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1532 © 2021 The Authors Journal of Water and Climate Change | 12.5 | 2021 Analysis of total monthly precipitation of Susurluk Basin in Turkey using innovative polygon trend analysis method Gokmen Ceribasi and Ahmet Iyad Ceyhunlu ABSTRACT The effects of climate change caused by global warming can be seen in changes of climate variables Gokmen Ceribasi (corresponding author) Ahmet Iyad Ceyhunlu such as precipitation, humidity, and temperatures. These effects of global climate change can be Faculty of Technology, Department of Civil Engineering, interpreted as a result of the examination of meteorological parameters. One of the most effective Sakarya University of Applied Sciences, methods to investigate these effects is trend analysis. The Innovative Polygon Trend Analysis (IPTA) Sakarya, Turkey method is a trend analysis method that has emerged in recent years. The distinctive features of this E-mail: [email protected] method compared with other trend methods are that it depends on time series and can compare data series among themselves. Therefore, in this study, the IPTA method was applied to total monthly precipitation data of Susurluk Basin, one of Turkey’s important basins. Data from ten precipitation observation stations in Susurluk Basin were used. Data were provided by the General Directorate of State Meteorology Affairs. The length of this data series was 12 years (2006–2017). As a result of the study, since there is no regular polygon in IPTA graphics of each station, it is seen that precipitation data varies by years. While this change is seen increasingly at some stations, it is seen decreasingly at other stations. Key words | Innovative Polygon Trend Analysis (IPTA), precipitation, Susurluk Basin, Turkey HIGHLIGHTS • Application Innovative Polygon Trend Analysis Method is for Susurluk Basin in Turkey. • Polygon trend analysis statistical values are derived. • Trend Length and Trend Slope components are identified. • The impact of climate change was investigated using innovative Polygon Trend Analysis Method. INTRODUCTION While climate is defined as the average of long-term weather examination of physical parameters (such as meteorological, events of a region, global climate change is defined as oceanographic, or geophysical parameters) (Mohorji et al. changes occurring in climate elements. The effects of ; Wu & Qian ; Ceribasi ). climate change caused by global warming are seen on par- Climate change resulting from global warming shows its ameters such as precipitation, humidity, air movements, effect in almost every region of the world. The impact of this sea surface temperatures, and air temperatures. These effects climate change occurs as water scarcity in some regions, and of global climate change can be interpreted as a result of the it occurs as floods in some regions. People experience great difficulties from both effects. Therefore, studies on the issue This is an Open Access article distributed under the terms of the Creative of climate change have been increasing recently. In particu- Commons Attribution Licence (CC BY 4.0), which permits copying, adaptation and redistribution, provided the original work is properly cited lar, it is seen that studies performed as forward-prediction (http://creativecommons.org/licenses/by/4.0/). models are increasing. However, data used in these studies doi: 10.2166/wcc.2020.253 Downloaded from http://iwaponline.com/jwcc/article-pdf/12/5/1532/923246/jwc0121532.pdf by guest on 28 September 2021 1533 G. Ceribasi & A. I. Ceyhunlu | Innovative polygon trend analysis method Journal of Water and Climate Change | 12.5 | 2021 do not establish an approach in transition between days, most common of these methodologies are trend analysis weeks, months, and years. In this context, the Innovative tests such as the Mann–Kendall test, Mann–Kendall Rank Polygon Trend Analysis (IPTA) method establishes an Correlation test, Trend Slope test, and Innovative Trend approach in transition between days, weeks, months, and Analysis (Mann ; Sen , ; Kendall ). These years. Hence, it is seen that the IPTA method will be used methods have been applied frequently by many researchers frequently in academic studies (Sen et al. ). (Bocheva et al. ; Wilson et al. ; Reihan et al. ; The mean and standard deviation changes in hydro- Jones et al. ; Zhang et al. ; Ceribasi & Dogan ; meteorological variables are very important in different Dabanli et al. ; Tabari et al. ; Almazroui et al. human activities such as water supply, hydroelectric power ; Ceribasi , ; Dabanli & Sen ; Han & generation, agricultural activities, and irrigation practices. Singh ; Li et al. ; Nikakhtar et al. ). In addition, In literature, there are various methodologies for assessment Alexander et al. () calculated and analyzed a series of of time series trend component and variability changes. The climate change indices derived from daily temperature and Figure 1 | Location of Susurluk Basin and stations on map of