National rural drinking water monitoring: progress and challenges with India's IMIS database
National drinking water programs seek to address monitoring challenges that include self-reporting, data sampling, data consistency and quality, and sufficient frequency to assess the sustainability of water systems. India stands out for its comprehensive rural water database known as Integrated Man...
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| Format: | Article |
| Language: | en_US |
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IWA Publishing
2017
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| Online Access: | http://hdl.handle.net/1721.1/106328 https://orcid.org/0000-0003-3289-2237 |
| _version_ | 1811081182816763904 |
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| author | Wescoat, James Fletcher, Sarah Marie Novellino, Marianna |
| author2 | Massachusetts Institute of Technology. Institute for Data, Systems, and Society |
| author_facet | Massachusetts Institute of Technology. Institute for Data, Systems, and Society Wescoat, James Fletcher, Sarah Marie Novellino, Marianna |
| author_sort | Wescoat, James |
| collection | MIT |
| description | National drinking water programs seek to address monitoring challenges that include self-reporting, data sampling, data consistency and quality, and sufficient frequency to assess the sustainability of water systems. India stands out for its comprehensive rural water database known as Integrated Management Information System (IMIS), which conducts annual monitoring of drinking water coverage, water quality, and related program components from the habitation level to the district, state, and national levels. The objective of this paper is to evaluate IMIS as a national rural water supply monitoring platform. This is important because IMIS is the official government database for rural water in India, and it is used to allocate resources and track the results of government policies. After putting India's IMIS database in an international context, the paper describes its detailed structure and content. It then illustrates the geographic patterns of water supply and water quality that IMIS can present, as well as data analysis issues that were identified. In particular, the fifth section of the paper identifies limitations on the use of state-level data for explanatory regression analysis. These limitations lead to recommendations for improving data analysis to support national rural water monitoring and evaluation, along with strategic approaches to data quality assurance, data access, and database functionality. |
| first_indexed | 2024-09-23T11:42:45Z |
| format | Article |
| id | mit-1721.1/106328 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T11:42:45Z |
| publishDate | 2017 |
| publisher | IWA Publishing |
| record_format | dspace |
| spelling | mit-1721.1/1063282022-10-01T05:28:19Z National rural drinking water monitoring: progress and challenges with India's IMIS database Wescoat, James Fletcher, Sarah Marie Novellino, Marianna Massachusetts Institute of Technology. Institute for Data, Systems, and Society Massachusetts Institute of Technology. Department of Architecture Massachusetts Institute of Technology. Engineering Systems Division Wescoat, James Fletcher, Sarah Marie Novellino, Marianna National drinking water programs seek to address monitoring challenges that include self-reporting, data sampling, data consistency and quality, and sufficient frequency to assess the sustainability of water systems. India stands out for its comprehensive rural water database known as Integrated Management Information System (IMIS), which conducts annual monitoring of drinking water coverage, water quality, and related program components from the habitation level to the district, state, and national levels. The objective of this paper is to evaluate IMIS as a national rural water supply monitoring platform. This is important because IMIS is the official government database for rural water in India, and it is used to allocate resources and track the results of government policies. After putting India's IMIS database in an international context, the paper describes its detailed structure and content. It then illustrates the geographic patterns of water supply and water quality that IMIS can present, as well as data analysis issues that were identified. In particular, the fifth section of the paper identifies limitations on the use of state-level data for explanatory regression analysis. These limitations lead to recommendations for improving data analysis to support national rural water monitoring and evaluation, along with strategic approaches to data quality assurance, data access, and database functionality. Massachusetts Institute of Technology. Tata Center for Technology and Design 2017-01-10T17:33:42Z 2017-01-10T17:33:42Z 2016-02 2015-11 Article http://purl.org/eprint/type/JournalArticle 1366-7017 1996-9759 http://hdl.handle.net/1721.1/106328 Wescoat, J. L., S. Fletcher, and M. Novellino. “National Rural Drinking Water Monitoring: Progress and Challenges with India’s IMIS Database.” Water Policy 18.4 (2016): 1015–1032. https://orcid.org/0000-0003-3289-2237 en_US http://dx.doi.org/10.2166/wp.2016.158 Water Policy Creative Commons Attribution 4.0 International License http://creativecommons.org/licenses/by/4.0/ application/pdf IWA Publishing IWA Publishing |
| spellingShingle | Wescoat, James Fletcher, Sarah Marie Novellino, Marianna National rural drinking water monitoring: progress and challenges with India's IMIS database |
| title | National rural drinking water monitoring: progress and challenges with India's IMIS database |
| title_full | National rural drinking water monitoring: progress and challenges with India's IMIS database |
| title_fullStr | National rural drinking water monitoring: progress and challenges with India's IMIS database |
| title_full_unstemmed | National rural drinking water monitoring: progress and challenges with India's IMIS database |
| title_short | National rural drinking water monitoring: progress and challenges with India's IMIS database |
| title_sort | national rural drinking water monitoring progress and challenges with india s imis database |
| url | http://hdl.handle.net/1721.1/106328 https://orcid.org/0000-0003-3289-2237 |
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