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1 In the format provided by the authors and unedited. DOI: /NGEO3047 Quality matters for water scarcity Michelle T.H. van Vliet 1*, Martina Flörke 2, Yoshihide Wada 3 1 Water Systems and Global Change group, Wageningen University, PO Box 47, 6700 AA Wageningen, Netherlands 2 Center for Environmental Systems Research, University of Kassel, Wilhelmshöher Allee 47, Kassel, Germany 3 International Institute for Applied Systems Analysis (IIASA), Schlossplatz 1, A 2361 Laxenburg, Austria * corresponding author: michelle.vanvliet@wur.nl NATURE GEOSCIENCE 1

2 1. Global hydrological models and datasets We used monthly simulations of water availability (i.e. discharge) and river water temperature on 0.5 x0.5 for of three global hydrological models (GHMs): PCR-GLOBWB 1-3, VIC-RBM 4-7 and WaterGAP as described by van Vliet et al. 11. These three GHMs were selected because of their ability to simulate water availability, river water temperatures and sectoral water uses on a global scale. The GHMs vary in levels of complexity in different process descriptions and can therefore be used to capture uncertainties related to the model structure and parameterization of hydrological processes and sectoral water use descriptions. Each of the three GHMs was forced with the global meteorological WATCH forcing data (WFD) for Discharge and water temperature simulations based on WFD for were previously evaluated with observed records of 1634 discharge stations of the Global Runoff Data Centre (GRDC) and 343 stream temperature stations of the Global Environment Monitoring System (GEMS/Water) showing a reasonable representation of the observed conditions by the GHMs 11. For the calculations of total water scarcity, we included GHM-mean monthly simulations of irrigation, domestic and manufacturing water uses for ,13. Annual time series of domestic and manufacturing water uses from WaterGAP were converted to monthly records by assuming equal distribution over the year. 2. Seasonal impacts on water scarcity including water quality We first assessed water scarcity levels including several water quality parameters that are relevant for various sectors of the Pearl River at Guangzhou (China) as an example (Fig. 1 of main text). We focussed on the combined impacts of increased salinity (electrical conductivity) for irrigation water use, exceeded nutrients (ammonia) concentrations for drinking water uses, and high water temperatures for cooling water use by the energy sector. Guangzhou (Pearl basin) was selected because of sufficient availability of observed records of electrical conductivity (EC), ammonia (NH3) and water temperature. In this river basin, water quality thresholds for various water uses are exceeded, and this commonly occurs during different months of the year. We used observed water quality records of EC, NH3 and water temperature for the Guangzhou station (in the Pearl River Delta) for from the United Nations Global Environment Monitoring System (GEMS/Water) and extracted the monthly simulated water availability and sectoral water withdrawals for irrigation, domestic and thermoelectric power (GHM-ensemble mean) (Section 1). For the sectoral water quality requirements we used international guidelines rather than national or basin authority guidelines to demonstrate our NATURE GEOSCIENCE 2

3 globally-applicable approach. The salinity threshold for irrigation water use is based on the international salinity standard according to the Food and Agriculture Organization (FAO) 14 of 700 μs cm -1 (0.7 ds m -1 ) representing slight to moderate restriction for irrigation uses. For domestic uses we used the ammonia threshold for drinking water use according to the World Health Organization (WHO) 15 of 1.5 mg l -1. For thermoelectric water uses we used the derived maximum water temperature limit (Tlmax; see Section 3), which was 28 C for Guangzhou. Monthly mean water withdrawals were assessed per sector, as well as the extra water withdrawal to dilute and meet water quality requirements given the water quality (temperature, EC, NH3 concentrations) status and sectoral water quality thresholds (see Fig S1a-c). Total water withdrawals for all water use sectors and the withdrawals for dilution were then added to estimate the total water withdrawal of acceptable water quality (see Fig S1d). We calculated water scarcity based on only water quantity as the ratio of total water withdrawals to the water availability (main text Fig. 1 grey lines) which is a widely used approach For water scarcity including water quality (main text Fig. 1 black lines), we calculate the ratio of total water withdrawal and dilution withdrawal to the water availability following equation (1) given in Box 1 of the main text. NATURE GEOSCIENCE 3

