Nature's contribution to SDG 6
Many parts of the planet have multiple, sometimes conflicting, sometimes synergistic, values to society when viewed through the lens of the Sustainable Development Goals (SDGs), The spatial mapping of SDGs and their coincidence has the potential to add a useful tool to support the implementation of SDG strategies and also to inform the further development of the SDG concept.
These maps represent a proof of concept analysis of nature's contribution to the delivery of targets under SDG 6 (freshwater). The maps show the spatial ‘footprint’ or area of natural land contributing to the delivery of targets 6.1(drinking water), 6.2 (sanitation and hygiene) and 6.6 (water related ecosystems) weighted by nr of downstream beneficaries. Within these footprints, the co-benefits for biodiversity (SDG 15) , carbon sequestration (SDG 13) and trade-offs with agricultural suitability (SDG 2) (SDG 2) were assessed as % of total within the top 50% (by area) of the footprint by country (click on country).
The maps were generated using the freely available web based Co$ting Nature and WaterWorld Policy Support Tools developed by King's College London and AmbioTEK. You can use Co$tingNature and WaterWorld to carry out analysis at country or basin scale.
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Methods
SDG target 6.1 is about achieving universal and equitable access to safe and affordable drinking water for all. Maintaining nature's contribution to universal access to safe water requires the sustainable use of all natural land that provides any clean water to any human populations downstream. In order to prioritise these were weighted by number of downstream people. Nature's contribution to 6.1 are the dilution services provided by clean water running off natural and semi-natural lands, therefore diluting pollutants from water generated on human land uses. This was calculated using the WaterWorld Natural Footprint on Water Quality (NFWQ) metric which represents the per-pixel percentage of clean water. The NFWQ is calculated from the Human Footprint on Water Quality (HFWQ). Where a pixel has no water balance or runoff (evapotranspiration>=precipitation) the NFWQ is zero since there is no downstream influence of this pixel. In order to prioritise, the NFWQ is normalised and weighted by downstream population such that the product of NFWQ and downstream population represents an index of priority based on the highest priority being those areas with a high NFWQ available to many downstream people.
The HFWQ (Mulligan, 2009) is a measure of the extent to which runoff is drawn from contaminating human land uses both point (urban, roads, mining, oil and gas) and non-point (unprotected cropland, unprotected pasture). Agriculture within protected areas is assumed to be highly regulated and thus non-polluting). This is calculated relative to runoff generated from upstream non-human, non-polluting land uses. Each land use class has an associated pollution (or dilution) intensity fraction, which is user-changeable as an area-wide constant or a spatially variable value, to reflect different eco-efficient management or pollution risk intensities. The default values are shown in table 1 below and reflect the usual fractional cover and intensity of contaminant inputs for each land use at each spatial resolution
Table 1 
The HFWQ is the percent of runoff at any point that fell as rainfall on these potentially contaminating land uses upstream. It is thus a measure of the ecosystem service of dilution of contaminated runoff from human land uses, by clean runoff from natural areas. It is calculated by cumulating the downstream runoff from polluting and non-polluting land uses and expressing the former runoff as a proportion of the total runoff. Runoff is calculated as the downstream cumulated water balance based on (rainfall+fog+snowmelt)-actual evapotranspiration (WaterWorld) or rainfall (Hijmans et al., 2005) minus actual evapotranspiration (Mulligan et al. 2011) (Co$tingNature). The dilution service provided is thus 100 minus the HFWQ. Areas with extensive agriculture or urban areas will leave a significant footprint on water downstream. This may be diluted as waters coming from undisturbed areas or protected areas. The influence of small (areal) footprint sources such as mines or oil and gas will tend to diminish quickly downstream whereas large areal footprint areas will influence downstream waters for much further. For further detail, see Mulligan (2009).
The NFWQ is (100-HFWQ) and thus represents the amount of runoff in a pixel that is unaffected by human land use. It is thus an index of the dilution ecosystem services provided by natural land as this proportion of water mixes with the proportion that is human affected to produce the overall water quality.
