From the global to the subnational scale: landing the compositional monitoring of drinking water and sanitation services
Monitoring of access to water and sanitation services is stipulated in Sustainable Development Goals (SDG) 6.1 and 6.2, respectively. The monitoring is carried out with a global, regional and country vision. However, in most developing countries, decentralization of services in water and sanitation...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/370227 |
| Acceso en línea: | https://hdl.handle.net/2117/370227 https://dx.doi.org/10.1016/j.scitotenv.2022.156005 |
| Access Level: | acceso abierto |
| Palabra clave: | Sanitation--Management Sustainable Development Goals (SDGs) Water quality Latin America and Caribbean Uncertainty Sanejament -- Gestió Àrees temàtiques de la UPC::Enginyeria civil::Enginyeria hidràulica, marítima i sanitària::Enginyeria sanitària |
| Sumario: | Monitoring of access to water and sanitation services is stipulated in Sustainable Development Goals (SDG) 6.1 and 6.2, respectively. The monitoring is carried out with a global, regional and country vision. However, in most developing countries, decentralization of services in water and sanitation management has tended to the sub-national level or has shared responsibilities between national and sub-national governments. Management at the subnational level becomes more important, since everything that is done there will impact the objectives and goals of the country. However, little or nothing progress has been made in harmonizing global indicators with those at the subnational level. Therefore, in this study we have proposed a way to disaggregate information and form WASH ladders at the subnational level. The results show using disaggregated data to interpolate models at the subnational level requires overcoming three main points: the validation of the data through statistical methods, interpolation techniques that go according to the compositional characteristics of the data and the incorporation of the uncertainty of the data into the model results. It also shows that subnational behavior is heterogeneous, which a general analysis does not capture correctly, i.e., there is a masking effect of subnational trends that the country's trend does not represent. However, these have been exceptional cases in some specific categories. Finally, the applicability of non-linear models is contrasted in a broader context, an issue that is still under discussion for its application to global monitoring. This study also provides a way to disaggregate information from the global to the sub-national level, allowing any sector analyst to replicate the methodology in a broader context. |
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