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Regional watershed characterization and classification with river network analyses
Authors:Cédric Gaucherel  Romain Frelat  Ludovic Salomon  Bastien Rouy  Neha Pandey  Christophe Cudennec
Institution:1. French Institute of Pondicherry, IFP – CNRS, Pondicherry, India;2. AMAP, INRA, CNRS, IRD, Université Montpellier, Montpellier, France;3. 146 rue des Marailles, Cité Grant, Cayenne, French Guiana;4. Agrocampus Ouest, UMR 1069, Sol Agro et hydrosystème Spatialisation, Rennes, France
Abstract:In order to understand and manage a hydrological region, one usually needs to comprehensively characterize the watersheds (basins) and their river networks. This usually and primarily involves analysis of hydrological and geomorphological properties of the watershed derived from the digital terrain model (DTM), but this approach neglects the information content of the associated river networks. In this study, we used a combination of traditional DTM and original river network‐related indices to the watersheds of an understudied region, Haiti. We also used Monte Carlo simulations to estimate index confidence levels of these indices. Compared to commonly used indices, the network indices provided valuable information that could then be used in statistical analyses as a way to identify the dominant features of the country's watershed morphology. On this basis, we identified four watershed groups in Haiti: (i) high, elongated watersheds, (ii) lowlands, with sinuous networks and relatively slow runoff, (iii) high watersheds with dendritic networks, and (iv) lowlands with high downstream–upstream contrast in properties and rapid runoffs. We argue that river network features provide complementary information in terms of flow topology, highly relevant to characterize contrasting relief countries, such as Haiti. Hence, more exhaustive characterization of watersheds would predictably benefit from the approach outlined in this paper. Copyright © 2017 John Wiley & Sons, Ltd.
Keywords:geomorphology  Haiti  regionalization  self‐similarity  multiscale
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