Scaling Up Ecosystem Service Values: Methodology and Applications in Water Quality Changes

1. Luke Brander Institute for Environmental Studies (IVM), VU University Amsterdam Division of Environment, Hong Kong University of Science and Technology Email: lukebrander@gmail.com Scaling up ecosystem service values: methodology and applications. II – Value of changes in water quality Co-authors: Roy Brouwer, Tjasa Bole, Dolf de Groot, Salman Hussain, Onno Kuik, Alistair McVittie, Sander van der Ploeg, Peter Verburg, Alfred Wagtendonk

2. Outline • Introduction • Methodology: meta-analysis and GIS • Water quality value data • Water quality value function • TEEB case study: global value of water quality changes • Conclusions and discussion

3. Introduction • Need for value information at large spatial scales (e.g. river basin) • CBA of investments in water quality improvements • Assess disproportionate costs • Value of water quality improvements varies with body body, context and beneficiary characteristics

4. Proposed method for scaling up values • Construct database of primary value estimates • Estimate a meta-analytic value function (including water abundance variable) • Construct database of water bodies using GIS • Estimate site-specific values for changes in water quality • Aggregate across relevant population and spatial level Meta- analysis Spatial Data (GIS) Estimate values

5. Valuation of changes in water quality $/annum Change in value P1 Marginal value curve P0 Q1 Q0 Water quality

6. Water quality value data • AquaMoney database of water quality values • 154 contingent valuation studies (1981 – 2006) • 54 with complete information for meta-analysis • 388 value estimates • Wide variety of descriptions of water quality change standardised to 10-point water quality index • Standardised values to WTP/household/year (USD 2007 prices) • Mean = 130 USD/household/year • Median = 78 USD/household/year

7. Location of water quality value study sites

8. Ecosystem services valued

9. Meta-analytic value function • Dependent variable y: Annual WTP per household (USD 2007) • Study characteristics Xsi: • Valuation method • Water characteristics Xwi: • Baseline water quality • Change in water quality • Water body type • Context characteristics Xci: • GCP per capita • Abundance of lakes and rivers within 10km radius • Accessibility index • Urban extent within 20km radius

10. Meta-analytic value function

11. TEEB case study: global value of water quality change • TEEB Quantitative Assessment • Change in water quality 2000 - 2050 • OECD baseline scenario of population and development • IMAGE/GLOBIO model • Global coverage at 50km grid cell resolution • Nitrogen and phosphorous concentrations • Converted to 10-point water quality index • Large variation in positive and negative changes in water quality

12. Changes in water quality 2000-2050

13. Changes in water quality 2000 - 2050 • Water quality changes combined with global map of lakes and rivers • Global lakes and wetlands database GLWD (1x1km grid) • 375,316 water bodies (lakes and rivers) • Site specific characteristics are substituted into value function • Household WTP is aggregated across number of households in 50km grid cell

14. Annual values in 2050 (billions USD 2007)

19. Discussion and conclusions • Value transfer on a large scale • GIS to account for spatial variation • Scale, substitutes, and income effects • Limitations: • Does not produce service specific values • Partial valuation: value data is focussed on recreational uses • Partly accounts for changes in water quantity • Restricted measure of water quality • Difficult to identify relevant population for aggregation