waterpumpkwale

The goal of waterpumpkwale is to provide datasets for monitoring weekly volume of hand pumps in Kwale, Kenya. This package contains valuable information of geo-locations of hand pumps in Kwale as well as monitoring data recorded in year 2014 and 2015. The data is collected part of the project UPGro (Unlocking the Potential of Groundwater for the Poor) which aimed to improve the evidence and understanding of groundwater across Sub-Saharan Africa to help tackle poverty.

Installation

You can install the development version of waterpumpkwale from GitHub with:

# install.packages("devtools")
devtools::install_github("openwashdata/waterpumpkwale")

Alternatively, you can download the individual datasets as CSV or XLSX file from the table below.

dataset	CSV	XLSX
location	Download CSV	Download XLSX
weeklyvol2014	Download CSV	Download XLSX
weeklyvol2015	Download CSV	Download XLSX

Introduction

This dataset contains a summary of the weekly volumetric output of pumps monitored using Smart Handpump sensors for 2014 and 2015 in Kwale, Kenya.¹²

Notes:

1. The accuracy of these volume figures should be considered to be +/- 20%.
2. The dataset has gaps due to variable signal, and some attrition due to damage and vandalism.
3. Not all pumps in the study area were under monitoring.

Data

The package provides access to three datasets location, weeklyvol2014, and weeklyvol2015.

library(waterpumpkwale)

location data

The location data set has 6 variables and 299 observations. They record 299 hand pumps location information. For an overview of the variable names, see the following table.

variable_name	variable_type	description
pumpid	character	ID number of the water pump
description	character	Name of the pump location
x_arc1960	double	Longitude in Arc 1960 coordinate system
y_rc1960	double	Latitude in Arc 1960 coordinate system
lat_wgs84	double	Latitude in WGS 84 coordinate system
long_wgs84	double	Longitude in WGS 84 coordinate system

weeklyvol2014 and weeklyvol2015 data

The weeklyvol2014 data set has 53 variables and 324 observations. The weeklyvol2015 data set has 53 variables and 297 observations.

These two datasets follow the same structure and we here use weeklyvol2014 as an illustration. For an overview of the variable names, see the following table.

variable_name	variable_type	description
pumpid	character	ID number of the water pump
n	double	Each column indicates the week number 1, 2, 3, …, 52

Example

We can have a look where the hand pumps locate in Kwale using the dataset location. For more data exploration, you may check out a detailed example here.

library(leaflet)
# customize marker icon 
handpumpicon <- makeIcon(
  iconUrl = "https://cdn-icons-png.flaticon.com/512/5984/5984318.png",
  iconWidth = 30, iconHeight = 30
)

# Display an interactive map
leaflet(options = leafletOptions(crs = leafletCRS(proj4def = "WGS84"))) |>
  addProviderTiles("OpenStreetMap") |>
  addMarkers(
    data = location,
    lng = ~`long_wgs84`,
    lat = ~`lat_wgs84`,
    popup = ~pumpid,
    label = ~`description`,
    icon = handpumpicon
)

Screenshot of hand pump location map

License

Data are available as CC-BY.

Citation

If you use the data or the package, consider to cite this package with the following information to give credits for authors of the dataset!

citation("waterpumpkwale")
#> To cite package 'waterpumpkwale' in publications use:
#> 
#>   Thomson P, Hope R, Foster T, Zhong M (2023). "waterpumpkwale: Weekly
#>   volume of water pumped for handpumps monitored with Smart Handpump
#>   technology, Kwale County, Kenya." doi:10.5281/zenodo.8399887
#>   <https://doi.org/10.5281/zenodo.8399887>.
#> 
#> A BibTeX entry for LaTeX users is
#> 
#>   @Misc{thomson_etall:2023,
#>     title = {waterpumpkwale: Weekly volume of water pumped for handpumps monitored with Smart Handpump technology, Kwale County, Kenya},
#>     author = {Patrick Thomson and Rob Hope and Tim Foster and Mian Zhong},
#>     year = {2023},
#>     doi = {10.5281/zenodo.8399887},
#>     abstract = {A dataset contains a summary of the weekly volumetric output of pumps monitored using Smart Handpump sensors for 2014 and 2015 in Kwale County of Kenya.},
#>     version = {0.0.1},
#>   }

Related References

[1] P. Thomson, R. Hope, and T. Foster, “GSM-enabled remote monitoring of rural handpumps: a proof-of-concept study,” Journal of Hydroinformatics, vol. 14, no. 4, pp. 829–839, 05 2012. [Online]. Available: https://doi.org/10.2166/hydro.2012.183

[2] Behar, J., Guazzi, A., Jorge, J., Laranjeira, S., Maraci, M.A., Papastylianou, T., Thomson, P., Clifford, G.D. and Hope, R.A., 2013. Software architecture to monitor handpump performance in rural Kenya. In Proceedings of the 12th International Conference on Social Implications of Computers in Developing Countries, Ochos Rios, Jamaica. pp. 978 (Vol. 991).

Footnotes

1. Grants that permitted the data collection include: Groundwater Risk Management for Growth and Development project (NE/M008894/1) funded by NERC/ESRC/DFID’s UPGro programme; New mobile citizens and waterpoint sustainability in rural Africa (ES/J018120/1) ESRC-DFID; Groundwater Risks and Institutional Responses for Poverty Reduction in Rural Africa (NE/L001950/1) funded by NERC/ESRC/DFID’s UPGro programme. ↩

2. More information of the data sources: https://metadata.bgs.ac.uk/geonetwork/srv/eng/catalog.search#/metadata/9ed6c5d2-124b-50ed-e054-002128a47908, https://webapps.bgs.ac.uk/services/ngdc/accessions/index.html?simpleText=upgro ↩