Indicator Code: WATQI
Objective: Ecosystem Vitality
Policy Category: Water Subcategory Water (Effects on Environment)
Indicator Short Name: Water Quality Index
Indicator Full Name: Water Quality Index

Indicator Description: The water quality parameters chosen to be included in the EPI were selected for two reasons. Firstly, they are good indicators of specific issues relevant on a global basis (eutrophication, nutrient pollution, acidification, salinization). Secondly, the parameters were chosen because they are the most consistently reported; that is, we have the most data for these parameters compared to other relevant parameters that were not included. Because water quality is a function of a number of different physical and chemical parameters measured during routine water quality monitoring, as outlined above, a global index of the general status of water quality, ranked on a country by country basis, is best developed as a composite index of several key parameters.

Units: Proximity-to-Target
Country Coverage: 232: 94 countries with quality monitoring data; 138 countries with imputed water quality
Reference Year: 2003 (average year for all stations and parameters)
Target: proximity-to-target score of 100 (based on monitoring station parameter scores)
Target Source: Expert judgment and national standards (see EPI Water Quality Expert Group report)
Short Source: GEMS, 2008
Source: United Nations Environment Program GEMS/Water Programme 2008, online database available at: http://www.gemstat.org

European Environment Agency Waterbase Rivers & Lakes data sets, v7 (2007), available at: http://www.eea.europa.eu/themes/water/datasets

Taiwan Environmental Protection Administration Executive Yuan, R.O.C. 2005. River and lake water quality data available at: http://edb.epa.gov.tw/eng/Index_water.htm

National contacts: Niger: Mr. Ilia Bounari, Hydrochimie à la Division de la Qualité et Pollution des Eaux, Niger Algeria : Mr. Mohamed Ramdane, Agence Nationale des Ressources Hydrauliques, ALGERIE Israel: Dr. Ami Nishri, Kinneret Limnological Laboratory, Israel Oceanographic & Limnological Research.
Source URL: http://www.gemswater.org

Methodology: WATQI is a proximity-to-target composite indicator with station density adjustment that was calculated as follows. Raw data for five parameters—Disolved Oxygen (DO), Electrical Conductivity (EC), pH, Total Phosphorus (P) (or Ortho Phosphorus), Total Nitrogen (N) (or Dissolved inorganic Nitrogen, Nitrate+Nitrite, or Ammonia)—were obtained from UNEP/GEMS Water and European Environmental Agency (EEA) Waterbase, and national sources listed in the source field. The raw data for all parameters except pH and DO were winsorized (trimmed) at the extreme 95th percentile. Then proximity-to-target (PTT) values were calculated using the targets specified by UNEP/GEMS water such that 100 corresponds to meeting the target (or falling into the target range in the case of pH) and values between 0 and less than 100 indicate an increasing distance from the target (or target range in the case of pH). The individual targets used were as follows: DO of 6 mg/L for “warm waters” (>20C) and 9.5 mg/L for “cold waters” (<20C); pH of 6.5-9.0; EC of 500 micro-Siemens/cm; P of 0.05 mg/L (or 0.025 for orthohosophate); N of 1 mg/L (or 0.5 for dissolved inorganic N or nitrate+nitrite and 0.05 for ammonia). Total N and Total P are the preferred indicators of nutrient pollution; thus, maximum possible scores for countries that reported other forms of nutrients were adjusted such that the best possible PTT scores for Ortho P and Dissolved inorganic N were set to 80, and for Nitrate+Nitrite and Ammonia were set to 60. Station-level PTT values were summed and divided by 5 to generate a station-level WQI that ranged from 0 to 100. Station-level WQI’s were averaged to country WATQI’s using only those stations that report the maximum number of parameters within the country.

Country WATQIs were adjusted for density of monitoring stations based on national water quality monitoring data collated by UNEP/GEMS Water. Country WATQI scores were adjusted using the following multipliers based on the density of the monitoring station network per populated land area (land area populated at >5 persons per sq. km, as calculated by CIESIN, 2007). Countries received full credit (using a multiplier of 1) if they have a station density greater than or equal to 1 per 1,000 sq. km; PTT scores were multiplied times 0.95 if they had a station density of 0.1-0.99 per 1,000 sq. km; PTT scores were multiplied times 0.9 if they had a station density of 0.01-0.099 per 1,000 sq. km; PTT scores were multiplied times 0.85 if they had a station density of 0.001-0.0099 per 1,000 sq. km; and PTT scores were multiplied times 0.8 if they had a station density of <0.001 per 1,000 sq. km.

We were able to use the above methodology to complete data for 94 countries. For countries with no WATQI from UNEP/GEMS or the EEA, a regional imputed value was used according to this rule: For UNEP-GEO subregions with UNEP/GEMS WATQI available for at least half of the countries in that region, the 0.33 percentile WATQI was used; for UNEP-GEO subregions with UNEP/GEMS WQI available for less than half of the countries in that region but more than 3 WQIs, the average minus a 10 point penalty was used. For remaining regions, we applied the following method: for Meso-America the average of available WQI’s for Meso and North America minus a 10pt penalty was used; for Eastern Africa, we took the average for Kenya and Uganda and applied a 10 point penalty; for Southern Africa we took the average for South Africa and Tanzania and applied a 10 point penalty; for Central Africa we took the score for the Democratic Republic of Congo and applied a 10 point penalty; for Centeral Asia we took the average of the 33rd percentile score for South Asia and the score for Russia with a 10 point penalty; for the Caribbean we took the score for Cuba with 10 point penalty; for the South Pacific we took the average scores for Fiji and Papua New Guinea and applied a 10 point penalty; for the Arabian Peninsula & Mashriq, we took the average scores for Iraq and Jordan and applied a 10 point penalty.

Additional Citations: Center for International Earth Science Information Network (CIESIN), Columbia University, (2007). National Aggregates of Geospatial Data: Population, Landscape and Climate Estimates, v. 2 (PLACE II), Palisades, NY: CIESIN, Columbia University. Available at: http://sedac.ciesin.columbia.edu/place/