Spatiotemporal changes in river network connectivity in the Nile River Basin due to hydropower dams

Abstract

Dams offer indispensable services, including hydropower generation, water for irrigation, and flood mitigation. These barriers disrupt natural river flows, affecting river ecosystems structural and functional connectivity. The number of hydropower dams in the Nile River Basin has increased during the last decades. However, little is known regarding the spatiotemporal variation in the river network fragmentation and the individual dam contributions. We used the Reach Connectivity Index (RCI) and network centrality measures to assess temporal and spatial changes in longitudinal connectivity. We selected the Equatorial Nile and Blue Nile basins, the major hotspots for present and future hydropower developments. We collated 101 existing, under construction, and proposed dams in the Equatorial Nile Basin (ENB) from 1954 to 2035 and 19 dams in the Blue Nile Basin (BNB) from 1925 to 2035. The dams in the ENB have significantly increased over time, with a sharp increase recorded between 2010 and 2015. The mean RCI for the BNB, considering impassable dam scenarios, ranged from 62.5% (SD = 12.5%) in 1925 to 21.35% (11.6%) in 2035. Similarly, in the ENB, the mean RCI for impassable dam scenarios ranged from 50.1% (SD = 2%) in 1954 to 18.1 (12.1%) in 2035. River segments in the middle section of both basins were the most affected. The decline in the mean RCI was significantly higher in the ENB compared to BNB. The reduced connectivity is mainly in the ENB, threatening the basin’s biodiversity. Existing dams, including the Grand Ethiopian Renaissance Dam on the BNB and Kakono on the ENB, should have effective fish migratory corridors that allow the passage of fish either upstream or downstream. We also recommend establishing a detailed basin-wide database for barriers and assessing their passability to understand the full extent of the river network fragmentation. We also recommend regular monitoring of barrier impacts by integrating safe, cost-effective methods such as remote sensing and environmental DNA (eDNA) to assess both flora (macrophytes, phytoplankton) and fauna (macroinvertebrates, fish, zooplankton).