No abstract

The main objective of this study was to investigate the applicability and efficiency of an artificial bee colony optimization algorithm to determine two statistical-based rainfall intensity duration frequency equations' weighting parameters. For this aim, the annual maximum rainfall records were obtained from seven meteorological stations of seven geographic regions in Turkey. It was observed that the Artificial Bee Colony algorithm, which is an alternative technique for solving the rainfall intensity duration frequency equations, gives very good results in selected seven meteorological stations.

No abstract

Hidrometeorolojik veriler kullanılarak yapılan mühendislik çalışmalarında, verilerin eksiksiz ve yeterli uzunlukta olması çalışmaların verimliliğini arttırmaktadır. Bölgesel mühendislik çalışmalarda ise verilerin istenen şekilde olmasının yanında uygun bölgelerin de belirlenmesi tasarım ve uygulama çalışmalarının daha verimli olmasını sağlayacaktır. Bu bölgelerin belirlenmesinde hidrometerolojik verilerin yanında coğrafi konum verilerin de kullanılması gerekmektedir. Bu çalışma kapsamında Karadeniz bölgesindeki Devlet Meteoroloji İşlerine ait meteoroloji gözlem istasyonlarında gözlemlenen, Standart Süreli Yağışların Şiddetlerine ait veriler kullanılarak bölgesel kümelerin oluşturulması amaçlanmıştır. Bu amaçla Bulanık C Ortalamalar yöntemi kullanılmıştır.. Kümeleme çalışmaları iki farklı küme sayısı için yapılmış olup en uygun küme sayısı 4 olarak belirlenmiştir.

Bilimsel ve teknolojik gelişmelerle birlikte artan nüfusun etkisiyle yeryüzündeki suyun paylaşımı ve kullanımı günden güne daha da önem kazanmaktadır. Yeryüzünde bu kadar değerli olan bu maddenin tasarruflu ve yeterince kullanılması bir zorunluluk haline gelmektedir. Sunulan bu çalışmada basit bir su dağıtım şebekesindeki borulardaki suyun taleplere göre en uygun şekilde belirlenmesi amaçlanmıştır. Bu amaçla Guguk Kuşu ve Ateşböceği Algoritmaları kullanılarak örnek şebekenin çözümü gerçekleştirilmiş olup literatürdeki sonuçlarla birlikte incelenmiştir. Şebekenin Guguk Kuşu Algoritması kullanılarak çözümünün diğer algoritmaya oranla daha iyi sonuç verdiği belirlenmiştir.

No abstract

Drought is the most dangerous natural disaster. It differs from the other disasters in that it occurs insidiously, its effects are revealed gradually, and it persists for a long period. Drought has huge, negative effects on both society and natural ecosystems. In this study, values from the Standardized Precipitation Index (SPI) were used to generate drought estimation models by using Artificial Neural Networks (ANN). In addition, the probability of hydrological drought was determined by using SPI values to predict Streamflow Drought Index (SDI) values with ANN. Also, the SPI and SDI were used as the meteorological and hydrological drought indices, respectively, in conjunction with Feed Forward Neural Networks (FFNN), in ANN models. For this purpose, three rainfall and three flow gauging stations located in the Yesilirmak River Basin of Turkey were selected as the study units. The SPI and SDI values for the stations were calculated in order to create ANN estimation models. Different ANN forecasting models for SPI and SDI were trained and tested. In addition, the effects of the spatial distribution of precipitation on flows were determined by using the Thiessen Method to develop the SDI prediction model. The results generated by the ANN prediction models and resulting values were compared and the performances of the models were analyzed. The combination of ANN and SPI predicted meteorological drought with high accuracy but the combination of ANN and SDI was not as good in predicting hydrological drought.

Climates are constantly changing on a temporal and spatial scale, so they are not static. In recent years, global warming and changes in climate have shown more and more effects on the hydrological cycle and water resources, and their effects have become so noticeable that they hinder sustainable life. For this reason, the studies on the investigation of the main causes of the observed changes in the climate, the evaluation of climate change as a process and the determination of the effects that will emerge, have increased over time. In the present study, the homogeneity of annual and seasonal temperature series in Hirfanli Dam basin were examined by using the Pettitt Test (PT), and the trends were examined with the Spearman's Rho (SR) test and Mann Kendall (MK) test. Hirfanli Dam basin, which is located in the semi-arid climate region where climate change can be seen due to its location, was chosen as the study area. The temperature data of the Gemerek, Kayseri, Kirsehir, Nevsehir, Sivas and Zara meteorological stations in the basin between 1965 and 2017 were analyzed. It was noted that summer temperatures increased throughout the basin. Significant trends to increase were also detected in spring and autumn. The trend to increase was statistically significant at a 95% confidence level in all stations except for the Zara in terms of annual temperatures. Trend maps were prepared for the basin by using the results obtained here and the Geographical Information Systems. It was reported that the tendency to increase in annual temperature series was because of the increase in summer temperatures at intense levels throughout the basin.