River transport, with more than 17,000 km of navigable channels in the Congo, is a crucial part of the economy for many of the countries sharing the river basin and allows the transport of many goods (timber, charcoal, minerals etc.) and enables access to many areas where roads do not exist. However, river transport falls short of the role it could play in development of the region and has actually declined since the Congo basin countries became independent in the 1960s. This is in part due to years of civil unrest, aging equipment, a lack of infrastructure maintenance, and the poor support and operation of public waterway agencies. River navigation maps are a specialist form of map specifically designed to allow safe navigation of river traffic such as for barges carrying cargo. Boat captains use them as they travel along the river to follow the advised navigation route and avoid hazards such as submerged rocks and shallow channels. The navigation maps for the 1,700 km of river between Kinshasa and Kisangani are issued by RVF (Régie de Voie Fluvial), the state river navigation authority, and are therefore used by all boat captains. These maps originate from the early 1900s and have not been updated since colonial times. As part of the CRuHM project we are exploring the possibility of updating these maps using modern remote sensing methods, together with RVFs experienced input. As part of the update process, RVF have provided us with detailed digital scans of the original navigation maps and we are geo-referencing these to modern geospatial projections, in line with the remote sensing data. This provides us with a unique opportunity to compare snapshots of the river system geomorphology separated by nearly 100 years. We will show the current state of the project and some of the river secrets we have discovered so far.

The latest work on the main African rivers on the Atlantic coast has made it possible to subdivide the multi-year streamflow records into several homogeneous phases. The year 1970 seems to mark both for West and Central Africa the major hydroclimatic event of the 20th century, heralding its main period of deficit flow. For the first time, this article presents a comparative study of the hydro-rainfall records of five drainage systems (those of the Congo River and its main tributaries Lualaba, Kasai, Sangha, Oubangui) based on field data, obtained on both the left and right banks of the Congo River. A reconstitution of the Cuvette Centrale regime is proposed. The 1970 hydro-rainfall disruption is common in most tributaries of the Congo River basin, with significant reductions in flows depending on various factors (geographical location, vegetation cover, surface conditions and land use, etc.). The Oubangui is the most fragile northern tributary that continues to suffer from flow deficits, with an increase in the duration and intensity of its low flows. Since 1995, flows of the Congo River at its main station in Brazzaville/Kinshasa seem to have returned to the interannual average since 1903. However, from the same year onwards, an increase in seasonal variability and a decrease in spring flood flows can also be observed for its bimodal tributaries. This article explains some of the hydrological paradoxes specific to this basin, which illustrate the complexity of its hydrological functioning. Finally, it shows that the period of excess flow in the 1960s is the major hydrological anomaly of the Congo River over a continuous 116-year history. For the whole basin, hydrological variations are attenuated compared to those of precipitation. Finally, the hydrometric regimes reconstructed by spatial altimetry and modelling are compared with those from in situ data.

A reach-scale high resolution digital elevation model (DEM) of the Congo’s main stem bathymetry is presented. The Bathymetry DEM covers a multichannel reach of the main stem situated in the Cuvette Centrale, and is developed from a series of in-situ measurements of bathymetry, water surface elevation and discharge that were obtained during a CRuHM fieldtrip in summer 2017. The main stem’s complex network of channel threads requires a bathymetry modelling methodology that is capable of intelligently interpolating the raw bathymetry measurements. The methodology must also estimate a significant portion of the bathymetry, since it is not feasible to measure the entire extent of the massive and complex channel network that this study reach is comprised of. This methodology is also presented. Remote sensing from satellites is increasingly being used to resolve the scarcity of contemporary hydrological and hydrographic measurements in the Congo Basin. However, river channel bathymetry information cannot yet be reliably obtained from remote sensing methods. This is problematic since river channel representation has been shown to be an essential input into a hydraulic model. Analyses of satellite observations suggest that, relative to other global rivers, in-channel flows on the Congo’s main stem represent a relatively large proportion of total flows through the river-floodplain system. This implies the Congo’s in-channel bathymetry may play a relatively large role in controlling Congo main stem hydrodynamics. When used in a hydraulic model, the bathymetry DEM presented here will provide new information on Congo in-channel hydraulics and the extent to which bathymetry controls the Congo’s middle reach hydrodynamics. It will help better quantify the capacity of the Congo main stem channels through the Cuvette Centrale, and thus provide further insights into the extent to which the main stem channel floods in this region. It is also intended to be used for testing simplified methods of Congo bathymetry representation that are necessary for larger scale hydraulic models.