SDG target 6.2 is to 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. Nature's contribution to sanitation is the dilution of the human footprint on water quality (diarrheal disease) by clean water i.e. dilution of effluent from sewage and livestock. Where a pixel has no water balance or runoff (evapotranspiration>=precipitation) the NFWQ[DD] is zero since there is no downstream influence of this pixel. In order to prioritise, the NFWQ[DD] is normalised and weighted by downstream population such that the product of NFWQ[DD] and downstream population represents an index of priority based on the highest priority being those areas with a high NFWQ[DD] available to many downstream people
The NFWQ[DD] is (100-HFWQ[DD]) and thus represents the amount of runoff in a pixel that is unaffected by contamination of DD vectors livestock and population. It is thus an index of the dilution ecosystem services provided by natural land as this proportion of water mixes with the proportion that is human affected to produce the overall bacterial and viral water quality.
SDG 6.6 is to is to Protect and restore (Nature's contribution to) water-related ecosystems, including mountains, forests, wetlands, rivers, aquifers and lakes. The named systems are examples, all natural (or part-natural) systems that have a hydrological footprint downstream will need sustainable use to fully achieve this target. In addition, non-natural systems require grey infrastructure to replace the functions formerly provided by natural systems. All natural, semi-natural areas beside the most intensively cultivated croplands contribute to this footprint. We use the NFWQ to capture the service provided by well functioning water-related ecosystems. In order to prioritise, the NFWQ is normalised and weighted by all downstream water uses (population,dams, irrigation) such that the product of NFWQ and the downstream beneficiaries represents an index of priority based on the highest priority being those areas with a high NFWQ available to many downstream beneficiaries.
Co-benefits are assessed via two key datasets Saatchi et al (2011) for Carbon stock and Mulligan (2018) for Species Endemism Richness. The footprint of the SDG targets are mapped and for the top 50% of areas of those areas (on the basis of the mapped beneficiaries) within each country, the proportion of the country's carbon or biodiversity within that footprint is calculated and then mapped at the global scale in order to represent the proportion of the co-benefit retained if a prioritisation that would protect or sustainably manage the top 50% of land underpinning the SDG target were realised. This is expressed per country. The same analysis is carried out against the FAO (2012) crop suitability data as processed by MUlligan (2013) into mean crop suitability (non-irrigated) as a means of capturing the trade-off of the SDG6 footprints for agriculture.
Saatchi S, Harris NL, Brown S, Lefsky M, Mitchard ET, Salas W, Zutta BR, Buermann W, Lewis SL, Hagen S, Petrova S, White L, Silman M, Morel A. (2011). Benchmark map of forest carbon stocks in tropical regions across three continents. Proc Natl Acad Sci U S A. 2011 Jun 14;108(24):9899-904. and Ruesch, Aaron, and Holly K. Gibbs. 2008. New IPCC Tier-1 Global Biomass Carbon Map For the Year 2000. Available online from the Carbon Dioxide Information Analysis Center http://cdiac.ornl.gov], Oak Ridge National Laboratory, Oak Ridge, Tennessee.
Mulligan, M. (2018) Species endemism richness of red-list species (mammals, amphibians, reptiles, birds). Model results from the Costingnature version 3 policy support system (non commercial-use).http://www.policysupport.org/costingnature [prepared by user mark.mulligan_kcl.ac.uk]
Mulligan, M. (2013) SimTerra : A consistent global gridded database of environmental properties for spatial modelling. http://www.policysupport.org/simterra [based on FAO (2012) Agro-ecological suitability and productivity.Crop suitability index (class).]
Mulligan, M. (2018) Relative realised water provisioning services index. Model results from the Costingnature version 3 policy support system (non commercial-use). http://www.policysupport.org/costingnature [prepared by user mark.mulligan_kcl.ac.uk]
Mulligan, M. (2018) Nature's contribution to SDG 6.1 (drinking water). Model results from the Costingnature version 3 policy support system (non commercial-use). http://www.policysupport.org/costingnature [prepared by user mark.mulligan_kcl.ac.uk]
Mulligan, M. (2018) Nature's contribution to SDG 6.2 (sanitation and hygiene). Model results from the Costingnature version 3 policy support system (non commercial-use). http://www.policysupport.org/costingnature [prepared by user mark.mulligan_kcl.ac.uk]
Mulligan, M. (2018) Nature's contribution to SDG 6.6 (functional water-related ecosystems). Model results from the Costingnature version 3 policy support system (non commercial-use). http://www.policysupport.org/costingnature [prepared by user mark.mulligan_kcl.ac.uk]
The maps were generated using the freely available web based Co$ting Nature and WaterWorld Policy Support Tools developed by King's College London and AmbioTEK
You can use Co$tingNature and WaterWorld to carry out analysis at country or basin scale