Download flood stage thresholds from NWS (National Weather Service). Use when determining flood levels for USGS stations, accessing action/minor/moderate/major flood stages, or matching stations to their flood thresholds.
npxskills add benchflow-ai/skillsbench--skill nws-flood-thresholdsLoading…
The National Weather Service (NWS) maintains flood stage thresholds for thousands of stream gages across the United States. These thresholds define when water levels become hazardous.
https://water.noaa.gov/resources/downloads/reports/nwps_all_gauges_report.csv
https://water.noaa.gov/gauges/<station_id>
Example: https://water.noaa.gov/gauges/04118105
| Category | CSV Column | Description |
|---|---|---|
| Action Stage | action stage | Water level requiring monitoring, preparation may be needed |
| Flood Stage (Minor) | flood stage | Minimal property damage, some public threat. Use this to determine if flooding occurred. |
| Moderate Flood Stage | moderate flood stage | Structure inundation, evacuations may be needed |
| Major Flood Stage | major flood stage | Extensive damage, significant evacuations required |
For general flood detection, use the flood stage column as the threshold.
import pandas as pd
import csv
import urllib.request
import io
nws_url = "https://water.noaa.gov/resources/downloads/reports/nwps_all_gauges_report.csv"
response = urllib.request.urlopen(nws_url)
content = response.read().decode('utf-8')
reader = csv.reader(io.StringIO(content))
headers = next(reader)
data = [row[:43] for row in reader] # Truncate to 43 columns
nws_df = pd.DataFrame(data, columns=headers)
The NWS CSV has a known issue: header row has 43 columns but data rows have 44 columns. Always truncate data rows to match header count:
data = [row[:43] for row in reader]
| Column Name | Description |
|---|---|
usgs id | USGS station ID (8-digit string) |
location name | Station name/location |
state | Two-letter state code |
action stage | Action threshold (feet) |
flood stage | Minor flood threshold (feet) |
moderate flood stage | Moderate flood threshold (feet) |
major flood stage |
Threshold columns need conversion from strings:
nws_df['flood stage'] = pd.to_numeric(nws_df['flood stage'], errors='coerce')
# Get stations for a specific state
state_stations = nws_df[
(nws_df['state'] == '<STATE_CODE>') &
(nws_df['usgs id'].notna()) &
(nws_df['usgs id'] != '') &
(nws_df['flood stage'].notna()) &
(nws_df['flood stage'] != -9999)
]
# Build a dictionary of station thresholds
station_ids = ['<id_1>', '<id_2>', '<id_3>']
thresholds = {}
for _, row in nws_df.iterrows():
usgs_id = str(row['usgs id']).strip()
if usgs_id in station_ids:
thresholds[usgs_id] = {
'name': row['location name'],
'flood': row['flood stage']
}
| Issue | Cause | Solution |
|---|---|---|
| Column mismatch error | CSV has 44 data columns but 43 headers | Truncate rows to 43 columns |
| Missing thresholds | Station not in NWS database | Skip station or use alternative source |
| Value is -9999 | No threshold defined | Filter out these values |
| Empty usgs id | NWS-only station | Filter by usgs id != '' |
| Major flood threshold (feet) |
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