Numeric hydrologic models can aid in water resource management by providing predictive simulations of water behavior. As computers become more advanced, the models developed also become more complex using more data to represent larger areas for forecasting hydrologic behavior. Unfortunately, as the simulations use more data, the output often becomes difficult to manage and share without investing time and effort into setting up server environments or decreasing the quality of the output to compensate for an efficient and effective user experience. A proposed solution to facilitate the accessibility of massive hydrologic model output is through the web-based visualization tool developed at Carnegie Mellon University called Time Machine. For a more efficient and automated workflow, a Python tool named TMAPS was developed from this research for rendering hydrologic model results, geoprocessing the rendered output, and generating Time Machines seamlessly. The tool can be installed from the CI-WATER GitHub repository and allows the user to 1) select the output parameters and visualization settings desired to be rendered, 2) run the code on a local or HPC setup, and 3) use a web browser interface to view the tiled transient results seamlessly while maintaining high quality. Currently, the only hydrologic model supported is ADHydro - a large-scale high-resolution multi-physics watershed simulation. In an effort to facilitate organizing the library of Time Machine products, an app was created through Tethys - a server-based Django application designed to aid in the development and sharing of water resource engineering apps.
| Identifer | oai:union.ndltd.org:BGMYU2/oai:scholarsarchive.byu.edu:etd-6855 |
| Date | 01 December 2015 |
| Creators | Taylor, Noah Robert |
| Publisher | BYU ScholarsArchive |
| Source Sets | Brigham Young University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | All Theses and Dissertations |
| Rights | http://lib.byu.edu/about/copyright/ |
Page generated in 0.0017 seconds