February 7, 2023 Dataset Open Access

Zhang, Alice Tianbo; Gu, Vincent Xinyi

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    <subfield code="a">Zhang, Alice Tianbo</subfield>
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    <subfield code="a">Global Dam Tracker: A database of more than 35,000 dams with location, catchment, and attribute information</subfield>
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    <subfield code="a">&lt;p&gt;&lt;strong&gt;Citation&lt;/strong&gt;&lt;/p&gt;

&lt;p&gt;Zhang, Alice Tianbo, and Vincent Xinyi Gu. 2023. &amp;ldquo;Global Dam Tracker: A Database of More than 35,000 Dams with Location, Catchment, and Attribute Information.&amp;rdquo; &lt;em&gt;Scientific Data&lt;/em&gt; 10 (1): 111.&lt;/p&gt;

&lt;p&gt;&lt;a href="https://www.nature.com/articles/s41597-023-02008-2"&gt;https://www.nature.com/articles/s41597-023-02008-2&lt;/a&gt;&lt;/p&gt;

&lt;p&gt;&amp;nbsp;&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;Description&lt;/strong&gt;&lt;/p&gt;

&lt;p&gt;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.&lt;/p&gt;</subfield>
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