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dc.creatorRubiano M. J.E.
dc.creatorCook, S.
dc.creatorRajasekharan, M.
dc.creatorDouthwaite, B.
dc.date.accessioned2018-09-11T19:41:40Z
dc.date.available2018-09-11T19:41:40Z
dc.date.issued2016
dc.identifier.citationWater International, 41(2): 290-307
dc.identifier.issn0250-8060
dc.identifier.urihttps://hdl.handle.net/20.500.12348/762
dc.description.abstractThis article present a Bayesian probabilistic method to support out-scaling of technologies from pilot projects. The method is applied to aerobic rice, a water-saving technology with probable global potential. The method assumes that areas similar to pilot sites are more likely to adopt than those that are different or unfavourable. Similarity is defined from climate, landscape and socio-economic attributes. Favourability is further evaluated by project specialists. Scaling out is not a simple linear process, so the method is proposed as a complement to learning processes. Results can support prioritization and strategic planning over specific geographic areas.
dc.formatapplication/pdf
dc.languageEn
dc.publisherInternational Water Resources Association
dc.sourceWater International
dc.titleA Bayesian method to support global out-scaling of water-efficient rice technologies from pilot project areas
dc.typeJournal Article
dcterms.bibliographicCitationRubiano M. J.E. et al. (2016). A Bayesian method to support global out-scaling of water-efficient rice technologies from pilot project areas. Water International, 41(2): 290-307
dc.description.versionPeer Review
cg.contributor.crpWater, Land and Ecosystems
cg.coverage.regionGlobal
cg.identifier.worldfish3933
cg.subject.agrovocresearch
cg.subject.agrovocrice
cg.contributor.affiliationUniversidad del Valle
cg.contributor.affiliationFundación Futuros Rurales
cg.contributor.affiliationInternational Center for Tropical Agriculture (CIAT)
cg.contributor.affiliationWorldFish
cg.identifier.statusLimited access
cg.contribution.worldfishauthorDouthwaite, B.
cg.description.themeMiscellaneous
dc.identifier.doihttps://doi.org/10.1080/02508060.2016.1138215en_US
cg.identifier.urlhttp://www.tandfonline.com/doi/abs/10.1080/02508060.2016.1138215


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