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| Created: | Jul 05, 2026 at 3:35 p.m. (UTC) | |
| Last updated: | Jul 05, 2026 at 3:40 p.m. (UTC) | |
| Citation: | See how to cite this resource |
| Sharing Status: | Discoverable (Accessible via direct link sharing) |
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Abstract
This resource contains the Jupyter notebook used in Learning Activity 2 of the HydroLearn module "Introduction to Impact-Based Forecasting" (from what the weather will be to what the weather will do), developed for the WMO capacity-building course series. On a clearly labeled synthetic demonstration region (a river valley with one town, villages, and farmland), the notebook builds a minimal flood IBF chain end to end: a hazard layer (probability of 24-hour rainfall exceeding a flood-relevant
threshold), an exposure layer (population density with a critical facility), a vulnerability index, and a transparent likelihood-by-impact warning matrix that combines them into No warning, Yellow, Amber, and Red zones on a map. Two stress tests follow: a festival that temporarily adds 50,000 visitors to a quiet floodplain cell, and a likelihood-threshold debate that shows what stricter warning criteria cost. All data are generated inside the notebook, so every learner gets identical, discussable results; the method, not the numbers, is what transfers to real national layers.
The notebook can be run using the JupyterHub environment available through HydroShare (Open with: CUAHSI JupyterHub) or on Google Colab; it needs only numpy and matplotlib, requires no downloads and no accounts, and runs in under a minute. Total hands-on time is about 30 to 45 minutes at the fundamentals level.
This resource is part of the learning activities in the HydroLearn module "Introduction to Impact-Based Forecasting": https://edx.hydrolearn.org/courses/course-v1:UniversityofIowa+WMO_05+2026/about
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This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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