The traffic circle is a common solution which is widely used in urban and rural areas of Turkey. Although, most of the traffic circles are designed to be signal-controlled, some of them are still being used as unsignalised intersections in order to provide higher capacity and better performance particularly in rural areas. Regression analysis and gap acceptance-based models are the most used estimation methods for capacity prediction of unsignalised traffic circles. In this study, an artificial neural network model (ANN) was investigated as a new approach as ANN models have been successfully applied in various other traffic studies. The entry capacity was predicted by using exponential and multiple linear regressions, gap acceptance theory and the feed forward backpropagation algorithm type of ANN. The results were compared with well known models. The ANN model including the geometric parameters was found to be the most reliable estimator with 71·6% of proper predictions when the discrepancy percentages of the predicted versus observed entry flows were examined for the models. The multiple linear regression and gap acceptance models followed the ANN model with proper prediction proportions of 63·3 and 51·6%, respectively. On the other hand, models that included only circulating flow parameters were only found to be acceptable for limited geometric data conditions.

Drought is one of the major disasters which might have consequences like hunger and poverty. The droughts depend on many factors including climatic and regional properties, soil type, population increase and environmental degradation. The complex character of drought makes it difficult to define. Hence, various specific criteria must be defined and used for the evaluated basin, region or territory to determine drought. In this study, several drought analysis methods are performed on the Central Anatolian Region in Turkey where has survived a severe drought. In comparative analysis, Palmer Drought Severity Index (PDSI), Erinc and De Martonne methods were used. The evaluated data consist of the observed monthly mean precipitation and temperature data of 13 selected meteorology stations in the region. The observed data in between 1965–2006 periods were evaluated for all stations. Thus, the distribution of dry and wet periods is investigated at monthly time scale. The comparative results show that PDSI index ...

Although many traffic circles have been designed in Turkey, in recent years few studies have been made on the capacity and performance of roundabouts. In practice, two major problems at intersections need to be solved: traffic accidents and limited intersection capacity. With this in mind, the applicability of various capacity models for single-lane roundabouts to six selected roundabouts in Izmir, Turkey, is discussed. The results show that the HCM2000 procedure can be used as an effective tool for an initial prediction of single-lane roundabout capacity if the lower and upper boundary limits are calibrated. But, since the research was conducted with limited data, the accuracy of the results should be tested with more data sets. Further studies should be conducted to develop a more reliable capacity and performance analysis procedure, especially for Turkey.

Although traffic circles have been widely used in Turkey for many years, only a few researchers are aware of the advantages of roundabouts. In recent years, few traffic circles were designed as roundabouts in Turkey, but limited study has been made on the capacity and performance analysis of roundabouts. In this study, the applicability of the Highway Capacity Manual 2000 (HCM 2000) procedure for roundabouts in Turkey is discussed. The results show that the HCM 2000 procedure can be an important tool for an initial prediction but further studies should be made in order to develop a more reliable capacity and performance analysis procedure for Turkey.

This study attempts to extend the prevailing definition of informational entropy, where entropy relates to the amount of reduction of uncertainty or, indirectly, to the amount of information gained through measurements of a random variable. The approach adopted herein describes informational entropy not as an absolute measure of information, but as a measure of the variation of information. This makes it possible to obtain a single value for informational entropy, instead of several values that vary with the selection of the discretizing interval, when discrete probabilities of hydrological events are estimated through relative class frequencies and discretizing intervals. Furthermore, the present work introduces confidence limits for the informational entropy function, which facilitates a comparison between the uncertainties of various hydrological processes with different scales of magnitude and different probability structures. The work addresses hydrologists and environmental engineers more than it does mathematicians and statisticians. In particular, it is intended to help solve information-related problems in hydrological monitoring design and assessment. This paper first considers the selection of probability distributions of best fit to hydrological data, using generated synthetic time series. Next, it attempts to assess hydrometric monitoring duration in a netwrok, this time using observed runoff data series. In both applications, it focuses, basically, on the theoretical background for the extended definition of informational entropy. The methodology is shown to give valid results in each case.