Uncertainties of cultivated landscape drainage network mapping and its consequences on hydrological fluxes estimations
Levavasseur, Florent | Bailly, Jean-Stéphane | Lagacherie, Philippe | Rabotin, Michael | Colin, François | Laboratoire d'étude des Interactions Sol - Agrosystème - Hydrosystème (UMR LISAH) ; Institut de Recherche pour le Développement (IRD)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro) | Territoires, Environnement, Télédétection et Information Spatiale (UMR TETIS) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Centre national du machinisme agricole, du génie rural, des eaux et forêts (CEMAGREF)
[Departement_IRSTEA]Territoires [TR1_IRSTEA]SYNERGIE
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Показать больше [+] Меньше [-]Английский. In this study, we use a network generation method to simulate equi-probable artificial drainage networks on a small Mediterranean cultivated catchment. The method consists in a stochastic algorithm assimilating sampled observations on the network that generates a ditch network based on the map of field boundaries. A set of one hundred simulations is used to represent the uncertainty on the ditch network. With regards to geometrical (lengths indices), and topographical metrics (slope indices), simulations similarities compared to the real network are computed. Secondly, uncertainty on the network is propagated through the hydrological model MHYDAS. The induced hydrological responses in hydrographs present a variability that can be linked to previous networks metrics. At this stage of the network generation process, this uncertainty propagation study allows to drive the choice of criteria for future network generation process improvement.
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