Articles | Volume 9, issue 2
https://doi.org/10.5194/essd-9-765-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/essd-9-765-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Review article
| 
10 Oct 2017
Review article |
| 10 Oct 2017
Overview of NASA's MODIS and Visible Infrared Imaging Radiometer Suite (VIIRS) snow-cover Earth System Data Records
George A. Riggs
CORRESPONDING AUTHOR
SSAI, Inc., 10210 Greenbelt Road, Suite 600, Lanham, MD 20706, USA
Dorothy K. Hall
Terrestrial Information Laboratory, Code 619, NASA/GSFC, Greenbelt, MD 20771, USA
Michigan State University, Department of Geography, East Lansing, MI 48824, USA
Miguel O. Román
Terrestrial Information Laboratory, Code 619, NASA/GSFC, Greenbelt, MD 20771, USA
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Dorothy K. Hall, George A. Riggs, Nicolo E. DiGirolamo, and Miguel O. Román
Hydrol. Earth Syst. Sci., 23, 5227–5241, https://doi.org/10.5194/hess-23-5227-2019, https://doi.org/10.5194/hess-23-5227-2019, 2019
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Global snow cover maps have been available since 2000 from the MODerate resolution Imaging Spectroradiometer (MODIS), and since 2000 and 2011 from the Suomi National Polar-orbiting Partnership (S-NPP) and the Visible Infrared Imaging Radiometer Suite (VIIRS), respectively. These products are used extensively in hydrological modeling and climate studies. New, daily cloud-gap-filled snow products are available from both MODIS and VIIRS, and are being used to develop an Earth science data record.
Jianglong Zhang, Jeffrey S. Reid, Blake Sorenson, Steven D. Miller, Miguel O. Román, Zhuosen Wang, Robert J. D. Spurr, Shawn Jaker, Thomas F. Eck, and Juli I. Rubin
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-181, https://doi.org/10.5194/amt-2024-181, 2024
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Using observations from the Visible Infrared Imaging Radiometer Suite Day-Night Band, we developed a method for constructing gridded nighttime aerosol optical thickness (AOT) data based on the spatial derivative of measured top-of-atmosphere attenuated upwelling artificial lights at night. The gridded nighttime AOT retrievals, compared against Aerosol Robotic Network data, show reasonable skill levels for potential data assimilation, air quality and climate studies of significant events.
Dorothy K. Hall, George A. Riggs, Nicolo E. DiGirolamo, and Miguel O. Román
Hydrol. Earth Syst. Sci., 23, 5227–5241, https://doi.org/10.5194/hess-23-5227-2019, https://doi.org/10.5194/hess-23-5227-2019, 2019
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Global snow cover maps have been available since 2000 from the MODerate resolution Imaging Spectroradiometer (MODIS), and since 2000 and 2011 from the Suomi National Polar-orbiting Partnership (S-NPP) and the Visible Infrared Imaging Radiometer Suite (VIIRS), respectively. These products are used extensively in hydrological modeling and climate studies. New, daily cloud-gap-filled snow products are available from both MODIS and VIIRS, and are being used to develop an Earth science data record.
Z. Wang, M. O. Román, Q. Sun, A. L. Molthan, L. A. Schultz, and V. L. Kalb
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1853–1856, https://doi.org/10.5194/isprs-archives-XLII-3-1853-2018, https://doi.org/10.5194/isprs-archives-XLII-3-1853-2018, 2018
Alden C. Adolph, Mary R. Albert, and Dorothy K. Hall
The Cryosphere, 12, 907–920, https://doi.org/10.5194/tc-12-907-2018, https://doi.org/10.5194/tc-12-907-2018, 2018
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In our studies of surface temperature in Greenland, we found that there can be differences between the temperature of the snow surface and the air directly above, depending on wind speed and incoming solar radiation. We also found that temperature measurements of the snow surface from remote sensing instruments may be more accurate than previously thought. Our results are relevant to studies of climate change in the remote sensing community and in studies of the atmospheric boundary layer.
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CAMELS-DE: hydro-meteorological time series and attributes for 1582 catchments in Germany
Observational partitioning of water and CO2 fluxes at National Ecological Observatory Network (NEON) sites: a 5-year dataset of soil and plant components for spatial and temporal analysis
CIrrMap250: annual maps of China's irrigated cropland from 2000 to 2020 developed through multisource data integration
HANZE v2.1: an improved database of flood impacts in Europe from 1870 to 2020
A Copernicus-based evapotranspiration dataset at 100 m spatial resolution over four Mediterranean basins
Gridded dataset of nitrogen and phosphorus point sources from wastewater in Germany (1950–2019)
High-resolution hydrometeorological and snow data for the Dischma catchment in Switzerland
A globally sampled high-resolution hand-labeled validation dataset for evaluating surface water extent maps
CAMELS-INDIA: hydrometeorological time series and catchment attributes for 472 catchments in Peninsular India
Satellite-based near-real-time global daily terrestrial evapotranspiration estimates
Multivariate characterisation of a blackberry–alder agroforestry system in South Africa: hydrological, pedological, dendrological and meteorological measurements
SHIFT: a spatial-heterogeneity improvement in DEM-based mapping of global geomorphic floodplains
First comprehensive stable isotope dataset of diverse water units in a permafrost-dominated catchment on the Qinghai–Tibet Plateau
Lena River biogeochemistry captured by a 4.5-year high-frequency sampling program
LamaH-Ice: LArge-SaMple DAta for Hydrology and Environmental Sciences for Iceland
High-resolution mapping of monthly industrial water withdrawal in China from 1965 to 2020
Evapotranspiration evaluation using three different protocols on a large green roof in the greater Paris area
Simbi: historical hydro-meteorological time series and signatures for 24 catchments in Haiti
CAMELE: Collocation-Analyzed Multi-source Ensembled Land Evapotranspiration Data
A hydrogeomorphic dataset for characterizing catchment hydrological behavior across the Tibetan Plateau
A synthesis of Global Streamflow Characteristics, Hydrometeorology, and Catchment Attributes (GSHA) for large sample river-centric studies
FOCA: a new quality-controlled database of floods and catchment descriptors in Italy
Dams in the Mekong: a comprehensive database, spatiotemporal distribution, and hydropower potentials
A global dataset of the shape of drainage systems
An extensive spatiotemporal water quality dataset covering four decades (1980–2022) in China
HERA: a high-resolution pan-European hydrological reanalysis (1950–2020)
BCUB - A large sample ungauged basin attribute dataset for British Columbia, Canada
Flood simulation with the RiverCure approach: the open dataset of the 2016 Águeda flood event
GloLakes: water storage dynamics for 27 000 lakes globally from 1984 to present derived from satellite altimetry and optical imaging
AltiMaP: altimetry mapping procedure for hydrography data
CAMELS-CH: hydro-meteorological time series and landscape attributes for 331 catchments in hydrologic Switzerland
The use of GRDC gauging stations for calibrating large-scale hydrological models
A long-term dataset of simulated epilimnion and hypolimnion temperatures in 401 French lakes (1959–2020)
GTWS-MLrec: global terrestrial water storage reconstruction by machine learning from 1940 to present
A global 5 km monthly potential evapotranspiration dataset (1982–2015) estimated by the Shuttleworth–Wallace model
A gridded dataset of consumptive water footprints, evaporation, transpiration, and associated benchmarks related to crop production in China during 2000–2018
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A global streamflow indices time series dataset for large-sample hydrological analyses on streamflow regime (until 2022)
Soil water retention and hydraulic conductivity measured in a wide saturation range
A high-frequency, long-term data set of hydrology and sediment yield: the alpine badland catchments of Draix-Bléone Observatory
Geospatial dataset for hydrologic analyses in India (GHI): a quality-controlled dataset on river gauges, catchment boundaries and hydrometeorological time series
Lake-TopoCat: a global lake drainage topology and catchment database
Three years of soil moisture observations by a dense cosmic-ray neutron sensing cluster at an agricultural research site in north-east Germany
A long-term monthly surface water storage dataset for the Congo basin from 1992 to 2015
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An ensemble of 48 physically perturbed model estimates of the 1∕8° terrestrial water budget over the conterminous United States, 1980–2015
The UKSCAPE-G2G river flow and soil moisture datasets: Grid-to-Grid model estimates for the UK for historical and potential future climates
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Ralf Loritz, Alexander Dolich, Eduardo Acuña Espinoza, Pia Ebeling, Björn Guse, Jonas Götte, Sibylle K. Hassler, Corina Hauffe, Ingo Heidbüchel, Jens Kiesel, Mirko Mälicke, Hannes Müller-Thomy, Michael Stölzle, and Larisa Tarasova
Earth Syst. Sci. Data, 16, 5625–5642, https://doi.org/10.5194/essd-16-5625-2024, https://doi.org/10.5194/essd-16-5625-2024, 2024
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The CAMELS-DE dataset features data from 1582 streamflow gauges across Germany, with records spanning from 1951 to 2020. This comprehensive dataset, which includes time series of up to 70 years (median 46 years), enables advanced research on water flow and environmental trends and supports the development of hydrological models.
