Analysis of water use impact assessment methods (part A): evaluation of modeling choices based on a quantitative comparison of scarcity and human health indicators
- 2k Downloads
In the past decade, several methods have emerged to quantify water scarcity, water availability and the human health impacts of water use. It was recommended that a quantitative comparison of methods should be performed to describe similar impact pathways, namely water scarcity and human health impacts from water deprivation. This is precisely the goal of this paper, which aims to (1) identify the key relevant modeling choices that explain the main differences between characterization models leading to the same impact indicators; (2) quantify the significance of the differences between methods, and (3) discuss the main methodological choices in order to guide method development and harmonization efforts.
The modeling choices are analysed for similarity of results (using mean relative difference) and model response consistency (through rank correlation coefficient). Uncertainty data associated with the choice of model are provided for each of the models analysed, and an average value is provided as a tool for sensitivity analyses.
The results determined the modeling choices that significantly influence the indicators and should be further analysed and harmonised, such as the regional scale at which the scarcity indicator is calculated, the sources of underlying input data and the function adopted to describe the relationship between modeled scarcity indicators and the original withdrawal-to-availability or consumption-to-availability ratios. The inclusion or exclusion of impacts from domestic user deprivation and the inclusion or exclusion of trade effects both strongly influence human health impacts. At both midpoint and endpoint, the comparison showed that considering reduced water availability due to degradation in water quality, in addition to a reduction in water quantity, greatly influences results. Other choices are less significant in most regions of the world. Maps are provided to identify the regions in which such choices are relevant.
This paper provides useful insights to better understand scarcity, availability and human health impact models for water use and identifies the key relevant modeling choices and differences, making it possible to quantify model uncertainty and the significance of these choices in a specific regional context. Maps of regions where these specific choices are of importance were generated to guide practitioners in identifying locations for sensitivity analyses in water footprint studies. Finally, deconstructing the existing models and highlighting the differences and similarities has helped to determine building blocks to support the development of a consensual method.
KeywordsImpact modeling Life cycle assessment Model comparison Water deprivation Water footprint
The authors would like to acknowledge the contribution of Francis Gassert from the World Resource Institute (WRI) for providing data and understanding into the Aquaduct model. We acknowledge the financial support of the industrial partners in the International Chair in Life Cycle Assessment (a research unit of CIRAIG): ArcelorMittal, Bombardier, le Mouvement Desjardins, Hydro-Québec, LVMH, Michelin, Nestlé, RECYC-QUÉBEC, RONA, SAQ, Solvay, Total, Umicore, Veolia Environnement.
- Aguilar-Manjarrez J (2006) WRI Major watersheds of the world delineation. FAO-Aquaculture Management and Conservation ServiceGoogle Scholar
- Alcamo J, Henrichs T, Rosch T (2000) World water in 2025—global modeling and scenario analysis for the World Commission on Water for the 21st century. Kassel World Water seriesGoogle Scholar
- Bauer C, Zapp P (2005) Towards generic factors for land Use and water consumption. In: Dubreuil A (ed) Life cycle assessment of metals: issues and research directions. SETAC - USA, Pensacola, USAGoogle Scholar
- Bourgault G, Lesage P, Margni M, Bulle C, Boulay A-M, Samson, R (2012) Quantification of uncertainty of characterisation factors due to spatial variability. SETAC Europe 22nd Annual Meeting / 6th SETAC World Congress, Berlin.Google Scholar
- Bulle C, Humbert S, Jolliet O, Rosenbaum R, Margni M (2012) IMPACT World+: A new global regionalized life cycle impact assessment method, LCA XII, United States, Washington, Tacoma.Google Scholar
- Fekete B, Vörösmarty C, Grabs W (2002) High-resolution fields of global runoff combining observed river discharge and simulated water balances. Global Biogeochem Cy 16(3):15.1-15-10Google Scholar
- Food and Agriculture Organization of the United Nations (nd.) AQUASTAT-FAO’s information system on water and agriculture. Available at: http://www.fao.org/NR/WATER/AQUASTAT/main/index.stm
- Frischknecht R et al. (2008) Swiss ecological scarcity method: the new version 2006Google Scholar
- Hertwich EG, McKone TE, Pease WS (1999) Parameter uncertainty and variability in evaluative fate and exposure models. Risk Anal 19(6):1193–1204Google Scholar
- Initiative, U.-S.L.C (2012) http://www.wulca-waterlca.org/
- ISO 14046 (2014) Water footprint—principles, requirements and guidelinesGoogle Scholar
- Mekonnen MM, Hoekstra AY (2011) National water footprint accounts: the green, blue and grey water footprint of production and consumption. UNESCO-IHE, Delft, The NetherlandsGoogle Scholar
- Motoshita M, Itsubo N, Inaba A (2010a) Damage assessment of water scarcity for agricultural use 1. In: Proceedings of 9th international conference on EcoBalance. National Institute of Advanced Industrial Science and Technology (AIST), pp 3–6Google Scholar
- Pfister S, Bayer P (2013) Monthly water stress: spatially and temporally explicit consumptive water footprint of global crop production. J Clean Prod. Available at: http://www.ifu.ethz.ch/ESD/downloads/reports/Monthly_WSI_LCA_FOOD.pdf
- Pfister S, Hellweg S (2011) Surface water use – human health impacts. Report of the LC-IMPACT project (EC: FP7) (p. http://www.ifu.ethz.ch/ESD/downloads/Uncertainty_w). Retrieved from http://www.ifu.ethz.ch/ESD/downloads/Uncertainty_water_LCIA.pdf
- Shiklomanov IA, Rodda JC (2003) World water resources at the beginning of the 21st century. Cambridge University Press, Cambridge, UKGoogle Scholar
- UNEP Global Environment Monitoring System (GEMS) Water programme (2009) GEMStatGoogle Scholar