World Resources Institute

Competition for and depletion of water in major agricultural areas. Proportion of crop production in areas facing different levels of water stress. Baseline water stress (Gassert et al. 2013) is a measure of demand and supply for water in a given area, and is calculated as the ratio of local water withdrawal over available water supply   Data citation: Aqueduct Global Maps 2.1 database is licensed under a Creative Commons Attribution International 4.0 License.

This dataset shows countries and river basins' average exposure to five of Aqueduct's water risk indicators: baseline water stress, interannual variability, seasonal variability, flood occurrence, and drought severity. Risk exposure scores are available for every country (except Greenland and Antarctica), the 100 most populous river basins, and the 100 largest river basins by area. Scores are also available for all industrial, agricultural, and domestic users' average exposure to each indicator in each country and river basin. Citation: Gassert, F., P. Reig, T. Luo, and A. Maddocks. 2013. “Aqueduct country and river basin rankings: a weighted aggregation of spatially distinct hydrological indicators.” Working paper. Washington, DC: World Resources Institute, November 2013. Available online at http://wri.org/publication/aqueduct-country-river-basin-rankings.

Recent Stress Ranking can be checked here: https://knoema.com/WRINWS2020/national-water-stress-rankings Suggested citation: Luo, T., R. Young, and P. Reig. 2015. "Aqueduct projected water stress rankings." Technical note. Washington, DC: World Resources Institute, August 215. Available online at http://www.wri.org/publication/aqueduct-projected-water-stress-country-rankings.    Supplemental Materials: Country Scores                         WRI projected future country-level water stress for 2020, 2030, and 2040 under business-as-usual (BAU), optimistic, and pessimistic scenarios. Each tab lists country projected water stress scores for each scenario and year, weighted by overall water withdrawals. Scores weighted by individual sectors (agricultural, domestic, and industrial) are provided as well.   These global projections are best suited to making comparisons among countries for the same year and among scenarios and decades for the same region. More detailed and localized data or scenarios can better estimate potential outcomes for specific regions and expose large sub-national variations that are subsumed under countrywide water-stress values. The country indicators face persistent limitations in attempting to simplify complex information, such as spatial and temporal variations, into a single number. They also do not account for the governance and investment structure of the water sector in different countries.    It is important to note the inherent uncertainty in estimating any future conditions, particularly those associated with climate change, future population and economic trends, and water demand. Additionally, care should be taken when examining the change rates of a country’s projected stress levels between one year and another, because the risk-score thresholds are not linear. For more information on these limitations, see the technical note.   Projections are described in further detail in: Luck, M., M. Landis, and F. Gassert, “Aqueduct Water Stress Projections: Decadal Projections of Water Supply and Demand Using CMIP5 GCMs,” Technical note (Washington, DC: World Resources Institute, April 2015), http://www.wri.org/publication/aqueduct-water-stress-projections.   Water Stress withdrawals / available flow Water stress measures total annual water withdrawals (municipal, industrial, and agricultural) expressed as a percentage of the total annual available blue water. Higher values indicate more competition among users. Score Value [0-1) Low (<10%) [1-2) Low to medium (10-20%) [2-3) Medium to high (20-40%) [3-4) High (40-80%) [4-5] Extremely high (>80%)    

Data Citation: CAIT Climate Data Explorer. 2017. Washington, DC: World Resources Institute. Available online at: http://cait.wri.org   CAIT data carries a Creative Commons Attribution-NonCommercial 4.0 International license   The data set contains emission projections reported by national government refered to "National Government" (the majority of which are National Communications and Biennial Reports submitted by governments to the UNFCCC), by the U.S. Energy Information Administration (EIA) and a set of Integrated Assessment Models (IAMs) from Netherlands Environmental Assessment Agency (PBL), International Institute for Applied Systems Analysis (IIASA), and Potsdam Institute for Climate Impact Research (PIK).    

Data cited at: World Resources Institute The Global Power Plant Database is a comprehensive, open source database of power plants around the world. It centralizes power plant data to make it easier to navigate, compare and draw insights for one’s own analysis. Each power plant is geolocated and entries contain information on plant capacity, generation, ownership, and fuel type. As of June 2018, the database includes around 28,500 power plants from 164 countries. It will be continuously updated as data becomes available. The most recent release of the Global Power Plant Database 1.1 includes the addition of two countries (China and Fiji), over 3,000 power plants, and nearly 1300 gigawatts of power capacity.Citation Global Energy Observatory, Google, KTH Royal Institute of Technology in Stockholm, Enipedia, World Resources Institute. 2018. Global Power Plant Database. Published on Resource Watch and Google Earth Engine; http://resourcewatch.org/https://earthengine.google.com/

string_id: contains a unique string for each geometry. Geometries are the union of hydrological basins, provinces and groundwater aquifers. String_id is a combination of pfaf_id-gid_1-aqid. name_0: Country bws_raw: raw value. Units depend on the indicator bws_score: each indicator is mapped to a [0-5] scale. bws_label: A label explaining the category of the indicator including the threshold. eg "Extremely High (more than 1 in 100)". w_awr_def_qan_raw raw value on 0-5 scale. Result of weighted composite approach w_awr_def_qan_score: score [0-5], the result of applying a quantile approach to raw values ​​w_awr_def_qan_label: A label explaining the category of the grouped water risk w_awr_def_qan_weight_fraction: the fraction [0-1] of the group towards the overall water risk score. NoData is excluded from the weights and therefore the fractions can be lower than 1 depending on data availability