| 06 Sep 2024
Discharge and sediment fluxes along the Amazon river: RDSM model concepts and validation
Abstract. The Amazon covering approximately 6.8 million km2, is the largest river by discharge in the world, and transports copious suspended sediment. In the Amazon, human activities such as dam construction and land use change are likely to affect sediment transport strongly as the basin moves further away from pristine conditions.
In this study, we applied the River Discharge and Sediment model RDSM to simulate annual and monthly discharge and sediment transport in the Amazon between 1980 and 2009. To this end, the model couples sediment production with runoff generation and river transport. The model works at a spatial resolution of 5 arc minutes. It accounts for the impacts of land use change on runoff generation and sediment production, and for the entrapment of sediment by lakes and reservoirs. The sediment load in the stream of every cell at every time-step, therefore, reflects sediment production, uptake and deposition as it is transported and accumulated along the drainage network.
We validated the model using the Hybam-project dataset for seven discharge stations distributed over the Amazon. Additionally, estimations of sediment transport from previous studies were used as benchmark. The model is able to effectively capture the monthly and annual variations of discharge with Kling-Gupta Efficiency ranges from 0.57 to 0.92 and sediment transport within the basin and to the ocean with Kling-Gupta Efficiency ranges from -1.7 to 0.49.
Based on the model results, the annual average sediment transport (1980–2009) at station Obidos Porto, the station furthest downstream, is 6.46 × 108 tonne/year and the annual average discharge is 17.5 × 104 m3/s.
The model estimates the annual average sediment transport to the ocean at 5.96 × 108 tonne/year, which is in the same order of magnitude as field measurements and is in line with the results of other studies.
The RDSM model facilitates future estimation of sedimentation impact in reservoirs incorporating water resource management and will so contribute to a better understanding of the complexity of the Amazon basin.
