4.7 Article Data Paper

Dataset of Georeferenced Dams in South America (DDSA)

期刊

EARTH SYSTEM SCIENCE DATA
卷 13, 期 2, 页码 213-229

出版社

COPERNICUS GESELLSCHAFT MBH
DOI: 10.5194/essd-13-213-2021

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资金

  1. Ministerio de Ciencia e Innovacion (Spain) [PID2019-105852RA-I00]
  2. Universidad Tecnica de Ambato (Ecuador) [1886-CU-P-2018]

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Dams and their reservoirs play a significant role in society and the environment, facilitating water resource management while potentially causing adverse impacts related to safety, ecology, and biodiversity. Studies suggest that climate change could exacerbate these impacts, underscoring the importance of continuous monitoring and research on dams.
Dams and their reservoirs generate major impacts on society and the environment. In general, its relevance relies on facilitating the management of water resources for anthropogenic purposes. However, dams could also generate many potential adverse impacts related to safety, ecology or biodiversity. These factors, as well as the additional effects that climate change could cause in these infrastructures and their surrounding environment, highlight the importance of dams and the necessity for their continuous monitoring and study. There are several studies examining dams both at regional and global scales; however, those that include the South America region focus mainly on the most renowned basins (primarily the Amazon basin), most likely due to the lack of records on the rest of the basins of the region. For this reason, a consistent database of georeferenced dams located in South America is presented: Dataset of Georeferenced Dams in South America (DDSA). It contains 1010 entries of dams with a combined reservoir volume of 1017 km(3), and it is presented in the form of a list describing a total of 24 attributes that include the dams' names, characteristics, purposes and georeferenced locations. Also, hydrological information on the dams' catchments is also included: catchment area, mean precipitation, mean near-surface temperature, mean potential evapotranspiration, mean runoff, catchment population, catchment equipped area for irrigation, aridity index, residence time and degree of regulation. Information was obtained from public records, governments records, existing international databases and extensive internet research. Each register was validated individually and geolocated using public-access online map browsers, and then, hydrological and additional information was derived from a hydrological model computed using the Hy-droSHEDS (Hydrological data and maps based on SHuttle Elevation Derivatives at multiple Scales) dataset. With this database, we expect to contribute to the development of new research in this region. The database is publicly available at https://doi.org/10.5281/zenodo.4315647 (Paredes-Beltran et al., 2020).

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