Articles | Volume 15, issue 3
https://doi.org/10.5194/essd-15-1329-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-15-1329-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
23 Mar 2023
Data description paper |
| 23 Mar 2023
| 23 Mar 2023
Lake surface temperature retrieved from Landsat satellite series (1984 to 2021) for the North Slave Region
Remote Sensing of Environmental Change (ReSEC) Research group, Department of Geography and Environmental Studies, Wilfrid Laurier University, 75 University Avenue West, Waterloo N2L 3C5, Canada
Cold Regions Research Centre, Wilfrid Laurier University, Waterloo,
ON, Canada
Homa Kheyrollah Pour
Remote Sensing of Environmental Change (ReSEC) Research group, Department of Geography and Environmental Studies, Wilfrid Laurier University, 75 University Avenue West, Waterloo N2L 3C5, Canada
Cold Regions Research Centre, Wilfrid Laurier University, Waterloo,
ON, Canada
K. Andrea Scott
Department of Systems Design Engineering, University of Waterloo, 200 University Avenue, West, Waterloo N2L 3G1, Canada
Related authors
No articles found.
Mohammad Sina Jahangir, John Quilty, Chaopeng Shen, Andrea Scott, Scott Steinschneider, and Jan Adamowski
EGUsphere, https://doi.org/10.5194/egusphere-2025-846, https://doi.org/10.5194/egusphere-2025-846, 2025
Short summary
Short summary
This study presents a novel hybrid approach to streamflow prediction, significantly improving the efficiency and accuracy of fine-tuning deep learning models for hydrological prediction. Tested across numerous catchments in the U.S. and Europe, this method accelerates the fine-tuning process and improves prediction accuracy in locations beyond the training data. This innovative approach sets the stage for future hydrological models leveraging transfer learning.
Arash Rafat and Homa Kheyrollah Pour
EGUsphere, https://doi.org/10.5194/egusphere-2025-975, https://doi.org/10.5194/egusphere-2025-975, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
Climate change in Canada’s Northwest Territories (NWT) is making lake ice less predictable, thereby affecting ice road safety for northern communities. In this study, observations of significant changes in ice formation and growth between Oct.–Dec. 2021–2023 in a small NWT lake are related to changes in local snowfall and air temperatures. Collected data was used to develop simple models that can be applied for ice road planning, construction, and design under future and current climate change.
Andreas Stokholm, Jørgen Buus-Hinkler, Tore Wulf, Anton Korosov, Roberto Saldo, Leif Toudal Pedersen, David Arthurs, Ionut Dragan, Iacopo Modica, Juan Pedro, Annekatrien Debien, Xinwei Chen, Muhammed Patel, Fernando Jose Pena Cantu, Javier Noa Turnes, Jinman Park, Linlin Xu, Katharine Andrea Scott, David Anthony Clausi, Yuan Fang, Mingzhe Jiang, Saeid Taleghanidoozdoozan, Neil Curtis Brubacher, Armina Soleymani, Zacharie Gousseau, Michał Smaczny, Patryk Kowalski, Jacek Komorowski, David Rijlaarsdam, Jan Nicolaas van Rijn, Jens Jakobsen, Martin Samuel James Rogers, Nick Hughes, Tom Zagon, Rune Solberg, Nicolas Longépé, and Matilde Brandt Kreiner
The Cryosphere, 18, 3471–3494, https://doi.org/10.5194/tc-18-3471-2024, https://doi.org/10.5194/tc-18-3471-2024, 2024
Short summary
Short summary
The AutoICE challenge encouraged the development of deep learning models to map multiple aspects of sea ice – the amount of sea ice in an area and the age and ice floe size – using multiple sources of satellite and weather data across the Canadian and Greenlandic Arctic. Professionally drawn operational sea ice charts were used as a reference. A total of 179 students and sea ice and AI specialists participated and produced maps in broad agreement with the sea ice charts.
Xinwei Chen, Muhammed Patel, Fernando J. Pena Cantu, Jinman Park, Javier Noa Turnes, Linlin Xu, K. Andrea Scott, and David A. Clausi
The Cryosphere, 18, 1621–1632, https://doi.org/10.5194/tc-18-1621-2024, https://doi.org/10.5194/tc-18-1621-2024, 2024
Short summary
Short summary
This paper introduces an automated sea ice mapping pipeline utilizing a multi-task U-Net architecture. It attained the top score of 86.3 % in the AutoICE challenge. Ablation studies revealed that incorporating brightness temperature data and spatial–temporal information significantly enhanced model accuracy. Accurate sea ice mapping is vital for comprehending the Arctic environment and its global climate effects, underscoring the potential of deep learning.
Alicia F. Pouw, Homa Kheyrollah Pour, and Alex MacLean
The Cryosphere, 17, 2367–2385, https://doi.org/10.5194/tc-17-2367-2023, https://doi.org/10.5194/tc-17-2367-2023, 2023
Short summary
Short summary
Collecting spatial lake snow depth data is essential for improving lake ice models. Lake ice growth is directly affected by snow on the lake. However, snow on lake ice is highly influenced by wind redistribution, making it important but challenging to measure accurately in a fast and efficient way. This study utilizes ground-penetrating radar on lakes in Canada's sub-arctic to capture spatial lake snow depth and shows success within 10 % error when compared to manual snow depth measurements.
