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

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. Full details about this dataset can be found at https://doi.org/10.5285/ec5cc84e-a8da-4ff8-80d4-26fca1a31e1f

Simple

Date (Publication)
2019-11-13
Identifier
https://catalogue.ceh.ac.uk/id/ec5cc84e-a8da-4ff8-80d4-26fca1a31e1f
Identifier
doi: / 10.5285/ec5cc84e-a8da-4ff8-80d4-26fca1a31e1f
Other citation details
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 10.5285/ec5cc84e-a8da-4ff8-80d4-26fca1a31e1f
Author
  University of Aberdeen - Fitton, N.
https://orcid.org/0000-0001-7386-0472
Author
  University of Edinburgh - Alexander, P.
Author
  University of Reading - Arnell, N.
Author
  University of Cambridge - Bajzelj, B.
Author
  Pacific Northwest National Laboratory - Calvin, K.
Author
  Netherlands Environmental Assessment Agency - Doelman, J.
Author
  University of Minnesota - Gerber, J.S.
Author
  International Institute for Applied Systems Analysis - Havlik, P.
Author
  National Institute for Environmental Studies, Tsukuba - Hasegawa, T.
Author
  Commonwealth Scientific and Industrial Research Organisation - Herrero, M.
Author
  International Institute for Applied Systems Analysis - Krisztin, T.
Author
  Wageningen University and Research Centre - van Meijl, H.
Author
  University of Exeter - Powell, T.
Author
  US Department of Agriculture - Sands, R.
Author
  Netherlands Environmental Assessment Agency - Stehfest, E.
Author
  University of Minnesota - West, P.C.
Author
  University of Aberdeen - Smith, P.
Custodian
  NERC EDS Environmental Information Data Centre
Publisher
  NERC Environmental Information Data Centre
Point of contact
  University of Aberdeen - Fitton, N.
GEMET - INSPIRE themes, version 1.0
  • Environmental Monitoring Facilities
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© Natural Environment Research Council
Use constraints
otherRestrictions Other restrictions
Other constraints
This resource is available under the terms of the Open Government Licence
Use constraints
otherRestrictions Other restrictions
Other constraints
If you reuse this data, you should cite: 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
Spatial representation type
textTable Text, table
Distance
100000  urn:ogc:def:uom:EPSG::9001
Metadata language
EnglishEnglish
Character set
utf8 UTF8
Topic category
  • Environment
  • Farming
Begin date
2050-01-01
End date
2050-12-31
N
S
E
W
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Unique resource identifier
WGS 84
Distribution format
  • Comma-separated values (CSV) ()

Distributor
  NERC EDS Environmental Information Data Centre
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dataset Dataset
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Conformance result

Date (Publication)
2010-12-08
Statement
Global maps, of the change in annual runoff (%) and water scarcity (index value between 1and 4, where 1 represents not water scarce and 4 is severely water scarce) were as estimated based on projections from five 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.
File identifier
ec5cc84e-a8da-4ff8-80d4-26fca1a31e1f XML
Metadata language
EnglishEnglish
Character set
ISO/IEC 8859-1 (also known as Latin 1) 8859 Part 1
Hierarchy level
dataset Dataset
Hierarchy level name
dataset
Date stamp
2025-03-21T13:23:37
Metadata standard name
UK GEMINI
Metadata standard version
2.3
Point of contact
  NERC EDS Environmental Information Data Centre
Lancaster Environment Centre, Library Avenue, Bailrigg , Lancaster , LA1 4AP , UK
https://eidc.ac.uk/
 
 

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GEMET - INSPIRE themes, version 1.0
Environmental Monitoring Facilities

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