ABSTRACT:

This workshop aimed at giving participants a sense of: forecast uncertainty, high consequence trade-offs, unclear decision thresholds, spatial variability in the forecast, and forecast latency. Participants were meant to take note of the factors influencing decision making, what information they wish they would've had, and certainty levels. Groups were made of different roles---Weather Forecast Office and Emergency Management staffs. They then went through multiple emergency scenarios based upon real historical storms in Hawaii. Participants were given real data and had to make high-pressure decisions. A debrief of the events, roleplaying, data, and questions from above was conducted after each scenario.

Acknowledgements:
This research was supported by the Cooperative Institute for Research to Operations in Hydrology (CIROH) with funding under award NA22NWS4320003 from the NOAA Cooperative Institute Program. The statements, findings, conclusions, and recommendations are those of the author(s) and do not necessarily reflect the opinions of NOAA.

ABSTRACT:

This HydroShare resource contains the datasets, Jupyter Notebooks, and supporting materials required to complete the HydroLearn module "Rainfall Spatial Characteristics and Their Impact on Hydrology." The module introduces learners to the use of NOAA's Multi-Radar Multi-Sensor (MRMS) precipitation products for watershed-scale hydrologic analysis and explores how the spatial organization of rainfall influences flood response.

The repository includes Jupyter Notebooks, watershed boundary files, streamflow observations, and supporting datasets used throughout the module. These resources are intended for educational purposes and support reproducible hydrologic and geospatial analyses within the HydroLearn learning environment.

Please cite the associated HydroLearn module:
Huang, Y., Gomez F., (2026). Rainfall Spatial Characteristics and Their Impact on Hydrology. HydroLearn. https://edx.hydrolearn.org/courses/course-v1:UH+HL401+2026_S2/about