Advanced computer simulations are important tools through which we understand hydrologic phenomena such as rainfall-runoff response, groundwater hydrology, stormwater conveyance, water distribution system, etc. But building a hydrologic model instance to simulate watershed properties requires investment in diverse geospatial data (e.g., terrain, land use, and soil information) and computer resources. It also typically demands a wide skill set from the analyst, and the workflow involved is often difficult to reproduce.
Join Stormwater University for this live, educational webinar as returning speaker Prasanna Dahal (Project Engineer at Sunrise Engineering) presents work that demonstrates simplified access to many hydrological modeling functionalities using automated approaches. This includes accessing and processing the necessary geospatial and climate data, preparing input files for a model by applying complex data preprocessing, and an example case of preparing input data for a hydrologic model.
Two open-source platforms, Python and R, will be used for the demonstration.
Learning Objectives:
- Explain automating data preparation processes for common modeling tasks
- Learn how to use APIs to access public data sources
- Discover the power of open-source platforms such as Python and R to preprocess datasets
About Instructor
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Notes
* Each state and certification agency have different requirements; it is your responsibility to know what they are. Note that 0.1 CEU = 1 PDH.
* Purchase of this course allows you access to the presentation for 6 months from the order date.
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hydrologic models
Course Content
Course Includes
- 5 Lessons
- 1 Quiz
- Course Certificate
