PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Powiadomienia systemowe
  • Sesja wygasła!
  • Sesja wygasła!
Tytuł artykułu

Analysis of temperature data by using innovative polygon trend analysis and trend polygon star concept methods: a case study for Susurluk Basin, Turkey

Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Climate change is an event that has significant effects as direct or indirect on ecosystem and living things. In order to be prepared for the effect of climate change, it is necessary to anticipate these changes and take measures for this change. Therefore, many studies have been carried out on changes in climate parameters in recent years. The most common method used in these studies is trend methods. Innovative Polygon Trend Analysis (IPTA) and Trend Polygon Star Concept are trend analysis methods. IPTA Method divides data series into two as first and second data set and analyzes these two data sets by comparing them with each other. Trend Polygon Star Concept analyzes distance between two months in data set in graph, which is result of IPTA, and shows analysis result by dividing it into four regions. Therefore, in this study, monthly average temperature data are analyzed by using this two-polygon method. This data set is for 22 years (1996–2017). Polygon graphics were created as a result of study. Besides, trend slopes and lengths of temperature data with IPTA Method were calculated. The values of graphs created with Trend Polygon Star Concept Method on x- and y-axis were given in a table. When the results of both analysis methods were examined for a station, the following results were observed. For example, a regular polygon was not seen in arithmetic mean and standard deviation graphs of IPTA Method of Bandirma Station. Besides, when general evaluation of arithmetic mean analysis results was examined an increasing trend in most months. When arithmetic average graph created by Trend Polygon Star Concept Method of Bandirma Station was examined, transition between two months was seen first and third region. When standard deviation graph was examined, transitions between two months were seen in all four regions.
Czasopismo
Rocznik
Strony
1949--1961
Opis fizyczny
Bibliogr. 29 poz.
Twórcy
  • Department of Civil Engineering, Faculty of Technology, Sakarya University of Applied Sciences, Sakarya, Turkey
  • Department of Civil Engineering, Faculty of Technology, Sakarya University of Applied Sciences, Sakarya, Turkey
autor
  • Key Laboratory of Mountain Surface Process and Ecological Regulations, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, China
  • University of Chinese Academy of Sciences (UCAS), Beijing, China
Bibliografia
  • 1. Aksay CS, Ketenoglu O, Kurt L (2005) Global warming and climatic change. Selcuk Univ J Sci Faculty 1:29–42
  • 2. Aktas B (2020) Possible changes in some climate parameters and climate types in Konya depending on global warming. Kastamonu University. Institute of Science. Department of Sustainable Agriculture and Natural Plant Resources. Kastamonu. Turkey.
  • 3. Altunay A (2016) Investigation of climatological data in Turkey by Mann-Kendall-Sen Trend method. Canakkale On Sekiz Mart University. Institute of Social Sciences. Department of Geography. Canakkale. Turkey.
  • 4. Ceribasi G (2018) Analysis of meteorological and hydrological data of iznik lake basin by using innovative sen method. J of Env Prot and Eco 19:15–24
  • 5. Ceribasi G (2019) Analyzing rainfall datas’ of eastern black sea basin by using sen method and trend methods. J of the Ins of Sci and Tech 9:254–264
  • 6. Ceribasi G, Ceyhunlu AI (2020) Analysis of total monthly precipitation of Susurluk Basin in Turkey using innovative polygon trend analysis method. Journal of Water and Climate Change. (In Press).
  • 7. Coban E (2013) Investigation into the effects of climate change on trends of precipitation in Turkey. Suleyman Demirel University. Institute of Science. Department of Civil Engineering. Isparta, Turkey
  • 8. Dabanli I, Sen Z, Yelegen MO, Sisman E, Selek B, Guclu YS (2016) Trend assessment by the innovative-Şen method. Water Resour Manage 30:5193–5203
  • 9. Demircan M, Demir O, Atay H, Eskioglu O, Yazici B, Gurkan H, Tuvan A, Akcakaya A (2014) Climate change projections in Turkey’s river basin with new scenarios. TUCAUM - VIII. Geography Symposium. Ankara. Turkey.
