تحلیل بارش‌های روزانه هفتاد ساله شهر تبریز با استفاده از داده‌کاوی بصری

نویسندگان

1 دانشیار گروه مهندسی آب، دانشکده کشاورزی، دانشگاه تبریز

2 دانش‌آموخته کارشناسی ارشد، گروه آمار، دانشکده ریاضی، دانشگاه تبریز

3 دانشجوی کارشناسی ارشد، گروه مهندسی آب، دانشکده کشاورزی، دانشگاه تبریز

چکیده

بارش روزانه با داشتن خصوصیتی کاملاً تصادفی یکی از مؤلفه‌های اساسی چرخه آب بوده و دارای نقش مهمی در مدیریت منابع آب‌های سطحی و زیرزمینی به لحاظ کمی و کیفی است. عدم وجود داده‌های طولانی مدت و قابل اتکای بارش، شناسایی رفتار آن را پیچیده نموده است. در این مقاله سعی شده از طریق تعامل انسان و داده که با عنوان داده‌کاوی بصری یاد می‌شود، اقدام به شناسایی رفتار و الگوی بارش نمود. در این پژوهش برای شناسایی الگوهای بارش از داده‌های روزانه بارش و دمای ایستگاه سینوپتیک تبریز در بازه زمانی هفتاد و یک ساله اخیر (1400-1330) استفاده شد. نتایج به‌دست آمده حاکی از تغییر الگوی بارش‌ها در ۵ سال اخیر (1400-1396) بود. علیرغم این که در این پنج سال میزان بارش سالانه بالای میانگین 71 ساله بوده، ولی همچنان از دوره طلایی بارش در دهه 40 پایین‌تر است. نتایج نشان داد که شدت بارش‌های بهاره تبریز در دوره 1385 تا 1399 کاهش محسوسی داشته است. این در حالیست که در دهه‌های ۳۰ تا ۶۰ بارش‌های بهاره هم به لحاظ میزان بارش و هم شدت بارش بیشتر بوده، اما در دوره‌های بعدی از دهه 70 تا 90 هم از شدت بارش و هم از میزان بارش کاسته شده است. یافته‌ها نشان داد بیشتر بارش بهاره مربوط به سال 1360 به میزان mm 3/276 بوده که 26/73% از کل بارش آن سال را تشکیل می‌داد. همچنین رفتار دمایی در کل این مدت افزایش میانگین دما را نشان داد که تأییدی بر افزایش دمای کره زمین است.

کلیدواژه‌ها


عنوان مقاله [English]

Analysis of 70 Years Daily Precipitation in Tabriz Using Visual Data Mining Approach

نویسندگان [English]

  • Mohammad Taghi Sattari 1
  • Javad Vahdat 2
  • Sahar Javidan 3
1 Assoc. Prof., Dept. of Water Engineering, Faculty of Agriculture, University of Tabriz
2 M.Sc., Dept. of Statistics, Faculty of Mathematic, University of Tabriz
3 M.Sc. Student, Dept. of Water Engineering, Faculty of Agriculture, University of Tabriz
چکیده [English]

Abstract
Background and Objectives
Daily precipitation, which is completely stochastic, is one of the basic components of the water cycle and has an important role in the management of surface and ground water resources in terms of quantity and quality. Indispensable element of drought analysis and flood control research is precipitation. The efficient management of surface water resources directly depends on precipitation. The lack of long-term and reliable data has made it difficult to determine precipitation behavior. In this study, we tried to determine the behavior and pattern of precipitation through human-data interaction called visual data mining approach. One of the new approaches that focuses on the use of visualization and graphics in the analysis of complexities in data is visual data mining. Visual data mining can be thought of as a combination of two disciplines, visualization and data mining. Visual data mining is also closely related to computer graphics, multimedia systems, human-computer interaction, pattern recognition, and high-performance computing. The aim of this study is to analyze Tabriz daily precipitation data and discover the patterns in this data with the help of visual data mining approaches. Discovering these patterns and identifying rainfall behavior will help to manage floods on the one hand and droughts on the other.
Methodology
In this study, daily precipitation and temperature data of Tabriz Synoptic Station for the last seventy one years (1951-2021) were used to determine precipitation patterns. Tabriz has a generally cold climate as the center of the eastern Azerbaijan province and is surrounded by mountains. Recently, with the increase in data and software, data mining techniques have also started to attract attention. Data alone cannot mean anything. However, graphs consisting of data can give very meaningful information and messages. Visual data mining approach is an effort to bring data to life with different graphics. In this research, various softwares such as R, ArcGIS and Tableau were used for visualization. In addition, ExcelStat was used to check the accuracy of the data and for statistical tests. R statistical language was used to create the data mining structure and to display the data graphically. Then, different diagrams were drawn using the Tableau program. Finally, the drawn diagrams were evaluated and the final graphics were selected. ArcGIS software was used for spatial analysis and map drawing. Also, multiple linear regression method was used to predict precipitation amount and probability of occurrence.
 
Findings
According to the temperature histogram, the long-term average annual temperature in Tabriz varies between 12 and 13 degrees Celsius. Also, according to the precipitation histogram, precipitation over 5 mm in Tabriz varies between 10 and 20 days per year on average. The results obtained showed that there has been a change in precipitation patterns in the last 5 years (2017-2021). Although annual precipitation during these five years is above the 71-year average, it is still below the golden precipitation period (1961 to 1970). The results showed that the intensity of spring rains decreased significantly in Tabriz during the period 2006-2021. However, from 1971 to 1980 and from 2001 to 2010, it was observed that the spring rains were more in terms of both precipitation values and precipitation intensity. However, in the following periods from 2011 to 2021, both precipitation intensity and precipitation values decreased. The results showed that most of the spring precipitation in 1981 was 276.3 mm, making up 73.26% of the total precipitation for that year. According to the findings, precipitation has started to decrease in the spring season in recent periods. Decreased dry grain yield in the Azerbaijan region may be affected by decreased spring precipitation. As a result of this decrease, it is expected that the agricultural economy in the study area will be negatively affected.
Conclusion
In this study, as a first, daily precipitation in Tabriz was investigated with visualized data mining techniques. Thus, interesting findings were obtained with the help of different graphics. The results showed an increase in precipitation in the last 5-6 years. It has also been proven that the temperature behavior during this period shows an increase in average temperature, a confirmation of the increase in global temperature. Although the results of this research showed that visualized data mining is successful in precipitation analysis, it is recommended to conduct more comprehensive studies in this field in the future.

کلیدواژه‌ها [English]

  • Daily precipitation
  • Precipitation pattern
  • Precipitation trend
  • Regression
  • Visual data mining
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