Web visualization of spatially large-scale flow and sediment numerical simulation data: case study of the Xiaolangdi reservoir

ABSTRACT Web visualization of numerical simulations of flow and sediment in river-type reservoirs is crucial for analyzing flow and sediment transport. To enhance the efficiency of visualizing spatially large-scale flow and sediment time series, this paper uses the Open Geospatial Consortium service specification to implement web visualization of data from a numerical model of a river-type reservoir. The numerical model calculates the spatial and temporal variations in water depth, velocity, and sediment concentration during reservoir regulation. Using the Python language, the results from the numerical model are efficiently converted into the ncWMS file format, which is supported by network service specifications. The GeoServer software is then utilized for data sharing on the web. This study utilizes the isosurface method for visualizing the scaler water depth and sediment concentration data but implements a particle tracking algorithm for the flow field vector time series. The introduced method is utilized for the web visualization of the numerical simulation results of spatially large-scale flow and sediment concentration for the Xiaolangdi Reservoir in the Yellow River in 2023, demonstrating that the proposed platform can smoothly present the spatiotemporal evolution of water depth and suspended sediment concentration.