  • 10. Guclu YS (2018) Fundamentals and applications of comparative innovative trend analysis. J Nat Hazards Environ 4:182–191
  • 11. Gungor S (2020) Comparison of Some Morphological Features of Squalius Species in the North Aegean, Susurluk and Gediz Basins. Eskisehir Osmangazi University. Institute of Science. Department of Biology. Eskisehir, Turkey
  • 12. Han J, Singh VP (2020) Forecasting of droughts and tree mortality under global warming: a review of causative mechanisms and modeling methods. J Water Clim Change 11:600–632
  • 13. Jones JR, Schwartz JS, Ellis KN, Hathaway JM, Jawdy CM (2015) Temporal variability of precipitation in the Upper Tennessee Valley. J Hydrol Reg Stud 3:125–138
  • 14. Karmeshu N (2012) Trend detection in annual temperature & precipitation using the Mann Kendall test – a case study to assess climate change on select states in the northeastern United States. University of Pennsylvania. Department of Earth and Environmental Science. Pennsylvania, USA
  • 15. Li T, Zhou Z, Fu Q, Liu D, Li M, Hou R, Pei W, Li L (2020) Analysis of precipitation changes and its possible reasons in Songhua River Basin of China. J Water Clim Change 11:839–864
  • 16. Nikakhtar M, Rahmati SH, Bavani ARM (2020) Impact of climate change on the future quality of surface waters: case study of the Ardak River, northeast of Iran. J Water Clim Change 11:685–702
  • 17. Ozkoca T (2015) Trend analysis of hydrometeorological parameters at middle Blacksea region coast band. Ondokuz Mayis University. Institute of Science. Department of Civil Engineering. Samsun, Turkey
  • 18. Saris F, Hannah DM, Eastwood WJ (2010) Spatial variability of precipitation regimes over Turkey. Hydrol Sci J –j Des Sci Hydrol 55:234–249
  • 19. Sen Z (2021) Conceptual monthly trend polygon methodology and climate change assessments. Hydrol Sci J 66:503–512
  • 20. Sen Z, Sisman E, Dabanli I (2019) Innovative polygon trend analysis (IPTA) and applications. J of Hydro 575:202–210
  • 21. Sezen C (2018) Effects of global atmospheric indexes on temperature and precipitation data in Turkey. Ondokuz Mayis University. Institute of Science. Department of Civil Engineering. Samsun, Turkey
  • 22. Tabari H, Taye MT, Onyutha C, Willems P (2017) Decadal analysis of river flow extremes using quantile-based approaches. Water Resour Manage 31:3371–3387
  • 23. Tokgoz S, Partal T (2020) Trend analysis with innovative sen and mann-kendall methods of annual precipitation and temperature data in the black sea region. J Inst Sci Technol 10:1107–1118
  • 24. Topuz M, Feidas H, Karabulut M (2021) Trend analysis of precipitation data in Turkey and relations to atmospheric circulation: (1955–2013). Ital J Agrometeorol 2:91–107
  • 25. Turkes M, Sümer UM (2004) Spatial and temporal patterns of trends and variability in diurnal temperature ranges of Turkey. Theoret Appl Climatol 77:195–227
  • 26. Yang XL, Xu LR, Liu KK, Li CH (2012) Trends in temperature and precipitation in the Zhangweinan river basin during the last 53 years. Procedia Environ Sci 13:1966–1974
  • 27. Yildirim A (2015) Trend analysis methods: Middle Firat region application. Istanbul Technical University. Institute of Energy. Department of Energy Science and Technology. Istanbul. Turkey.
  • 28. Zeybekoglu U, Partal T (2018) Evaluated of monthly total annual mean and rainfall intensity series of standard duration of sinop by different trend analysis methods. Clim Change Environ 3:1–8
  • 29. Zhang A, Zheng C, Wang S, Yao Y (2015) Analysis of streamflow variations in the Heihe River Basin, northwest China: trends, abrupt changes, driving factors and ecological influences. J Hydrol Reg Stud 3:106–124
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-230644e1-439d-4966-93e3-46eb4db3e6d5
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.