GeoDAR: Georeferenced global dam and reservoir dataset for bridging attributes and geolocations

Abstract. Dams and reservoirs are among the most widespread human-made infrastructure on Earth. Despite their societal and environmental significance, spatial inventories of dams and reservoirs, even for the large ones, are insufficient. A dilemma of the existing georeferenced dam datasets is the polarized focus on either dam quantity and spatial coverage (e.g., GOODD) or detailed attributes for limited dam quantity or regions (e.g., GRanD and national inventories). One of the most comprehensive datasets, the World Register of Dams (WRD) maintained by the International Commission on Large Dams (ICOLD), documents nearly 60,000 dams with an extensive suite of attributes. Unfortunately, WRD records are not georeferenced, limiting the benefits of their attributes for spatially explicit applications. To bridge the gap between attribute accessibility and spatial explicitness, we introduce the Georeferenced global Dam And Reservoir (GeoDAR) dataset, created by utilizing online geocoding API and multi-source inventories. We release GeoDAR in two successive versions (v1.0 and v1.1) at https://doi.org/10.6084/m9.figshare.13670527. GeoDAR v1.0 holds 21,051 dam points georeferenced from WRD, whereas v1.1 consists of a) 23,680 dam points after a careful harmonization between GeoDAR v1.0 and GRanD and b) 20,214 reservoir polygons retrieved from high-resolution water masks. Due to geocoding challenges, GeoDAR spatially resolved 40 % of the records in WRD which, however, comprise over 90 % of the total reservoir area, catchment area, and reservoir storage capacity. GeoDAR does not release the proprietary WRD attributes, but upon individual user requests we can assist in associating GeoDAR spatial features with the WRD attribute information that users have acquired from ICOLD. With a dam quantity triple that of GRanD, GeoDAR significantly enhances the spatial details of smaller but more widespread dams and reservoirs, and complements other existing global dam inventories. Along with its extended attribute accessibility, GeoDAR is expected to benefit a broad range of applications in hydrologic modelling, water resource management, ecosystem health, and energy planning.

[1]  Y. Sheng,et al.  GeoDAR: georeferenced global dams and reservoirs dataset for bridging attributes and geolocations , 2022, Earth System Science Data.

[2]  Dai Yamazaki,et al.  A new vector-based global river network dataset accounting for variable drainage density , 2021, Scientific data.

[3]  Dai Yamazaki,et al.  Role of dams in reducing global flood exposure under climate change , 2021, Nature Communications.

[4]  A. Castelletti,et al.  More than one million barriers fragment Europe’s rivers , 2020, Nature.

[5]  Chunqiao Song,et al.  Estimating seasonal water budgets in global lakes by using multi-source remote sensing measurements , 2020 .

[6]  Chunqiao Song,et al.  Remote Sensing‐Based Modeling of the Bathymetry and Water Storage for Channel‐Type Reservoirs Worldwide , 2020, Water Resources Research.

[7]  T. Pavelsky,et al.  A Participatory Science Approach to Expanding Instream Infrastructure Inventories , 2020, Earth's Future.

[8]  Huilin Gao,et al.  A high-resolution bathymetry dataset for global reservoirs using multi-source satellite imagery and altimetry , 2020 .

[9]  D. Or,et al.  Distribution of small seasonal reservoirs in semi-arid regions and associated evaporative losses , 2020, Environmental Research Communications.

[10]  K. Kornei.  Europe’s Rivers Are the Most Obstructed on Earth , 2020 .

[11]  Mark Mulligan,et al.  GOODD, a global dataset of more than 38,000 georeferenced dams , 2020, Scientific Data.

[12]  Huilin Gao,et al.  Towards Global Hydrological Drought Monitoring Using Remotely Sensed Reservoir Surface Area , 2019, Geophysical Research Letters.

[13]  Fangfang Yao,et al.  Constructing long-term high-frequency time series of global lake and reservoir areas using Landsat imagery , 2019, Remote Sensing of Environment.

[14]  H. Wheater,et al.  Representation and improved parameterization of reservoir operation in hydrological and land-surface models , 2019, Hydrology and Earth System Sciences.

[15]  Michael Durand,et al.  Global Reconstruction of Naturalized River Flows at 2.94 Million Reaches , 2019, Water resources research.

[16]  Dai Yamazaki,et al.  MERIT Hydro: A High‐Resolution Global Hydrography Map Based on Latest Topography Dataset , 2019, Water Resources Research.

[17]  Huilin Gao,et al.  Estimating reservoir evaporation losses for the United States: Fusing remote sensing and modeling approaches , 2019, Remote Sensing of Environment.

[18]  M. Thieme,et al.  Mapping the world’s free-flowing rivers , 2019, Nature.

[19]  Y. Sheng,et al.  A Global Assessment of Terrestrial Evapotranspiration Increase Due to Surface Water Area Change , 2019, Earth's future.

