Research with GDW data
Research and applications using the GDW v1 global database and foundational GDW datasets
The GDW global database brings together our foundational datasets into a consistent global database of river barrier locations and attributes. In the paper Global Dam Watch: Curated Data and Tools for Management and Decision Making, we highlight GDW's aim to create a comprehensive, open-access global database of dams and instream barriers to support research, policy-making, and management. We describe the challenges of existing fragmented and inconsistent dam data, and present GDW's efforts to harmonize global datasets, provide visualization tools, and thus facilitate sustainable water resource management across scales.
Here we present key research using the GDW v1 database and our foundational datasets (GOODD, GRanD and FHReD) from which it is derived, among others. The GDW v1 global database is being used for a wide range of environmental, developmental, and research purposes. These include water resources planning, dam safety analysis, conservation planning, hydropower development research, and evaluating the impacts of dams on agriculture, river connectivity, and biodiversity. Researchers and policymakers are using the data to assess the environmental effects of dams, analyze flood risks, study the relationship between dams and water scarcity, and develop sustainable management strategies for water and energy resources globally.
Previous research with the GDW foundational datasets
GOODD dams
GOODD contains the geospatial coordinates for more than 38,000 dams across the planet. It has been cited >299 times and used in a wide range of global analyses, including the following:
The paper "Mapping the World’s Free-Flowing Rivers" provides a comprehensive global assessment of river connectivity by identifying rivers that remain free-flowing (FFRs). The study develops a Connectivity Status Index (CSI) to evaluate the impact of dams, reservoirs, and other infrastructure on river connectivity across four dimensions: longitudinal, lateral, vertical, and temporal. The findings reveal that only 37% of rivers longer than 1,000 km remain free-flowing, mostly in remote areas. The paper utilised the Global Overview Of Dam Database (GOODD) to enhance the analysis of river fragmentation. GOODD provided detailed data on medium-sized dams, which was critical for assessing the impact of these structures on river connectivity. By integrating GOODD with other global datasets, the study was able to offer a more precise evaluation of the extent to which dams and reservoirs fragment and regulate rivers, thus reducing their free-flowing status. T
The paper "Human alteration of global surface water storage variability" examines the extent of human influence on global water storage using NASA’s ICESat-2 satellite data. It finds that human-managed reservoirs account for 61% of the Earth's seasonal surface water storage variability, with significant impacts in arid regions. The study highlights the use of the GlObal GeOreferenced Database of Dams (GOODD) to identify and analyze human-managed reservoirs, providing a crucial dataset that aids in assessing the global hydrological cycle's alteration by human activities.
The paper "More than half of data deficient species predicted to be threatened by extinction" presents a machine learning approach to estimate the extinction risk for species classified as "Data Deficient" (DD) by the IUCN Red List. By analyzing data from 28,363 data-sufficient species, the study predicts that 56% of DD species are likely threatened, with particularly high risks among amphibians. The paper emphasises the importance of including DD species in conservation efforts and highlights how current biodiversity assessments might underestimate threats. The study utilises the Global Overview Of Dam Database (GOODD) as part of the predictor data for machine learning models. The inclusion of GOODD contributes to understanding human impacts, such as infrastructure development, on species’ habitats and extinction risks.
The paper titled "Recent changes to Arctic river discharge" explores the variations in water discharge from Arctic rivers over 35 years (1984-2018) using a new dataset called Remotely-sensed Arctic Discharge Reanalysis (RADR). The study found increased water export, changes in the timing of spring freshet, and reduced stream intermittency. The findings suggest significant regional variability in discharge trends, which have critical implications for understanding Arctic hydrology in the context of climate change. The study utilised the Global Overview Of Dam Database (GOODD) to identify river reaches impacted by dams. By incorporating GOODD, the researchers could better assess how human-made dams influence river discharge patterns, particularly in the regulated reaches of the Arctic rivers. This allowed the study to distinguish between natural and anthropogenic factors affecting Arctic river discharge trends.
Concentration of GOODD dams by state in North America
Concentration of GOODD dams by state in Europe
Concentration of GOODD dams by state in Asia
GRanD v1.1 and v1.3 dams
GRanD v1.1 and v1.3 contain the locations and characteristics for 7,320 dams and reservoirs across the planet. GRanD dams are snapped to the HydroSHEDS river network, which facilitates research on the size of rivers being dammed. Example applications for GRAND are shown here.
When focusing on reservoirs with storage greater than 100 million cubic metres (MCM), large dam and reservoir construction peaked between 1960 and 1969. Cumulative volume of water impounded peaked later, between 1970 and 1979. Large reservoir construction slowed considerably after these peaks. Though dam and reservoir construction has not returned to rates seen over the middle of the 20th century, the size of rivers being dammed has increased. Fewer dams with large reservoirs were built between 2000 and 2016, but the cumulative discharge of rivers being impounded by large dams nearly reaches that of the much more active decade between 1970 and 1979, indicating that recent dams are increasingly built on larger rivers.
FHReD dams
Future Hydropower Reservoirs and Dams contains the spatial location and planned megawatts for 3,700 hydropower dams that are either planned or under construction. The highest concentration of future hydropower projects can be found in Brazil. Countries like China and India also feature high concentrations of future hydropower projects. Example applications for FHRED are shown here.
Though Brazil is planning more dams than China, China is planning the highest concentration in terms of total megawatts of energy produced.
