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v1.0 paper-matched: 806 L3 / 21 primary, agent flags, master_metadata, AGENTS.md + tool schema, annual L3-expansion pipeline + tools
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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

# 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.