Trend analysis is continuously in the research and application agenda due to climate change effect searches on various engineering, social, economic, agriculture, environmental and water resources design, management, operation and management studies. Classical trend analysis is useable for holistic trend identification and then statistical quantification as for its intercept and slope. The main drawbacks in these classical approaches are the set of fundamental assumptions such as the serial independence of the given time series, pre-whitening, normality of the data and non-existence of serial comparison among different sections of the same record. This paper explains a non-parametric approach to avoid almost all these difficulties by simple methodology, which is referred as the Innovative Polygonal Trend Analysis (IPTA). Such an approach helps not only to identify the trend in a given series, but also trend transitions between successive sections of the two equal segments from the original hydro-meteorological time series leading to trend polygon, which provides a productive basis for finer interpretation with linguistic and numerical interpretations and inferences from a given time series. The application of the IPTA is presented for rainfall records from New Jersey, USA, Danube River and Goksu River discharge records from Romania and Turkey.