Africa is endowed with abundant freshwater resources. It has sufficient rainfall and relatively low levels of water withdrawals for three major uses: domestic, agricultural and industrial uses. Changes in Africa’s water resources has been noticed transpiring in changes in water flow and variability, falling groundwater levels, changes in rainfall levels and timing, strongly influenced under climate change. The continent has a huge potential for energy production through hydropower. Moreover, water resource is widely recognized to play a crucial role in accomplishing the needed socio-economic development goals (UN water/Africa, 2000, Diop et al. 2021).
These freshwater resources are stored as surface reservoirs made of rivers, lakes, artificial reservoirs, wetlands, inundated areas and subsurface reservoirs that include root zones and aquifers. Being part of the climate system, and terrestrial waters (freshwater resources) are continuously exchanged with the atmosphere and oceans through vertical and horizontal mass fluxes (i.e., precipitation, evaporation, transpiration of the vegetation and surface and underground flow) defining the global hydrological water cycle (Cazenave et al. 2016). The knowledge of the global hydrological cycle, in particular its terrestrial component, is of significant importance for creating an inventory of water resources and its management for African countries.
A better understanding of the terrestrial hydrological cycle relies on a huge amount of spatial and temporal water monitoring measurements. However, the scarcity of water information in African countries is one of the main obstacles. The poor maintenance of the existing water information network has caused a decline in available water monitoring systems. The substantial losses in monitoring capacity has resulted in the limited understanding of the hydroclimatic characteristics and their variability in many places.
The gradual decline of water monitoring systems due to the higher cost of maintenance in most of the developing countries especially in Africa, necessitates the introduction of new solutions to improve water resource assessment, protection, development, management and governance based on reliable and timely water information (Koetz et al. 2016). Earth Observation (EO) technologies can help fill these gaps in many ways. Satellite remote sensing provides a valuable global overview that can monitor changes in rainfall, the extent of water bodies, vegetation and at a more local level help to identify zones with groundwater potential (Meijerink, 2007). Moreover, the processes of the terrestrial branch of the hydrologic cycle are strongly affected by the land-atmosphere dynamics and surface heterogeneity in soil type, topography, and vegetation. In situ systems cannot capture entirely the variability at the surface as these often are point measurements. Therefore, EO offers a unique opportunity to better characterize hydrological components’ variability in ungauged or sparse gauged basins due to their broad coverage (Becker et al. 2018).
1. Remote sensing of hydrological components
The 1990s is considered as the Earth observing system era when many space agencies like the National Aeronautics and Space Administration (NASA), European Space Agency (ESA), and Japan Aerospace Exploration Agency (JAXA) launched numerous space-borne sensors to study the various components of the terrestrial water cycle (Fig. 1). These include sensors to estimate soil moisture using Advanced Microwave Scanning Radiometer (AMSR), Soil Moisture and Ocean Salinity (SMOS); precipitation using Tropical Rainfall Measuring Mission (TRMM); vegetation using Moderate Resolution Imaging Spectroradiometer (MODIS); surface water level using JASON-1 and JASON-2 and TOPEX-POSEIDON; and groundwater by the mean of Gravity Recovery and Climate Experiment (GRACE) (Lakshmi et al. 2015).
Precipitation is a major element of the hydrologic cycle. The accurate quantification of its spatiotemporal variability is essential for applications in environmental, atmospheric, water resource, and related science and engineering fields (Karamouz et al., 2013; Lakshmi et al., 2015).
The two major methods for measuring precipitation are by using standard gauges and satellites. Progressively, remote sensing data/ products are becoming more available and information from these products is contributing to our understanding of the spatial and temporal distribution of precipitation as they provide near-real-time, spatially continuous precipitation estimates at smaller temporal sampling intervals. These satellite products (Fig. 2) include the Special Sensor Microwave Imager (SSM/I), Advanced Microwave Sounding Unit (AMSU), Tropical Rainfall Measuring Mission (TRMM) microwave imager (TMI) and precipitation radar (PR), Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E), etc. (Karamouz et al. 2013). It is important to note that these satellite-derived products contain uncertainties that need to be assessed before their utilization. These uncertainties are related to the retrieval methods to remotely sense clouds and precipitation from space. Infrared and visible techniques provide information only on top of the cloud that generates the precipitation. Microwave techniques are directly sensitive to precipitation. Therefore, no existing technique is suitable to serve all the spatial and temporal requirements. One of the solutions is to combine techniques to compensate the benefits and the limitations of each technique (Prigent, 2010).