Einara Zahn and Elie Bou-Zeid
Earth Syst. Sci. Data, 16, 5603–5624, https://doi.org/10.5194/essd-16-5603-2024, https://doi.org/10.5194/essd-16-5603-2024, 2024
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Quantifying water and CO2 exchanges through transpiration, evaporation, net photosynthesis, and soil respiration is essential for understanding how ecosystems function. We implemented five methods to estimate these fluxes over a 5-year period across 47 sites. This is the first dataset representing such large spatial and temporal coverage of soil and plant exchanges, and it has many potential applications, such as examining the response of ecosystems to weather extremes and climate change.
Ling Zhang, Yanhua Xie, Xiufang Zhu, Qimin Ma, and Luca Brocca
Earth Syst. Sci. Data, 16, 5207–5226, https://doi.org/10.5194/essd-16-5207-2024, https://doi.org/10.5194/essd-16-5207-2024, 2024
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This study presented new annual maps of irrigated cropland in China from 2000 to 2020 (CIrrMap250). These maps were developed by integrating remote sensing data, irrigation statistics and surveys, and an irrigation suitability map. CIrrMap250 achieved high accuracy and outperformed currently available products. The new irrigation maps revealed a clear expansion of China’s irrigation area, with the majority (61%) occurring in the water-unsustainable regions facing severe to extreme water stress.
Dominik Paprotny, Paweł Terefenko, and Jakub Śledziowski
Earth Syst. Sci. Data, 16, 5145–5170, https://doi.org/10.5194/essd-16-5145-2024, https://doi.org/10.5194/essd-16-5145-2024, 2024
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Knowledge about past natural disasters can help adaptation to their future occurrences. Here, we present a dataset of 2521 riverine, pluvial, coastal, and compound floods that have occurred in 42 European countries between 1870 and 2020. The dataset contains available information on the inundated area, fatalities, persons affected, or economic loss and was obtained by extensive data collection from more than 800 sources ranging from news reports through government databases to scientific papers.
Paulina Bartkowiak, Bartolomeo Ventura, Alexander Jacob, and Mariapina Castelli
Earth Syst. Sci. Data, 16, 4709–4734, https://doi.org/10.5194/essd-16-4709-2024, https://doi.org/10.5194/essd-16-4709-2024, 2024
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This paper presents the Two-Source Energy Balance evapotranspiration (ET) product driven by Copernicus Sentinel-2 and Sentinel-3 imagery together with ERA5 climate reanalysis data. Daily ET maps are available at 100 m spatial resolution for the period 2017–2021 across four Mediterranean basins: Ebro (Spain), Hérault (France), Medjerda (Tunisia), and Po (Italy). The product is highly beneficial for supporting vegetation monitoring and sustainable water management at the river basin scale.
Fanny J. Sarrazin, Sabine Attinger, and Rohini Kumar
Earth Syst. Sci. Data, 16, 4673–4708, https://doi.org/10.5194/essd-16-4673-2024, https://doi.org/10.5194/essd-16-4673-2024, 2024
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Nitrogen (N) and phosphorus (P) contamination of water bodies is a long-term issue due to the long history of N and P inputs to the environment and their persistence. Here, we introduce a long-term and high-resolution dataset of N and P inputs from wastewater (point sources) for Germany, combining data from different sources and conceptual understanding. We also account for uncertainties in modelling choices, thus facilitating robust long-term and large-scale water quality studies.
Jan Magnusson, Yves Bühler, Louis Quéno, Bertrand Cluzet, Giulia Mazzotti, Clare Webster, Rebecca Mott, and Tobias Jonas
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-374, https://doi.org/10.5194/essd-2024-374, 2024
Preprint under review for ESSD
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In this study, we present a dataset for the Dischma catchment in eastern Switzerland, which represents a typical high-alpine watershed in the European Alps. Accurate monitoring and reliable forecasting of snow and water resources in such basins are crucial for a wide range of applications. Our dataset is valuable for improving physics-based snow, land-surface, and hydrological models, with potential applications in similar high-alpine catchments.
Rohit Mukherjee, Frederick Policelli, Ruixue Wang, Elise Arellano-Thompson, Beth Tellman, Prashanti Sharma, Zhijie Zhang, and Jonathan Giezendanner
Earth Syst. Sci. Data, 16, 4311–4323, https://doi.org/10.5194/essd-16-4311-2024, https://doi.org/10.5194/essd-16-4311-2024, 2024
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Global water resource monitoring is crucial due to climate change and population growth. This study presents a hand-labeled dataset of 100 PlanetScope images for surface water detection, spanning diverse biomes. We use this dataset to evaluate two state-of-the-art mapping methods. Results highlight performance variations across biomes, emphasizing the need for diverse, independent validation datasets to enhance the accuracy and reliability of satellite-based surface water monitoring techniques.
Nikunj K. Mangukiya, Kanneganti Bhargav Kumar, Pankaj Dey, Shailza Sharma, Vijaykumar Bejagam, Pradeep P. Mujumdar, and Ashutosh Sharma
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-379, https://doi.org/10.5194/essd-2024-379, 2024
Revised manuscript accepted for ESSD
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We introduce CAMELS-INDIA (Catchment Attributes and MEteorology for Large-sample Studies – India), which provides daily hydrometeorological time series and static catchment attributes representing location, topography, climate, hydrological signatures, land-use, land cover, soil, geology, and anthropogenic influences for 472 catchments in peninsular India, to foster large-sample hydrological studies in India and promote the inclusion of Indian catchments in global hydrological research.
Lei Huang, Yong Luo, Jing M. Chen, Qiuhong Tang, Tammo Steenhuis, Wei Cheng, and Wen Shi
Earth Syst. Sci. Data, 16, 3993–4019, https://doi.org/10.5194/essd-16-3993-2024, https://doi.org/10.5194/essd-16-3993-2024, 2024
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Timely global terrestrial evapotranspiration (ET) data are crucial for water resource management and drought forecasting. This study introduces the VISEA algorithm, which integrates satellite data and shortwave radiation to provide daily 0.05° gridded near-real-time ET estimates. By employing a vegetation index–temperature method, this algorithm can estimate ET without requiring additional data. Evaluation results demonstrate VISEA's comparable accuracy with accelerated data availability.
Sibylle Kathrin Hassler, Rafael Bohn Reckziegel, Ben du Toit, Svenja Hoffmeister, Florian Kestel, Anton Kunneke, Rebekka Maier, and Jonathan Paul Sheppard
Earth Syst. Sci. Data, 16, 3935–3948, https://doi.org/10.5194/essd-16-3935-2024, https://doi.org/10.5194/essd-16-3935-2024, 2024
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Agroforestry systems (AFSs) combine trees and crops within the same land unit, providing a sustainable land use option which protects natural resources and biodiversity. Introducing trees into agricultural systems can positively affect water resources, soil characteristics, biomass and microclimate. We studied an AFS in South Africa in a multidisciplinary approach to assess the different influences and present the resulting dataset consisting of water, soil, tree and meteorological variables.
