Streamflow Hydrograph Classification Using Functional Data Analysis
AbstractClassification of streamflow hydrographs plays an important role in a large number of hydrological and hydraulic studies. For instance, it allows decisions to be made regarding the implementation of hydraulic structures and characterization of different flood types, leading to a better understanding of extreme flow behavior. The employed hydrograph classification methods are generally based on a finite number of hydrograph characteristics and do not include all the available information contained in a discharge time series. In this paper, two statistical techniques from the theory of functional data classification are adapted and applied for the analysis of flood hydrographs. Functional classification directly employs all data of a discharge time series and thus contains all available information on shape, peak, and timing. This potentially allows a better understanding and treatment of floods as well as other hydrological phenomena. The considered functional methodology is applied to streamflow d.