GOODD, a global dataset of more than 38,000 georeferenced dams

Mulligan, Mark; Soesbergen, Arnout van; Sáenz, Leonardo

doi:10.1038/s41597-020-0362-5

Cited by 270 publications

(203 citation statements)

References 19 publications

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“…There are no agreed standards regarding the collection of dam data. At a global level, there are only two open-access data publications on dams (Lehner et al, 2011;Mulligan et al, 2020). In order to create a national dam inventory for Germany (DIG), we have followed six steps ( Figure 1).…”

Section: Data Compilation Proceduresmentioning

confidence: 99%

“…In the case of conflicting information, the following hierarchy of information sources was applied taking into consideration the perceived reliability of the sources: 1) book of dams in Germany (Deutsche TalsperrenKomitee e. V., 2013); 2) state agencies reports (e.g. Landesanstalt für Umwelt Baden-Württemberg); 3) other dam databases (Lehner et al, 2011;Mulligan et al, 2020); 4) engineering reports; 5) web-pages. In order to have as much information as possible for each dam, the search was an iterative process, where the priority rule was applied during every round.…”

Section: Data Compilation Proceduresmentioning

confidence: 99%

“…by Lehner et al (2011) is the second most complete set of dam information for Germany, containing information of geolocation, dam height, purpose and lake area for 60 dams in Germany. The GOODD database (Mulligan et al, 2020) covers 142 dams in Germany but contains no information apart from the geolocation and watershed size. The global databases are the only information that can be used directly in a GIS environment and provide coordinates for each dam.…”

Section: Data Compilation Proceduresmentioning

confidence: 99%

“…The first version was made publicly available in 2011 with 6,862 dams, and an updated version was released in 2019 containing more than 7,000 dams. Recently, the GlObal geOreferenced Databased of Dams -GOODD, (Mulligan et al, 2020) was published, containing more than 38,000 dams (and their catchments) across the whole globe. For the German territory, the GRanD database contains 60 dams, while the GOODD database contains 142 dams.…”

mentioning

confidence: 99%

“…We collected information about 530 dams in Germany and individually identified their location using satellite images from Google Earth. The database was evaluated via a comparison with the available dam databases GRanD (Lehner et al, 2011) and GOODD (Mulligan et al, 2020), and the Sustainable Development Goal 6 product (Pekel et al, 2016). Our database contains significantly more dams than the compilation of the German Commission on Dams and combines different sources of information to provide detailed information, that are herewith made freely available.…”

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confidence: 99%

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Inventory of dams in Germany

Speckhann¹,

Kreibich²,

Merz³

2020

Preprint

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Abstract. Dams are an important element of water resources management. Data about dams are crucial for practitioners, scientists and policymakers for various purposes, such as seasonal forecasting of water availability or flood mitigation. However, detailed information on dams on the national level for Germany is so far not freely available. We present the most comprehensive, open-access dam inventory for Germany (DIG) to date. We have collected and combined information on dams using books, state agency reports, engineering reports, and internet pages. We have applied a priority rule that ensures the highest level of reliability for the dam information. Our dam inventory comprises 530 dams in Germany with information on name, location, river, start year of construction and operation, crest length, dam height, lake area, lake volume, purpose, dam structure and building characteristics. We have used a global, satellite-based water surface raster to evaluate the location of the dams. A significant part (63 %) of dams has been built between 1950–2013. Our inventory shows that dams in Germany are mostly single-purpose (52 %), 53 % can be used for flood control, and 25 % are involved in energy production. The inventory will be freely available through GFZ Data Services (https://doi.org/10.5880/GFZ.4.4.2020.005) after discussion. In the meantime the data can be downloaded using the following temporary link https://dataservices.gfz-potsdam.de/panmetaworks/review/09c134e13a7ede5d80d67f641d615698c05917fac25fc776240a110d2df96a66/ (Speckhann et al., 2020).

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Section: Data Compilation Proceduresmentioning

confidence: 99%

Section: Data Compilation Proceduresmentioning

confidence: 99%

Section: Data Compilation Proceduresmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Inventory of dams in Germany

Speckhann¹,

Kreibich²,

Merz³

2020

Preprint

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Growing water scarcities: Responses of India and China

Lele

2021

Applied Eco Perspectives Pol

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Identifying priority areas for surface water protection in data scarce regions: An integrated spatial analysis for Zambia

Lehner

Katiyo

Chivava

et al. 2021

Aquatic Conservation

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1. This study aimed to develop an integrated analytical framework to identify candidate sites for surface water protection that is applicable at broad scales and in data scarce regions, using Zambia as a case study. In the Zambian Water Resources Management Act of 2011, Water Resource ProtectionAreas are defined as areas where special measures are necessary for the protection of a catchment, sub-catchment, aquifer, or geographical area. Three specific selection criteria are listed for the definition of Water Resource Protection Areas: (i) areas of high importance in providing water to users in a catchment; (ii) aquatic areas of high ecological importance; and (iii) areas that are particularly sensitive to human impact.3. In this project, each sub-catchment and river reach of Zambia was characterized for their importance regarding these three criteria. 'Water provisioning' was assessed by analysing patterns of runoff generation and human water use; 'aquatic ecological importance' was determined by conducting a freshwater biodiversity and ecosystem assessment using a systematic conservation planning approach; and 'sensitive areas' were identified by quantifying erosion potential and sediment transport. The work was supported by an assessment of free-flowing rivers in Zambia, i.e., those rivers where aquatic ecosystem functions and services are largely unaffected by changes to fluvial connectivity through dams and other infrastructure. 4. Highly ranked sub-catchments were found in the Liuwa, Barotse, and Bangweulu floodplains and wetlands, and in the headwater regions of the upper Zambezi, Kafue, Chambeshi/Luapula, and Tanganyika catchments. The Luangwa was identified as the highest ranked candidate river for protection within Zambia.5. The resulting maps, data, and methods are intended to support national-scale efforts to prioritize areas for surface water protection, identify catchments and rivers with high conservation value, optimize decision making for infrastructure development, and inform concerted strategies to maintain and restore freshwater ecosystem services in Zambia.

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GOODD, a global dataset of more than 38,000 georeferenced dams

Cited by 270 publications

References 19 publications

Inventory of dams in Germany

Inventory of dams in Germany

Growing water scarcities: Responses of India and China

Identifying priority areas for surface water protection in data scarce regions: An integrated spatial analysis for Zambia

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