Evaporation and evapotranspiration are important links in the hydrologic cycle. In hydrology and irrigation, evaporation € and transportation (Et) can be jointly considered as evapotranspiration (Karamouz et al. 2013). Traditionally, Et can be quantified by using tanks and lysimeters, field plots, and studies of groundwater fluctuations. Satellite remote sensing can be used to map the spatial distribution of Et at scales that range from region to region (e.g., due to the satellite footprint or the inter-track distance at the equator). Its accurate quantification, however, is still difficult, due to the heterogeneity of the land surface and the large number of factors that control Et (Xiong et al., 2015).
Satellite remote sensors provide very relevant information to feed Et models enabling the development of the satellite-based estimation model of global land Et (Zhang et al., 2020). Remote-sensing-based methods fall under two established categories:
• the empirical/statistical methods that estimate Et using an empirical equation deduced from remotely sensed variables; and the analytical methods, which estimate Et based on the Priestley-Taylor approach,
• the Penman-Monteith equation, or the residual method of the energy balance equation (Xiong et al., 2015).
With ongoing research, global-scale Et products like Atmosphere-Land Exchange Inverse model (ALEXI), the Global Land Evaporation Amsterdam Model (GLEAM V3.3b) and the Surface Energy Balance System (SEBS V3) are increasingly becoming available (Fig. 3).
2.3 Soil moisture
The spatiotemporal distribution of the surface soil moisture is one of the crucial variables in hydrological and meteorological applications that influences the exchange of water and energy fluxes at the land surface/ atmosphere interface (Kousik and Prabir, 2015). An accurate estimate of the spatial and temporal variations of soil moisture is critical for numerous environmental studies.
The thermogravimetric method is recognized as the standard method of measuring soil moisture content. Moreover, there are others point automated measurements such as neutron scattering, gamma-ray attenuation, soil electrical conductivity, tensiometry, and soil dielectric constant (Walker et al., 2004). Recent technological advancements in satellite remote sensing have shown that soil moisture can be measured (Fig. 4) by a variety of remote sensing techniques like optical and thermal infrared remote sensing, as well as passive and active microwave remote sensing techniques (Wang and Qu, 2009). It is important to note that each of these approaches has its advantages and constraints.
Groundwater is the most commonplace source of freshwater on continents outside the polar
regions, followed by ice caps, lakes, wetlands, reservoirs, and rivers. This position shows the importance of its optimal management as secured water resources (Karamouz et al., 2013). Unfortunately, groundwater resources assessment, modelling, and management have been significantly impeded by the lack of data. Groundwater models need spatial and temporal distributions of data for input and calibration, but classical hydrological measurements can only provide point data. Fortunately, remote sensing has opened new sources for distributed spatial data that allows the analysis of the dynamics and the changes in the storage of groundwater (Brunner, 2006; Lee, 2017).
The status of qualitative groundwater storage can be retrieved from the geological features, surface water altimetry and topography, distribution of vegetation, and the difference between precipitation and evapotranspiration. On the other hand, a quantification status (changes in mass, therefore the variation in the amount of water) can be inferred from GRACE and GRACE FOLLOW UP (Fig. 5) and InSAR sensors (Lee, 2017).
3. Spatial altimetry
Satellite radar altimetry potential value has been identified and given a high priority from 1969 and it was first designed to study spatial and temporal variability of ocean height below the vertical position of the satellite (at nadir). Furthermore, space altimetry techniques have proven to be efficient for large inland water bodies in monitoring such features as rivers, lakes, and so on (Stammer and Cazenave, 2017).
