Global River Barrier Detection Using Multi-Temporal SWOT Water Surface Elevation Observations

Rivers worldwide are increasingly harnessed to meet growing demands for hydropower, irrigation, water supply, and flood control. With over 58,000 large dams, 82,891 smaller hydropower installations, and countless undocumented barriers globally, humans have appropriated more than half of accessible freshwater runoff. Consequently, only an estimated 23% of the world's large rivers (>1,000 km in length) flow uninterrupted to the ocean.

Demand for non-fossil fuel energy and water security will likely increase reliance on river infrastructure throughout the 21st century, with hydropower production projected to grow by 50% by 2030. However, dam construction has modified flow conditions, altered thermal regimes and dissolved gas concentrations, disrupted fish migration routes, and degraded spawning habitats. Freshwater ecosystems are consequently among the most threatened globally, with biodiversity declining faster than in terrestrial or marine systems. In response, dam removals are accelerating in Europe and the United States, and the European Biodiversity Strategy aims to restore at least 25,000 km of free-flowing rivers by 2030 through barrier removal and floodplain restoration. Climate change amplifies these pressures, intensifying droughts and flooding while making river conservation increasingly urgent.

Regularly updating barrier databases is therefore essential for tracking new, existing, and removed structures, as well as those modified for fish passage or sediment transport. Yet significant gaps persist. While Global Dam Watch documents over 41,000 barrier locations and the AMBER database catalogues at least 1.2 million instream barriers across 36 European countries, current detection methods perpetuate systematic biases. Ground surveys are resource-intensive and geographically concentrated in developed regions. Optical satellite imagery cannot reliably identify submerged weirs, low-head structures beneath vegetation canopy, or barriers in cloud-prone areas. Smaller anthropogenic structures—which constitute the majority of barriers globally—remain underrepresented outside well-surveyed regions, and natural obstructions are rarely catalogued despite their ecological and hydraulic significance.

We present a detection framework exploiting multi-temporal Surface Water and Ocean Topography (SWOT) water surface elevation (WSE) observations to identify barriers through diagnostic hydraulic signatures. Any obstruction creating step changes in WSE—whether anthropogenic (dams, weirs, culverts) or natural (waterfalls, logjams, bedrock outcrops)—generates characteristic spatial discontinuities and temporal variations in upstream ponding extent. By analysing WSE patterns across multiple satellite overpasses, the framework identifies anomalous hydraulic behaviour indicative of flow obstruction. Applied globally, the framework successfully detects barriers previously absent from existing databases, proving particularly effective for submerged weirs, recently constructed structures, low-head barriers obscured in optical imagery, and natural obstructions in remote regions. While previous studies report that Europe has the highest density of medium and small river barriers, we found that Asian rivers—especially in China and India—are disproportionately impacted by large dams. This approach represents a paradigm shift from geographically constrained inventories toward continuous, satellite-based global monitoring. The resulting datasets will enhance hydrological modelling, inform ecosystem restoration and flood risk mitigation worldwide.