تعداد ایستگاه­ها (65) و m تعداد ما­ه­ها (12) است، نوشته شدند. تجزیه مؤلفه‌های اصلی (PCA) روی ماتریس داده­ها انجام شد و با توجه به معیار دارا بودن مقدار ویژه بالای یک، مؤلفه‌های اصلی انتخاب شدند. آنگاه مقادیر امتیازات مؤلفه‌های اصلی (PCS) برای مؤلفه‌های منتخب محاسبه شد. این مقادیر به­عنوان ورودی روش تجزیه خوشه­ای با روش وارد استفاده شدند. سپس جهت تعیین ایستگاه­های شاخص از روش پروکراستس استفاده شد. نتایج نشان داد که دو مؤلفه اصلی اول، 87 درصد واریانس کل داده­ها را توجیه می­کنند. براساس مؤلفه‌های منتخب، در کل حوضه، شش ناحیه بارشی متمایز تشخیص داده شد. همچنین معلوم شد که چهار ایستگاه واقع در نقاط مختلف حوضه آبریز دریاچه ارومیه شامل مهماندار، سراب، بابارود و سنته می­توانند به­عنوان ایستگاه­های شاخص در نظر گرفته شوند. این ایستگاه­ها بیش از %84 واریانس کل داده­های ایستگاه­های حوضه را در بر داشتند. آزمون روند من-کندال نشان داد که بارش در فصل پاییز دارای روند افزایشی معنی­دار می­باشد، درحالی­که بارش سالانه فقط در یکی از خوشه­ها دارای روند افزایشی معنی­دار می­باشد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Trend Analysis and Spatio-Temporal Zoning of Urmia Lake Basin Precipitation and Selection of Indicator Stations by Multivariate Statistical Methods

نویسندگان [English]

  • Behrooz Sobhani 1
  • Mohammad Isazadeh 2
  • Yaghob Dinpashoh 3
1 Associate Professor, Department of Climatology, Faculty of Humanities, University of Mohaghegh Ardabili, Ardabil, Iran
2 Ph.D. Student, Department of Water Science and Engineering, Faculty of Agriculture, University of Tabriz, Tabriz, Iran
3 Associate Professor, Department of Water Science and Engineering, Faculty of Agriculture, University of Tabriz, Tabriz, Iran
چکیده [English]

Lake Urmia, as one of the most important lakes in the country, has an inappropriate environmental condition due to excessive consumption of water and climate change. The study of climate change and rainfall distribution in this area can improve water management in this basin. In this study, the information of 65 weather stations in the period of 1997-2016 were used for precipitation zoning of Urmia lake basin. For this purpose, the data of each month were standardized and arranged in a matrix with dimensions of (n*m) in which n is the number of stations (65) and m is the number of months (12). Principal Component Analysis (PCA) was performed on data matrix and the main components were determined according to their Eigen values greater than one. Then the principal component score (PCS) values were calculated for the selected components. These values were used as inputs in the Ward cluster analysis method. Then, the Procrustes method was used to determine the index stations. The results showed that the first two main components incorporated more than 87% of the all data variances. Based on the selected components, six distinct precipitation regions were identified throughout the basin. Moreover, it was found that four stations located in different points of the Urmia lake basin namely Mehmandar, Sarab, Babaroud and Santeh can be considered as indicator stations. These stations incorporated more than 84% of the all data variances of basin stations. The Mann-Kendall trend test showed that the rainfall in the autumn season has a significant increase trend, while annual precipitation has only a significant increase trend in one of the clusters.

کلیدواژه‌ها [English]

  • Cluster Analysis
  • Mann-Kendall
  • Multivariate Methods
  • Principal component analysis
  • Urmia Lake
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