Gabriela Gesualdo1* and Antonia Hadjimichael1
1 Department of Geosciences, The Pennsylvania State University, 116 Deike Building, University Park, PA 16801, USA
corresponding author: [email protected]
| Dataset | Description | Reference/DOI |
|---|---|---|
| Original ERA-5 Land dataset | Hydroclimatic inputs: potential evaporation, total evaporation, volumetric soil water, precipitation flux, and 2m air temperature | Muñoz Sabater, J. (2019): ERA5-Land hourly data from 1950 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). DOI: 10.24381/cds.e2161bac (Accessed on 20-March-2024); Boogaard, H., Schubert, J., De Wit, A., Lazebnik, J., Hutjes, R., Van der Grijn, G., (2020): Agrometeorological indicators from 1979 to present derived from reanalysis. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). DOI: 10.24381/cds.6c68c9bb (Accessed on 20-March-2024) |
| National Hydrography Dataset - 4 digit Hydrologic Unit (HUC4) | Shapefile of 4-digit Hydrologic Unit Codes (HUC4) for CONUS | U.S. Geological Survey, 2019, National Hydrography Dataset (ver. 20191002). https://www.usgs.gov/national-hydrography/access-national-hydrography-products (Accessed on 20-March-2024) |
| Hydroclimatic Data by Catchment (HUC4) | ERA5-Land hydroclimatic data averaged over each HUC4 unit |  |
| Total Crops Production - Montana | Crop production (excluding horticulture) in USD for Montana, 2007–2023 | U.S. Department of Agriculture, 2025, National Agricultural Statistics Service. https://quickstats.nass.usda.gov (Accessed on 05-May-2025) |
| Dataset | Description | Repository Link | DOI |
|---|---|---|---|
| Flash drought indicators by catchment (HUC4) | Flash drought classifications from 1983 to 2023 for each catchment | Link | |
| Correlation Matrix | Mean pairwise agreement between indicators across all catchments | Link | |
| Number of events per catchment (HUC4) | CCount and duration of events by indicator and catchment | Link | |
| Events per Indicators Agreement | Count and duration of events based on indicator agreement | Link | |
Download the hydroclimatic input data at catchment scale (HUC4) from the data repository. Once you have the input datasets downloaded, you can use the R package fdClassify to identify the flash drought with different indicators. You can also directly download the output fdClassify (i.e., “Flash Drought Indicators by catchment (HUC4)”) from the data repository. The "Flash Drought Indicators by catchment (HUC4)" is used as input to compute the pairwise agreement between flash drought indicators and the event-level agreement between flash drought indicators, using the following analysis scripts:
| Script Name | Description |
|---|---|
| FDCorrelationMatrix.ipynb | Computes the pairwise agreement between flash drought indicators |
| FDIndicatorAgreement.ipynb | Assesses event-level agreement between multiple flash drought indicators |
To reproduce the figures, download the necessary input files and use the scripts below:
| Figure Name | Script Name | Description |
|---|---|---|
| Detected flash drought events | FDNumberEvents_Figure1.ipynb | Plots the number of detected flash drought events per indicator and catchment (HUC4) |
| Flash drought indicator agreement matrix | FDAgreements_Figure2.ipynb | Visualizes the correlation matrix of flash drought detection methods |
| Montana 2017 Case study | MontanaPlot.ipynb | Plots indicators and hydroclimatic variables during a 2017 event in a Montana HUC4 code 0105 |
| Connecticut 2022 Case study | ConnecticutPlot.ipynb | Plots indicators and hydroclimatic variables during a 2022 event in a Connecticut HUC4 code 0110 |
| Flash drought mean event duration | FDMeanDuration_Supplement_01.ipynb | Calculates and visualizes the average duration of events by method |