Environmental Engineering Reference
In-Depth Information
Water points (WP) are discrete locations of water supply sources (e.g. wells,
springs) of diverse uses for which data (e.g. GPS location, photography, number of
people to supply) is collected (Welle
2005
). Because of the allocation of geographic
information to the WP, the collected data can be visualized based on maps or
statistical graphs. This helps to visualize the spatial distribution of water supply
coverage (water points per population) and can thereby be used to highlight unequal
water distribution issues quickly, as well as regions that are disconnected to the
water supply infrastructure (Gin
-Garriga et al.
2013
). The information collected
provides insights into water quality levels (e.g. biological quality) and management-
related aspects (e.g. households
é
'
water accessibility, status of WP functionality) of
water points (Gin
-Garriga et al.
2013
).
According to Nyitambe (
2014
), WPM is useful for:
é
Infrastructure improvement planning to support water supply coverage,
Identi
cation of regions where basic water services are lacking and to support
them with needed resources,
Monitoring and planning of water sectorial investments,
Assessment and monitoring of progress and performance of water supply.
The biggest challenge and the bottleneck of the whole system is routine data
acquisition, data quality and, even more so, data updating (Gin
é
-Garriga et al.
2013
). For any ongoing monitoring tool, this represents the biggest problem, and
unfortunately, there is no simple answer. Every country
is water sector is different
and each presents its own challenges. A major one is the continuous updating of the
information about non-functioning and water-losing water points, which can help
save water by quick-response repair. This goes along the lines of what Ardakanian
and Bernhardt (
2011
) are postulating in their paper about water loss reduction in
Africa.
Technological developments such as remote sensing (Sect.
2.3.3
) or mobile
phone availability along with speci
'
c software applications for (e.g. OpenDataKit)
improvement of data quality, scalability as well as data availability for monitoring
purposes (Sect.
2.4
) is growing quickly. Hence, it has been proposed (Feurer et al.
2008
) to use geocoded ultra-high resolution satellite images as an appropriate
substitute. This type of imagery has the big advantage that due to their pictorial
nature, it is easily understandable by non-expert decision-makers and politicians. As
another example, WPM mapping can be supported by the software tool
'
Water
Point Mapper
es the manual data collection at each
water point location. The data collection is still manually done by
'
, which accelerates and simpli
filling out a
digital spreadsheet. The spreadsheet data can then automatically be visualized with
Google Earth (offline) by the software tool (waterpointmapper.org) (Fig.
9
). Google
Earth maps can be made accessible to the public by connecting the offline Google
Earth maps to web-based Google maps service, which is addable to any internet
page by using the Google web widget. However, the aspect of covering the
maintenance costs of technological-based systems on one side and of giving
incentives to the individuals in charge of keeping the system working and
—
most of
all
—
the data up-to-date must not be underestimated and treated with appropriate
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