NWIS Data Downloader

A Python package to fetch and process daily USGS National Water Information System (NWIS) data. Supports batch downloading across many sites and parameters, dynamic parameter code discovery, and filtering for data quality.

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Features

• Dynamic Parameter Discovery – Fetch and search all USGS parameter codes (e.g., discharge, sediment, temperature).
• Batch Fetching – Robust multi-site downloads with progress bars and retries.
• Data Processing – Convert NWIS JSON responses into tidy Pandas DataFrames.
• Filtering Tools – Keep only sites with sufficient data for desired variables.
• Robust & Safe – Handles rate limits, errors, and empty responses gracefully.

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Installation

pip install nwis-data-downloader

Or install from source:

git clone https://github.com/bluerrror/NWIS_Data_Downloader.git
cd NWIS_Data_Downloader
pip install -e .

Requirements: Python ≥ 3.8, plus requests, pandas, tqdm.

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Common Parameter Codes

Some frequently used USGS parameter codes (from USGS documentation):

Parameter Code	Short Name	Description	Units
00010	Temperature	Water temperature	°C
00060	Discharge	Streamflow discharge	ft³/s
00065	Gage Height	Gage height	ft
00045	Precipitation	Precipitation depth	in
00400	pH	pH value	unitless
00630	Nitrate	Nitrogen, nitrate	mg/L as N
00631	Nitrate + Nitrite	Nitrate plus nitrite	mg/L as N
80155	Suspended Sediment	Suspended sediment concentration	mg/L

For a complete list, call:

get_usgs_parameters()

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Quickstart

1. Discover and Search Parameters

from usgs_data_fetcher import get_usgs_parameters, search_parameters

params_df = get_usgs_parameters()
print(f"Total parameters: {len(params_df)}")

# Search for discharge-related parameters
discharge_params = search_parameters(params_df, 'discharge')
print(discharge_params[['parm_cd', 'parameter_nm', 'parameter_unit']].head())

# Example: search for temperature or pH
wq_params = search_parameters(params_df, 'temperature OR pH', columns=['parameter_nm'])
print(f"Water Quality Matches: {len(wq_params)}")

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2. Fetch Data for a Single Site

from usgs_data_fetcher import fetch_usgs_daily, usgs_json_to_df

site = '01491000'
json_data = fetch_usgs_daily(
    sites=[site],
    parameter_codes=['00060'],  # Discharge
    start='2024-01-01',
    end='2025-01-01'
)

df = usgs_json_to_df(json_data)
print(df.head())
print(df.shape)

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3. Batch Fetch with Filtering

from usgs_data_fetcher import fetch_batch_usgs_data

sites = [
    '01491000',
    '01646500',
    '09522500'
]

selected_codes = ['00060', '80155']  # Discharge + Suspended Sediment

data_df = fetch_batch_usgs_data(
    sites=sites,
    parameter_codes=selected_codes,
    start='2000-01-01',
    end='2025-01-01',
    required_params=['80155'],
    min_records=100,
    batch_size=10
)

print(data_df.shape)
print(data_df.describe())

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4. Interactive Parameter Selection

import pandas as pd
from usgs_data_fetcher import get_usgs_parameters, search_parameters

params_df = get_usgs_parameters()
query = input("Enter search term (e.g., 'sediment'): ").strip()
matches = search_parameters(params_df, query)

if not matches.empty:
    print(matches[['parm_cd', 'parameter_nm']].to_string(index=False))
    codes = input("Enter comma-separated codes (or 'all'): ").strip()
    selected_codes = matches['parm_cd'].tolist() if codes.lower() == 'all' else [c.strip() for c in codes.split(',')]
    print(f"Selected: {selected_codes}")
else:
    print("No matches found.")
    selected_codes = ['00060']  # Default

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5. Save & Visualize Data

import matplotlib.pyplot as plt

data_df.to_csv('usgs_hydrology_data.csv', index=False)

data_df['time'] = pd.to_datetime(data_df['time'])
plt.figure(figsize=(12, 6))

for site in data_df['site_no'].unique()[:2]:
    site_data = data_df[data_df['site_no'] == site]
    plt.plot(site_data['time'], site_data['00060'], label=f'Site {site}')

plt.xlabel('Date')
plt.ylabel('Discharge (cfs)')
plt.title('Daily Streamflow Trends')
plt.legend()
plt.savefig('discharge_plot.png')
plt.show()

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API Reference

Core Functions

• fetch_usgs_daily(sites, parameter_codes, ...) — Fetch raw NWIS daily JSON data.
• usgs_json_to_df(json_data) — Convert JSON to tidy DataFrame.
• fetch_batch_usgs_data(sites, parameter_codes, ...) — Multi-site batch fetch with filtering.

Parameter Utilities

• get_usgs_parameters() — Download complete parameter catalog.
• search_parameters(params_df, query, ...) — Query parameters by keyword.

Full documentation can be found in fetcher.py and parameters.py.

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Examples

• Water Quality Batch: Use ['00010', '00400'] for temperature + pH.
• Precipitation Analysis: Use ['00045'] for precipitation depth.
• Large-Scale Fetching: Set batch_size=200 for thousands of sites.
• Error Handling: Wrap fetches in try/except for production pipelines.

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Contributing

1. Fork the repo
2. Create a feature branch:

   git checkout -b feature/amazing-feature
   

3. Commit changes:

   git commit -m "Add amazing feature"
   

4. Push:

   git push origin feature/amazing-feature
   

5. Open a Pull Request

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License

MIT License — see LICENSE for details.

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Acknowledgments

Built on the excellent USGS NWIS API:
https://waterservices.usgs.gov