Civil Engineering / İnşaat Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/13
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Article Citation - WoS: 35Citation - Scopus: 38Historical Trends Associated With Annual Temperature and Precipitation in Aegean Turkey, Where Are We Heading?(MDPI, 2022) Mersin, Demirhan; Tayfur, Gökmen; Vaheddoost, Babak; Safari, Mir Jafar SadeghThe trend analysis of annual temperature (daily average) and total precipitation has been conducted for 14 stations located in the Aegean Region, Turkey. The Sen, Spearman’s rho, and Mann-Kendall test methods are used in the detection of the historical trends in the region. The Pettitt test is also implemented to find the significance of the trend, while the Theil-Sen approach is applied to detect the change point(s) in the time series. Findings of the following study indicate that both precipitation and temperature time series in the selected stations depict statistically significant trends with increasing nature. The rate of increase in precipitation and temperature by the Theil-Sen test is found to be 4.2–7.9 mm/year and 0.20–0.35 °C/decade, respectively. It is also found that the turn points of the temperature trends determined by the Pettitt test occurred in 1998 for all the stations. According to the results, the magnitude of the extreme events would change in the future, which may help in conceptualizing the framework and the resilience of the infrastructures against climate change.Article Citation - WoS: 4Citation - Scopus: 8Investigating a Suitable Empirical Model and Performing Regional Analysis for the Suspended Sediment Load Prediction in Major Rivers of the Aegean Region, Turkey(Springer Verlag, 2017) Ülke, Aslı; Tayfur, Gökmen; Özkul, SevinçThis study investigates the appropriateness of four major empirical methods [Lane and Kalinske, Einstein, Brooks, Chang—Simons—Richardson] for predicting suspended sediment loads (SSLs) in three major rivers in the Aegean Region, Turkey. The measured data from 1975 to 2005 were used to test performance of the models. It was found that Brooks method was more appropriate, among the others, for predicting suspended sediment loads from each river. The prediction results of Brooks method were further improved by the use of genetic algorithm (GA_Brooks) optimizing a fitting parameter and showing a comparable performance to those of artificial neural networks (ANNs) and neuro-fuzzy (ANFIS) models for the same rivers. GA_Brooks, ANNs, and ANFIS models can be used for predicting loads at a regional scale. The sensitivity analysis results revealed that suspended and bed material particle diameters affect suspended sediment loads significantly.