Uncertainty quantification in shallow water-sediment flows: A stochastic Galerkin shallow water hydro-sediment-morphodynamic model - Ji Li (Applied Mathematical Modelling, 2021)
All shallow water hydro-sediment-morphodynamic (SHSM) models are prone to uncertainty arising from inadequate representation of the underlying physics and error in input parameters. At the time of writing, most SHSM models solve deterministic problems, whilst studies of uncertainty quantification in SHSM models remain rare. Here a new stochastic SHSM model is proposed, extended from a well-balanced, operator-splitting-based, generalized polynomial chaos stochastic Galerkin (gPC-SG) solver of the one-dimensional shallow water hydrodynamic equations. A series of probabilistic numerical tests are carried out, corresponding to idealized test of dam break flow over a fixed bed and laboratory experiments of flow-sediment-bed evolutions induced by a sudden dam break and by landslide dam failure. The proposed modelling framework shows promise for uncertainty quantification of shallow water-sediment flows over erodible beds.