Rainfall for Modern Flood Hazard Assessment
Welcome to Web-based RainyDay Beta! RainyDay is a framework for generating large numbers of realistic extreme rainfall scenarios based on remotely-sensed precipitation fields. It is founded on a statistical resampling concept known as stochastic storm transposition (SST). These rainfall scenarios can then be used to examine the extreme rainfall statistics for a user-specified region, or to drive a hazard model (usually a hydrologic model, but the method produces output that would also be useful for landslide models).
This web-based version of RainyDay is intended to make the software more accessible to a wide range of potential users. Since you won’t need to configure Python, download large amounts of input data, etc., you just need to make sure you understand how the SST method works and how to best use it in your specific application. For that, I would recommend consulting the supporting documentation and example “.sst” file here. Please contact us if you have questions or comments about this web interface.
Additional useful references include:
- Wright, D.B., R. Mantilla, and C.D. Peters-Lidard. “A remote sensing-based tool for assessing rainfall-driven hazards,” Environmental Modelling & Software 90 (34-54), 2017.
- Wright, D.B., J.A. Smith, M.L. Baeck. “Flood Frequency Analysis Using Radar Rainfall Fields and Stochastic Storm Transposition,” Water Resources Research, 50 (1592-1615), 2014.
- Wright, D.B., J.A. Smith, G. Villarini, M.L. Baeck. “Estimating the frequency of extreme rainfall using weather radar and stochastic storm transposition,” Journal of Hydrology, 448(150-165), 2013.
The framework is made to be simple yet powerful and easily modified to meet specific needs, taking advantage of Python’s simple syntax and well-developed libraries. It is still a work in progress. Therefore, the contents of the user guide may be out-of-date. I would appreciate any feedback on the guide and on RainyDay itself, so I can continue to improve both.
RainyDay is published under the MIT License for open source distribution (see https://opensource.org/licenses/MIT/). The source code is available at https://github.com/danielbwright/RainyDay2.
Thanks,
Daniel Wright (danielb.wright@wisc.edu)
Acknowledgements:
The development of RainyDay was sponsored by The NASA Postdoctoral Program. The development of the web-based version is supported by the Research and Development Office at the Bureau of Reclamation (see here).