scientificwaterenvironmentclimatesustainabilityESGfreshwaterglobalcountry-level

Water Stress & Freshwater Access

2024

Free

Open dataset

Sample structure: 98.2 / 100

5 download links issued

Seller: waseemahmad

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Source, license and coverage

Supplier documentation. These claims are separate from the automated sample score. A listing edit date is not a data freshness date.

License: Not documented — confirm reuse terms with the seller
Source / creator: Supplier-cited: World Bank Open Data; World Resources Institute; FAO
Collection method: uploaded
Coverage / snapshot: 2024
Data last updated: Not documented
Update schedule: Not documented

Source documentation ↗

Source attribution is supplier-reported. The source link identifies publisher documentation; it does not independently verify this uploaded extract. Other cited publishers: World Resources Institute: https://github.com/wri/global-power-plant-database; FAO: https://www.fao.org/faostat/

Sample structure score: 98.2 / 100

This automated check describes the inspected sample, not factual accuracy, legal rights, representativeness, or the quality of the entire dataset. It is not a customer rating.

Assessed 10 sample records (CSV) on 2026-10-09. All records in the provided sample were checked.

Check	Points	Evidence
Populated cells	48.2 / 50	106 of 110 top-level cells contain a value. Null, absent and blank values count as missing; zero and false count as populated.
Consistent value types	30 / 30	106 of 106 populated cells match their column's most common observed type. Types are inferred, not checked against real-world truth.
Consistent record shape	20 / 20	10 of 10 records have the expected fields. CSV/TSV use the header width; JSON uses the union of observed keys.

Field-level findings and improvements

Check missing cells and mixed types below. Document intentional missing values or mixed types in your field descriptions. Do not fill legitimate unknowns with invented values just to increase this score.

Field	Missing cells	Most common type	Other populated types
Country	0 / 10	string	0 / 10
ISO_Alpha3	0 / 10	string	0 / 10
Region	0 / 10	string	0 / 10
Population_Millions_2024	0 / 10	number	0 / 10
WRI_Aqueduct_Baseline_Water_Stress_Score_0to5	0 / 10	number	0 / 10
Water_Stress_Category	0 / 10	string	0 / 10
Pct_Safely_Managed_Drinking_Water_JMP	4 / 10	number	0 / 6
Renewable_Freshwater_Per_Capita_m3_yr_FAO	0 / 10	number	0 / 10
Ag_Water_Withdrawal_Pct_of_Total_FAO	0 / 10	number	0 / 10
GDP_Per_Capita_USD_2024	0 / 10	number	0 / 10
Water_Productivity_USD_per_m3_2017	0 / 10	number	0 / 10

How the score is calculated, its limitations, and how to correct an assessment →

About this data

Multi-source dataset combining WRI Aqueduct baseline water stress scores, WHO/UNICEF drinking water access percentages, FAO renewable freshwater availability, and World Bank water productivity metrics across 67 countries. Covers all five stress categories from Low to Extremely High.

Retrieve with your agent or Python

Create an account and configure DATABAZAAR_API_KEY. This example retrieves free or already purchased data; it never makes a purchase. For a multi-file dataset, choose a file index from the manifest.

Download the Python example

python3 retrieve-dataset.py bb266903-0826-4320-ad41-87b1892ade1e --output dataset.bin

Full supplier documentation

Original supplier listing: Water Stress & Freshwater Access — 67 Countries (2024) Multi-source dataset tracking water stress levels, freshwater availability, and drinking water access across 67 countries spanning all continents and income levels. Combines data from four authoritative sources: WRI Aqueduct 4.0 baseline water stress scores (0-5 scale), WHO/UNICEF Joint Monitoring Programme safely managed drinking water percentages, FAO AQUASTAT renewable freshwater per capita and agricultural withdrawal ratios, and World Bank GDP and water productivity metrics. Covers all five water stress categories from Low to Extremely High. Ideal for environmental research, climate policy analysis, ESG scoring, and development economics.

Schema

Name	Type	Description
Country	string
ISO_Alpha3	string
Region	string
Population_Millions_2024	string
WRI_Aqueduct_Baseline_Water_Stress_Score_0to5	string
Water_Stress_Category	string
Pct_Safely_Managed_Drinking_Water_JMP	string
Renewable_Freshwater_Per_Capita_m3_yr_FAO	string
Ag_Water_Withdrawal_Pct_of_Total_FAO	string
GDP_Per_Capita_USD_2024	string
Water_Productivity_USD_per_m3_2017	string

Sample Data

Preview a sample of the data before downloading.

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For AI Agents

Via MCP Server

# 1. Add to your agent's MCP config (claude_desktop_config.json or similar):
{
  "mcpServers": {
    "databazaar": { "command": "npx", "args": ["databazaar-mcp"] }
  }
}

# 2. Your agent can then call:
search_datasets({ query: "Water Stress & Freshwater Acce" })
// Found: bb266903-0826-4320-ad41-87b1892ade1e
get_download_url({ dataset_id: "bb266903-0826-4320-ad41-87b1892ade1e" })  // free — sign in with MCP OAuth first

Via REST API

# Free dataset — sign in or use your account API key:
curl https://api.databazaar.io/datasets/bb266903-0826-4320-ad41-87b1892ade1e/download-url -H "Authorization: Bearer $DATABAZAAR_API_KEY"