Data on surface water bodies like rivers, dams, reservoirs, and related  flow characteristics, along with assessments for water risks, stress, and flood risk. 

freshwater

Freshwater

Data related to water scarcity, water quality, flood risk, and water stress.

water-risks

Water Risks

### Overview  
  
This dataset shows the baseline water stress rating at a national scale. Baseline water stress is a measure of the level of competition for available freshwater. The dataset was calculated by comparing water withdrawals in a region to the quantity of water available. Higher water stress values indicate that there is more competition among people for available freshwater. The dataset was grouped by water usage for different sectors (agricultural, domestic, and industrial) to help understand which sectors had the greatest impact on water stress. The results were projected on a global map in five water stress risk categories: low, low to medium, medium to high, high, and extremely high.
  
  
Understanding water stress is integral for human wellbeing. Water is a limited resource and a necessity for life. Water stress can have serious environmental consequences, with damage occurring to natural ecosystems reliant on a steady water supply. Additionally, water stress can lead to human and business conflicts, particularly between industrial and agricultural users that rely on water supply for production.
  
  
This dataset was created by the World Resources Institute (WRI) to assist companies, investors, and governments in creating water use policies.
  
  
### Methodology  
  
The Water Stress Country Ranking is based on baseline water stress measurements. Baseline water stress measures the ratio of total water withdrawals to available renewable surface and groundwater supplies. Gridded output data from the [PCRaster Global Water Balance](https://gmd.copernicus.org/articles/11/2429/2018/) (PCRGLOBWB 2) hydrological model was used for both water withdrawal and available water. The water withdrawal output data from PCRGLOBWB 2 included monthly data from January 1960 to December 2014 for four sectors: domestic, industrial, irrigation, and livestock. Output data for available water was also available over the same time frame. Data from the model was then aggregated spatially to the sub-basin level using the World Wildlife Fund’s (WWF) [HydroBASINS level 6](https://hydrosheds.org/page/hydrobasins) hydrological sub-basins. Next, the data was regressed at the sub-basin level using an ordinary least square (OLS) regression with a trailing moving window size of 10 years to reduce noise in the data. This process resulted in gross water withdrawal and available water for each month for each sub-basin in the dataset. 
  
  
Next, the overall baseline water stress per month, per year, per sub-basin was determined. This was done by dividing the gross total water withdrawal by the difference between the available water and consumptive water withdrawal. This resulted in 12 time series of baseline water stress for each sub-basin: one time series for each month, with each time series spanning the years 1960-2014. Then, a single baseline water stress value for each month in each sub-basin was calculated by fitting a second OLS regression to each of the 12 time series and using the value for 2014 as the baseline water stress for that month. While the 2014 regression value is used, this value actually represents the baseline value, rather than an estimate of the water stress in 2014.
  
  
To compute national baseline water stress scores, the sub-basins had to be aggregated to a national scale. Aggregation was made possible by following the steps outlined on page 4 of the [2013 version](https://files.wri.org/s3fs-public/aqueduct_coutnry_rankings_010914.pdf) of the methodology. This resulted in raw country score percentages in which water stress was classified as follows:
- Low (0-1): <10%
- Low to medium (1-2): 10-20%
- Medium to high (2-3): 20-40%
- High (3-4): 40-80%
- Extremely high (4-5): >80%
  
  
Each category represents the risk of water stress in the country. For the full documentation, please see the source [methodology](https://files.wri.org/s3fs-public/aqueduct-30-updated-decision-relevant-global-water-risk-indicators_1.pdf).  
  
### Additional Information  
  
Resource Watch also shows [interannual variability](https://resourcewatch.org/data/explore/wat052-Aqueduct-Interannual-Variability) and [seasonal variability](https://resourcewatch.org/data/explore/wat053-Aqueduct-Seasonal-Variability) in water supply from the same dataset.  
  
  
Resource Watch shows only a subset of the dataset. Additional information on drought risk and riverine flood risk is available from the data provider. For access to the full dataset and additional information, click on the “Learn more” button.
  
  
### Visualizing the Data  
  
Our team reformatted this dataset before displaying it on Resource Watch. See the documentation on how Resource Watch processed the data on [Github](https://github.com/resource-watch/data-pre-processing/tree/master/wat_036_rw1_water_stress_country_ranking). This data has been mapped on Resource Watch by joining it with Natural Earth boundaries.  
  
### Disclaimer  
  
Excerpts of this description page were taken from the source metadata.

Aqueduct Country and River Basin Rankings

wat-036-rw1water-stress-country-ranking-rw

1960-2014 Baseline Water Stress Score

Global baseline water stress score by country

No Team

Water Stress Country Ranking

1960-2014 Baseline Water Stress Score