Hannah Adams, Jane Ye, Bhaleka D. Persaud, Stephanie Slowinski, Homa Kheyrollah Pour, and Philippe Van Cappellen
Earth Syst. Sci. Data, 14, 5139–5156, https://doi.org/10.5194/essd-14-5139-2022, https://doi.org/10.5194/essd-14-5139-2022, 2022
Short summary
Short summary
Climate warming and land-use changes are altering the environmental factors that control the algal
productivityin lakes. To predict how environmental factors like nutrient concentrations, ice cover, and water temperature will continue to influence lake productivity in this changing climate, we created a dataset of chlorophyll-a concentrations (a compound found in algae), associated water quality parameters, and solar radiation that can be used to for a wide range of research questions.
Nazanin Asadi, Philippe Lamontagne, Matthew King, Martin Richard, and K. Andrea Scott
The Cryosphere, 16, 3753–3773, https://doi.org/10.5194/tc-16-3753-2022, https://doi.org/10.5194/tc-16-3753-2022, 2022
Short summary
Short summary
Machine learning approaches are deployed to provide accurate daily spatial maps of sea ice presence probability based on ERA5 data as input. Predictions are capable of predicting freeze-up/breakup dates within a 7 d period at specific locations of interest to shipping operators and communities. Forecasts of the proposed method during the breakup season have skills comparing to Climate Normal and sea ice concentration forecasts from a leading subseasonal-to-seasonal forecasting system.
Kiana Zolfaghari, Claude R. Duguay, and Homa Kheyrollah Pour
Hydrol. Earth Syst. Sci., 21, 377–391, https://doi.org/10.5194/hess-21-377-2017, https://doi.org/10.5194/hess-21-377-2017, 2017
Short summary
Short summary
A remotely-sensed water clarity value (Kd) was applied to improve FLake model simulations of Lake Erie thermal structure using a time-invariant (constant) annual value as well as monthly values of Kd. The sensitivity of FLake model to Kd values was studied. It was shown that the model is very sensitive to variations in Kd when the value is less than 0.5 m-1.
Related subject area
Domain: ESSD – Land | Subject: Hydrology
High-resolution hydrometeorological and snow data for the Dischma catchment in Switzerland
CAMELS-IND: hydrometeorological time series and catchment attributes for 228 catchments in Peninsular India
HERA: a high-resolution pan-European hydrological reanalysis (1951–2020)
BCUB – a large-sample ungauged basin attribute dataset for British Columbia, Canada
Lena River biogeochemistry captured by a 4.5-year high-frequency sampling program
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
GRILSS: Opening the Gateway to Global Reservoir Sedimentation Data Curation
CAMELS-FR dataset: A large-sample hydroclimatic dataset for France to explore hydrological diversity and support model benchmarking
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)
A 1985–2023 time series dataset of absolute reservoir storage in Mainland Southeast Asia (MSEA-Res)
A worldwide event-based debris-flow barrier dam dataset from 1800 to 2023
One year of high frequency monitoring of groundwater physico-chemical parameters in the Weierbach Experimental Catchment, Luxembourg
A globally sampled high-resolution hand-labeled validation dataset for evaluating surface water extent maps
Features of the Italian Large Dams and their upstream catchments
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
CAMELS-AUS v2: updated hydrometeorological timeseries and landscape attributes for an enlarged set of catchments in Australia
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
An in-situ daily dataset for benchmarking temporal variability of groundwater recharge
CAMELS-DK: Hydrometeorological Time Series and Landscape Attributes for 3330 Catchments in Denmark
Mapping the world’s inland surface waters: an update to the Global Lakes and Wetlands Database (GLWD v2)
Rainfall erosivity mapping in mainland China using 1-minute precipitation data from densely distributed weather stations
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
Optimal feature selection for improved ML based reconstruction of Global Terrestrial Water Storage Anomalies
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
Discrete Global Grid System-based Flow Routing Datasets in the Amazon and Yukon Basins
Deriving a Transformation Rate Map of Dissolved Organic Carbon over the Contiguous U.S.
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
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
Jan Magnusson, Yves Bühler, Louis Quéno, Bertrand Cluzet, Giulia Mazzotti, Clare Webster, Rebecca Mott, and Tobias Jonas
Earth Syst. Sci. Data, 17, 703–717, https://doi.org/10.5194/essd-17-703-2025, https://doi.org/10.5194/essd-17-703-2025, 2025
Short summary
Short summary
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.