Kaihao Zheng, Peirong Lin, and Ziyun Yin
Earth Syst. Sci. Data, 16, 3873–3891, https://doi.org/10.5194/essd-16-3873-2024, https://doi.org/10.5194/essd-16-3873-2024, 2024
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We develop a globally applicable thresholding scheme for DEM-based floodplain delineation to improve the representation of spatial heterogeneity. It involves a stepwise approach to estimate the basin-level floodplain hydraulic geometry parameters that best respect the scaling law while approximating the global hydrodynamic flood maps. A ~90 m resolution global floodplain map, the Spatial Heterogeneity Improved Floodplain by Terrain analysis (SHIFT), is delineated with demonstrated superiority.
Yuzhong Yang, Qingbai Wu, Xiaoyan Guo, Lu Zhou, Helin Yao, Dandan Zhang, Zhongqiong Zhang, Ji Chen, and Guojun Liu
Earth Syst. Sci. Data, 16, 3755–3770, https://doi.org/10.5194/essd-16-3755-2024, https://doi.org/10.5194/essd-16-3755-2024, 2024
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We present the temporal data of stable isotopes in different waterbodies in the Beiluhe Basin in the hinterland of the Qinghai–Tibet Plateau (QTP) produced between 2017 and 2022. In this article, the first detailed stable isotope data of 359 ground ice samples are presented. This first data set provides a new basis for understanding the hydrological effects of permafrost degradation on the QTP.
Bennet Juhls, Anne Morgenstern, Jens Hölemann, Antje Eulenburg, Birgit Heim, Frederieke Miesner, Hendrik Grotheer, Gesine Mollenhauer, Hanno Meyer, Ephraim Erkens, Felica Yara Gehde, Sofia Antonova, Sergey Chalov, Maria Tereshina, Oxana Erina, Evgeniya Fingert, Ekaterina Abramova, Tina Sanders, Liudmila Lebedeva, Nikolai Torgovkin, Georgii Maksimov, Vasily Povazhnyi, Rafael Gonçalves-Araujo, Urban Wünsch, Antonina Chetverova, Sophie Opfergelt, and Pier Paul Overduin
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-290, https://doi.org/10.5194/essd-2024-290, 2024
Revised manuscript accepted for ESSD
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The Siberian Arctic is warming fast: permafrost is thawing, river chemistry is changing, and coastal ecosystems are affected. We want to understand changes to the Lena River, a major Arctic river flowing to the Arctic Ocean, by collecting 4.5 years of detailed water data, including temperature and carbon and nutrient contents. This dataset records current conditions and helps us to detect future changes. Explore it at https://doi.org/10.1594/PANGAEA.913197 and https://lena-monitoring.awi.de/.
Hordur Bragi Helgason and Bart Nijssen
Earth Syst. Sci. Data, 16, 2741–2771, https://doi.org/10.5194/essd-16-2741-2024, https://doi.org/10.5194/essd-16-2741-2024, 2024
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LamaH-Ice is a large-sample hydrology (LSH) dataset for Iceland. The dataset includes daily and hourly hydro-meteorological time series, including observed streamflow and basin characteristics, for 107 basins. LamaH-Ice offers most variables that are included in existing LSH datasets and additional information relevant to cold-region hydrology such as annual time series of glacier extent and mass balance. A large majority of the basins in LamaH-Ice are unaffected by human activities.
Chengcheng Hou, Yan Li, Shan Sang, Xu Zhao, Yanxu Liu, Yinglu Liu, and Fang Zhao
Earth Syst. Sci. Data, 16, 2449–2464, https://doi.org/10.5194/essd-16-2449-2024, https://doi.org/10.5194/essd-16-2449-2024, 2024
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To fill the gap in the gridded industrial water withdrawal (IWW) data in China, we developed the China Industrial Water Withdrawal (CIWW) dataset, which provides monthly IWWs from 1965 to 2020 at a spatial resolution of 0.1°/0.25° and auxiliary data including subsectoral IWW and industrial output value in 2008. This dataset can help understand the human water use dynamics and support studies in hydrology, geography, sustainability sciences, and water resource management and allocation in China.
Pierre-Antoine Versini, Leydy Alejandra Castellanos-Diaz, David Ramier, and Ioulia Tchiguirinskaia
Earth Syst. Sci. Data, 16, 2351–2366, https://doi.org/10.5194/essd-16-2351-2024, https://doi.org/10.5194/essd-16-2351-2024, 2024
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Nature-based solutions (NBSs), such as green roofs, have appeared as relevant solutions to mitigate urban heat islands. The evapotranspiration (ET) process allows NBSs to cool the air. To improve our knowledge about ET assessment, this paper presents some experimental measurement campaigns carried out during three consecutive summers. Data are available for three different (large, small, and point-based) spatial scales.
Ralph Bathelemy, Pierre Brigode, Vazken Andréassian, Charles Perrin, Vincent Moron, Cédric Gaucherel, Emmanuel Tric, and Dominique Boisson
Earth Syst. Sci. Data, 16, 2073–2098, https://doi.org/10.5194/essd-16-2073-2024, https://doi.org/10.5194/essd-16-2073-2024, 2024
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The aim of this work is to provide the first hydroclimatic database for Haiti, a Caribbean country particularly vulnerable to meteorological and hydrological hazards. The resulting database, named Simbi, provides hydroclimatic time series for around 150 stations and 24 catchment areas.
Changming Li, Ziwei Liu, Wencong Yang, Zhuoyi Tu, Juntai Han, Sien Li, and Hanbo Yang
Earth Syst. Sci. Data, 16, 1811–1846, https://doi.org/10.5194/essd-16-1811-2024, https://doi.org/10.5194/essd-16-1811-2024, 2024
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Using a collocation-based approach, we developed a reliable global land evapotranspiration product (CAMELE) by merging multi-source datasets. The CAMELE product outperformed individual input datasets and showed satisfactory performance compared to reference data. It also demonstrated superiority for different plant functional types. Our study provides a promising solution for data fusion. The CAMELE dataset allows for detailed research and a better understanding of land–atmosphere interactions.
Yuhan Guo, Hongxing Zheng, Yuting Yang, Yanfang Sang, and Congcong Wen
Earth Syst. Sci. Data, 16, 1651–1665, https://doi.org/10.5194/essd-16-1651-2024, https://doi.org/10.5194/essd-16-1651-2024, 2024
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We have provided an inaugural version of the hydrogeomorphic dataset for catchments over the Tibetan Plateau. We first provide the width-function-based instantaneous unit hydrograph (WFIUH) for each HydroBASINS catchment, which can be used to investigate the spatial heterogeneity of hydrological behavior across the Tibetan Plateau. It is expected to facilitate hydrological modeling across the Tibetan Plateau.
Ziyun Yin, Peirong Lin, Ryan Riggs, George H. Allen, Xiangyong Lei, Ziyan Zheng, and Siyu Cai
Earth Syst. Sci. Data, 16, 1559–1587, https://doi.org/10.5194/essd-16-1559-2024, https://doi.org/10.5194/essd-16-1559-2024, 2024
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Large-sample hydrology (LSH) datasets have been the backbone of hydrological model parameter estimation and data-driven machine learning models for hydrological processes. This study complements existing LSH studies by creating a dataset with improved sample coverage, uncertainty estimates, and dynamic descriptions of human activities, which are all crucial to hydrological understanding and modeling.
