ADHI: The African Database of Hydrometric Indices (1950-2018)

The African continent is probably the one with the lowest density of hydrometric stations currently measuring river discharge, despite the fact that the number of stations was quite important until the 70s. In addition, there is a major issue of data availability, since the different existing datasets are scattered across vast regions, heterogeneous and often with a large amount of missing data in the time series. The aim of this African Dataset of Hydrometric Indices (ADHI) is to provide a set of hydrometric indices computed from an unprecedented large set of daily discharge data in Africa. The ADHI database is based on a new streamflow dataset of 1466 gauging stations with an average record length of 33 years and for over 100 stations complete records are available over 50 years. ADHI is compiling data from different sources carefully checked, based on the historical databases of ORSTOM / IRD and the GRDC, including also other contributions from different countries and basin agencies. The criterion for a station to be included in ADHI is to have a minimum of 10 full years of daily discharge data between 1950 and 2018 with less than 5% missing data. Some time series originating from different sources were concatenated, after making sure the rating curves applied on the different time periods to compute river discharge were similar. Data records were scrutinized to identify suspicious discharge records and time periods where gap-filling methods have been applied to the original records. The selected stations are spread across the whole African continent, with the highest density in Western and Southern Africa and the lowest density in Eastern Africa. They are representative of most of the climate zones of Africa according the Köppen-Geiger climate classification. From this dataset, a large range of hydrological indices and flow signatures have been computed and made available to the scientific community (https://doi.org/10.23708/LXGXQ9). They are representing mean flow characteristics and extremes (low flows and floods) but also catchment characteristics, allowing to study the long-term evolution of hydrology in Africa and support the modelling efforts that aim at reducing the vulnerability of African countries to hydro-climatic variability.