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The authors wish to make a change in author names (adding new author—Dimitrios Mentis) to this paper [1]: Author Contributions On page 19, author contributions are updated as follows: Conceptualization, A.K., D.M. and M.H.; Methodology, A.K., A.S., B.K. and D.M.; Software, A.K., B.K., A.S. and C.A.; Validation, M.H.; Formal Analysis, A.K.; Investigation, A.K.; Resources, A.K. and B.K.; Data Curation, A.K., B.K. and A.S.; Writing—Original Draft Preparation, A.K.; Writing—Review and Editing, A.K., D.M., M.H., C.A.; Visualization, A.K. and B.K.; Supervision, M.H.; Project Administration, M.H.; Funding Acquisition, M.H., D.M. and A.K. All authors have read and agreed to the published version of the manuscript. Funding On page 19, funding sources are updated as follows: This research was funded by the World Bank under the contract number 7185716 and partially by (a) the Swedish Center for Smart Grids and Energy Storage (SweGRIDS-ABB) under grant VF-2015-0018 and (b) the ÅForsk Foundation under grant 17-604. The authors would like to apologize for any inconvenience caused to the readers and contributors by these changes. The changes do not a ect the scientific results. The manuscript will be updated, and the original will remain online on the article webpage, with a reference to this correction., QC 20210223

Sub-Saharan Africa has been at the epicenter of an ongoing global dialogue around the issue of energy poverty. More than half of the world's population without access to modern energy services lives there. It also happens to be a sub-continent with plentiful renewable energy resource potential. Hydropower is one of them, and to a large extent it remains untapped. This study focuses on the technical assessment of small-scale hydropower (0.01-10 MW) in Sub-Saharan Africa. The underlying methodology was based on open source geospatial datasets, whose combination allowed a consistent evaluation of 712,615 km of river network spanning over 44 countries. Environmental, topological, and social constraints were included in the form of constraints in the optimization algorithm. The results are presented on a country and power pool basis., QC 20190503