Pierluigi Claps, Giulia Evangelista, Daniele Ganora, Paola Mazzoglio, and Irene Monforte
Earth Syst. Sci. Data, 16, 1503–1522, https://doi.org/10.5194/essd-16-1503-2024, https://doi.org/10.5194/essd-16-1503-2024, 2024
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FOCA (Italian FlOod and Catchment Atlas) is the first systematic collection of data on Italian river catchments. It comprises geomorphological, soil, land cover, NDVI, climatological and extreme rainfall catchment attributes. FOCA also contains 631 peak and daily discharge time series covering the 1911–2016 period. Using this first nationwide data collection, a wide range of applications, in particular flood studies, can be undertaken within the Italian territory.
Wei Jing Ang, Edward Park, Yadu Pokhrel, Dung Duc Tran, and Ho Huu Loc
Earth Syst. Sci. Data, 16, 1209–1228, https://doi.org/10.5194/essd-16-1209-2024, https://doi.org/10.5194/essd-16-1209-2024, 2024
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Dams have burgeoned in the Mekong, but information on dams is scattered and inconsistent. Up-to-date evaluation of dams is unavailable, and basin-wide hydropower potential has yet to be systematically assessed. We present a comprehensive database of 1055 dams, a spatiotemporal analysis of the dams, and a total hydropower potential of 1 334 683 MW. Considering projected dam development and hydropower potential, the vulnerability and the need for better dam management may be highest in Laos.
Chuanqi He, Ci-Jian Yang, Jens M. Turowski, Richard F. Ott, Jean Braun, Hui Tang, Shadi Ghantous, Xiaoping Yuan, and Gaia Stucky de Quay
Earth Syst. Sci. Data, 16, 1151–1166, https://doi.org/10.5194/essd-16-1151-2024, https://doi.org/10.5194/essd-16-1151-2024, 2024
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The shape of drainage basins and rivers holds significant implications for landscape evolution processes and dynamics. We used a global 90 m resolution topography to obtain ~0.7 million drainage basins with sizes over 50 km2. Our dataset contains the spatial distribution of drainage systems and their morphological parameters, supporting fields such as geomorphology, climatology, biology, ecology, hydrology, and natural hazards.
Jingyu Lin, Peng Wang, Jinzhu Wang, Youping Zhou, Xudong Zhou, Pan Yang, Hao Zhang, Yanpeng Cai, and Zhifeng Yang
Earth Syst. Sci. Data, 16, 1137–1149, https://doi.org/10.5194/essd-16-1137-2024, https://doi.org/10.5194/essd-16-1137-2024, 2024
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Our paper provides a repository comprising over 330 000 observations encompassing daily, weekly, and monthly records of surface water quality spanning the period 1980–2022. It included 18 distinct indicators, meticulously gathered at 2384 monitoring sites, ranging from inland locations to coastal and oceanic areas. This dataset will be very useful for researchers and decision-makers in the fields of hydrology, ecological studies, climate change, policy development, and oceanography.
Aloïs Tilloy, Dominik Paprotny, Stefania Grimaldi, Goncalo Gomes, Alessandra Bianchi, Stefan Lange, Hylke Beck, and Luc Feyen
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-41, https://doi.org/10.5194/essd-2024-41, 2024
Revised manuscript accepted for ESSD
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This article presents a reanalysis of Europe's rivers streamflow for the period 1950–2020, using a state-of-the-art hydrological simulation framework. The dataset, called HERA (Hydrological European ReAnalysis), uses detailed information about the landscape, climate, and human activities to estimate river flow. HERA can be a valuable tool for studying hydrological dynamics, including the impacts of climate change and human activities on European water resources, flood and drought risks.
Daniel Kovacek and Steven Weijs
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-508, https://doi.org/10.5194/essd-2023-508, 2024
Revised manuscript accepted for ESSD
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We made a dataset for British Columbia describing the terrain, soil, land cover, and climate of over 1 million watersheds. The attributes are often used in hydrology because they are related to the water cycle. The data is meant to be used for water resources problems that can benefit from lots of basins and their attributes. The data and instructions needed to build the dataset from scratch are freely available. The permanent home for the data is https://doi.org/10.5683/SP3/JNKZVT.
Ana M. Ricardo, Rui M. L. Ferreira, Alberto Rodrigues da Silva, Jacinto Estima, Jorge Marques, Ivo Gamito, and Alexandre Serra
Earth Syst. Sci. Data, 16, 375–385, https://doi.org/10.5194/essd-16-375-2024, https://doi.org/10.5194/essd-16-375-2024, 2024
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Floods are among the most common natural disasters responsible for severe damages and human losses. Agueda.2016Flood, a synthesis of locally sensed data and numerically produced data, allows complete characterization of the flood event that occurred in February 2016 in the Portuguese Águeda River. The dataset was managed through the RiverCure Portal, a collaborative web platform connected to a validated shallow-water model.
Jiawei Hou, Albert I. J. M. Van Dijk, Luigi J. Renzullo, and Pablo R. Larraondo
Earth Syst. Sci. Data, 16, 201–218, https://doi.org/10.5194/essd-16-201-2024, https://doi.org/10.5194/essd-16-201-2024, 2024
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The GloLakes dataset provides historical and near-real-time time series of relative (i.e. storage change) and absolute (i.e. total stored volume) storage for more than 27 000 lakes worldwide using multiple sources of satellite data, including laser and radar altimetry and optical remote sensing. These data can help us understand the influence of climate variability and anthropogenic activities on water availability and system ecology over the last 4 decades.
Menaka Revel, Xudong Zhou, Prakat Modi, Jean-François Cretaux, Stephane Calmant, and Dai Yamazaki
Earth Syst. Sci. Data, 16, 75–88, https://doi.org/10.5194/essd-16-75-2024, https://doi.org/10.5194/essd-16-75-2024, 2024
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As satellite technology advances, there is an incredible amount of remotely sensed data for observing terrestrial water. Satellite altimetry observations of water heights can be utilized to calibrate and validate large-scale hydrodynamic models. However, because large-scale models are discontinuous, comparing satellite altimetry to predicted water surface elevation is difficult. We developed a satellite altimetry mapping procedure for high-resolution river network data.
Marvin Höge, Martina Kauzlaric, Rosi Siber, Ursula Schönenberger, Pascal Horton, Jan Schwanbeck, Marius Günter Floriancic, Daniel Viviroli, Sibylle Wilhelm, Anna E. Sikorska-Senoner, Nans Addor, Manuela Brunner, Sandra Pool, Massimiliano Zappa, and Fabrizio Fenicia
Earth Syst. Sci. Data, 15, 5755–5784, https://doi.org/10.5194/essd-15-5755-2023, https://doi.org/10.5194/essd-15-5755-2023, 2023
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CAMELS-CH is an open large-sample hydro-meteorological data set that covers 331 catchments in hydrologic Switzerland from 1 January 1981 to 31 December 2020. It comprises (a) daily data of river discharge and water level as well as meteorologic variables like precipitation and temperature; (b) yearly glacier and land cover data; (c) static attributes of, e.g, topography or human impact; and (d) catchment delineations. CAMELS-CH enables water and climate research and modeling at catchment level.
Peter Burek and Mikhail Smilovic
Earth Syst. Sci. Data, 15, 5617–5629, https://doi.org/10.5194/essd-15-5617-2023, https://doi.org/10.5194/essd-15-5617-2023, 2023
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We address an annoying problem every grid-based hydrological model must solve to compare simulated and observed river discharge. First, station locations do not fit the high-resolution river network. We update the database with stations based on a new high-resolution network. Second, station locations do not work with a coarser grid-based network. We use a new basin shape similarity concept for station locations on a coarser grid, reducing the error of assigning stations to the wrong basin.
