Microproduct Data GuideBeginner

U.S. Drought Monitor

Weekly U.S. drought-category statistics for building local agricultural, water, and risk-monitoring tools.

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At a Glance

Difficulty
Beginner — comfortable for a first prototype
Size
Tiny · ≤0.05 GB
Formats
JSON, CSV, XML
Access
API or Download
API Key
Not Required
Provider
National Drought Mitigation Center
Updates
Weekly
Last Verified
Aug 18, 2026
Source Type
Academic Source
  • Python Syntax Checked
  • Runnable Notebook

From Source to Product Signal

Test a Product Idea in Four Steps

The U.S. Drought Monitor REST services return weekly None and D0–D4 area statistics for a selected geography. Start with one state's two-digit FIPS code (Colorado is 08) and a few months. Categories are expert-blended drought intensity, not crop-loss claims, water-right determinations, or a forecast.

1

Check the Setup

  • Python 3.10 or newer
  • A notebook environment such as Jupyter or Google Colab
  • An internet connection
2

Access the Data

  1. 1.Read the web-service documentation and choose StateStatistics with percent-of-area output.
  2. 2.Request JSON for one state FIPS code and a bounded date window.
  3. 3.Cite NDMC, USDA, and NOAA with the retrieval date before charting D0–D4 shares.
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3

Run the Python Example

Install the packages, then run the notebook cell.

python -m pip install pandas requests

import pandas as pd
import requests

response = requests.get(
    "https://usdmdataservices.unl.edu/api/StateStatistics/GetDroughtSeverityStatisticsByAreaPercent",
    params={
        "aoi": "08",
        "startdate": "1/1/2025",
        "enddate": "3/25/2025",
        "statisticsType": 1,
    },
    headers={"Accept": "application/json"},
    timeout=30,
)
response.raise_for_status()
drought = pd.DataFrame(response.json())
drought["retrieved_at_utc"] = pd.Timestamp.now(tz="UTC")
print(drought.head())
4

Test a Useful Signal

Track One State's Weekly Drought Coverage

Describe how much of Colorado spent time in D1 or worse during a bounded winter window.

  1. 01Convert the week dates and keep D0–D4 percent-of-area columns.
  2. 02Plot D1 or worse over time and note weeks with missing or zero values.
  3. 03State that D-categories are not insurance triggers and that county statistics can differ from the state series.

Dataset Details

National Drought Mitigation Center is an academic source. Last verified 2026-08-18. Temporal coverage: 2000-present.

Geography

Formats

Provider

National Drought Mitigation Center

Data Terms

U.S. Drought Monitor citation policy (NDMC, USDA, and NOAA)

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