Turkey’s basins. Table 1 | Information of observation stations Location No. Station name Station No. Latitude Longitude Altitude (m) 1 Bandirma 17,114 4019053.4″N2759047.4″E 20.00 2 Erdek 17,635 40230.9″N27470.6″E 180.00 3 Karacabey 17,673 40070.8″N28190.2″E 15.00 4 Uludag 17,676 4006027.0″N29070.4″E 2,543.00 5 Keles 17,695 3954054.0″N29130.7″E 1,240.00 6 Manyas 17,699 4002049.6″N27580.3″E 50.00 7 Dursunbey 17,700 3934040.1″N28370.9″E 672.00 8 Susurluk 17,705 3955002.3″N2809052.9″E 63.00 9 Simav 17,748 3905033.0″N28580.0″E 830.00 10 Mustafa Kemalpasa 17,675 40020.0″N2823058.2″E 60.00 Downloaded from http://iwaponline.com/jwcc/article-pdf/12/5/1532/923246/jwc0121532.pdf by guest on 28 September 2021 1534 G. Ceribasi & A. I. Ceyhunlu | Innovative polygon trend analysis method Journal of Water and Climate Change | 12.5 | 2021 precipitation data, focusing on extreme events. As a result, and that there would be a tendency towards more rainy con- differences in temperature index distributions showed that ditions throughout the 20th century (Alexander et al. ). they would be particularly prominent between the last two Niu et al. () analyzed air temperature from 1961 to 2014 periods and for indices related to minimum temperature in the Yellow and Yangtze river basins and made a Figure 2 | Course line of total monthly precipitation data of stations in Susurluk Basin. Downloaded from http://iwaponline.com/jwcc/article-pdf/12/5/1532/923246/jwc0121532.pdf by guest on 28 September 2021 1535 G. Ceribasi & A. I. Ceyhunlu | Innovative polygon trend analysis method Journal of Water and Climate Change | 12.5 | 2021 comparison using 16 temperature indices provided by Mustafakemalpasa Stream, Simav Stream, and Koca ETCCDI and using a series of high-density observations Stream. Annual water potential is 6.08 × 109 m3. Uluabat from 300 weather stations. Sen et al. () proposed the and Manyas Lakes are located in this basin. Susurluk IPTA method in their study. They analyzed the three Basin is located in the south of the Marmara region and hydro-meteorological data sets from different parts (rainfall includes some of Bursa, Balıkesir, Kutahya, Bilecik, Canak- and stream New Jersey (USA), Danube River (Romania) kale, Manisa, and Izmir provinces (Dorum et al. ; Bulut and Goksu River (Turkey)) of the world. While these trend & Saler ; Albayrak et al. ). The location of Susurluk analysis tests are applied, there may be a linear relationship Basin and stations selected for this study are shown in and a nonlinear (stochastic) relationship between hydro- Figure 1. meteorological data and time. Total monthly precipitation data for the region used in The purpose of trend analysis tests is to make future this study was taken from the General Directorate of State predictions about objective, quantitative, and systematic Meteorology Affairs (DMI). Information from stations used detection, identification, and prediction mechanisms of in the study is given in Table 1. linear or nonlinear data over time. For this reason, trend The course line of total monthly precipitation data of the analysis is widely applied in many fields, especially in the observation stations (Bandirma, Erdek, Karacabey, Uludag, field of engineering. Furthermore, it is observed that it is Keles, Manyas, Dursunbey, Susurluk, Simav, and Mustafa widely used in climate change research arising from global Kemalpasa) in Susurluk Basin are given in Figure 2. The warming (Sen et al. ). length of this data series is 12 years (2006–2017). The IPTA method is a new trend test and it is the newest trend analysis method in recent years. The purpose of this method is to establish a relationship between available IPTA method data. Other trend methods show weakness in this area since they do not establish an approach in seasonal tran- The IPTA method was obtained by the development of the sitions. Since the IPTA method establishes an approach in Innovation Trend Analysis method, which was introduced seasonal transitions, it will be preferable to other trend by Sen in the years 2012, 2014, and 2017 (Sen , , tests. Therefore, in this study, the IPTA method will be a, b; Sen et al. ). In this method, time scales of applied to total monthly precipitation data of Susurluk Basin, one of Turkey’s important basins. The reason for choosing Susurluk Basin in this study is that it is a basin with high population density and industry. Therefore, it is important to analyze this region in terms of climate change. Data from ten precipitation observation stations in Susurluk Basin are used. Data are provided by the General Directorate of State Meteorology Affairs. The length of this data series is 12 years (2006–2017). MATERIALS AND METHODS Study area Susurluk Basin is one of Turkey’s most important basins. The basin has a total precipitation area of 24,332 km2. Important streams of the basin are Nilufer Stream, Figure 3 | Hypothetical Innovative Polygon Trend Analysis template for monthly records.

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