Najwa Sharaf, Jordi Prats, Nathalie Reynaud, Thierry Tormos, Rosalie Bruel, Tiphaine Peroux, and Pierre-Alain Danis
Earth Syst. Sci. Data, 15, 5631–5650, https://doi.org/10.5194/essd-15-5631-2023, https://doi.org/10.5194/essd-15-5631-2023, 2023
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We present a regional long-term (1959–2020) dataset (LakeTSim) of daily epilimnion and hypolimnion water temperature simulations in 401 French lakes. Overall, less uncertainty is associated with the epilimnion compared to the hypolimnion. LakeTSim is valuable for providing new insights into lake water temperature for assessing the impact of climate change, which is often hindered by the lack of observations, and for decision-making by stakeholders.
Jiabo Yin, Louise J. Slater, Abdou Khouakhi, Le Yu, Pan Liu, Fupeng Li, Yadu Pokhrel, and Pierre Gentine
Earth Syst. Sci. Data, 15, 5597–5615, https://doi.org/10.5194/essd-15-5597-2023, https://doi.org/10.5194/essd-15-5597-2023, 2023
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This study presents long-term (i.e., 1940–2022) and high-resolution (i.e., 0.25°) monthly time series of TWS anomalies over the global land surface. The reconstruction is achieved by using a set of machine learning models with a large number of predictors, including climatic and hydrological variables, land use/land cover data, and vegetation indicators (e.g., leaf area index). Our proposed GTWS-MLrec performs overall as well as, or is more reliable than, previous TWS datasets.
Shanlei Sun, Zaoying Bi, Jingfeng Xiao, Yi Liu, Ge Sun, Weimin Ju, Chunwei Liu, Mengyuan Mu, Jinjian Li, Yang Zhou, Xiaoyuan Li, Yibo Liu, and Haishan Chen
Earth Syst. Sci. Data, 15, 4849–4876, https://doi.org/10.5194/essd-15-4849-2023, https://doi.org/10.5194/essd-15-4849-2023, 2023
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Based on various existing datasets, we comprehensively considered spatiotemporal differences in land surfaces and CO2 effects on plant stomatal resistance to parameterize the Shuttleworth–Wallace model, and we generated a global 5 km ensemble mean monthly potential evapotranspiration (PET) dataset (including potential transpiration PT and soil evaporation PE) during 1982–2015. The new dataset may be used by academic communities and various agencies to conduct various studies.
Wei Wang, La Zhuo, Xiangxiang Ji, Zhiwei Yue, Zhibin Li, Meng Li, Huimin Zhang, Rong Gao, Chenjian Yan, Ping Zhang, and Pute Wu
Earth Syst. Sci. Data, 15, 4803–4827, https://doi.org/10.5194/essd-15-4803-2023, https://doi.org/10.5194/essd-15-4803-2023, 2023
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The consumptive water footprint of crop production (WFCP) measures blue and green evapotranspiration of either irrigated or rainfed crops in time and space. A gridded monthly WFCP dataset for China is established. There are four improvements from existing datasets: (i) distinguishing water supply modes and irrigation techniques, (ii) distinguishing evaporation and transpiration, (iii) consisting of both total and unit WFCP, and (iv) providing benchmarks for unit WFCP by climatic zones.
Emma L. Robinson, Matthew J. Brown, Alison L. Kay, Rosanna A. Lane, Rhian Chapman, Victoria A. Bell, and Eleanor M. Blyth
Earth Syst. Sci. Data, 15, 4433–4461, https://doi.org/10.5194/essd-15-4433-2023, https://doi.org/10.5194/essd-15-4433-2023, 2023
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This work presents two new Penman–Monteith potential evaporation datasets for the UK, calculated with the same methodology applied to historical climate data (Hydro-PE HadUK-Grid) and an ensemble of future climate projections (Hydro-PE UKCP18 RCM). Both include an optional correction for evaporation of rain that lands on the surface of vegetation. The historical data are consistent with existing PE datasets, and the future projections include effects of rising atmospheric CO2 on vegetation.
Xinyu Chen, Liguang Jiang, Yuning Luo, and Junguo Liu
Earth Syst. Sci. Data, 15, 4463–4479, https://doi.org/10.5194/essd-15-4463-2023, https://doi.org/10.5194/essd-15-4463-2023, 2023
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River flow is experiencing changes under the impacts of climate change and human activities. For example, flood events are occurring more often and are more destructive in many places worldwide. To deal with such issues, hydrologists endeavor to understand the features of extreme events as well as other hydrological changes. One key approach is analyzing flow characteristics, represented by hydrological indices. Building such a comprehensive global large-sample dataset is essential.
Tobias L. Hohenbrink, Conrad Jackisch, Wolfgang Durner, Kai Germer, Sascha C. Iden, Janis Kreiselmeier, Frederic Leuther, Johanna C. Metzger, Mahyar Naseri, and Andre Peters
Earth Syst. Sci. Data, 15, 4417–4432, https://doi.org/10.5194/essd-15-4417-2023, https://doi.org/10.5194/essd-15-4417-2023, 2023
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The article describes a collection of 572 data sets of soil water retention and unsaturated hydraulic conductivity data measured with state-of-the-art laboratory methods. Furthermore, the data collection contains basic soil properties such as soil texture and organic carbon content. We expect that the data will be useful for various important purposes, for example, the development of soil hydraulic property models and related pedotransfer functions.
Sebastien Klotz, Caroline Le Bouteiller, Nicolle Mathys, Firmin Fontaine, Xavier Ravanat, Jean-Emmanuel Olivier, Frédéric Liébault, Hugo Jantzi, Patrick Coulmeau, Didier Richard, Jean-Pierre Cambon, and Maurice Meunier
Earth Syst. Sci. Data, 15, 4371–4388, https://doi.org/10.5194/essd-15-4371-2023, https://doi.org/10.5194/essd-15-4371-2023, 2023
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Mountain badlands are places of intense erosion. They deliver large amounts of sediment to river systems, with consequences for hydropower sustainability, habitat quality and biodiversity, and flood hazard and river management. Draix-Bleone Observatory was created in 1983 to understand and quantify sediment delivery from such badland areas. Our paper describes how water and sediment fluxes have been monitored for almost 40 years in the small mountain catchments of this observatory.
Gopi Goteti
Earth Syst. Sci. Data, 15, 4389–4415, https://doi.org/10.5194/essd-15-4389-2023, https://doi.org/10.5194/essd-15-4389-2023, 2023
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Data on river gauging stations, river basin boundaries and river flow paths are critical for hydrological analyses, but existing data for India's river basins have limited availability and reliability. This work fills the gap by building a new dataset. Data for 645 stations in 15 basins of India were compiled and checked against global data sources; data were supplemented with additional information where needed. This dataset will serve as a reliable building block in hydrological analyses.
Md Safat Sikder, Jida Wang, George H. Allen, Yongwei Sheng, Dai Yamazaki, Chunqiao Song, Meng Ding, Jean-François Crétaux, and Tamlin M. Pavelsky
Earth Syst. Sci. Data, 15, 3483–3511, https://doi.org/10.5194/essd-15-3483-2023, https://doi.org/10.5194/essd-15-3483-2023, 2023
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We introduce Lake-TopoCat to reveal detailed lake hydrography information. It contains the location of lake outlets, the boundary of lake catchments, and a wide suite of attributes that depict detailed lake drainage relationships. It was constructed using lake boundaries from a global lake dataset, with the help of high-resolution hydrography data. This database may facilitate a variety of applications including water quality, agriculture and fisheries, and integrated lake–river modeling.
Maik Heistermann, Till Francke, Lena Scheiffele, Katya Dimitrova Petrova, Christian Budach, Martin Schrön, Benjamin Trost, Daniel Rasche, Andreas Güntner, Veronika Döpper, Michael Förster, Markus Köhli, Lisa Angermann, Nikolaos Antonoglou, Manuela Zude-Sasse, and Sascha E. Oswald
Earth Syst. Sci. Data, 15, 3243–3262, https://doi.org/10.5194/essd-15-3243-2023, https://doi.org/10.5194/essd-15-3243-2023, 2023
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Cosmic-ray neutron sensing (CRNS) allows for the non-invasive estimation of root-zone soil water content (SWC). The signal observed by a single CRNS sensor is influenced by the SWC in a radius of around 150 m (the footprint). Here, we have put together a cluster of eight CRNS sensors with overlapping footprints at an agricultural research site in north-east Germany. That way, we hope to represent spatial SWC heterogeneity instead of retrieving just one average SWC estimate from a single sensor.
