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Identifying the Links Among Poverty, Hydroenergy and Water Use Using Data Mining Methods

dc.contributor.authorTian, Fuyou
dc.contributor.authorWu, Bingfang
dc.contributor.authorZeng, Hongwei
dc.contributor.authorAhmed, Shukri
dc.contributor.authorYan, Nana
dc.contributor.authorWhite, Ian
dc.contributor.authorZhang, Miao
dc.contributor.authorStein, Alfred
dc.date.accessioned2022-06-29T04:15:28Z
dc.date.issued2020
dc.date.updated2021-08-01T08:21:38Z
dc.description.abstractWater is fundamental to human well-being, social development and the environment. Water development, particularly hydropower, provides an important source of renewable energy. Water development is strongly affected by poverty, but only few attempts have been made to understand the links between water development and poverty from a global water development point of view. In this work, this linkage was explored using reservoir construction, hydroenergy and water use data along with six derived indicators. We used association rule mining and classification and regression trees (CART) to identify the links. Random forests were employed to search for factors sensitive to poverty. This study shows that the reservoir density is significantly related to poverty, and reservoir densities are lower in countries with higher poverty rates. Countries with a higher use of small hydropower (SHP) systems are generally more prosperous as follows: an SHP utilization rate above 27% corresponds to a poverty rate below 4.9%. The ratio of water utilization, water availability per capita (WAPC) and reservoir density were essential for the prediction of the poverty class. All three ratios could be related to poverty alleviation as they enable the identification of the potential for water resource development and their constraints. This study concludes that water development in poor countries needs to receive more attention.en_AU
dc.description.sponsorshipThis study was financially supported by the National Key Research and Development Program (2016YFA0600304) and the National Natural Science Foundation of China (41561144013)en_AU
dc.format.mimetypeapplication/pdfen_AU
dc.identifier.issn0920-4741en_AU
dc.identifier.urihttp://hdl.handle.net/1885/268575
dc.language.isoen_AUen_AU
dc.publisherSpringeren_AU
dc.rights© Springer Nature B.V. 2020en_AU
dc.sourceWater Resources Managementen_AU
dc.subjectPovertyen_AU
dc.subjectAssociation analysisen_AU
dc.subjectWater resource developmenten_AU
dc.subjectSustainable developmenten_AU
dc.titleIdentifying the Links Among Poverty, Hydroenergy and Water Use Using Data Mining Methodsen_AU
dc.typeJournal articleen_AU
local.bibliographicCitation.lastpage1741en_AU
local.bibliographicCitation.startpage1725en_AU
local.contributor.affiliationTian, Fuyou, University of Chinese Academy of Sciencesen_AU
local.contributor.affiliationWu, Bingfang, University of Chinese Academy of Sciencesen_AU
local.contributor.affiliationZeng, Hongwei, University of Chinese Academy of Sciencesen_AU
local.contributor.affiliationAhmed, Shukri, UN FAOen_AU
local.contributor.affiliationYan, Nana, Chinese Academy of Sciencesen_AU
local.contributor.affiliationWhite, Ian, College of Science, ANUen_AU
local.contributor.affiliationZhang, Miao, Chinese Academy of Scienceen_AU
local.contributor.affiliationStein, Alfred, University of Twenteen_AU
local.contributor.authoruidWhite, Ian, u9609393en_AU
local.description.embargo2099-12-31
local.description.notesImported from ARIESen_AU
local.identifier.absfor440600 - Human geographyen_AU
local.identifier.absfor461005 - Informetricsen_AU
local.identifier.ariespublicationa383154xPUB11381en_AU
local.identifier.citationvolume34en_AU
local.identifier.doi10.1007/s11269-020-02524-5en_AU
local.identifier.scopusID2-s2.0-85082959610
local.publisher.urlhttps://link.springer.com/en_AU
local.type.statusPublished Versionen_AU

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