Your search found 2 records
1 Ponnambalam, K.; Heemink, A.; Fletcher, S.. 2000. Research and development for management of water resources: Modernizing the teaching of water resources management. In Mehrotra, R.; Soni, B.; Bhatia, K. K. S. (Eds.), Integrated water resources management for sustainable development - Volume 1. Roorkee, India: National Institute of Hydrology. pp.41-51.
(Location: IWMI-HQ Call no: 333.91 G000 MEH Record No: H028038)
2 Wescoat, J. L. Jr.; Fletcher, S.; Novellino, M. 2016. National rural drinking water monitoring: progress and challenges with India’s IMIS database. Water Policy, 18(4):1015-1032. [doi: https://doi.org/10.2166/wp.2016.158]
Drinking water ; Water quality ; Databases ; Monitoring ; Water supply ; Rural areas ; Water policy ; Households ; Regression analysis ; Models ; State intervention ; Development projects ; Planning / India / Gandhinagar
(Location: IWMI HQ Call no: e-copy only Record No: H047684)
http://wp.iwaponline.com/content/ppiwawaterpol/18/4/1015.full.pdf
https://vlibrary.iwmi.org/pdf/H047684.pdf
https://vlibrary.iwmi.org/pdf/H047684.pdf
(0.61 MB) (616 KB)
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.
Powered by DB/Text WebPublisher, from
