Application of trend analysis and arti cial neural networks methods: The case of Sakarya River

Various arti cial intelligence techniques are used in order to make prospective estimations with available data. The most common and applied method among these artifi cial intelligence techniques is Arti cial Neural Networks (ANN). On the other hand, another method which is used in order to make prospective estimations with available data is Trend Analysis. When the relation of these two methods is analyzed, Artfii cial Neural Networks method can present the prospective estimation numerically, while there is no such a case in Trend Analysis. Trend Analysis method presents result of prospective estimation as a decrease or increase in data. Therefore, it is quite important to make a comparison between these methods which brings about prospective estimation with the available data, because these two methods are used in most of these studies. In this study, annual average stream flow and suspended load measured in Sakarya River along withaverage annual rainfall trend were analyzed with trend analysis method. Daily, weekly, and monthly average stream ows and suspended loads measured in Sakarya River and average daily, weekly, and monthly rainfall data of Sakarya were all analyzed by ANN Model. Results of trend analysis method and ANN model were compared.