Flood disasters have regularly been reported in the Congo Basin with significant damages to human lives, food production systems and infrastructure. Losses incurred by these damages are huge and represent a major challenge for economic expansion in developing nations. In the Congo River Basin, where availability of in-situ data is a significant challenge, new approaches are needed to investigate flood risks and enable effective management strategies. This study uses recently developed global flood prediction data in order to produce flood risk maps for the Congo River Basin, where flood information currently does not exist. Flood hazard maps that estimate fluvial flooding at a grid cell resolution of 3 arc-seconds (~ 90 m), gridded population density data of 1 arc-second (~ 30 m) spatial resolution, and a spatial layer of infrastructure dataset are used to addresses flood risk at the scale of the Congo Basin. The global flood data provides different return periods of exposure to flooding in the Congo Basin and identifies flood extents. The risk analysis results are presented in terms of the percentage of population and infrastructure at flood risk for six return periods (5, 10, 20, 50, 75 and 100 year). Of the 525 administrative territories, 374 are AGU Books

The Congo Basin exhibits tremendous heterogeneities, out of which it emerges as an intricate system where complexity will vary consistently over time and space. Increased complexity in the absence of adequate knowledge will always result in increased uncertainties. One way of simplifying this complexity is through an understanding of organisational relationships of the landscape features, which is termed here as catchment classification. The need for a catchment classification framework for the Congo Basin is obvious given the basin’s inherent heterogeneities, the ungauged nature of the basin, and the pressing needs for water resources management that include the quantification of current and future supplies and demands, which also encompass the impacts of future changes associated with climate and land use, as well as water resources operational policies. The need is also prompted by many local-scale management concerns within the basin. This study uses an a priori approach to determine homogenous climatic-physiographic regions that are expected to underline dominant hydrological processes characteristics. A set of 1740 catchment units are partitioned across the whole basin, based on a set of comprehensive criteria, including natural break of the elevation gradient (199 units), inclusion of socio-economic and anthropogenic systems (204 units), and water management units based on traditional nomenclature of the rivers within the basin (1337 units). The identified catchment units are used to assess existing datasets of the basin physical properties, necessary to derive descriptors of the catchments characteristics. An unsupervised classification, based on Hierarchical Agglomerative Cluster algorithm is used, that yields 11 homogenous groups that are consistent with the current perceptual understanding of the Congo Basin physiographic and climatic settings. These regions represent therefore an a priori classification that will be further used to derive functional relationships of the catchments, necessary to enable hydrological prediction and water management in the basin.

The Congo River provides potential for socio-economic growth at the regional scale, but with limited information on the river dynamics it is difficult for basin countries to benefit from this potential, and to invest in the development of water resources. In recent years, the number of hazards related to navigation and flooding has sharply increased, resulting in high loss of human lives as well as economic losses. Associated problems of river management in the Congo also include inefficiency in hydropower production, an increase in rate of river sedimentation and land use changes. Accurate information is needed to support adequate management strategies such as prediction of navigation water levels and sediment movement, and assessment of environmental impacts and engineering implications of water resources infrastructure. Modelling approaches and space observations have been used to understand the Congo River dynamics, but their effective application has proved difficult due to a lack of ground-based observational data for validation. Recent developments in data capture with acoustic Doppler technologies have considerably improved measurements of river dynamics. As well measuring river discharge, they also allow the analysis of the multiple hydrodynamic features occurring in fluvial systems. This paper presents the results of field measurement campaigns carried out in the middle reach of the Congo River and the Kasai tributary using state of the art measurement technology (ADCP, Sonar, GNSS) for investigation of large rivers. The measurements relate to river flow at multiple transects, river bathymetry, static and continuous water surface elevation, and targeted sediment sampling along the river. The paper provides a descriptive summary of the measurement results, a discussion on the application and performance of the equipment used in the Congo River, and lessons for future use of this equipment for measurements of large rivers in a data scarce environment such as the Congo Basin.

