Cross-mode stabilized stochastic shallow water systems using stochastic finite element methods

The development of surrogate models to study uncertainties in hydrologic systems requires significant effort the sampling strategies and forward model simulations. Furthermore, applications where prediction time is critical, such as hurricane storm surge, predictions system response can be required within short frames. Here, we develop an efficient stochastic shallow water address these issues. To discretize physical probability spaces use a Stochastic Galerkin method Incremental Pressure Correction Scheme advance solution time. overcome discrete stability issues, propose cross-mode stabilization methods which employs existing space by adding terms every mode modes-coupled way. We extensively verify developed for both idealized test cases hindcasting past hurricanes. subsequently verified perform comprehensive statistical analysis established models. Finally, predictor surge under uncertain wind drag coefficients demonstrate its effectivity Hurricanes Ike Harvey.