Bayesian networks as a decision support tool for rural water supply and sanitation sector

Despite the efforts made towards the Millennium Development Goals targets during the last decade, still millions of people across the world lack of improved access to water supply or basic sanitation. The increasing complexity of the context in which these services are delivered is not properly capt...

ver descrição completa

Detalhes bibliográficos
Autor: Requejo Castro, David|||0000-0002-5676-6318
Formato: tesis de maestría
Fecha de publicación:2016
País:España
Recursos:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/106392
Acesso em linha:https://hdl.handle.net/2117/106392
Access Level:acceso abierto
Palavra-chave:Mathematical statistics
Water -- Supply
WaSH
WaSH Poverty Index
Bayesian network
Kenya
Estadística matemàtica
Aigua -- Abastament
Àrees temàtiques de la UPC::Enginyeria civil
id ES_f94fa20c490e96c1d60fe8a09b6eafa1
oai_identifier_str oai:upcommons.upc.edu:2117/106392
network_acronym_str ES
network_name_str España
repository_id_str
spelling Bayesian networks as a decision support tool for rural water supply and sanitation sectorRequejo Castro, David|||0000-0002-5676-6318Mathematical statisticsWater -- SupplyWaSHWaSH Poverty IndexBayesian networkKenyaEstadística matemàticaAigua -- AbastamentÀrees temàtiques de la UPC::Enginyeria civilDespite the efforts made towards the Millennium Development Goals targets during the last decade, still millions of people across the world lack of improved access to water supply or basic sanitation. The increasing complexity of the context in which these services are delivered is not properly captured by the conventional approaches that pursue to assess water, sanitation and hygiene (WaSH) interventions. Instead, a holistic framework is required to integrate the wide range of aspects which are influencing sustainable and equitable provision of safe water and sanitation, especially to those in vulnerable situations. In this context, the WaSH Poverty Index (WaSH-PI) was adopted, as a multi-dimensional policy tool that tackles the links between access to basic services and the socio-economic drivers of poverty. Nevertheless, this approach does not fully describe the increasing interdependency of the reality. For this reason, appropriate Decision Support Systems (DSS) are required to i) inform about the results achieved in past and current interventions, and to ii) determine expected impacts of future initiatives, particularly taking into account envisaged investments to reach the targets set by the Sustainable Development Goals (SDGs). This would provide decision-makers with adequate information to define strategies and actions that are efficient, effective, and sustainable. This master thesis explores the use of object-oriented Bayesian networks (ooBn) as a powerful instrument to support project planning and monitoring, as well as targeting and prioritization. Based on WaSH-PI theoretical framework, a simple ooBn model has been developed and applied to reflect the main issues that determine access to safe water, sanitation and hygiene. A case study is presented in Kenya, where the Government launched in 2008 a national program aimed to increase the access to improved water, sanitation and hygiene in 22 of the 47 existing districts. Main impacts resulted from this initiative are assessed and compared against the initial situation. This research concludes that the proposed approach is able to accommodate the conditions at different scales, at the same time that reflects the complexities of WaSH-related issues. Additionally, this DSS represents an effective management tool to support decisionmakers to formulate informed choices between alternative actions.Universitat Politècnica de CatalunyaPérez Foguet, Agustí20162016-06-2320172017-07-14master thesishttp://purl.org/coar/resource_type/c_bdccNAhttp://purl.org/coar/version/c_be7fb7dd8ff6fe43info:eu-repo/semantics/masterThesisapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttps://hdl.handle.net/2117/106392reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution 3.0 Spainhttp://creativecommons.org/licenses/by/3.0/es/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/1063922026-05-27T15:37:01Z
dc.title.none.fl_str_mv Bayesian networks as a decision support tool for rural water supply and sanitation sector
title Bayesian networks as a decision support tool for rural water supply and sanitation sector
spellingShingle Bayesian networks as a decision support tool for rural water supply and sanitation sector