Land use change due to population growth and an increase in anthropogenic activities such as logging and mining (mostly illegal) have led to an increase in the sediment load of the Kasai River in the Congo River Basin. However, even with recent developments in technologies such as remote sensing and improvements in erosion prediction models to study sediment transport in water bodies; this phenomenon has been little studied in this poorly gauged catchment and the wider Congo River Basin due to lack of field-based sediment concentration measurements required to calibrate the results of such studies. The present study describes recently concluded field excursions to set up a high frequent sediment sampling station on one of the major tributaries of Congo River, the Kasai River. The station is fitted with an ISCO 6712 automatic pumping sampler to enable high frequency sampling. The ISCO is coupled with an OBS 501 turbidity sensor to collect even higher frequent sediment concentration data. The site is also fitted with other instruments to measure other hydrologic and climatic variables such as a manual staff gauge and an automatic water levels logger. The preliminary sampling efforts have been designed to guide a comprehensive sediment sampling programme which is part of a wider study to build a sediment yield model for the Congo River Basin in order to study the impacts of sedimentation on hydropower planning.

This study intends to integrate heterogeneous remote sensing observations and hydrological modelling into a simple framework to monitor hydrological variables in the poorly gauged Congo River basin (CRB). It focuses on the possibility to retrieve effective channel depths and discharges all over the basin in near real time (NRT). First, this paper discusses the complexity of calibrating and validating a hydrologic–hydrodynamic model (namely the MGB model) in the CRB. Next, it provides a twofold methodology for inferring discharge at newly monitored virtual stations (VSs, crossings of a satellite ground track with a water body). It makes use of remotely sensed datasets together with in-situ data to constrain, calibrate and validate the model, and also to build a dataset of stage/discharge rating curves (RCs) at 709 VSs distributed all over the basin. The model was well calibrated at the four gages with recent data (Nash-Sutcliffe Efficiency, NSE> 0.77). The satisfactory quality of RCs basin-wide (mean NSE between simulated discharge and rated discharge at VSs, NSEmean = 0.67) is an indicator of the overall consistency of discharge simulations even in ungauged upstream sub-basins. This RC dataset provides an unprecedented possibility of NRT monitoring of CRB hydrological state from the current operational satellite altimetry constellation. The discharges estimated at newly monitored locations proved to be consistent with observations. They can be used to increase the temporal sampling of water surface elevation (WSE) monitoring from space with no need for new model runs. The RC located under the fast sampling orbit of the SWOT satellite, to be flown in 2022, will be used to infer daily discharge in major contributors and in the Cuvette Centrale, as soon as data is released.

A multi-model hydrological assessment in the Congo Basin is performed to assess water availability conditions for historical and future periods (1913–2099). With models limited by scarce in situ observations, a combination of GRACE satellite data and soil-moisture-based drought indices is shown to be capable of estimating water budget, streamflow, and drought and storage variability. Changes in land use and land cover played a role in modifying the hydrologic responses but were found to be within the uncertainties of other inputs, including weather, soil, and model parameters. Seasonal and annual variability in total water storage anomalies (TWSAs) and the modified Palmer drought severity index (MPDSI) display a good correlation with each other. A selected set of global climate models is used to characterize the future temperature and precipitation patterns. It is expected that subbasin-scale variability in future temperature and precipitation increases will result in increased evapotranspiration, decreased runoff, and more drought events in the Congo Basin.