TOOLS TO MODEL TEXAS ESTUARIES Solomon Negusse, Dharhas Pothina - PowerPoint PPT Presentation

THE OPEN ESTUARY: USING OPEN SOURCE TOOLS TO MODEL TEXAS ESTUARIES Solomon Negusse, Dharhas Pothina

Modeling Bays and Estuaries Predictive modeling needs:  Environmental flow needs  Assisting navigation  Oil spill  Study impact of man made changes to the bays.

Hydrodynamic Model Numerical Formulation of Governing Equations

Hydrodynamic Model Numerical Formulation of Governing Equations

Hydrodynamic Model Numerical Formulation of Governing Equations

Hydrodynamic Model Numerical Formulation of Governing Equations

Hydrodynamic Model Numerical Formulation of Governing Equations Water level, velocity, salinity temperature prediction at computational elements

Selfe Model Applications  An open source hydrodynamic code written in fortran.  Solves 3D physical variables(Free surface elevation, velocity), Temperature & Salinity  Coded with mpi and run on in‐house HPC cluster  Finite element model – run on unstructured triangular mesh

SELFE Model work flow

Computation Grid Generation  Surface Modeling Systems software

Computation Grid Generation  Good resolution control, grid modification tools.  Nice user friendly Interface (kind of).  Still a lot of limitations:  available for windows os only, crashes a lot, doesn’t handle big grids well.  Interpolation of bathymetry on to grid not efficient

Interpolation in SMS

Anisotropic stretched IDW interpolation in python

Stretched Anisotropic IDW in SMS Interpolation w/ Python

More input file processing  Pwl_interp.py  Usgsflow_interp.py  2dm2gr3.py

Output Processing and Visualization  Pyselfe: python class for model output storage and access.

Output Processing and Visualization  Matplotlib 2d plots.

Field data for Calibration and Validation  Python INstrumentationToolkit (PINT): putting data to common format  Pyhis : access timeseries data on the web from different sources

Output Processing and Visualization  Selfe2tec2D.py  Converts data to structured data format.

Conclusion and feature goals  Efficiency has improved through automation  Improved accuracy  Enhanced visualization capability Goals: ‐ visualization with Mayavi, viSit, ‐ Making codes available for contribution ‐ Generic code structure with ability to write translators for other hydro models inputs