[20]  Yadu Pokhrel,et al.  High‐Resolution Modeling of Reservoir Release and Storage Dynamics at the Continental Scale , 2019, Water Resources Research.

[21]  Kai Liu,et al.  Identifying Emerging Reservoirs along Regulated Rivers Using Multi-Source Remote Sensing Observations , 2018, Remote. Sens..

[22]  Xi Chen,et al.  Recognizing Global Reservoirs From Landsat 8 Images: A Deep Learning Approach , 2018, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[23]  F. Habets,et al.  The cumulative impacts of small reservoirs on hydrology: A review. , 2018, The Science of the total environment.

[24]  L. Ruby Leung,et al.  A New Global Storage‐Area‐Depth Data Set for Modeling Reservoirs in Land Surface and Earth System Models , 2018, Water Resources Research.

[25]  T. Pavelsky,et al.  Global extent of rivers and streams , 2018, Science.

[26]  Christian Schwatke,et al.  A global lake and reservoir volume analysis using a surface water dataset and satellite altimetry , 2018, Hydrology and Earth System Sciences.

[27]  Yongwei Sheng,et al.  LakeTime: Automated Seasonal Scene Selection for Global Lake Mapping Using Landsat ETM+ and OLI , 2017, Remote. Sens..

[28]  S. Kanae,et al.  A high‐accuracy map of global terrain elevations , 2017 .

[29]  B. Flyvbjerg,et al.  Damming the rivers of the Amazon basin , 2017, Nature.

[30]  Yongwei Sheng,et al.  Little impact of the Three Gorges Dam on recent decadal lake decline across China's Yangtze Plain , 2017, Water resources research.

[31]  B. Lehner,et al.  Estimating the volume and age of water stored in global lakes using a geo-statistical approach , 2016, Nature Communications.

[32]  J. Pekel,et al.  High-resolution mapping of global surface water and its long-term changes , 2016, Nature.

[33]  Chunqiao Song,et al.  Recent Changes in Land Water Storage and its Contribution to Sea Level Variations , 2016, Surveys in Geophysics.

[34]  Feng Gao,et al.  Representative lake water extent mapping at continental scales using multi-temporal Landsat-8 imagery , 2016 .

[35]  D. Lettenmaier,et al.  The SWOT Mission and Its Capabilities for Land Hydrology , 2016, Surveys in Geophysics.

[36]  J. Crétaux,et al.  Lake Volume Monitoring from Space , 2016, Surveys in Geophysics.

[37]  Christian Schwatke,et al.  DAHITI – an innovative approach for estimating water level time series over inland waters using multi-mission satellite altimetry , 2015 .

[38]  Huilin Gao,et al.  Monitoring reservoir storage in South Asia from multisatellite remote sensing , 2014 .

[39]  D. Lettenmaier,et al.  Global monitoring of large reservoir storage from satellite remote sensing , 2011 .

[40]  P. Döll,et al.  High‐resolution mapping of the world's reservoirs and dams for sustainable river‐flow management , 2011 .

[41]  Stephen R. Carpenter,et al.  State of the world's freshwater ecosystems: physical, chemical, and biological changes. , 2011 .

[42]  Bin Li,et al.  Flood monitoring and analysis over the middle reaches of Yangtze River basin using MODIS time-series imagery , 2011, 2011 IEEE International Geoscience and Remote Sensing Symposium.

[43]  A. Cazenave,et al.  SOLS: A lake database to monitor in the Near Real Time water level and storage variations from remote sensing data , 2011 .

[44]  F. Ludwig,et al.  Impact of reservoirs on river discharge and irrigation water supply during the 20th century , 2011 .

[45]  Faisal Hossain,et al.  The influence of large dams on surrounding climate and precipitation patterns , 2011 .

[46]  Petra Döll,et al.  Global-scale analysis of river flow alterations due to water withdrawals and reservoirs , 2009 .

[47]  Bryan Tilt,et al.  Social impacts of large dam projects: a comparison of international case studies and implications for best practice. , 2009, Journal of environmental management.

[48]  B. Chao,et al.  Impact of Artificial Reservoir Water Impoundment on Global Sea Level , 2008, Science.

[49]  C. Vörösmarty,et al.  Anthropogenic sediment retention: major global impact from registered river impoundments , 2003 .

[50]  C. Nilsson,et al.  Alterations of Riparian Ecosystems Caused by River Regulation , 2000 .

[51]  W. Tobler.  A Computer Movie Simulating Urban Growth in the Detroit Region , 1970 .

[52]  J. Crétaux,et al.  Global surveys of reservoirs and lakes from satellites and regional application to the Syrdarya river basin , 2015 .

[53]  K. Tockner,et al.  A global boom in hydropower dam construction , 2014, Aquatic Sciences.