ABSTRACT:

This is a toy model that is used to walk through a Delft3D-Flexible Mesh application of the Lagrangian particle tracking model, dorado (Hariharan et al., 2020a). This Jupyter Notebook walkthough can be found on github (https://github.com/passaH2O/dorado) using the example: unstructured_grid_Delft3dFM.ipynb. This model was additionally used in the Jupyter Notebook walkthrough of spatial exposure time using the example: spatial_exposure_time_example_Delft3DFM.ipynb. This model is for 30 days (April 15th, 2025 to May 16th, 2025). Accurate data was used for tidal and meteorological data. Tributary inputs are an approximate average of that time period and the diversion was set to be open during this time period; although no opening occurred during this time,. This model was created for educational purposes only. A fully calibrated model can be found on HydroShare (Turner & Hiatt, 2025b), with the model creation process and applications of these codes outlined in "Water exposure time distributions controlled by freshwater releases in a semi-enclosed estuary (Turner & Hiatt, 2025b)".

ABSTRACT:

This dataset supports the hydrodynamic modeling study described in "Water exposure time distributions controlled by freshwater releases in a semi-enclosed estuary," published in Water Resources Research (2025). The model was developed using the Delft3D Flexible Mesh (D3DFM) system to simulate circulation dynamics in the Lake Pontchartrain Estuary (LPE). This repository includes all files needed to reproduce the model for the years 2011, 2014, and multiple hydrodynamic scenarios. These files include the unstructured computational grid, boundary and initial condition inputs, meteorological and hydrological forcings, and scenario-specific discharge time series. Water level and velocity observations from moored sensors are also provided for additional model validation.

Model scenarios reflect filtered 2014 conditions, which were selected as a representative year based on a historical analysis of wind and river discharge records. Scenario definitions, calibration performance, and modeling methodology are fully described in the associated publication. Analysis scripts and post-processing tools are available via GitHub: https://github.com/caitlinturner/turner2025WRR.