Determination of precipitation trend by time series: A case study Erbaa plain
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Abstract
Changes in precipitation occur due to global or local climate changes. Studying this change is very important for human life. Rainfall is very important in meeting essential needs such as agricultural activities and clean water resources. Therefore, trend analysis in precipitation data is important. In this study, in order to examine whether there is a trend in the precipitation data of Erbaa Plain (Turkey), first homogeneity test was performed and then the standard precipitation index was calculated. The calculated data were analyzed using the Mann-Kendall test and Sen's Slope test. Monthly precipitation data for 40 years covering the years 1981-2020 were used in the study. Precipitation data were analyzed according to 90% confidence interval. Trends were detected in January and September in monthly precipitation series
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Alexandersson, H. (1986). A Homogeneity test applied to precipitation data. Journal of Climatology, 6(6), 661-675.
Basara, A. C., Tabar, M. E., & Sisman, Y. (2021). Landslide susceptibility mapping of Samsun (Turkey) province using frequency ratio and AHP methods. Turkish Journal of Geographic Information Systems, 3(1), 24-30.
Beden, N., Demir, V., & Keskin, A. Ü. (2020). Trend Analysis of SPI and PNI drought indices in Samsun City. Dokuz Eylul University Faculty of Engineering Journal of Science and Engineering (DEUFMD), 22(64), 107-116.
Besel, C., Tanir Kayıkçı, E. (2019). The effect of serial correlation on nonparametric trend determination at zenith total delay time series. Gümüşhane University Journal of Science and Technology Institute, 9 (1), 180-188.
Coskun, M. (2019). Earth Science. Pegem Academy.
Gençer, M., Uğurlu, A., Kaçar, M., Özcan, H., Kesim, A., & Aydın, B (2005). Hydrometeorology. MGM.
Gilbert, R. O. (1987). Statistical methods for environmental pollution monitoring. Van Nostrand Reinhold Company.
Gunes, O. E., Basara. A. C., & Sisman, Y. (2021). Trend analysis of precipitation data using mann kendall and sen’s slope test. 2nd Intercontinental Geoinformation Days (IGD), Mersin, Turkey, 202-205.
Kendall, M. G. (1975). rank correlation methods. Charles Griffin.
Mann, H. B. (1945). Non-parametric test against trend. Econometrika, 13, 245-259.
Mckee, T. B., Doesken, N. J., & Kleist, J. (1993). The relationship of drought frequency and duration to time scales. Eighth Conference on Applied Climatology, Anaheim, California, 179–184.
Mercan, Y. (2016). The relationship between the meteorological parameters and air pollution, and the deaths and emergency department admissions because of cardiovascular diseases and respiratory diseases in Kirklareli in 2010-2014 (Publication No. 448886) [Doctoral Thesis, Istanbul University]. YÖK National Thesis Center.
Özdel , M. M. (2020). Trend analysis of temperature and precipitation parameters in Diyarbakir basin (Publication No. 645267) [Master's Thesis, Nevşehir Hacı Bektaş Veli University]. YÖK National Thesis Center.
Sarıyer, G. (2018). Time series modelling for forecasting demand in the emergency. International Journal of Engineering Research and Development, 10(1), 66- 77.
Sen, P. K. (1968). Estimates of the regression coefficient based on Kendall’s Tau. Journal of the American Statistical Association, 63, 1379–1389.
Sfetsos, A. (2000). A comparison of various forecasting techniques applied to mean hourly wind speed time series. Renewable Energy, 21(1), 23-35.
Yavuz, M. (2012). The effect of exports on economic growth in Turkey: A time series analysis. Ege University 15th Economics Students Congress, Izmır, Turkey.
Yu, Y. S., Zou, S., & Whittemore, D. (1993). Non-parametric trend analysis of water quality data of rivers in Kansas. Journal of Hydrology, 150: 61-80.