ugabore

The goal of ugabore is to provide users with documentation on borehole repair data collected from two districts in central Uganda where a borehole operation and maintenance program is run. The dataset is associated with the following project report completed by Joseph Lwere for the “data science for openwashdata” course offered by openwashdata.org.

Installation

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

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

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

dataset	CSV	XLSX
ugabore	Download CSV	Download XLSX

Project goal

Boreholes are the main technology used to access groundwater in Uganda, according to (Owor et al. 2022), and they are also a source of drinking water for households in rural communities in Africa, including Uganda (Lapworth et al. 2020). Therefore, it is crucial to have good quality data to inform decision-making and planning. This project examines data collected from two districts in central Uganda where a borehole operation and maintenance program is run. As professional operation and maintenance is considered the future for borehole functionality in Uganda (Smith, Ongom, and Davis 2023), this project report offers more insights into research on this topic.

Data

The dataset includes information about borehole repair records used by the borehole operation and maintenance company operating in central Uganda. The package provides access to one dataset.

library(ugabore)

The ugabore data set has 10 variables and 171 observations. For an overview of the variable names, see the following table.

variable_name	variable_type	description
community	character	Local name used to refer to the administrative unit 5 where the borehole is located.
parish	character	Local name used to refer to the administrative unit 4 where the borehole is located.
sub_county	character	Local name used to refer to the administrative unit 3 where the borehole is located.
source_id	character	Unique identification number assigned to the borehole by the borehole maintenance company.
repair_date	double	Most recent repair date of the borehole.
population_served	double	Number of people that collect water from the borehole.
well_depth	double	Total depth of the borehole (measured in meters).
static_water_depth	double	Depth of the stable water level within the borehole when pumping isn’t happening (measured in meters).
pump_installation_depth	double	Depth of the pump when installed from land surface (measured in meters).
well_yield	double	Water production capacity of the borehole (measured in m3/h).

Example: Water production capacity versus number of people collecting

Here is an example illustrating the relationship between the number of people collecting water from boreholes in a sub-county and the water production capacity of the corresponding boreholes. From the plot, we see that the sub-county of Kalagala has the highest water production capacity by far. However, it is not the sub-county that serves the most people, suggesting it may be the richest one. On another note, the sub-counties Bombo Town Council and Luwero Town Council have the most people collecting water from their boreholes but do not have high water production capacity, indicating a need for improvement.

library(ugabore)
library(ggplot2)
library(dplyr)

# Define custom colors for plotting
custom_colors <- c(
  "Bamunanika" = "dodgerblue2", "Bombo Tc" = "#E31A1C",
  "Busukuma" = "green4",
  "Butuntumula" = "#6A3D9A",
  "Gombe" = "#FF7F00", 
  "Kajjansi Town Council" = "black", "Kakiri" = "gold1",
  "Kakiri Town Council" = "skyblue2", "Kalagala" = "#FB9A99",
  "Kamira" = "palegreen2",
  "Kasangati Town Council" = "#CAB2D6", 
  "Kasangombe" = "#FDBF6F", 
  "Katikamu" = "gray70", "Kikyusa" = "khaki2",
  "Kira" = "maroon", "Luwero" = "orchid1", "Luwero Tc" = "deeppink1", 
  "Makulubita" = "blue1", "Namayumba Town Council" = "steelblue4",
  "Wobulenzi Tc" = "darkturquoise", "Zirobwe" = "green1", 
  "NA" = "yellow4")

# Summarize data by sub_county
summary_data <- ugabore |> 
  group_by(sub_county) |> 
  summarise(mean_well_yield = mean(well_yield, na.rm = TRUE),
            mean_population_served = mean(population_served, na.rm = TRUE))

# Plot summarized data
ggplot(summary_data, aes(x = mean_well_yield, y = mean_population_served, 
                         color = sub_county)) +
  geom_point(size = 3, alpha = 0.7) +
  labs(title = "Water collection versus production by sub-county",
       x = "\naverage water production capacity in m3/h",
       y = "average number of people\n",
       color = "sub-county") +
  scale_color_manual(values = custom_colors) +
  theme_minimal() 

License

Data are available as CC-BY.

Citation

Please cite this package using:

citation("ugabore")
#> To cite package 'ugabore' in publications use:
#> 
#>   Götschmann M, Lwere J (2024). _ugabore: Borehole repair data from
#>   central Uganda_. R package version 0.0.0.9000,
#>   <https://github.com/openwashdata/ugabore>.
#> 
#> A BibTeX entry for LaTeX users is
#> 
#>   @Manual{,
#>     title = {ugabore: Borehole repair data from central Uganda},
#>     author = {Margaux Götschmann and Joseph Lwere},
#>     year = {2024},
#>     note = {R package version 0.0.0.9000},
#>     url = {https://github.com/openwashdata/ugabore},
#>   }

Lapworth, DJ, AM MacDonald, S Kebede, M Owor, G Chavula, H Fallas, P Wilson, et al. 2020. “Drinking Water Quality from Rural Handpump-Boreholes in Africa.” Environmental Research Letters 15 (6): 064020.

Owor, Michael, Joseph Okullo, Helen Fallas, Alan M MacDonald, Richard Taylor, and Donald John MacAllister. 2022. “Permeability of the Weathered Bedrock Aquifers in Uganda: Evidence from a Large Pumping-Test Dataset and Its Implications for Rural Water Supply.” Hydrogeology Journal 30 (7): 2223–35.

Smith, Daniel W, Stephen Atwii Ongom, and Jennifer Davis. 2023. “Does Professionalizing Maintenance Unlock Demand for More Reliable Water Supply? Experimental Evidence from Rural Uganda.” World Development 161: 106094.