JupyterCon-2018

Using JupyterLab for flood map development: Approaches for improving productivity and reproducibility

JupyterCon, August 24, 2018
New York City, NY

Resilience Solutions Group

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Our Clients

Contents

Rationale for this talk

1. (Proprietary) Tool diversity
2. Cost
3. Learning curve
4. Silos
5. Conceptualizing Workflows- technical & non-technical
6. Reproducibility & Traceability
7. Copy/Paste
8. Standard Models
9. Interactivity
10. Quality Control
11. Batch processing

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Riverine Modeling: Proven Models, New Approaches

Notebooks created by STARR II (Strategic Alliance for Risk Reduction) in support of FEMA.

• Monte Carlo Approaches (html) Conceptualizing Workflows
• USGS API Copy/Paste
• Model Development (html) Standard Models, Reproducibility & Traceability
• Data Visualization (html) Interactivity

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Coastal Modeling: Finite Element Methods

Notebooks developed by Tyler Miesse for production runs of the coupled hydrodynamic and wave models ADCIRC + SWAN.

• Model Development Silos, Learning curve
• Model Validation Copy/Paste, Interactivity
• Production QAQC Quality Control
• Troubleshooting QAQC Quality Control, Visualization*

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GIS Integration: Mapping & Analysis

Notebooks for working with vector and raster datasets common in flood risk analysis.

• Vector Datasets Learning Curve, Cost, Reproducibility & Traceability
• Raster Datasets Learning Curve, Cost, Reproducibility & Traceability
• Batch Processing with CL Tools Batch Processing

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