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

nwis Module Functions

Returned DataFrame Structure

The DataFrame has a datetime index and these columns:

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

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