Providing water in areas with unsustainable usage

Fresh water is a fundamental requirement for humanity’s wellbeing. However, more than one billion people today are without safe drinking water. The United Nations (UN) estimates 20% of the world’s population lives in areas with unsustainable water use and predicts that by 2025 two-thirds of the population will live in water-stressed conditions. Water for the World, a program to bring fresh water to those who do not have it, is supported by the US National Aeronautics and Space Administration and the IEEE Foundation. The program is part of IEEE’s collaboration with Group on Earth Observations (GEO), a voluntary partnership of governments and international organizations that provides a framework for developing new projects and coordinating strategies and investments. GEO also is assembling a Global Earth Observation System of Systems (GEOSS), a flexible global network linking existing and planned observing systems around the world, to allow decisionmakers and users access to an vast range of information. This data and these tools are central to accomplishing Water for the World’s mission. Water for the World is being implemented in three phases.1 The first phase produced a ‘vision’ that identified realizable activities to deliver adequate clean water to much of the world. It also described suitable pilot projects to demonstrate the utility of the vision’s proposals. The second phase outlines 15 pilot projects, three of which have been started. The final phase will focus on institutionalizing an accepted and supported international plan to provide a Water for the World project that can be owned and directed by users and beneficiaries. The Water for the World leadership held several global meetings to identify the 15 key phase-two projects, which—when successfully implemented—are expected to make significant impact on solving global water issues. The three active pilot projects Figure 1. Identification of micro level in-field water harvesting sites in northwestern India using the Earth observation dataset.