The Aqueduct Water Risk Atlas makes use of a framework, that includes 12 global indicators grouped into three categories of risk and one overall score. The data selection and validation process involves three steps:
a literature review,
identification of data sources in the public domain, and
the compilation and expert review of the selected data sources. Calculation of 6 of the 12 indicators required the creation of original datasets to estimate water availability and use. The hydrological catchments were based on the Global Drainage Basin Database developed by Masutomi et al. Computation of the original datasets was completed by ISciences, L.L.C.
Two measures of water use are required, water withdrawal, the total amount of water abstracted from freshwater sources for human use, and consumptive use, the portion of water that evaporates or is incorporated into a product, thus no longer available for downstream use. Withdrawals for the global basins are spatially disaggregated by sector based on regressions with spatial datasets to maximize the correlation with the reported withdrawals (i.e. irrigated areas for agriculture, nighttime lights for industrial, and population for domestic withdrawals). Consumptive use is derived from total withdrawals based on ratios of consumptive use to withdrawals from Shiklomanov and Rodda. Both withdrawals and consumptive use are coded at the hydrological catchment scale.
Two metrics of water supply were computed: total blue water and available blue water. Total blue water approximates natural river discharge and does not account for withdrawals or consumptive use. Available blue water is an estimate of surface water availability minus upstream consumptive use. Modeled estimates of water supply are calculated using a catchment-to-catchment flow- accumulation approach, which aggregates water by catchment and transports it to the next downstream catchment. Water supply is computed from runoff (R), the water available to flow across the landscape from a particular location, and is calculated as the remainder of precipitation P) after evapotranspiration (ET) and change in soil moisture storage (ΔS) are accounted for (i.e., R = P – ET – ΔS). The runoff data is courtesy of NASA Goddard Earth Sciences Data and Information Services Center’s Global Land Data Assimilation System Version 2 NOAH v. 3.3 land surface model for the years 1950 to 2010.