Benjamin M. Kitambo, Fabrice Papa, Adrien Paris, Raphael M. Tshimanga, Frederic Frappart, Stephane Calmant, Omid Elmi, Ayan Santos Fleischmann, Melanie Becker, Mohammad J. Tourian, Rômulo A. Jucá Oliveira, and Sly Wongchuig
Earth Syst. Sci. Data, 15, 2957–2982, https://doi.org/10.5194/essd-15-2957-2023, https://doi.org/10.5194/essd-15-2957-2023, 2023
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The surface water storage (SWS) in the Congo River basin (CB) remains unknown. In this study, the multi-satellite and hypsometric curve approaches are used to estimate SWS in the CB over 1992–2015. The results provide monthly SWS characterized by strong variability with an annual mean amplitude of ~101 ± 23 km3. The evaluation of SWS against independent datasets performed well. This SWS dataset contributes to the better understanding of the Congo basin’s surface hydrology using remote sensing.
Natalie Lützow, Georg Veh, and Oliver Korup
Earth Syst. Sci. Data, 15, 2983–3000, https://doi.org/10.5194/essd-15-2983-2023, https://doi.org/10.5194/essd-15-2983-2023, 2023
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Glacier lake outburst floods (GLOFs) are a prominent natural hazard, and climate change may change their magnitude, frequency, and impacts. A global, literature-based GLOF inventory is introduced, entailing 3151 reported GLOFs. The reporting density varies temporally and regionally, with most cases occurring in NW North America. Since 1900, the number of yearly documented GLOFs has increased 6-fold. However, many GLOFs have incomplete records, and we call for a systematic reporting protocol.
Hanieh Seyedhashemi, Florentina Moatar, Jean-Philippe Vidal, and Dominique Thiéry
Earth Syst. Sci. Data, 15, 2827–2839, https://doi.org/10.5194/essd-15-2827-2023, https://doi.org/10.5194/essd-15-2827-2023, 2023
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This paper presents a past and future dataset of daily time series of discharge and stream temperature for 52 278 reaches over the Loire River basin (100 000 km2) in France, using thermal and hydrological models. Past data are provided over 1963–2019. Future data are available over the 1976–2100 period under different future climate change models (warm and wet, intermediate, and hot and dry) and scenarios (optimistic, intermediate, and pessimistic).
Youjiang Shen, Karina Nielsen, Menaka Revel, Dedi Liu, and Dai Yamazaki
Earth Syst. Sci. Data, 15, 2781–2808, https://doi.org/10.5194/essd-15-2781-2023, https://doi.org/10.5194/essd-15-2781-2023, 2023
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Res-CN fills a gap in a comprehensive and extensive dataset of reservoir-catchment characteristics for 3254 Chinese reservoirs with 512 catchment-level attributes and significantly enhanced spatial and temporal coverage (e.g., 67 % increase in water level and 225 % in storage anomaly) of time series of reservoir water level (data available for 20 % of 3254 reservoirs), water area (99 %), storage anomaly (92 %), and evaporation (98 %), supporting a wide range of applications and disciplines.
Hui Zheng, Wenli Fei, Zong-Liang Yang, Jiangfeng Wei, Long Zhao, Lingcheng Li, and Shu Wang
Earth Syst. Sci. Data, 15, 2755–2780, https://doi.org/10.5194/essd-15-2755-2023, https://doi.org/10.5194/essd-15-2755-2023, 2023
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An ensemble of evapotranspiration, runoff, and water storage is estimated here using the Noah-MP land surface model by perturbing model parameterization schemes. The data could be beneficial for monitoring and understanding the variability of water resources. Model developers could also gain insights by intercomparing the ensemble members.
Alison L. Kay, Victoria A. Bell, Helen N. Davies, Rosanna A. Lane, and Alison C. Rudd
Earth Syst. Sci. Data, 15, 2533–2546, https://doi.org/10.5194/essd-15-2533-2023, https://doi.org/10.5194/essd-15-2533-2023, 2023
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Climate change will affect the water cycle, including river flows and soil moisture. We have used both observational data (1980–2011) and the latest UK climate projections (1980–2080) to drive a national-scale grid-based hydrological model. The data, covering Great Britain and Northern Ireland, suggest potential future decreases in summer flows, low flows, and summer/autumn soil moisture, and possible future increases in winter and high flows. Society must plan how to adapt to such impacts.
Jamie Hannaford, Jonathan D. Mackay, Matthew Ascott, Victoria A. Bell, Thomas Chitson, Steven Cole, Christian Counsell, Mason Durant, Christopher R. Jackson, Alison L. Kay, Rosanna A. Lane, Majdi Mansour, Robert Moore, Simon Parry, Alison C. Rudd, Michael Simpson, Katie Facer-Childs, Stephen Turner, John R. Wallbank, Steven Wells, and Amy Wilcox
Earth Syst. Sci. Data, 15, 2391–2415, https://doi.org/10.5194/essd-15-2391-2023, https://doi.org/10.5194/essd-15-2391-2023, 2023
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The eFLaG dataset is a nationally consistent set of projections of future climate change impacts on hydrology. eFLaG uses the latest available UK climate projections (UKCP18) run through a series of computer simulation models which enable us to produce future projections of river flows, groundwater levels and groundwater recharge. These simulations are designed for use by water resource planners and managers but could also be used for a wide range of other purposes.
Cited articles
Arsenault, K. R., Houser, P. R., and De Lannoy, G. J. M.: Evaluation of the MODIS snow cover fraction product, Hydrol. Process., 28, 980–998, https://doi.org/10.1002/hyp.9636, 2012.
Ault, T. W., Czajkowski, K. P., Benko, T., Coss, J., Struble, J., Spongberg, A., Templin, M., and Gross, C.: Validation of the MODIS Snow Product and Cloud Mask using student and NWS Cooperative Station Observations in the Lower Great Lakes Region, Remote Sens. Environ., 105, 341–353, https://doi.org/10.1016/j.rse.2006.07.004, 2006.
Bojinski, S., Verstraete, M., Peterson, T. C., Richter, C., Simmons, A., and Zemp, M.: The concept of essential climate variables in support of climate research, applications, and policy, BAMS, 95, 1431–1443, https://doi.org/10.1175/BAMS-D-13-00047.1, 2014.
Bowker, D. E., Davis, R. E., Myrick, D. L., Stacy, K., and Jones, W. T.: Spectral Reflectances of Natural Targets for Use in Remote Sensing Studies, NASA Reference Publication 1139, N85-30450, 1985.
Bunting, J. T. and d'Entremont, R. P.: Improved cloud detection utilizing Defense Meteorological Satellite Program near infrared measurements, Air Force Geophysics Laboratory, Environmental Research Papers, No. 765, AFGL-TR-82-0027, 91 pp., 1982.
Crane, R. G. and Anderson, M. R.: Satellite discrimination of snow/cloud surfaces, Int. J. Remote Sens., 5, 213–223, 1984.
Crawford, C. J.: MODIS Terra Collection 6 fractional snow cover validation in mountainous terrain during spring snowmelt using Landsat TM and ETM+, Hydrol. Process., 29, 128–138, https://doi.org/10.1002/hyp.10134, 2015.
Déry, S., Salomonson, V. V., Stieglitz, M., Hall, D. K., and Appel, I.: An Approach to Using Snow Areal Depletion Curves Inferred from MODIS and its Application to Land Surface Modeling in Alaska, Hydrol. Process., 19, 2755–2774, 2005.
