dc.contributor.author | Osborne, JM | |
dc.contributor.author | Hugo Lambert, F | |
dc.date.accessioned | 2019-01-30T14:14:47Z | |
dc.date.issued | 2018-11-27 | |
dc.description.abstract | There is a growing desire for reliable 21st-century projections of water availability at the regional scale. Global climate models (GCMs) are typically used together with global hydrological models (GHMs) to generate such projections. GCMs alone are unsuitable, especially if they have biased representations of aridity. The Budyko framework represents how water availability varies as a non-linear function of aridity and is used here to constrain projections of runoff from GCMs, without the need for computationally expensive GHMs. Considering a Chinese case study, we first apply the framework to observations to show that the contribution of direct human impacts (water consumption) to the significant decline in Yellow River runoff was greater than the contribution of aridity change by a factor of approximately 2, although we are unable to rule out a significant contribution from the net effect of all other factors. We then show that the Budyko framework can be used to narrow the range of Yellow River runoff projections by 34%, using a multi-model ensemble and the high-end Representative Concentration Pathway (RCP8.5) emissions scenario. This increases confidence that the Yellow River will see an increase in runoff due to aridity change by the end of the 21st century. Yangtze River runoff projections change little, since aridity biases in GCMs are less substantial. Our approach serves as a quick and inexpensive tool to rapidly update and correct projections from GCMs alone. This could serve as a valuable resource when determining the water management policies required to alleviate water stress for future generations. | en_GB |
dc.description.sponsorship | Natural Environment Research Council | en_GB |
dc.description.sponsorship | UK–China Research & Innovation Partnership Fund | en_GB |
dc.identifier.citation | Vol. 22, pp. 6043 - 6057 | en_GB |
dc.identifier.doi | 10.5194/hess-22-6043-2018 | |
dc.identifier.grantnumber | NE/M006123/1 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/35657 | |
dc.language.iso | en | en_GB |
dc.publisher | European Geosciences Union | en_GB |
dc.relation.url | http://hdl.handle.net/10871/34612 | |
dc.rights | © The Author(s). Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. | en_GB |
dc.subject | Global climate models | en_GB |
dc.subject | Water availability | en_GB |
dc.subject | Water consumption | en_GB |
dc.subject | China | en_GB |
dc.subject | Budyko framework | en_GB |
dc.title | A simple tool for refining GCM water availability projections, applied to Chinese catchments | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2019-01-30T14:14:47Z | |
dc.identifier.issn | 1027-5606 | |
dc.description | This is the final version. Available from the European Geosciences Union via the DOI in this record. | en_GB |
dc.description | The discussion paper version of this article was published in Hydrology and Earth System Sciences Discussions and is available in ORE at http://hdl.handle.net/10871/34612 | |
dc.identifier.journal | Hydrology and Earth System Sciences | en_GB |
dc.rights.uri | http://www.rioxx.net/licenses/all-rights-reserved | en_GB |
dcterms.dateAccepted | 2018-11-01 | |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2018-11-27 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2019-01-30T14:07:37Z | |
refterms.versionFCD | VoR | |
refterms.dateFOA | 2019-01-30T14:14:50Z | |
refterms.panel | B | en_GB |
refterms.dateFirstOnline | 2018-11-27 | |