Spatial analysis of intermittent water supply in Kampala : a case study of NWSC – Kampala Water
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Intermittent water supply has been adopted widely as a measure for controlling water demand among consumers. In Uganda, NWSC is mandated to effectively provide continuous water supply to all Ugandans and is currently supplying water services in about two hundred and fifty-six towns. There has been a growing number of people requesting for connection to the water network, because of this water demand versus supply issues have increased. Currently, the utility has employed water rationing methods by use of schedules to try to avert this problem but the methods are not based on spatial methods making the supply more unreliable and unstable. This research therefore explored a geographic approach to determine hot spot of IWS using CRM records of issues like leakages, bursts, low pressure, no water, and defective meters which were analyzed using Optimized Hot Spot Analysis. Identification of hotspots would paint a clear picture that was used to address water service equity issues which would be a forward step toward NWSC’s mandate of providing water for all Ugandans. The main objective of this study was to analyse the spatial variation of intermittent water supply in Kampala water. The specific objectives were to identify factors responsible for IWS, analyse the spatial distribution of hotspots of IWS, and to determine Strategies for obtaining service equity in the IWS situation. Primary and Secondary methods of data collection were adopted for this research, the secondary data was obtained from the NWSC GIS centre and Customer relations module (CRM) which is used for logging in customers concerns while the primary data was got from questionnaires and interviews carried out in the different KW-Branches. The call records were classified quarterly to get an appreciation of the Hotspots of the IWS Summary statistics for the different IWS factors (Leakages, bursts, no water,) were determined and results showed that the leakages and the no water cases contributed to the biggest percentage of the IWS situation. The hotspots were seen in areas of branches of the City center, Kanyanya, Bwaise, Ntinda, and Nakawa. IWS particularly being due to leakages in these areas, while areas far from the Ggaba plant experienced IWS due to no water issues. In conclusion, traditional hot spot analysis methods can be supplemented with statistical methods in order to make informed decisions and management of IWS situations to achieve equity in distribution.