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| Storage: | The size of this resource is 205.7 MB | |
| Created: | Sep 16, 2025 at 7:15 p.m. (UTC) | |
| Last updated: | Sep 16, 2025 at 7:39 p.m. (UTC) | |
| Citation: | See how to cite this resource |
| Sharing Status: | Public |
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Abstract
To automate the analysis of post-wildfire rainfall-runoff events across numerous storms and watersheds, the hydrologic time-series analysis Rainfall-Runoff Event Detection and Information (RREDI) algorithm was developed. The RREDI algorithm first uses feature detection and signal processing of storm precipitation and flow data to identify rainfall-runoff events. Then each rainfall-runoff event is extracted using 15-minute flow and instantaneous precipitation data and the timing and magnitude of the start, peak, and end of event is extracted. These identifiers are then used to calculate a set of event attributes including time to peak, response time, duration, volume, and percent rise. These attributes from the identified rainfall-runoff events can then analyzed to answer research questions regarding variability in rainfall-runoff patterns within and between watersheds. This algorithm utilizes the open-source Python.
Utah Water Research Laboratory, Utah State University
This resource, RREDI toolkit V2, updates and supersedes:
Canham, H., Lane, B. (2022). Rainfall-Runoff Event Detection and Identification (RREDI) toolkit, HydroShare, http://www.hydroshare.org/resource/797fe26dfefb4d658b8f8bc898b320de
Paired Paper:
Canham, H. A., Lane, B., Phillips, C. B., and Murphy, B. P. (2025). Leveraging a time-series event separation method to disentangle time-varying hydrologic controls on streamflow – application to wildfire-affected catchments, Hydrol. Earth Syst. Sci., 29, 27–43, https://doi.org/10.5194/hess-29-27-2025.
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Related Resources
| This resource is referenced by | Canham, H. A., Lane, B., Phillips, C. B., and Murphy, B. P. (2025). Leveraging a time-series event separation method to disentangle time-varying hydrologic controls on streamflow – application to wildfire-affected catchments, Hydrol. Earth Syst. Sci., 29, 27–43, https://doi.org/10.5194/hess-29-27-2025. |
| The content of this resource is derived from | Canham, H., B. Lane (2022). Rainfall-Runoff Event Detection and Identification (RREDI) toolkit, HydroShare, http://www.hydroshare.org/resource/797fe26dfefb4d658b8f8bc898b320de, accessed on: 09/16/2025 |
Credits
Funding Agencies
This resource was created using funding from the following sources:
| Agency Name | Award Title | Award Number |
|---|---|---|
| National Science Foundation | Monitoring and modeling watershed-scale post-wildfire streamflow response through space and time | 2051762 |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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