Less than half the population in all the Sub-Saharan African countries included had access to safely managed drinking water in 2022. The share was lowest in the Central African Republic and Chad, where only six percent of the population had access to clean drinking water. Worldwide, Sub-Saharan Africa was the region with the lowest share of access to clean drinking water.

Historical dataset showing Sub-Saharan Africa clean water access by year from 2000 to 2022.

Around ***** in every ten people living in Sub-Saharan Africa had improved drinking water accessible on premises in 2020. The coverage of water available when needed was higher, at nearly ** percent. However, when considering the quality of water, only ** percent of Sub-Saharan Africa's population had access to drinking water free from contamination.

Water point monitoring data associated with the paper "Rural water point functionality estimates and associations: evidence from nine countries in sub-Saharan Africa and South Asia". The cross-sectional data were collected jointly by charity: water and ten country programs that construct rural drinking water supply infrastructure with charity: water funding. The research aimed to elucidate factors associated with functional water points in rural areas of low- and middle-income countries.

In 2017, South Africa had the largest market share of water filtration products within Sub-Saharan Africa, corresponding to ** percent of the total. Ethiopia and Nigeria followed, with ** and ** percent market share, respectively. Overall, the demand for water technologies in Sub-Saharan Africa has been increasing in the last years, following the rise of industrial production and engineering capacity.

This dataset contains the gridded estimates per 1 km2 for mean and median ensemble outputs from 4-6 individual ecosystem service models for Sub-Saharan Africa, for above ground Carbon stock, firewood use, charcoal use and grazing use. Water use and supply are identically supplied as polygons. Individual model outputs are taken from previously published research. Making ensembles results in a smoothing effect whereby the individual model uncertainties are cancelled out and a signal of interest is more likely to emerge. Included ecosystem service models were: InVEST, Co$ting Nature, WaterWorld, Monetary value benefits transfer, LPJ-GUESS and Scholes models. Ensemble outputs have been normalised, therefore these ensembles project relative levels of service across the full area and can be used, for example, for optimisation or assignment of most important or sensitive areas. The work was completed under the "EnsemblES - Using ensemble techniques to capture the accuracy and sensitivity of ecosystem service models" project (NE/T00391X/1) funded by the UKRI Landscape Decisions programme. Full details about this dataset can be found at https://doi.org/10.5285/11689000-f791-4fdb-8e12-08a7d87ad75f

In 2022, an estimated 91 percent of the world population had access to at least basic drinking water services. Access was highest in Europe and North America and Australia and New Zealand, with approximately 100 percent of both regions having access to at least basic drinking water services.

Access to safe drinking water

Improved drinking water refers to a source that can be adequately protected from outside contamination, mostly by fecal matter. An improved sanitation facility keeps human waste out of reach, for example, by using a flush toilet or a septic tank. These protected sources include rainwater, protected springs, and piped water into a dwelling. Global investments in water supply infrastructure are expected to increase.

Global water inequality

In most regions of the world, 90 percent of the population has access to at least basic drinking water services. However, just 65 percent of the population in sub-Saharan Africa and 60 percent of the population in Oceania had basic access in 2022. In sub-Saharan Africa, about 16 percent of people had access to unimproved water sources and eight percent only had access to surface waters. Unimproved water sources include bottled water and tanker-trucks. Currently, eight out of ten people living in rural areas still lack even basic drinking water services. A lack of access to safe water is considered one of the top risks based on impact to global societies.

The full text of this article can be freely accessed on the publisher's website.

In the Central African Republic and Chad, only six percent of the population has access to safely managed drinking water, making them the countries in the world where the lowest share of the population has access to clean drinking water. A high number of the countries on the list are located in Sub-Saharan Africa.

Technical information: model formulation and predicted coverage. (DOCX)

Close to three-quarters of the global population had access to safely managed drinking water in 2024, increasing by five percentage points since 2015. Europe and North America was the region with the highest share at 94 percent, while it was lowest in Sub-Saharan Africa, reaching only 32 percent.

