Skillsbench usgs-data-download

Download water level data from USGS using the dataretrieval package. Use when accessing real-time or historical streamflow data, downloading gage height or discharge measurements, or working with USGS station IDs.

install

source · Clone the upstream repo

git clone https://github.com/benchflow-ai/skillsbench

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/benchflow-ai/skillsbench "$T" && mkdir -p ~/.claude/skills && cp -r "$T/tasks/flood-risk-analysis/environment/skills/usgs-data-download" ~/.claude/skills/benchflow-ai-skillsbench-usgs-data-download && rm -rf "$T"

manifest: tasks/flood-risk-analysis/environment/skills/usgs-data-download/SKILL.md

source content

USGS Data Download Guide

Overview

This guide covers downloading water level data from USGS using the

dataretrieval

Python package. USGS maintains thousands of stream gages across the United States that record water levels at 15-minute intervals.

Installation

pip install dataretrieval

nwis Module (Recommended)

The NWIS module is reliable and straightforward for accessing gage height data.

from dataretrieval import nwis

# Get instantaneous values (15-min intervals)
df, meta = nwis.get_iv(
    sites='<station_id>',
    start='<start_date>',
    end='<end_date>',
    parameterCd='00065'
)

# Get daily values
df, meta = nwis.get_dv(
    sites='<station_id>',
    start='<start_date>',
    end='<end_date>',
    parameterCd='00060'
)

# Get site information
info, meta = nwis.get_info(sites='<station_id>')

Parameter Codes

Code	Parameter	Unit	Description
`00065`	Gage height	feet	Water level above datum
`00060`	Discharge	cfs	Streamflow volume

nwis Module Functions

Function	Description	Data Frequency
`nwis.get_iv()`	Instantaneous values	~15 minutes
`nwis.get_dv()`	Daily values	Daily
`nwis.get_info()`	Site information	N/A
`nwis.get_stats()`	Statistical summaries	N/A
`nwis.get_peaks()`	Annual peak discharge	Annual

Returned DataFrame Structure

The DataFrame has a datetime index and these columns:

Column	Description
`site_no`	Station ID
`00065`	Water level value
`00065_cd`	Quality code (can ignore)

Downloading Multiple Stations

from dataretrieval import nwis

station_ids = ['<id_1>', '<id_2>', '<id_3>']
all_data = {}

for site_id in station_ids:
    try:
        df, meta = nwis.get_iv(
            sites=site_id,
            start='<start_date>',
            end='<end_date>',
            parameterCd='00065'
        )
        if len(df) > 0:
            all_data[site_id] = df
    except Exception as e:
        print(f"Failed to download {site_id}: {e}")

print(f"Successfully downloaded: {len(all_data)} stations")

Extracting the Value Column

# Find the gage height column (excludes quality code column)
gage_col = [c for c in df.columns if '00065' in str(c) and '_cd' not in str(c)]

if gage_col:
    water_levels = df[gage_col[0]]
    print(water_levels.head())

Common Issues

Issue	Cause	Solution
Empty DataFrame	Station has no data for date range	Try different dates or use `get_iv()`
`get_dv()` returns empty	No daily gage height data	Use `get_iv()` and aggregate
Connection error	Network issue	Wrap in try/except, retry
Rate limited	Too many requests	Add delays between requests

Best Practices

Always wrap API calls in try/except for failed downloads
Check
```
len(df) > 0
```
before processing
Station IDs are 8-digit strings with leading zeros (e.g., '04119000')
Use
```
get_iv()
```
for gage height, as daily data is often unavailable
Filter columns to exclude quality code columns (
```
_cd
```
)
Break up large requests into smaller time periods to avoid timeouts