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In this study, of water mites (Hydrachnidia) which are among the main representatives of aquatic faunas, 71 species belonging to 18 families were determined from samplings made in Köprüçay River and its branches, a major river of Mediterranean region situated within provinces Isparta and Antalya having great importance in tourism and as a water resource. These are belonging to the families Sperchontidae (11), Lebertidae (4), Torrenticolidae (10), Hygrobatidae (13), Aturidae (4), Feltridae (4), Arrenuridae (2), Protzidae (3), Limnesidae (1), Anisitsiellidae (4), Thyasidae (3) Hydrovolziidae (1), Limnocharidae (1), Eylaidae (2), Hydrodromidae (1), Teutoniidae (1), Axonopsidae (4) and Mideopsidae (2). Furthermore, some water quality values of Köprüçay river were also given. [ABSTRACT FROM AUTHOR]

It is very important to make reliable runoff predictions and runoff modeling studies when planning and designing of water resources. In the study presented, an artificial neural network (ANN) model is improved and applied to the daily runoff values of Coruh River which is located in the Coruh basin. The ANN model which requires one day and two days ahead runoff values as the input data is trained by using the runoff data depending on the records that spreads to a time frame of 1643 days, made between 03.10.1991 and 01.04.1996, and then tested by the 1643 days of runoff data set which recorded between 02.04.1996 and 30.09.2000. The ANN model was also compared with autoregressive stochastic AR(2) model structure. After analysis, it was noticed that the results of each model are approximately similar but ANN is more successful than the autoregressive model. When the statistics of the long term recorded and modeled runoff values are compared, it can be seen that the ANN model structure that has been developed, successfully represents the daily runoff values of the Coruh River and can be also used to forecast the daily runoff values of the other river basin. [ABSTRACT FROM AUTHOR]