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Files and code for the paper "Unprecedented flooding foretold by stream network organization and flow regime" by S. Basso, R. Merz, L. Tarasova and A. Miniussi
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| Type: | Resource | |
| Storage: | The size of this resource is 7.6 MB | |
| Created: | Apr 13, 2022 at 9:51 a.m. | |
| Last updated: | Feb 02, 2023 at 9:38 p.m. | |
| DOI: | 10.4211/hs.a6bcc341413c4fb0b195b25ebe1bb3e6 | |
| Citation: | See how to cite this resource |
| Sharing Status: | Published |
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| Views: | 781 |
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Abstract
Files and code for the paper "Unprecedented flooding foretold by stream network organization and flow regime" by S. Basso, R. Merz, L. Tarasova and A. Miniussi
Subject Keywords
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readme.md
Manuscript_files
- "code_for_Basso_et_al.py": code for the manuscript "Unprecedented flooding foretold by stream network organization and flow regime" by Basso, S., Merz, R., Tarasova, L. and Miniussi, A. The root path needs to be defined, all the other paths are relative to it. Please note that you can make the code run just for the MOPEX catchments. Refer to the links in the manuscript section "Data Availability" to get the links where streamflow time series can be downloaded. The parula.py file contains the parula colormap for maps.
- Folder "Train_dataset": contains the streamflow/precipitation data for the catchments in the US used as train dataset (German ones not shared due to license limitations). The file "train_list.txt" includes a summary of all the parameters estimated for each catchment (both in Germany and US) and if a flood divide was detected or not in the observed or PHEV time series (variable values equal to -1 are indicated when no flood divide was detected)
- Folder "Test_dataset": contains the file "id_test.txt" where for each catchment several variables are saved (among others, recession exponent, coefficient of variation daily streamflow, if a flood divide is detected)
- Folder "Binary regression": contains the results of the binary regression analysis, namely: "BR_train.txt" for the 100 resamplings on the train dataset, "BR_test.txt" for the prediction on the whole test dataset, "test_1000.txt" for the prediction in a number of test catchments equal to the number of train catchments
- Folder "Data_for_maps": contains the coordinates for the MOPEX ("allrfc438.gls") and German ("coord_Germany.txt") datasets. The precipitation gridded 30-years normals (used in Extended Figure 1) are available from the PRISM and DWD websites respectively.
How to Cite
Miniussi, A., S. Basso (2023). Files and code for the paper "Unprecedented flooding foretold by stream network organization and flow regime" by S. Basso, R. Merz, L. Tarasova and A. Miniussi, HydroShare, https://doi.org/10.4211/hs.a6bcc341413c4fb0b195b25ebe1bb3e6
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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