OWG draft targets for the Water SDG prepared for the UN General Assembly 6.1 by 2030, achieve universal and equitable access to safe and affordable drinking water for all 6.2 by 2030, achieve access to adequate and equitable sanitation and hygiene for all, and end open defecation, paying special attention to the needs of women and girls and those in vulnerable situations 6.3 by 2030, improve water quality by reducing pollution, eliminating dumping and minimizing release of hazardous chemicals and materials, halving the proportion of untreated wastewater, and increasing recycling and safe reuse by x% globally 6.4 by 2030, substantially increase water-use efficiency across all sectors and ensure sustainable withdrawals and supply of freshwater to address water scarcity, and substantially reduce the number of people suffering from water scarcity 6.5 by 2030 implement integrated water resources management at all levels, including through transboundary cooperation as appropriate 6.6 by 2020 protect and restore water-related ecosystems, including mountains, forests, wetlands, rivers, aquifers and lakes 6.a by 2030, expand international cooperation and capacity-building support to developing countries in water and sanitation related activities and programmes, including water harvesting, desalination, water efficiency, wastewater treatment, recycling and reuse technologies 6.b support and strengthen the participation of local communities for improving water and sanitation management

The global water system has natural and human components (Oki and Kanae, Science, 2006)

This map from AQUEDUCT shows that we have a good understanding of the basins that are producing the waste water (Red basins have the highest emissions)

The challenge is to find data to address separate parts of the waste water path Containment Emptying Transport Treatment Reuse/Disposal improved and unimproved sanitation facilities Off-site (sewered) % Access to basic sanitation Def 3: Are stored on site until they are safe to handle and re-use % Safely Reused On-site (pits, septic tanks etc) % of wastewater treated % safely managed services House hold surveys WHO/ UNICEF JMP Regulators, Utilities, AquaStat, IBNET Triangulation Primary data, estimates technology classification Utilities, AquaStat, models? very limited data Household surveys (possibly) ? (from WHO)

Satellite Data can provide high resolution imagery for inspection of potential problem areas Local Treatment Pond? Fertilizers: Source of nutrients in the runoff Wastewater disposal channel ?

7 Requirements for monitoring the Water SDG Indicators Global advocacy: monitoring for action Measuring progress for the global community Informing global investments Informing investments at country level by governments and donors Supporting regional and country benchmarking and reporting Focus on national governments and citizens

Target 6.3: Possible waste water indicator: A consolidated indicator of waste water production, treatment and reuse/recycling Rationale: AQUASTAT and national Environment agencies have reliable statistics for some countries but these data are limited. Estimates generated by a global algorithm and validated by AQUASTAT data may hold the greatest promise. EO support for the indicator: Population densities derived from Landsat data can be combined with census data to estimate waste water generation potential, releases and their impacts. 1) High resolution satellite images could document the location of treatment facilities. 2)

GIS layering allows integration of EO and other data Water accessibility: (combination of layers ‘a’ and ‘d’) Access measured in amount of energy per capita (calories) needed to collect water, highlighting access limitations due to terrain. Also shows populations living on marginal land without water access. Water resources per person: (combination of layers ‘b’ and ‘d’) Determines whether underlying water resources (aquifer yield) can meet demand of overlying population based on 50 liters per person per day. Areas with improved water access: (combination of layers ‘c’ and ‘d’) Displays 1-km LandScan areas that have achieved water access per guidelines, i.e. at least one access point per 1- sq.km (a) Digital Elevation Model (DEM): Worldwide coverage from NASA’s ASTER mission with 30-meter resolution. (b) Water Resource Map: Aquifer yield data from multiple sources. (c) Improved water source location: Location of wells continually updated with new water projects via interactive Web 2.0 application. (d) LandScan Population Database: commercially available 1-kilometer population database updated yearly ( /landscan_data_avail.shtml). (a) (b) (c) (d) INPUT LAYERS: COMBINED OUTPUT LAYERS :

Models allow the dynamics of waste water situations to be monitored (after T. Koike). Precipitation data from satellites can be input to a hydrologic model that routes the water through the urban drainage system (e.g. Hue Citadel in Viet Nam.). Areas of overflow under during heavy rains are often polluted. As shown below dry conditions can also cause water quality problems: Past inundation record C1C1 C3C3 C2C2 C1 and C3 are affected by the river water inflow from river water. At C2, canal water might be stagnant and less diluted by river water.

Target 6.3: Possible indicator: Adoption of the UN Water recommendation related to nitrogen and phosphorus pollution producing algal blooms that accumulate in large lakes, water bodies and coastal zones. Rationale: GEMSTAT data are very helpful in identifying water quality in countries where they are available. EO data combined with a model could provide information for every country. EO support for the indicator:. LANDSAT and MODIS data provide global data on phytoplankton blooms and sedimentation Hydrologic models can estimate the movement and changes of concentrations of pollutants (incl. N and Ph) in rivers

New approach: The use of real-time Population with toilets connected to sewer > 90% 51 – 90% % <25% Data not available

Summary There are some countries which collect high resolution Earth observation data for public purposes. These data represent a rich resource for use in monitoring waste water production and treatment capabilities. With some modifications and integration with other data sets these data could be used to monitor indicators related to waste water on a geospatially consistent basis for the entire globe. The resultant maps could show indicators on the time scales needed for biannual SDG reporting and for real-time interventions in areas where indicator thresholds are being exceeded.