Beta version 1.0 released March 2022
This tool evaluates all possible locations that a water point could be constructed in a given district and evaluates how many people that are not near an existing water point (regardless of functionality) could gain access if a water point was constructed in that location.
- Identify locations to build new water points
- Evaluate the relative benefit of building new water points compared to rehabilitating existing water point
- Provide insights on potential data gaps which could be filled by uploading data to WPdx
- Select area of interest by clicking on the gear icon in the lower left corner and selecting ‘Filter by Region.’ Select country and administrative divisions from dropdown menus.
- Select New Construction Priority Analysis from the Decision-Support Tool dropdown menu.
- Click on the table icon in the lower left corner to view the Top Water Points table which shows the GPS coordinates and local population within 1km for the top fifteen proposed points for new construction based on potential population reached.
- The results from the analysis can be downloaded by clicking on the gear icon and selecting Download Data. Select “New Construction Analysis.” The downloaded file includes the country, administrative divisions, latitude, longitude and population living within 1km for the proposed point.
For each administrative region, we inspect the ‘uncharted’ areas to find concentrations of population. Uncharted areas are those in which the population is outside of a 1km radius of an existing (functional or non-functional) water point in the WPdx+ dataset.
- First, we find the point location that has the most uncharted population in a 1km radius and save its coordinates and population size.
- Then we repeat the process, while ignoring population that was already “found” in previous iterations.
- We end the process when we can’t find any point in the administrative region that has more than 100 people in less than 1km distance from it.
Considerations and Limitations:
This analysis is based on the latest available data from the WPdx+ dataset, population estimates from the Facebook High Resolution Population Datasets and administrative boundaries from GADM or HDX (Eswatini, Ghana and Uganda).
WPdx is an open-source repository for data and contributors include governments, NGOs, academic researchers, and others. WPdx has not directly collected this data or verified the accuracy of the data on the platform. WPdx does perform basic validation checks to ensure that required parameters are included and that GPS locations match with the country boundaries of the provided datasets. Additional cleaning and categorizing steps are taken to prepare the dataset for analysis. Full details of these processes can be found on our website. Questions and feedback are more than welcome.
Populations in urban areas, as defined by the EU Global Human Settlement Database are removed from the total administrative region population to provide an estimate of the rural population. While included on the maps for visualization purposes, packaged and delivered water facilities are not included in the analyses to determine served and unserved populations.
Any water points that have been broken, rehabilitated, or constructed since data was uploaded are not included in this analysis. Additionally, household connections are not captured in WPdx. While large urban areas are removed from the analysis if they reach a specified population density, smaller piped schemes with household connections may be missed. As a result, peri-urban areas may be identified as optimal locations for rehabilitation or new construction, even if those communities are already served by household connections. Additionally, because urban populations are based on population density, there may be areas that are locally considered urban which are considered rural in this analysis, or inversely rural areas that are considered urban for this analysis.
Figure shows how DHS regions in Uganda (labeled) compared to WPdx regions (sub-counties from GADM) in red What data should I use? Is the data