4 Figure S1: Monthly sectoral water withdrawals based on various water quality parameters relevant for different water use sectors. Results are presented for the Pearl River at Guangzhou (China) for Monthly mean water withdrawals are shown for thermoelectric power (a), irrigation (b), and domestic (c) uses as well as water withdrawals for dilution to obtain acceptable water quality by using observed data of water temperature, electrical conductivity, ammonia concentrations, and their thresholds for sectoral water uses (a-c). In a next step, sectoral water withdrawals and dilution withdrawals are summed for all sectors (d). NATURE GEOSCIENCE 4

5 3. Critical regions of water scarcity including water quality (temperature) In addition to the impacts of water quality on water scarcity for various sectors throughout the year we also assessed the spatial impacts on water scarcity patterns by focussing on water temperature. This is an important physical aspect of water quality for both freshwater ecosystems and for the energy sector in terms of cooling water use by thermoelectric power plants. In addition, water temperature was selected because this was simulated on a worldwide level by all three global hydrological models involved in this study. Global water scarcity for the electricity (thermoelectric power) sector (main text Fig. 2a) was calculated by the ratio of thermoelectric water withdrawals to the simulated monthly water availability (GHM-ensemble mean) for 1,542 thermoelectric power plants worldwide for We used selected thermoelectric power plants from the World Electric Power Plant Database (WEPPD) with available information of technology (fuel source), cooling system type and installed capacity. Location (latitude-longitude) information was derived as described by van Vliet et al. 19. Thermoelectric water withdrawal based on only water quantity was assessed as described by Flörke et al. 20 using plant installed capacities and mean withdrawal intensity per plant. We calculated mean withdrawal intensity per plant based on technology and cooling system type using mean literature estimates of Fricko et al. 21. Thermoelectric water withdrawals including water quality (i.e. water temperature) were estimated by using the ensemble mean simulated water temperature from the three GHMs at each plant location and using derived values of maximum permitted water temperature (Tlmax) for cooling water use for each of the thermoelectric power plants as described by van Vliet et al. 19. We then calculated the extra water withdrawal needed to dilute thermal effluents from power plants under conditions that water temperature exceeds Tlmax according to equation (1) presented in Box 1 of the main text. In a next step, we calculated for each power plant the relative (percentage) increase in water scarcity including water temperature and dilution impacts compared to the approach that only focussed on water quantity. Water scarcity for freshwater ecosystems (main text Fig. 2b) was calculated using the ratio of the monthly environmental flow requirements (EFRs) to the simulated monthly water availability of the three GHMs for EFRs were calculated using monthly variable environmental flow requirements, allocating 60% of the monthly flow during the low flow period and 30% during the high flow period 22. To estimate freshwater ecosystem scarcity NATURE GEOSCIENCE 5

6 including a water quality dimension, we added the simulated monthly water temperatures (GHM-mean) for and used the 95-percentile water temperature as a coarse water temperature threshold 23 to quantify the extra water needed to lower temperatures below thresholds for ecosystem health. It should however be kept in mind that on a local level the release of cold water from the deep layers of reservoirs can be used to manage downstream river water temperatures and to sustain suitable thermal habitats, for instance for salmonides 24,25. This might result in an overestimation of our estimates of freshwater ecosystem water scarcity for some regulated rivers with cold water releases. We calculated the relative (percentage) increase in freshwater water scarcity including water temperature compared to the approach that only focussed on water quantity. Total water scarcity was estimated in a next step by using the GHM-mean monthly simulations of sectoral water withdrawals, water availability and water temperature. Total water scarcity based on solely water quantity was calculated using the ratio of the total sectoral water withdrawals (i.e. sum of irrigation, livestock, domestic, manufacturing and thermoelectric water withdrawals) to the water availability subtracting EFR, which is in line with previous global water scarcity or water stress assessments For total water scarcity including water temperature (main text Fig. 2c), we added the dilution water withdrawals for thermoelectric power to the total sectoral water withdrawals, assuming that water temperatures only constrain thermoelectric water uses (not irrigation, livestock, domestic, manufacturing). For freshwater ecosystems, both the EFRs and temperature-driven water demands for freshwater ecosystems were subtracted from the water availability as given in equation (1) (Box 1 of the main text). NATURE GEOSCIENCE 6

