There are trend identification methodologies in the literature but they have three crucial points that should be cared with great attention in practical applications. These points are that the available time series should have independent serial correlation structure, Gaussian (normal) distribution and monotonic trend fitting to whole time series through the least square technique. The existing methods consider the whole duration of the time series and try to identify a monotonic trend in increasing or decreasing forms. This paper presents partial trend methodology as an innovative and simple trend identification method, which yields low, medium and high cluster trends separately. It provides the opportunity to segregate between the low, high and medium flow trends and their relative intensities, durations as well as magnitudes. The application of the partial trend methodology is presented for 7 precipitation stations from 7 different sub-climatic regions of Turkey leading to spatial and temporal trend interpretations.