Dietz, A. J., Wohner, C., and Kuenzer, C.: European snow cover characteristics between 2000 and 2011 derived from improved MODIS daily snow cover products, Remote Sensing 4, 2432–2454, https://doi.org/10.3390/rs4082432, 2012.
Dietz, A. J., Kuenzer, C., and Conrad, C.: Snow-cover variability in central Asia between 2000 and 2011 derived from improved MODIS daily snow-cover products, Int. J. Remote Sens., 34, 3879–3902, https://doi.org/10.1080/01431161.2013.767480, 2013.
Dobreva, I. and Klein, A. G.: Fractional snow cover mapping through artificial neural network analysis of MODIS surface reflectance, Remote Sens. Environ., 115, 3355–3366, https://doi.org/10.1016/j.rse.2011.07.018, 2011.
Dozier, J.: Spectral signature of alpine snow cover from the Landsat Thematic Mapper, Remote Sens. Environ., 28, 9–22, 1989.
Dozier, J., and Marks, D.: Snow mapping and classification from Landsat Thematic Mapper data, Ann. Glaciol., 9, 1–7, 1987.
Frei, A. and Robinson, D. A.: Northern Hemisphere snow extent – Regional variability 1972–1994, Int. J. Climatol., 19, 1535–1560, 1999.
Gao, Y., Xie, H., Lu, N., Yao, T., and Liang, T.: Toward advanced daily cloud-free snow cover and snow water equivalent products from Terra-Aqua MODIS and Aqua AMSR-E measurements, J. Hydrol., 385, 23–35, https://doi.org/10.1016/j.jhydrol.2010.01.022, 2010a.
Gao, Y., Xie, H., Lu, N., Yao, T., and Xue, C.: Integrated assessment on multi-temporal and multi-sensor combinations for reducing cloud obscuration of MODIS snow cover products of the Pacific Northwest USA, Remote Sens. Environ., 114, 1662–1675, https://doi.org/10.1016/j.rse.2010.02.017, 2010b.
Gascoin, S., Hagolle, O., Huc, M., Jarlan, L., Dejoux, J.-F., Szczypta, C., Marti, R., and Sánchez, R.: A snow cover climatology for the Pyrenees from MODIS snow products, Hydrol. Earth Syst. Sci., 19, 2337–2351, https://doi.org/10.5194/hess-19-2337-2015, 2015
Gladkova, I., Grossberg, M., Bonev, G., Romanov, P., and Shahriar, F.: Increasing the accuracy of MODIS/Aqua snow product using quantitative image restoration technique, IEEE Geosci. Remote S., 9, 740–743, 2012.
Hall, D. K. and Riggs, G. A.: Accuracy assessment of the MODIS snow-cover products, Hydrol. Process., 21, 1534–1547, https://doi.org/10.1002/hyp.6715, 2007.
Hall, D. K. and Riggs, G. A.: Normalized-difference snow index (NDSI), in: Encyclopedia of Snow, Ice and Glaciers, edited by: Singh, V. P., Singh, P., and Haritashya, U. K., Springer Netherlands, 779–780, https://doi.org/10.1007/978-90-481-2642-2_376, 2011.
Hall, D. K., Riggs, G. A., and Salomonson, V. V.: Development of methods for mapping global snow cover using Moderate Resolution Imaging Spectroradiometer data, Remote Sens. Environ., 54, 127–140, 1995.
Hall, D. K., Riggs, G. A., Salomonson, V. V., DiGirolamo, N. E., and Bayr, K. J.: MODIS snow-cover products, Remote Sens. Environ., 83, 181–194, 2002.
Hall, D. K., Foster, J. L., DiGirolamo, N. E., and Riggs, G. A.: Snow cover, snowmelt timing and stream power in the Wind River Range, Wyoming, Geomorphology, 137, 87–93, https://doi.org/10.1016/j.geomorph.2010.11.011, 2012.
Hall, D. K., Crawford, C. J., DiGirolamo, N. E., Riggs, G. A., and Foster, J. L.: Detection of earlier snowmelt in the Wind River Range, Wyoming, using Landsat imagery, 1972–2013, Remote Sens. Environ., 162, 45–54, https://doi.org/10.1016/j.rse.2015.01.032, 2015.
Hassan, Q. K., Sekhon, N. S., Magai, R., and McEachern, P.: Reconstruction of Snow Water Equivalent and Snow Depth Using Remote Sensing Data, Journal of Environmental Informatics, 20, 67–74, https://doi.org/10.3808/jei.201200221, 2012.
Hawotte, F., Radoux, J., Chomé, G., and Defourny, P.: Assessment of automated snow cover detection at high solar zenith angles with PROBA-V, Remote Sensing, 8, 699, https://doi.org/10.3390/rs8090699, 2016.
Helfrich, S. R., McNamara, D., Ramsay, B. H., Baldwin, T., and Kasheta, T.: Enhancements to, and forthcoming developments in the Interactive Multisensor Snow and Ice Mapping System (IMS), Hydrol. Process., 21, 1576–1586, https://doi.org/10.1002/hyp.6720, 2007.
Huang, X., Liang, T., Zhang, X., and Guo, Z.: Validation of MODIS snow cover products using Landsat and ground measurements during the 2001–2005 snow seasons over northern Xinjiang, China, Int. J. Remote Sens., 32, 133–152, https://doi.org/10.1080/01431160903439924, 2011.
Jain, S. K., Goswami, A., and Saraf, A. K.: Accuracy assessment of MODIS, NOAA and IRS data in snow cover mapping under Himalayan conditions, Int. J. Remote Sens., 29, 5863–5878, https://doi.org/10.1080/01431160801908129, 2008.
JPSS: Joint Polar Satellite System (JPSS) Ground Project, Code 474, Joint Polar Satellite System (JPSS) Operational Algorithm Description (OAD) Document for VIIRS Cloud Mask (VCM) Intermediate Product (IP) Software, https://jointmission.gsfc.nasa.gov/sciencedocs/2015-08/474-00062_OAD-VIIRS-Cloud-Mask-IP_I.pdf, last access: 8 March 2015.
Justice, C. O., Román, M. O., Csiszar, I., Vermote, E. F., Wolfe, R. E., Hook, S. J., Friedl, M., Wang, Z., Schaff, C. B., Miura, T., Tschudi, M., Riggs, G., Hall, D. K., Lyapustin, A. I., Devadiga, S., Davidson, C., and Masuoka, E. J.: Land and cryosphere products from Sunomi NPP VIIRS: Overview and status, J. Geophys. Res.-Atmos., 118, 9753–9765, https://doi.org/10.1002/jgrd.50771, 2013.
Klein, A. G. and Barnett, A. C.: Validation of daily MODIS snow cover maps of the Upper Rio Grande River Basin for the 2000–2001 snow year, Remote Sens. Environ., 86, 162–176, https://doi.org/10.1016/S0034-4257(03)00097-X, 2003.
Klein, A. G., Hall, D. K., and Riggs, G. A.: Improving Snow-cover mapping in forests through the use of a canopy reflectance model, Hydrol. Process., 12, 1723–1744, 1998.
Kolberg, S. and Gottschalk, L.: Interannual stability of grid cell snow depletion curves as estimated from MODIS images, Water Resour. Res., 46, W11555, https://doi.org/10.1029/2008WR007617, 2010.
Kyle, H. L., Curran, R. J., Barnes, W. L., and Escoe, D.: A cloud physics Radiometer, in: Conference on Atmospheric Radiation, 3rd, Davis, CA, 28–30 June 1978, Preprints, (A79-21026 07-47) Boston, Mass., American Meteorological Society, 107–09, 1978.
Lin, J., Feng, X., Xiao, P., Li, H., Wang, J. and Li, Y.: Comparison of snow indexes in estimating snow cover fraction in a mountainous area in northwestern China, IEEE Geosci. Remote S., 9, 725–729, https://doi.org/10.1109/LGRS.2011.2179634, 2012.