Achieving access to safe water and sanitation still pose major challenges in urban areas of sub-Saharan Africa countries, despite all the progress achieved in the last decade. This study assessed the ability of populations living in poor peri-urban settlements to access improved water and sanitation and identified factors influencing this access, in order to guide sustainable mitigating solutions to address associated health and environmental risks. We conducted a cross-sectional study in six poor peri-urban settlements of Yopougon, the largest municipality of Abidjan. A total of 556 randomly selected households were included. The factors associated with access to improved water and sanitation were identified through explanatory models using multivariate logistic regression. A proportion of 25% of all households assessed did not have access to clean water and 57% lacked improved sanitation. Socioeconomic status and settlement characteristics appear as the main indicators of poor access to reliable water and sanitation in peri-urban settlements. The presence of the household head’s wife at home was associated with greater access to clean water (OR = 3.57; 95% CI: 1.74, 7.31), thus highlighting the important role of women in ensuring access to clean water in these specific environments. Household size, education and religion were not significantly associated with the two considered outcomes. Women therefore should be involved at all levels of programming in water promotion in these settlements to improve the population’s well-being. While religion does not appear to play an important role in access to water and sanitation, successful interventions should involve religious communities because of their large representation.

Given nearly one third of sub-Saharan Africa’s population lack access to an improved water source that is available when needed, service continuity restricts access to safely managed services. Household surveys, water regulators, and utilities all gather data on service continuity, but few studies have integrated these disparate datasets to quantify continuity-related risk factors and inequalities. This study aimed to assess the added value of utility and regulator data for international monitoring by assessing factors affecting piped water availability in urban and peri-urban Zambia. Household ‘user’ data from the 2018 Demographic and Health Survey (n = 3047) were spatially linked to provider data from an international utility database and regulator reports. Multilevel modelling quantified provider-related and socio-economic risk factors for households reporting water being unavailable for at least one day in the previous fortnight. 47% (95% CI: 45%, 49%) of urban and peri-urban households reported water being unavailable for at least one full day, ranging from 18% (95% CI: 14%, 23%) to 76% (95% CI: 70%, 81%) across providers. Controlling for provider, home ownership (odds ratio (OR) = 1.31; p

Sub-Saharan countries not included are Botswana, Cape Verde, Comoros, Djibouti, Eritrea, Reunion, Sao Tome and Principe, and Seychelles, representing

A common challenge in interpreting and validating remote sensing data is in comparing these data to direct observations on the ground. Often remotely sensed data will cover large regions and have different temporal and spatial sampling frequency than point observations derived in the field. This kind of analysis requires geospatial tools to enable resampling, assessment of spatial statistics and extrapolation of point data to broader regions. The integration of satellite missions (GRACE) with hydrology models for determining drought indicators and water levels has been done in the United States (Houborg, et al., 2012; Zaitchick et al., 2008) using data assimilation from sophisticated observatory networks that are not available, for example, in sub-saharan Africa. However, there are studies that have analyzed operational, technical, institutional, financial, and environmental predictors of functionality for groundwater access (well) data collected from over 25,000 community-managed handpumps in Liberia, Sierra Leone, and Uganda (Foster, 2013). Lahren and Cook (2016) code and analyze the reasons for failure in 250,000 water points in 25 countries and found that 30% of boreholes are not functioning, either for "technical or mechanical” reasons, or for "low quantity". According to the World Bank, water supply failure in Africa is estimated to “represent a lost investment in excess of $1.2 billion” (Bonsor et. al. 2015). Women and girls continue to be the world’s water collectors, spending a significant fraction of their time and energy on the task (Sorenson et al 2011, Graham et al 2016, Cook et al 2016). Can a planetary scale observational tool be used to understand groundwater access and vulnerability for domestic use in rural households? If so, we can further investigate and develop the GRACE for Girls project.

Research Questions

How much is hydrological scarcity contributing to handpump failure in Africa?

In areas where domestic water access is primarily through wells, are areas with non-functional wells because of low quantity observable with remote sensing data? What spatial statistics can be used to understand the reasons for well failure using geolocated water points and falling groundwater levels?

Sample data

Point data: The Water Point Data Exchange (WPDx) is a global platfrom for sharing water point data to understand water services with 240,000 + water points in the dataset with the quantity of data varying between government support for complete datasets (all 101,000 water points in Uganda) as well as data in other countries with known GRACE observable groundwater levels (India).

