Real-time simulation of hydrodynamic and scalar transport in large river-lake systems

Abstract

Real-time coupling of a hydro-environmental model and an optimization model is difficult because hydrodynamic model (HDM) and scalar transport model (STM) are both time-consuming, especially when the computational domain is large (e.g., river-lake system). This study presents a new 1D hydro-environmental model for free-surface flows and scalar transport in large river-lake systems. Using a prediction–correction method, hydrodynamic is simulated by solving local linear systems based on domain decomposition. A flux-form Eulerian-Lagrangian method (ELM) is constructed to solve advective transport of scalars in 1D grid systems, and a nested technique is proposed to reduce its startup cost. The resulting STM and HDM both allow large time steps for which the Courant–Friedrichs–Lewy number (CFL) is greater than 1, and they are parallelized using the open multiprocessing technique (OpenMP). Moreover, the STM is good at solving multiscalar transport and has low startup cost. The new model is tested using the Jing-Dongting (JDT) system which is covered by a grid of 2382 cells (with 113,600 sub-grids). Stable and accurate simulations are achieved at large time steps for which the CFL can be larger than 5. A sequential run of the new model runs tens of times faster than that of a conventional 1D model such as the Mike11. Moreover, the efficiency of the new model can be further improved by the OpenMP parallel technique. In the test of scale property of the HDM + STM model (using 32 kinds of scalars and 16 cores), a parallel run is 11.8 times faster than a sequential run, and it only takes the new model 33.3 s to complete a simulation of a 1-year process of unsteady flow and scalar transport in the JDT system.