Marchane, A., Jarlan, L., Hanich, L., Boudhar, A., Gascion, S., Taternier, A., Filali, N., LePage, M., Hagolle, O., and Berjamy, B.: Assessment of daily MODIS snow cover products to monitor snow cover dynamics over the Moroccan Atlas mountain range, Remote Sens. Environ., 160, 72–86, https://doi.org/10.1016/j.rse.2015.01.002, 2015.
Matson, M., Roeplewski, C. F., and Varnadore, M. S.: An atlas of satellite-derived Northern Hemisphere snow cover frequency, NOAA Atlas, U.S. Dept. of Commerce Washington, D.C., National Weather Service, 75 pp., March 1986.
MCST: MODIS Characterization Support Team, http://mcst.gsfc.nasa.gov, last access: 8 March 2017.
Mir, R. A., Jain, S. K., Saraf, A. K., and Goswami, A.: Accuracy assessment and trend analysis of MODIS derived data on snow-covered areas in the Sutley basin, Western Himalayas, Int. J. Remote Sens., 36, 3837–3858, https://doi.org/10.1080/01431161.2015.1070320, 2015.
Mishra, V. D., Neghi, H. S., Rawat, A. K., Chaturvedi, A., and Singh, R. P.: Retrieval of sub-pixel snow cover information in the Himalayan region using medium and coarse resolution remote sensing data, Int. J. Remote Sens., 30, 4707–4731, https://doi.org/10.1080/01431160802651959, 2009.
Parajka, J. and Blöschl, G.: Validation of MODIS snow cover images over Austria, Hydrol. Earth Syst. Sci., 10, 679–689, https://doi.org/10.5194/hess-10-679-2006, 2006.
Parajka, J. and Blöschl, G.: MODIS-based snow cover products, validation, and hydrologic applications, in: Multiscale Hydrologic Remote Sensing Perspectives and Applications, edited by: Chang, N. and Hong, Y., CRC Press, 2012.
Pu, Z., Zu, L., and Salomonson, V. V.: MODIS/Terra Observed Seasonal Variations of Snow Cover Over the Tibetan Plateau, Geophys. Res. Lett., 34, L06706, https://doi.org/10.1029/2007GL029262, 2007.
Punia, M. and Dhankar, V.: Mapping of snow spectral properties and regional climatic variability in Alaknanda Baisin, Uttarakhand, India, in: Proceedings 2014/ISPRSTCVIII Mid-Symposium, Hyderabad, India, No. 356/ISRS, 2014.
Ramsay, B. H.: The interactive multisensor snow and ice mapping system, Hydrol. Process., 12, 1537–1546, 1998.
Riggs, G. A. and Hall, D. K.: Tracking seasonal Appalachian snow cover with MODIS daily snow cover product, in: Proceedings of the 71st Annual Eastern Snow Conference, 3–5 June 2014, Boone, NC, USA, 121–129, 2014.
Riggs, G. A., Hall, D. K., Barker, J. L., and Salomonson, V. V.: The Developing Moderate Resolution Imaging Spectroradiometer (MODIS) Snow Cover Algorithm, in: Proceedings of the 50th Annual Eastern Snow Conference, 8–10 June 1993, Quebec, Quebec City, Canada, 51–58, 1993.
Riggs, G. A., Hall, D. K., and Salomonson, V. V.: MODIS snow products user guide to Collection 5, available at: http://modis-snow-ice.gsfc.nasa.gov/?c=userguides (last access: 8 March 2017), 2006.
Riggs, G. A., Hall, D. K., and Román, M. O.: MODIS Snow Products User Guide for Collection 6 (C6), available at: http://modis-snow-ice.gsfc.nasa.gov/?c=userguides (last access: 8 March 2017), 2016a.
Riggs, G. A., Hall, D. K., and Román, M. O.: VIIRS Snow Products User Guide for Collection 1 (C1), available at: http://modis-snow-ice.gsfc.nasa.gov/?c=userguides (last access: 8 March 2017), 2016b.
Riggs, G. A., Hall, D. K., and Román, M. O.: VIIRS Snow Cover Algorithm Theoretical Basis Document (ATBD), NASA VIIRS project document, available at: http://modis-snow-ice.gsfc.nasa.gov/?c=atbd&t=atbd (last access: 8 March 2017), 2016c.
Rittger, K., Painter, T. H., and Dozier J.: Assessment of methods for mapping snow cover from MODIS, Adv. Water Resour., 51, 367–380, https://doi.org/10.1016/j.advwatres.2012.03.002, 2013.
Robinson, D. A.: Climate Data Record Program (CDRP): Climate Algorithm Theoretical Basis Document (C-ATBD) Northern Hemisphere Snow Cover Extent, CDRP-ATBD-0156, Asheville, North Carolina, USA, 28 pp., 2013.
Rodell, M. and Houser, P. R.: Updating a Land Surface Model with MODIS Derived Snow Cover, J. Hydrometeorol., 5, 1064–1075, 2004.
Rosenthal, W. and Dozier, J.: Automated mapping of montane snow cover at subpixel resolution from the Landsat Thematic Mapper, Water Resour. Res., 32, 115–130, 1996.
Satterwhite, M. B., Mitchell, H., Hemmer, T., and Leckie, J. D.: Field spectral signatures of snow, ice and water, in: Proceedings of SPIE 5093, Algorithms and Technologies for Multispectral, Hyperspectral and Ultraspectral Imagery IX, edited by: Shen, S. S. and Lewis, P. E., https://doi.org/10.1117/12.488363, 2003.
Schaaf, C. B., Wang, Z. and Strahler, A. H.: Commentary on Wang and Zender – MODIS snow albedo bias at high solar zenith angles relative to theory and to in situ observations in Greenland, Remote Sens. Environ., 115, 1296–1300, 2011.
Singh, S. K., Kuldarni, A. V., and Chaudhary, B. S.: Hyperspectral analysis of snow reflectance to understand the effects of contamination and grain size, Ann. Glaciol., 51, 83–88, https://doi.org/10.3189/172756410791386535, 2010.
Tong, J., Déry, S. J., and Jackson, P. L.: Interrelationships between MODIS/Terra remotely sensed snow cover and the hydrometeorology of the Quesnel River Basin, British Columbia, Canada, Hydrol. Earth Syst. Sci., 13, 1439–1452, https://doi.org/10.5194/hess-13-1439-2009, 2009.
Valovcin, F. R.: Snow/cloud discrimination, Air Force Geophysics Lab., Hanscom AFB, MA, AFGL-TR-76-0174, ADA032385, 1976.
Valovcin, F. R.: Spectral radiance of snow and clouds in the near infrared spectral region, Air Force Geophysics Lab., Hanscom AFB, MA, Final Report, AFGL-TR-78-0289, ADA063761, 1978.
Wolfe, R. E., Lin, G., Nishihama, M., Tewari, K. P., Tilton, J. C., and Isaacman, A. R.: Suomi NPP VIIRS prelaunch and on orbit geometric calibration and characterization, J. Geophys. Res.-Atmos., 118, 11508–11521, https://doi.org/10.1002/jgrd.50873, 2013.
Zhang, J. and Zhou, Z: Spectra reflectance characteristics of different snow and snow-covered land surface objects and mixed spectrum fitting, in: Geoinformatics, 2011, 19th International Conference on Geoinformatics, Shanghai, China, 24–26 June 2011, IEEE, https://doi.org/10.1109/GeoInformatics.2011.5980696, 2011.
Short summary
The current collections of the NASA snow-cover data products generated from the MODIS and Visible Infrared Imaging Radiometer Suite (VIIRS) satellite instruments are described. Revisions in the MODIS snow cover algorithm increased accuracy, and the data content of products is increased from previous collection. The VIIRS algorithm and data product are very similar to those of MODIS. The objective of generating similar products is to enable the creation of a snow-cover extent climate-data record.
The current collections of the NASA snow-cover data products generated from the MODIS and...
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