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Assessing Hydrograph Similarity and Rare Runoff Dynamics by Cross Recurrence Plots
Author(s) -
Wendi Dadiyorto,
Merz Bruno,
Marwan Norbert
Publication year - 2019
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/2018wr024111
Subject(s) - hydrograph , similarity (geometry) , event (particle physics) , recurrence quantification analysis , computer science , surface runoff , representation (politics) , range (aeronautics) , runoff model , flood myth , data mining , mathematics , hydrology (agriculture) , artificial intelligence , geography , geology , machine learning , nonlinear system , engineering , physics , ecology , law , image (mathematics) , aerospace engineering , archaeology , biology , quantum mechanics , political science , geotechnical engineering , politics , watershed
This paper introduces a novel measure to assess similarity between event hydrographs. It is based on cross recurrence plots (CRP) and recurrence quantification analysis (RQA), which have recently gained attention in a range of disciplines when dealing with complex systems. The method attempts to quantify the event runoff dynamics and is based on the time delay embedded phase space representation of discharge hydrographs. A phase space trajectory is reconstructed from the event hydrograph, and pairs of hydrographs are compared to each other based on the distance of their phase space trajectories. Time delay embedding allows considering the multidimensional relationships between different points in time within the event. Hence, the temporal succession of discharge values is taken into account, such as the impact of the initial conditions on the runoff event. We provide an introduction to cross recurrence plots and discuss their parameterization. An application example based on flood time series demonstrates how the method can be used to measure the similarity or dissimilarity of events, and how it can be used to detect events with rare runoff dynamics. It is argued that this methods provides a more comprehensive approach to quantify hydrograph similarity compared to conventional hydrological signatures.