Abstract. We develop a phenomenological model of suspended-sediment transport on the basis of data acquired in the Capesterre river, which drains a small tropical catchment in Guadeloupe. The model correctly represents the transport of suspended sediment during floods, provided that the relation between concentration and water-level forms a counterclockwise loop. In the model, the properties of the sediment and of the river are all lumped into four parameters: a settling velocity related to the size of the suspended sediment, a threshold water-level which acts as a proxy for the threshold shear stress, a characteristic erosion rate and a dimensionless exponent, both of which are related to the availability of fine sediment. The assimilation of field data to our model shows that the value of the parameters change from one flood to the next, probably reflecting changes in the characteristics of the river and the sediment. Finally, a test of the model against data acquired in a small catchment in the french Alps, suggests that the model is versatile enough to be used in diverse hydrological settings.
Abstract. We develop a phenomenological model of suspended sediment transport on the basis of data acquired in the Capesterre river, which drains a small tropical catchment in Guadeloupe. The model correctly represents the concentration of suspended sediment during floods, provided that the relation between concentration and water level forms a counterclockwise loop. In the model, the properties of the sediment and of the river are all lumped into four parameters: a settling velocity related to the size of the suspended sediment, a threshold water level which acts as a proxy for the threshold shear stress, a characteristic entrainment rate, and a dimensionless exponent. The value of the parameters changes from one flood to the next, probably reflecting changes in the characteristics of the river and the fine sediment. Finally, a test of the model against data acquired in a small catchment in the French Alps suggests that the model is versatile enough to be used in diverse hydrological settings.
<p>Fine particles represent an important fraction of the mass of sediment transported by rivers (Syvitski et Saito, 2007). Suspended load is therefore a significant contributor to the erosion of landscapes. Fine particles are often considered to travel through streams and rivers with minimal interaction. Yet, recent field campaigns demonstrate that fine particles interact with the bed through erosion and deposition (Misset et al., 2019). Based on this observation, we develop a simplified model of suspended transport that accounts explicitly for the exchange of small particles between the river bed and the water column. This model involves three parameters: (1) a threshold water level above which the flow starts eroding fine particles from the bed, (2) an erosion rate that characterizes the intensity of sediment entrainment, and (3) a characteristic settling time accounting for sediment deposition.</p><p>We then test the validity of the model against data collected in the Capesterre catchment, a small catchment (16.6 km2) monitored by the Observatory of Water and Erosion in the Antilles (ObsErA). Located in Basse-Terre Island (Guadeloupe archipelago, lesser Antilles arc), this catchment is regularly exposed to floods induced by hurricanes and tropical storms (Allemand et al., 2014; Gaillardet et al., 2011). The discharge and the turbidity of the river are measured with a time step of 5 minutes. Using in-situ calibrations, we convert the turbidity signal into a suspended load concentration. The resulting data reveal that the transport of fine sediment is highly intermittent: the concentration of suspended particles rises abruptly when the river height exceeds a threshold of the order of 25cm, corresponding to a discharge of 5 m<sup>3</sup>/s. The concentration decrease following the flood peak is more gentle. The resulting concentration-discharge curve takes the form of a counter-clockwise hysteretic loop, as commonly observed in many streams (Williams, 1989).</p><p><img 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