Browsing by Author "Kale S."

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An adaptive neuro-fuzzy inference system (ANFIS) to predict of cadmium (Cd) concentrations in the filyos river, Turkey
(2018-01-01) Sonmez A.; Kale S.; Ozdemir R.; Kadak A.
Water quality is one of the main characteristics of a river system and prediction of water quality is the key factor in water resource management. Different physical, biological and chemical parameters including heavy metals can be used to assess river water quality. Evaluation of the water quality in the rivers is quite difficult and requires more time and effort because of the fact that many factors affect water quality. Traditional data processing methods are insufficient to solve this problem. Therefore, in this study, an adaptive neuro-fuzzy inference system (ANFIS) model was developed to predict the concentrations of cadmium (Cd) in the Filyos River, Turkey. For this purpose, water samples collected at 7 sampling locations in the river during December 2014-2015 were used to develop ANFIS model. The available data set was apportioned into two separate sections for training and testing the ANFIS model. Developed models aimed to use the least parameters to estimate Cd concentration. As a result, a relatively higher correlation (R2=0.91) was found between observed and modelled Cd concentrations. The results indicated that the ANFIS model gave reasonable estimates for the concentrations of Cd with a high degree accuracy and robustness. In conclusion, this paper suggests that ANFIS methodology produce very successful findings and has the ability to predict Cd concentration in water resources. The outcomes of this research provide more information, simulation, and prediction about heavy metal concentration in natural aquatic ecosystems. Therefore, ANFIS can be used in further researches on water quality monitoring.
An assessment of the effects of climate change on annual streamflow in rivers in Western Turkey
(2018-01-01) Kale S.; Hisar O.; Sönmez A.Y.; Mutlu F.; Filho W.L.
Global warming and its impacts are known to cause serious problems in sustainability of natural resources. In this study, change-point analysis and trend analysis were applied to climatic (temperature, precipitation, evaporation) and streamflow data for Tuzla, Gediz and Büyük Menderes rivers. Box-Jenkins technique and ARIMA model were used for trend analysis. Results showed that there were decreases in streamflow of all rivers. The paper suggests that climate change effects on streamflow could be changeable and that many factors (anthropogenic effects, geographical location, agricultural activities) should be considered. Management strategies specified regionally are required to mitigate the potential climate change effects.
Climate change effects on annual streamflow of filyos river (Turkey)
(2020-06-01) Sönmez A.Y.; Kale S.
The main purpose of this study was to estimate possible climate change effects on the annual streamflow of Filyos River (Turkey). Data for annual streamflow and climatic parameters were obtained from streamflow gauging stations on the river and Bartın, Karabük, Zonguldak meteorological observation stations. Time series analysis was performed on 46 years of annual streamflow data and 57 years of annual mean climatic data from three monitoring stations to understand the trends. Pettitt change-point analysis was applied to determine the change time and trend analysis was performed to forecast trends. To reveal the relationship between climatic parameters and streamflow, correlation tests, namely, Spearman’s rho and Kendall’s tau were applied. The results of Pettitt change-point analysis pointed to 2000 as the change year for streamflow. Change years for temperature and precipitation were detected as 1997 and 2000, respectively. Trend analysis results indicated decreasing trends in the streamflow and precipitation, and increasing trend in temperature. These changes were found statistically significant for streamflow ( p < 0.05) and temperature ( p < 0.01). Also, a statistically significant ( p < 0.05) correlation was found between streamflow and precipitation. In conclusion, decreasing precipitation and increasing temperature as a result of climate change initiated a decrease in the river streamflow.
Trend analysis and forecasting of the Gökırmak River streamflow (Turkey)
(2020-09-01) Arslan G.; Kale S.; Sönmez A.Y.
The objective of this paper is to determine the trend and to estimate the streamflow of the Gökırmak River. The possible trend of the streamflow was forecasted using an autoregressive integrated moving average (ARIMA) model. Time series and trend analyses were performed using monthly streamflow data for the period between 1999 and 2014. Pettitt's change point analysis was employed to detect the time of change for historical streamflow time series. Kendall's tau and Spearman's rho tests were also conducted. The results of the change point analysis determined the change point as 2008. The time series analysis showed that the streamflow of the river had a decreasing trend from the past to the present. Results of the trend analysis forecasted a decreasing trend for the streamflow in the future. The decreasing trend in the streamflow may be related to climate change. This paper provides preliminary knowledge of the streamflow trend for the Gökırmak River.