Requejo Castro, David|||0000-0002-5676-6318
Mathematical statistics
Water -- Supply
WaSH
WaSH Poverty Index
Bayesian network
Kenya
Estadística matemàtica
Aigua -- Abastament
Àrees temàtiques de la UPC::Enginyeria civil
title_short Bayesian networks as a decision support tool for rural water supply and sanitation sector
title_full Bayesian networks as a decision support tool for rural water supply and sanitation sector
title_fullStr Bayesian networks as a decision support tool for rural water supply and sanitation sector
title_full_unstemmed Bayesian networks as a decision support tool for rural water supply and sanitation sector
title_sort Bayesian networks as a decision support tool for rural water supply and sanitation sector
dc.creator.none.fl_str_mv Requejo Castro, David|||0000-0002-5676-6318
author Requejo Castro, David|||0000-0002-5676-6318
author_facet Requejo Castro, David|||0000-0002-5676-6318
author_role author
dc.contributor.none.fl_str_mv Pérez Foguet, Agustí
dc.subject.none.fl_str_mv Mathematical statistics
Water -- Supply
WaSH
WaSH Poverty Index
Bayesian network
Kenya
Estadística matemàtica
Aigua -- Abastament
Àrees temàtiques de la UPC::Enginyeria civil
topic Mathematical statistics
Water -- Supply
WaSH
WaSH Poverty Index
Bayesian network
Kenya
Estadística matemàtica
Aigua -- Abastament
Àrees temàtiques de la UPC::Enginyeria civil
description Despite the efforts made towards the Millennium Development Goals targets during the last decade, still millions of people across the world lack of improved access to water supply or basic sanitation. The increasing complexity of the context in which these services are delivered is not properly captured by the conventional approaches that pursue to assess water, sanitation and hygiene (WaSH) interventions. Instead, a holistic framework is required to integrate the wide range of aspects which are influencing sustainable and equitable provision of safe water and sanitation, especially to those in vulnerable situations. In this context, the WaSH Poverty Index (WaSH-PI) was adopted, as a multi-dimensional policy tool that tackles the links between access to basic services and the socio-economic drivers of poverty. Nevertheless, this approach does not fully describe the increasing interdependency of the reality. For this reason, appropriate Decision Support Systems (DSS) are required to i) inform about the results achieved in past and current interventions, and to ii) determine expected impacts of future initiatives, particularly taking into account envisaged investments to reach the targets set by the Sustainable Development Goals (SDGs). This would provide decision-makers with adequate information to define strategies and actions that are efficient, effective, and sustainable. This master thesis explores the use of object-oriented Bayesian networks (ooBn) as a powerful instrument to support project planning and monitoring, as well as targeting and prioritization. Based on WaSH-PI theoretical framework, a simple ooBn model has been developed and applied to reflect the main issues that determine access to safe water, sanitation and hygiene. A case study is presented in Kenya, where the Government launched in 2008 a national program aimed to increase the access to improved water, sanitation and hygiene in 22 of the 47 existing districts. Main impacts resulted from this initiative are assessed and compared against the initial situation. This research concludes that the proposed approach is able to accommodate the conditions at different scales, at the same time that reflects the complexities of WaSH-related issues. Additionally, this DSS represents an effective management tool to support decisionmakers to formulate informed choices between alternative actions.
publishDate 2016
dc.date.none.fl_str_mv 2016
2016-06-23
2017
2017-07-14
dc.type.none.fl_str_mv master thesis
http://purl.org/coar/resource_type/c_bdcc
NA
http://purl.org/coar/version/c_be7fb7dd8ff6fe43
dc.type.openaire.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/106392
url https://hdl.handle.net/2117/106392
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 3.0 Spain
http://creativecommons.org/licenses/by/3.0/es/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 3.0 Spain
http://creativecommons.org/licenses/by/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Universitat Politècnica de Catalunya
publisher.none.fl_str_mv Universitat Politècnica de Catalunya
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869425083386167296
score 15.300719

Registos relacionados