Abstract
Comprehensive characterization of its flow rates is prerequisite to a proper understanding and water management of a given hydrological region. Several studies question the soundness of stationarity in time series and suggest the need for a quantification of the events and non-stationary features in flow-rate time series. In this study, we combine statistical and time-frequency (TF) analyses to characterize and classify the flow rates of an understudied region, namely Haiti. Wavelet transforms and cyclostationarity analyses were combined with principal component analysis and hierarchical clustering to identify three groups of hydrological regimes in the country, suggesting similar managements: (i) relatively stable flow rates with TF behaviours; (ii) periodic and strongly seasonal flow rates; and (iii) unstable flow rates. We argue that the TF methodology can yield additional information in regard to flow events and multiscale behaviours, even for short records. Flow-rate characterization would predictably be more exhaustive if done with the approach described here.