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Mapping access to domestic water supplies from incomplete data in developing countries: an illustrative assessment for Kenya

Mapping access to domestic water supplies from incomplete data in developing countries: an illustrative assessment for Kenya
Mapping access to domestic water supplies from incomplete data in developing countries: an illustrative assessment for Kenya
Water point mapping databases, generated through surveys of water sources such as wells and boreholes, are now available in many low and middle income countries, but often suffer from incomplete coverage. To address the partial coverage in such databases and gain insights into spatial patterns of water resource use, this study investigated the use of a maximum entropy (MaxEnt) approach to predict the geospatial distribution of drinking-water sources, using two types of unimproved sources in Kenya as illustration. Geographic locations of unprotected dug wells and surface water sources derived from the Water Point Data Exchange (WPDx) database were used as inputs to the MaxEnt model alongside geological/hydrogeological and socio-economic covariates. Predictive performance of the MaxEnt models was high (all > 0.9) based on Area Under the Receiver Operator Curve (AUC), and the predicted spatial distribution of water point was broadly consistent with household use of these unimproved drinking-water sources reported in household survey and census data. In developing countries where geospatial datasets concerning drinking-water sources often have necessarily limited resolution or incomplete spatial coverage, the modelled surface can provide an initial indication of the geography of unimproved drinking-water sources to target unserved populations and assess water source vulnerability to contamination and hazards.
1932-6203
1-19
Yu, Weiyu
4cca6f0a-badb-4f1c-8b38-da29ba0b9e09
Wardrop, Nicola A
8f3a8171-0727-4375-bc68-10e7d616e176
Bain, Robert
f65e0039-8c5f-4a90-a265-329f08af7d27
Alegana, Victor
6fdaa47e-c08c-48bc-b881-1dc7b89085e4
Graham, Laura
bc76bad7-f0fd-4e94-acf9-c7450ec36ae2
Wright, James
94990ecf-f8dd-4649-84f2-b28bf272e464
Yu, Weiyu
4cca6f0a-badb-4f1c-8b38-da29ba0b9e09
Wardrop, Nicola A
8f3a8171-0727-4375-bc68-10e7d616e176
Bain, Robert
f65e0039-8c5f-4a90-a265-329f08af7d27
Alegana, Victor
6fdaa47e-c08c-48bc-b881-1dc7b89085e4
Graham, Laura
bc76bad7-f0fd-4e94-acf9-c7450ec36ae2
Wright, James
94990ecf-f8dd-4649-84f2-b28bf272e464

Yu, Weiyu, Wardrop, Nicola A, Bain, Robert, Alegana, Victor, Graham, Laura and Wright, James (2019) Mapping access to domestic water supplies from incomplete data in developing countries: an illustrative assessment for Kenya. PLoS ONE, 14 (5), 1-19, [e0216923]. (doi:10.1371/journal.pone.0216923).

Record type: Article

Abstract

Water point mapping databases, generated through surveys of water sources such as wells and boreholes, are now available in many low and middle income countries, but often suffer from incomplete coverage. To address the partial coverage in such databases and gain insights into spatial patterns of water resource use, this study investigated the use of a maximum entropy (MaxEnt) approach to predict the geospatial distribution of drinking-water sources, using two types of unimproved sources in Kenya as illustration. Geographic locations of unprotected dug wells and surface water sources derived from the Water Point Data Exchange (WPDx) database were used as inputs to the MaxEnt model alongside geological/hydrogeological and socio-economic covariates. Predictive performance of the MaxEnt models was high (all > 0.9) based on Area Under the Receiver Operator Curve (AUC), and the predicted spatial distribution of water point was broadly consistent with household use of these unimproved drinking-water sources reported in household survey and census data. In developing countries where geospatial datasets concerning drinking-water sources often have necessarily limited resolution or incomplete spatial coverage, the modelled surface can provide an initial indication of the geography of unimproved drinking-water sources to target unserved populations and assess water source vulnerability to contamination and hazards.

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Accepted/In Press date: 6 May 2019
Published date: 17 May 2019

Identifiers

Local EPrints ID: 431107
URI: http://eprints.soton.ac.uk/id/eprint/431107
ISSN: 1932-6203
PURE UUID: a193613a-641b-4fb7-ba5b-6e96cf821958
ORCID for James Wright: ORCID iD orcid.org/0000-0002-8842-2181

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Date deposited: 23 May 2019 16:30
Last modified: 07 Oct 2020 01:50

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