The WPDx data downloaded in February 2016, and coded for well failure due to water resources issues (Lahren and Cook (2016)), is provided on Hydroshare. Go to Collaborate. Ask to Join Freshwater Group. Click on link for Freshwaterhack of UWGeohackweek. Go to Collection Contents. Click on Freshwaterhack Project: Groundwater Resources and GRACE

Remote sensing data: The Gravity Recovery and Climate Experiment (GRACE, a joint mission of NASA and the German Aerospace Center) measures the Earth's gravity anomalies to study how mass is distributed around the planet and used for studying Earth's eceans, geology, and climate.

GRACE land are available at http://grace.jpl.nasa.gov, supported by the NASA MEaSUREs Program. D.N. Wiese. 2015. GRACE monthly global water mass grids NETCDF RELEASE 5.0. Ver. 5.0. PO.DAAC, CA, USA. Dataset accessed [YYYY-MM-DD] at http://dx.doi.org/10.5067/TEMSC-OCL05.

Watkins, M. M., D. N. Wiese, D.-N. Yuan, C. Boening, and F. W. Landerer (2015), Improved methods for observing Earth’s time variable mass distribution with GRACE using spherical cap mascons, J. Geophys. Res. Solid Earth, 120, doi:10.1002/2014JB011547.

Since the 1990s, integrated catchment management (ICM) has been promoted as a holistic and integrated approach to water resources management. However, there is evidence to show that the costs and benefits associated with ICM are often inequitably distributed. This study investigates impacts of the implementation of catchment strategies on four rural communities and the coping mechanisms available to residents to cope with concomitant socioeconomic hardships within the Densu River basin, Ghana. The study relies on data collected through reviewing regulatory and policy documents, interviews, observations, and a household survey of 327 respondents. The results show that the implementation of the catchment strategies has negatively impacted the economies of all communities leading to local resistance. Increasing unemployment, decreasing incomes, and decreasing sales are generating increasing crime rates, out migration, and changing gender roles with additional burden on women. What compounds the problem are that socioeconomic interventions and coping mechanisms have failed to make any significant impact. We argue that for effective ICM, proportional representation of local people on catchment committees should be central in order to incorporate a thorough understanding of the local socioeconomic issues and integrating those issues into the implementation process; otherwise catchment strategies risk disproportionately impacting rural communities.

WATCH Forcing Data 20th Century. A meteorological forcing dataset (based on ERA-40) for land surface and hydrological models (1901-2001). Data generated in 2 tranches with slightly different methodology: 1901-1957 and 1958-2001. Five variables are at 6 hourly resolution and five variables are at 3 hourly resolution: Tair_WFD_ - 2m Air temperature (K) Tmin_WFD_ - 2m Minimum air temperature (K) Tmax_WFD_ - 2m Maximum air temperature (K) PSurf_WFD_ - 10m Surface pressure (Pa) Qair_WFD_ - 2m Specific umidity (kg/kg) Wind_WFD_ - 10m Wind speed (m/s) LWdown_WFD_ - Downwards long-wave radiation flux (W/m-2) SWdown_WFD_ - Downwards short-wave radiation flux (W/m-2) Rainf_WFD_GPCC_ - Rainfall rate GPCC bias corrected and undercatch corrected Snowf_WFD_GPCC_ - Snowfall rate GPCC bias corrected and undercatch corrected (kg/m-2/s) Rainf_WFD_CRU_ - Rainfall rate CRU bias corrected and undercatch corrected (kg/m-2/s) Snowf_WFD_CRU_ - Snowfall rate CRU bias corrected and undercatch corrected (kg/m-2/s). This data set has been produced in the framework of the "Climate change predictions in Sub-Saharan Africa: impacts and adaptations (ClimAfrica)" project, Work Package 1 (WP1). WP1 (Past climate variability) aimed to provide consolidated data to other WPs in ClimAfrica, and to analyze the interactions between climate variability, water availability and ecosystem productivity of Sub-Saharan Africa. Various data streams that diagnose the variability of the climate, in particular the water cycle, and the productivity of ecosystems in the past decades, have been collected, analyzed and synthesized. The data streams range from ground-based observations and satellite remote sensing to model simulations. More information on ClimAfrica project is provided in the Supplemental Information section of this metadata.

