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5th Conference on Water , Climate and Environment

This study examines the trends in annual extreme short duration rainfall in the Black Sea region of Turkey using nonparametric methods. The results provide insights into the changing patterns of precipitation in the region.

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5th Conference on Water , Climate and Environment

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  1. 5thConference on Water, ClimateandEnvironment ANNUAL EXTREME SHORT DURATION RAINFALL (SDR) TRENDS IN BLACK SEA REGION OF TURKEY SERKAN ŞENOCAK, REŞAT ACAR and SELİM ŞENGÜL

  2. Introduction • Climate change is very likely to have a major impact on hydrological cycle and consequently on available water resources, flood and drought frequencies, natural ecosystems, society and the economy. It has been documented that the global average surface temperature has increased by 0.6o ± 0.2oC over the twentieth century. Precipitation is perhaps the most important component of the complex hydrologic cycle because of its impact on our daily life. Therefore, precipitation is often taken as a starting point towards the understanding of changes of the governing processes of climate.

  3. The climatic variability has been studied by many researchers in terms of precipitation trends for Turkey and Mediterranean region. This study aims to determine possible trends in the annual extreme Short Duration Rainfall (SDR) series using nonparametric methods (such as the Mann–Kendall and Sen’s T tests).

  4. Data • The area which has the highest average rainfall in a year in Turkey is the Black Sea region. Besides the yearly average expanding to the whole year and reaching 2500 mm from time to time, the maximum rate of precipitation in this region reaches very high figures. • The annual short duration rainfall (SDR) extreme data set (t = 5, 10, 15, 30 and 60 minutes) in 10 cities of Black Sea Region of Turkey were collected by the Turkish State Meteorological Service (TSMS). The spatial distributionsof the stations in the Black Sea Region are shown in Fig. 1.

  5. Figure 1. Black Sea Region in Turkey

  6. Methodology 1. Swed- Eisenhart Run test • The Swed and Eisenhart run test is a non-parametric procedure used in determining the homogeneity of a time series. The test procedure depends on the truncation of the analyzed time series at the median level, giving rise to data values greater or smaller than the median. • The Mann-Kendall test is a rank based method that has been applied widely to identify trends in hydroclimatic variables. The test is designed to detect a monotonically increasing or decreasing trend in the data rather than the occurrence of an episodic event. 2. Mann – Kendall test

  7. 3. Sen’s T test • This technique is an aligned rank method having procedures that first remove the block (season) effect from each datum, then sum the data over blocks, and finally produce a statistic from these sums. It is distribution free and not affected by seasonal fluctuations . All the trend results in this paper have been evaluated at the 5% level of significance to ensure an effective exploration of the trend characteristics within the study area

  8. Results • Annual extreme rainfall trends corresponding to 5, 10, 15, 30 and 60 minutes annual extreme precipitations observed in 10 meteorological stations of the Black Sea region in Turkey has been investigated. The purpose is to determine whether there has been an increase or decrease in the duration of each SDR. It is known that short duration rainfalls are intense precipitations and may often lead to flooding. In recent years, Turkey has suffered such examples of flooding due to SDR affecting especially city centers, which are devoid of adequate drainage systems, leading to casualties and loss of property.

  9. The Swed and Eisenhart run test non-parametric procedure was used in determining the homogeneity of the annual extreme rainfall time series. Tests indicated heterogeneity for 5 and 10 minutes in Çorum data series, while the other series was homogeneous at the 5% level of significance. The results for the Swed and Eisenharth run test are shown in Table 1.

  10. Table 1. The Swed and Eisenharth run test results.

  11. The Mann-Kendall and Sen’s estimator of the slope values of the analyzed annual extreme rainfall series are shown in Table 2. Table 2. Mann – Kendall and Sen’s Slope results for annual extreme rainfall series. * Significant at the 5 percent level , + Significant at the 10 percent level

  12. Artvin has positive trends in 5 minutes (10% level of significance) and in 10, 15, 30 and 60 minutes (5% level of significance). Çorum and Kastamonu have positive trends in 60 minutes (10% level of significance). Samsun has increase in 5, 10 and 15 minutes (5% level of significance) and in 60 minutes (10% level of significance). Trabzon has positive trends in 5 minutes (10% level of significance) and in 30 minutes (5% level of significance). Amasya, Bolu, Gümüşhane, Rize and Zonguldak have no trends. Figure 2.5 minutes duration precipitation analysis at Artvin.

  13. Discussion and Conclusion • Trend analysis of precipitation records at the 10 stations in the Black Sea region in Turkey has been carried out using annual extreme series of short duration rainfall (SDR) (t = 5, 10, 15, 30 and 60 minutes).The Swed and Eisenharth run test were carried out to time series before trend analysis. Time series of SDR were analyzed using nonparametric methods (such as the Mann–Kendall and Sen’s T tests) to determine any trend.

  14. Significantly positive trends are determined at 90% and 95% confidence levels. The application of a trend detection framework resulted in the identification of some significant trends, especially in Artvin, Çorum, Kastamonu, Samsun, and Trabzon stations for some different short duration at 5% and 10% levels of significance. Amasya, Bolu, Gümüşhane, Rize and Zonguldak have no trends. The directions of the short duration rainfall trends are upward. The conclusions are beneficial for predictions of regional climate changes. The upward trends give reason for concern with regard to climate-induced risks, for example floods because of short duration rainfalls etc.

  15. THANK YOU…

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