7 Supplementary references 1 van Beek, L. P. H., Wada, Y. & Bierkens, M. F. P. Global monthly water stress: 1. Water balance and water availability. Water Resources Research 47, doi:w /2010wr (2011). 2 Wada, Y. et al. Global monthly water stress: 2. Water demand and severity of water stress. Water Resources Research 47, doi:w /2010wr (2011). 3 van Beek, L. P. H., Eikelboom, T., van Vliet, M. T. H. & Bierkens, M. F. P. A physically based model of global freshwater surface temperature. Water Resources Research 48, doi: /2012wr (2012). 4 Liang, X., Lettenmaier, D. P., Wood, E. F. & Burges, S. J. A Simple Hydrologically Based Model of Land-Surface Water and Energy Fluxes for General-Circulation Models. Journal of Geophysical Research-Atmospheres 99, (1994). 5 Lohmann, D., NolteHolube, R. & Raschke, E. A large-scale horizontal routing model to be coupled to land surface parametrization schemes. Tellus Series a-dynamic Meteorology and Oceanography 48, (1996). 6 van Vliet, M. T. H. et al. Coupled daily streamflow and water temperature modelling in large river basins. Hydrology and Earth System Sciences 16, , doi: /hess (2012). 7 Yearsley, J. R. A semi-lagrangian water temperature model for advection-dominated river systems. Water Resources Research 45 doi: /2008wr (2009). 8 Döll, P., Kaspar, F. & Lehner, B. A global hydrological model for deriving water availability indicators: model tuning and validation. Journal of Hydrology 270, (2003). 9 Müller Schmied, H. et al. Sensitivity of simulated global-scale freshwater fluxes and storages to input data, hydrological model structure, human water use and calibration. Hydrol. Earth Syst. Sci. 18, , doi: /hess (2014). 10 Punzet, M., Voß, F., Voß, A., Kynast, E. & Bärlund, I. A Global Approach to Assess the Potential Impact of Climate Change on Stream Water Temperatures and Related In-Stream First-Order Decay Rates. Journal of Hydrometeorology 13, , doi: /jhm-d (2012). 11 van Vliet, M. T. H. et al. Multi-model assessment of global hydropower and cooling water discharge potential under climate change. Global Environmental Change 40, , doi: (2016). 12 Weedon, G. P. et al. The WFDEI meteorological forcing data set: WATCH Forcing Data methodology applied to ERA-Interim reanalysis data. Water Resources Research 50, , doi: /2014wr (2014). 13 Flörke, M. et al. Domestic and industrial water uses of the past 60 years as a mirror of socio-economic development: A global simulation study. Global Environmental Change 23, , doi: (2013). 14 Ayers, R. S. & Westcot, D. W. Water quality for agriculture. p. 186 (Food and Agriculture Organization of the United Nations, Rome, 1985). 15 WHO. Guidelines for Drinking-water Quality, FOURTH EDITION. 541 pp. (World Health Organization, Geneva, Switzerland, 2011). NATURE GEOSCIENCE 7

8 16 Liu, J. et al. Water scarcity assessments in the past, present and future. Earth's Future 5, doi: /2016EF (2017). 17 Veldkamp, T. I. E. et al. Water scarcity hotspots travel downstream due to human interventions in the 20th and 21st century. Nature Communications 8, (2017). 18 Alcamo, J. et al. Global estimates of water withdrawals and availability under current and future "business-as-usual" conditions. Hydrological Sciences Journal-Journal Des Sciences Hydrologiques 48, (2003). 19 van Vliet, M. T. H., Wiberg, D., Leduc, S. & Riahi, K. Power-generation system vulnerability and adaptation to changes in climate and water resources. Nature Climate Change 6, (2016). 20 Flörke, M., Teichert, E. & Bärlund, I. Future changes of freshwater needs in European power plants. Management of Environmental Quality: An International Journal 22, , doi: / (2011). 21 Fricko, O. et al. Energy sector water use implications of a 2 C climate policy. Environmental Research Letters 11, (2016). 22 Pastor, A. V., Ludwig, F., Biemans, H., Hoff, H. & Kabat, P. Accounting for environmental flow requirements in global water assessments. Hydrol. Earth Syst. Sci. 18, , doi: /hess (2014). 23 van Vliet, M. T. H., Ludwig, F. & Kabat, P. Global streamflow and thermal habitats of freshwater fishes under climate change. Climatic Change 121, , doi: /s (2013). 24 Carron, J. C. & Rajaram, H. Impact of variable reservoir releases on management of downstream water temperatures. Water Resources Research 37, , doi: /2000wr (2001). 25 Connor, W. P., Burge, H. L., Yearsley, J. R. & Bjornn, T. C. Influence of flow and temperature on survival of wild subyearling fall chinook salmon in the Snake River. North American Journal of Fisheries Management 23, (2003). NATURE GEOSCIENCE 8