Fitton, N. et al

The percentage of total pasture land, by country, subject to water scarcity in 2050 as estimated from a multi-model ensemble

https://doi.org/10.5285/ec5cc84e-a8da-4ff8-80d4-26fca1a31e1f Cite this dataset
This dataset contains the percentage of the total pasture area in each country classified as vulnerable to water scarcity (annual run-off is declining and the water shed is defined as water scarce in 2050). Projections of global changes in water scarcity with the current extent of pasture land were combined to identify the potential country level vulnerabilities of pasture land to water scarcity in 2050. The data relate to an analysis of the impact changes in water availability will have on pasture availability in 2050.
Publication date: 2019-11-13

Format

Comma-separated values (CSV)

Where/When

Study area
Temporal extent
2050-01-01    to    2050-12-31

Provenance & quality

Global maps, of the change in annual runoff (%) and water scarcity (index value between 1 – 4, where 1 represents not water scarce and 4 is severely water scarce) were as estimated based on projections from 5 different general circulation models/ global climate models (GCMs) were obtained directly from Prof. N. Arnell (University of Reading).
Global maps of the current cropland area were directly downloaded from www.earthstat.org, which is an open access platform that hosts the most up to date versions of data. Maps of croplands were created based on a mixture of satellite derived data mixed with national, state and country census statistics, and were expressed on a global 5 arc-minute grid.
Data used in this study was collected from several sources and cited in the supporting documentation.

Related

This dataset is included in the following collections

Delivering Food Security on Limited Land (DEVIL)

Correspondence/contact details

Dr Nuala Fitton
University of Aberdeen
 n.fitton@abdn.ac.uk

Authors

Fitton, N.
University of Aberdeen
ORCID iD icon https://orcid.org/0000-0001-7386-0472
Alexander, P
University of Edinburgh
Arnell, N.
University of Reading
Bajzelj, B.
University of Cambridge
Calvin, K.
Pacific Northwest National Laboratory
Doelman, J.
Netherlands Environmental Assessment Agency
Gerber, J.S.
University of Minnesota
Havlik, P.
International Institute for Applied Systems Analysis
Hasegawa, T.
National Institute for Environmental Studies, Tsukuba
Herrero, M.
Commonwealth Scientific and Industrial Research Organisation
Krisztin, T.
International Institute for Applied Systems Analysis
van Meijl, H.
Wageningen University and Research Centre
Powell, T.
University of Exeter
Sands, R.
US Department of Agriculture
Stehfest, E.
Netherlands Environmental Assessment Agency
West, P.C.
University of Minnesota
Smith, P.
University of Aberdeen

Other contacts

Custodian
NERC EDS Environmental Information Data Centre
 info@eidc.ac.uk
Publisher
NERC Environmental Information Data Centre
 info@eidc.ac.uk

Additional metadata

Topic categories
environment
farming
INSPIRE theme
Environmental Monitoring Facilities
Other keywords
Climate and climate change , Agriculture , Environmental risk , Hydrology
Spatial representation type
Tabular (text)
Spatial reference system
WGS 84
Last updated
18 May 2022 12:37

Get the data

By accessing or using this dataset, you agree to the terms of the relevant licence agreement(s). You will ensure that this dataset is cited in any publication that describes research in which the data have been used.

This dataset is available under the terms of the Open Government Licence

Download the data Supporting documentation

CITE AS: Fitton, N.; Alexander, P ; Arnell, N.; Bajzelj, B.; Calvin, K.; Doelman, J.; Gerber, J.S.; Havlik, P.; Hasegawa, T.; Herrero, M.; Krisztin, T.; van Meijl, H.; Powell, T.; Sands, R.; Stehfest, E.; West, P.C.; Smith, P. (2019). The percentage of total pasture land, by country, subject to water scarcity in 2050 as estimated from a multi-model ensemble. NERC Environmental Information Data Centre. https://doi.org/10.5285/ec5cc84e-a8da-4ff8-80d4-26fca1a31e1f

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