Many studies carried out on different river basins using satellite‐based altimetry show the usefulness of radar altimetry in monitoring water levels with an accuracy of a few centimetres (Kitambo et al. 2021). Thus, radar altimetry can complement existing hydrometric measurement networks, or even replace certain gauging stations considered to be unreliable or inefficient.
More than two decades, EO through satellite radar altimetry helped to retrieve continuously surface water level from multi-mission satellites (Fig. 6) such as European Remote Sensing 2 (ERS-2), Environmental Satellite (Envisat), Satellite with ARgos and ALtika (SRL) (with a repeat cycle of 35 days), Jason-2 and 3 (with a repeat cycle of 10 days) and Sentinel-3A and 3B (S3A/B) (with a repeat cycle of 27 days).
Recent developments and improvements in remote sensing techniques have allowed the measurement and monitoring of other hydrological parameters such as surface current velocity, discharge (in combination wi odellinging), water quality, surface water temperature, water extent (Cnes/Aviso 2021).
4. The case of the Ogooué and Congo River Basin
Ogooué River is known as the largest Gabonese river. The Ogooué River Basin (ORB) (Fig. 7) has faced up difficulties regarding the availability of hydrological stations. The ORB was an ungauged basin between the 1980s and 2001, and later a sparse gauged basin with one in situ gauge. Therefore, the management of water resources within the basin was hindered for longtime by the lack of a hydrological monitoring network. Recently, a study conducted by Bogning et al. (2018) was performed based on EO specifically radar altimetry to monitor water stage and discharge in the almost ungauged ORB.
An altimetry-based network of 34 virtual stations (VS) was defined across the Ogooué River and its major tributaries. Based on the rating curve relating water stages and discharge, established for the Lambaréné gauge using in situ measurements of water levels and discharge, an altimetry-based time series of discharge was obtained (Fig. 8) (Bogning et al. 2018).
The Congo River Basin (CRB) is the second-largest river basin in the world, but its hydro-climatic variability is not still well known (Laraque et al., 2020). Limited understanding of the spatial and temporal variability is mainly due to the lack of in-situ monitoring of hydrological variables. Hydrological station networks are sparse and poorly maintained (Becker, 2014). Efforts have been made to perform studies using remote sensing to overcome the issue of the lack of in situ measurements. This would allow to characterize diverse components of the hydrological cycle such as surface storage, groundwater, soil moisture, river discharge and, evapotranspiration.
Recently, a study was undertaken by Kitambo et al. (2021) based on satellite-derived observations to characterize the variability of the surface hydrology using radar altimetry and Global Inundation Extent from Multi-satellite (GIEMS-2) dataset. Both datasets have helped to understand the CRB spatio-temporal hydrological variability in terms of Surface Water Level (SWL) and Surface Water Extent (SWE) for the first time at large scale. In the beforementioned study, it has been shown that the northern sub-basins vary in large proportion while the middle and southern sub-basins present small variations of water level amplitude. GIEMS-2 dataset helped to point out that the cuvette centrale is flooded at its maximum in October/November.
A better understanding of the terrestrial hydrological cycle is relevant for creating an inventory of water resources and for managing them. However, hydrological phenomena are so complex that they require a vast amount of spatial and temporal observations. The in-situ observational network that has been installed for several years are uneven distributed due in part to the decline of several existing stations, therefore, unable to provide a good spatial coverage of data. As a result, there is an insufficient knowledge of the terrestrial hydrological water cycle that is a key issue in climate research today.
Fortunately, recent developments in remote sensing have opened new sources for distributed spatial data and remote sensing techniques have demonstrated their excellent capability to monitor several components of the water balance such as precipitation, evapotranspiration, soil moisture and groundwater of large rivers, lakes, and reservoirs, on timescales ranging from months to decades in certain African basins. It is important to notice that due to their retrieval techniques, satellite products are affected with uncertainties. In situ techniques for monitoring the above hydrological components have shown to be inadequate in terms of the spatial coverage. We presented an application case of Ogooué and Congo River Basin where radar altimetry is applied to understand the variability in these two basins. A major constraint recognized in Africa is the lack of qualified specialists to exploit these new remote sensing applications. There is therefore a pressing need to facilitate technology transfers and or to increase capacity building to Africa.