In 2022, countries in Sub-Saharan Africa received the most official development assistance (ODA) for water supply and sanitation with roughly *** billion U.S. dollars. Additionally, the group of least developed countries in the world, of which most are located in Sub-Saharan Africa, received assistance for more than *** billion U.S. dollars. ODA commitments are flows of official financing administered with the main objective of promoting developing countries' economic development and welfare.

This map features the GLDAS total monthly precipitation modeled globally by NASA. The map shows the monthly precipitation for the period of May 2016 to May 2018, focused on Africa. You can click the Play button on the time slider to see precipitation over time.Great parts of Northern Africa and Southern Africa, as well as the whole Horn of Africa, mainly have a hot desert climate, or a hot semi-arid climate for the wetter locations. The equatorial region near the Intertropical Convergence Zone is the wettest portion of the continent. Annually, the rain belt across the country marches northward into Sub-Saharan Africa by August, then moves back southward into south-central Africa by March.Precipitation is water released from clouds in the form of rain, sleet, snow, or hail. It is the primary source of recharge to the planet's fresh water supplies. This map contains a historical record showing the volume of precipitation that fell during each month from March 2000 to the present. Snow and hail are reported in terms of snow water equivalent - the amount of water that will be produced when they melt. Dataset SummaryThe GLDAS Precipitation layer is a time-enabled image service that shows average monthly precipitation from 2000 to the present, measured in millimeters. It is calculated by NASA using the Noah land surface model, run at 0.25 degree spatial resolution using satellite and ground-based observational data from the Global Land Data Assimilation System (GLDAS-2.1). The model is run with 3-hourly time steps and aggregated into monthly averages. A complete list of the model inputs can be seen here, and the output data (in GRIB format) is available here.Phenomenon Mapped: PrecipitationUnits: MillimetersTime Interval: MonthlyTime Extent: 2000/01/01 to presentCell Size: 28 kmSource Type: ScientificPixel Type: Signed IntegerData Projection: GCS WGS84Mosaic Projection: Web Mercator Auxiliary SphereExtent: Global Land SurfaceSource: NASAUpdate Cycle: SporadicWhat can you do with this layer?This layer is suitable for both visualization and analysis. It can be used in ArcGIS Online in web maps and applications and can be used in ArcGIS for Desktop. It is useful for scientific modeling, but only at global scales.By applying the "Calculate Anomaly" processing template, it is also possible to view these data in terms of deviation from the mean, instead of total evapotranspiration. Mean evapotranspiration for a given month is calculated over the entire period of record - 2000 to present.Time: This is a time-enabled layer. It shows the total evaporative loss during the map's time extent, or if time animation is disabled, a time range can be set using the layer's multidimensional settings. The map shows the sum of all months in the time extent. Minimum temporal resolution is one month; maximum is eight years.Variables: This layer has two variables: rainfall and snowfall. By default the two are summed, but you can view either by itself using the multidimensional filter, or by applying the relevant raster function. You must disable time animation on the layer before using its multidimensional filter.Important: You must switch from the cartographic renderer to the analytic renderer in the processing template tab in the layer properties window before using this layer as an input to geoprocessing tools.

Armed conflicts exacerbate public health challenges in Sub-Saharan Africa. Inequality across groups and poverty in rural areas can be an important factor in triggering local wars there. This study investigates whether equitable distribution of public services by governments across urban and rural geographical regions reduces the risk of local wars initiated by armed groups in Sub-Saharan African countries. Does an equitable distribution of public services such as healthcare and clean water public services across regions decrease the risk of armed conflicts? Uneven distribution of public services can increase the risk of conflict by contributing to group grievances, rural poverty, and rent-seeking competition over state resources. Analyses of 39 Sub-Saharan African countries from 1947 to 2021 show that a one-standard deviation increase in equal access to public services by urban-rural location lowers the risk of armed conflict a substantial 37 to 53 percent with consideration of a battery of control variables.