Opportunities from low-resolution modelling of river morphology in remote parts of the world
- 1Research Center for Constructions – Fluid Dynamics Unit, University of Bologna, Italy
- 2Hydraulic Laboratory, University of Bologna, Italy
- 3University of Padova, Department of Civil, Environmental and Architectural Engineering ICEA, Padova, Italy; currently at Cà Foscari Venice University, Department of Environmental Sciences, Informatics and Statistics, Venice, Italy
Abstract. River morphodynamics are the result of a variety of processes, ranging from the typical small-scale of fluid mechanics (e.g. flow turbulence dissipation) to the large-scale of landscape evolution (e.g. fan deposition). However, problems inherent in the long-term modelling of large rivers derive from limited computational resources and the high level of process detail (i.e. spatial and temporal resolution). These modelling results depend on processes parameterization and calibrations based on detailed field data (e.g. initial morphology). Thus, for these cases, simplified tools are attractive. In this paper, a simplified 1-D approach is presented that is suited for modelling very large rivers. A synthetic description of the variations of cross-sections shapes is implemented on the basis of satellite images, typically also available for remote parts of the world. The model's flexibility is highlighted here by presenting two applications. In the first case, the model is used for analysing the long-term evolution of the lower Zambezi River (Africa) as it relates to the construction of two reservoirs for hydropower exploitation. In the second case, the same model is applied to study the evolution of the middle and lower Paraná River (Argentina), particularly in the context of climate variability. In both cases, having only basic data for boundary and initial conditions, the 1-D model provides results that are in agreement with past studies and therefore shows potential to be used to assist sediment management at the watershed scale or at boundaries of more detailed models.