Global Dam Tracker: A database of more than 35,000 dams with location, catchment, and attribute information

<p><strong>Citation</strong></p> <p>Zhang, Alice Tianbo, and Vincent Xinyi Gu. 2023. &ldquo;Global Dam Tracker: A Database of More than 35,000 Dams with Location, Catchment, and Attribute Information.&rdquo; <em>Scientific Data</em> 10 (1): 111.</p> <p><a href="https://www.nature.com/articles/s41597-023-02008-2">https://www.nature.com/articles/s41597-023-02008-2</a></p> <p>&nbsp;</p> <p><strong>Description</strong></p> <p>We present one of the most comprehensive geo-referenced global dam databases to date. The Global Dam Tracker (GDAT) contains 35,000 dams with cross-validated geo-coordinates, satellite-derived catchment areas, and detailed attribute information. Combining GDAT with fine-scaled satellite data spanning three decades, we demonstrate how GDAT improves upon existing databases to enable the inter-temporal analysis of the costs and benefits of dam construction on a global scale. Our findings show that over the past three decades, dams have contributed to a dramatic increase in global surface water coverage, especially in developing countries in Asia and South America. This is an important step toward a more systematic understanding of the worldwide impact of dams on local communities. By filling in the data gap, GDAT would help inform a more sustainable and equitable approach to energy access and economic development.</p>