| # TORRENT generic tools |
|
|
| Standalone utilities for working with (and extending) the TORRENT dataset. |
| They talk only to public agency services — USGS NWIS, USGS NLDI, and the Iowa |
| State MT MRMS archive — and never require the authors' build environment. |
|
|
| Requirements: Python ≥3.9, `pandas`, `requests`; `download_forcing.py` also |
| needs `rasterio` (GDAL with the GRIB driver), `shapely`, `numpy`. |
|
|
| | Tool | Purpose | |
| |---|---| |
| | `find_gauges.py` | List stream gauges near an episode (by TORRENT episode ID or lat/lon) and optionally check NWIS discharge/stage availability over the event window — the candidate-generation step as a utility. | |
| | `download_streamflow.py` | Fetch the NWIS IV discharge record for a gauge over the standard window (begin −24 h … end +72 h) → `streamflow.csv`. | |
| | `get_watershed.py` | Retrieve the NLDI contributing watershed for a gauge → `watershed.geojson` (retries transient NLDI failures). | |
| | `download_forcing.py` | Download 2-min MRMS PrecipRate for a window, clip to a watershed, write the basin-mean series → `mrms_2min_precip_basin_mean.csv`. Use it to add forcing to the 115 light packages. | |
| | `build_testbed.py` | Compose the above into a candidate testbed package (watershed + streamflow + summary) for any episode–gauge pair. | |
|
|
| ## Typical session |
|
|
| ```bash |
| # which gauges could observe this episode? |
| python find_gauges.py --episode FF_2025_07_TX_ep002 --radius 50 --check-iv |
| |
| # build a candidate package for one of them |
| python build_testbed.py --episode FF_2025_07_TX_ep002 --gauge 08165500 --outdir ./my_testbeds |
| |
| # add forcing (also works for the released light packages) |
| python download_forcing.py \ |
| --watershed ./my_testbeds/FF_2025_07_TX_ep002/08165500/watershed.geojson \ |
| --begin 2025-07-04T02:00 --end 2025-07-04T17:41 --cache ./mrms_cache \ |
| --out ./my_testbeds/FF_2025_07_TX_ep002/08165500/mrms_2min_precip_basin_mean.csv |
| ``` |
|
|
| Notes |
| - Basin-mean values from `download_forcing.py` agree with the released series to |
| within a few percent (mask-rasterization details differ slightly from the |
| release pipeline). |
| - Packages built this way are **candidates**: apply the screening criteria in |
| `code/pipeline` (paper Sect. 3.4) before comparing them with benchmark |
| testbeds. |
| - NLDI throttles around 800 requests/hour; most failures are transient — retry. |
|
|