Nikunj K. Mangukiya, Kanneganti Bhargav Kumar, Pankaj Dey, Shailza Sharma, Vijaykumar Bejagam, Pradeep P. Mujumdar, and Ashutosh Sharma
Earth Syst. Sci. Data, 17, 461–491, https://doi.org/10.5194/essd-17-461-2025, https://doi.org/10.5194/essd-17-461-2025, 2025
Short summary
Short summary
We introduce CAMELS-IND (Catchment Attributes and MEteorology for Large-sample Studies – India), which provides daily hydrometeorological time series and static catchment attributes representing the 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.
Aloïs Tilloy, Dominik Paprotny, Stefania Grimaldi, Goncalo Gomes, Alessandra Bianchi, Stefan Lange, Hylke Beck, Cinzia Mazzetti, and Luc Feyen
Earth Syst. Sci. Data, 17, 293–316, https://doi.org/10.5194/essd-17-293-2025, https://doi.org/10.5194/essd-17-293-2025, 2025
Short summary
Short summary
This article presents a reanalysis of Europe's river streamflow for the period 1951–2020. Streamflow is estimated through a state-of-the-art hydrological simulation framework benefitting from detailed information about the landscape, climate, and human activities. The resulting Hydrological European ReAnalysis (HERA) can be a valuable tool for studying hydrological dynamics, including the impacts of climate change and human activities on European water resources and flood and drought risks.
Daniel Kovacek and Steven Weijs
Earth Syst. Sci. Data, 17, 259–275, https://doi.org/10.5194/essd-17-259-2025, https://doi.org/10.5194/essd-17-259-2025, 2025
Short summary
Short summary
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 are meant to be used for water resources problems that can benefit from lots of watersheds 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.
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, 17, 1–28, https://doi.org/10.5194/essd-17-1-2025, https://doi.org/10.5194/essd-17-1-2025, 2025
Short summary
Short summary
The Siberian Arctic is warming fast: permafrost is thawing, river chemistry is changing, and coastal ecosystems are affected. We aimed to understand changes in 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/.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Sanchit Minocha and Faisal Hossain
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-470, https://doi.org/10.5194/essd-2024-470, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
Trustworthy and independently verifiable information on declining storage capacity or sedimentation rates around the world is sparse and suffers from inconsistent metadata and curation to allow global-scale archiving and analyses. Global Reservoir Inventory of Lost Storage by Sedimentation (GRILSS) dataset addresses this challenge by providing organized, well-curated and open-source data on sedimentation rates and capacity loss for 1,015 reservoirs in 75 major river basins across 54 countries.
Olivier Delaigue, Guilherme Mendoza Guimarães, Pierre Brigode, Benoît Génot, Charles Perrin, Jean-Michel Soubeyroux, Bruno Janet, Nans Addor, and Vazken Andréassian
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-415, https://doi.org/10.5194/essd-2024-415, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
This dataset covers 654 rivers all flowing in France. The provided time series and catchment attributes will be of interest to those modelers wishing to analyse hydrological behavior, perform model assessments.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Shanti Shwarup Mahto, Simone Fatichi, and Stefano Galelli
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-441, https://doi.org/10.5194/essd-2024-441, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
The MSEA-Res database offers an open-access dataset tracking absolute water storage for 185 large reservoirs across Mainland Southeast Asia from 1985–2023. It provides valuable insights into how reservoir storage has grown by 130 % between 2008 and 2017, driven by dams in key river basins. Our data also reveal how droughts, like the 2019–2020 event, significantly impacted water reservoirs. This resource can aid water management, drought planning, and research globally.
Haiguang Cheng, Kaiheng Hu, Shuang Liu, Xiaopeng Zhang, Hao Li, Qiyuan Zhang, Lan Ning, Manish Raj Gouli, Pu Li, Anna Yang, and Peng Zhao
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-382, https://doi.org/10.5194/essd-2024-382, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
After reviewing 2,519 literature and media reports, we compiled the first comprehensive global dataset of 555 debris flow barrier dams (DFBDs) from 1800 to 2023. Our dataset meticulously documents 36 attributes of DFBDs, and we have utilized Google Earth for validation. Additionally, we discussed the applicability of landslide dam stability and peak discharge models to DFBDs. This dataset offers a rich foundation of data for future studies on DFBDs.
Karl Nicolaus van Zweel, Laurent Gourdol, Jean François Iffly, Loïc Léonard, François Barnich, Laurent Pfister, Erwin Zehe, and Christophe Hissler
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-259, https://doi.org/10.5194/essd-2024-259, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
Our study monitored groundwater in a Luxembourg forest over a year to understand water and chemical changes. We found seasonal variations in water chemistry, influenced by rainfall and soil interactions. This data helps predict environmental responses and manage water resources better. By measuring key parameters like pH and dissolved oxygen, our research provides valuable insights into groundwater behavior and serves as a resource for future environmental studies.
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
Short summary
Short summary
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.
Giulia Evangelista, Paola Mazzoglio, Daniele Ganora, Francesca Pianigiani, and Pierluigi Claps
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-387, https://doi.org/10.5194/essd-2024-387, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
This paper presents the first comprehensive dataset of 528 Large Dams in Italy. It contains structural characteristics of the dams, such as coordinates, reservoir surface area and volume, together with a range of geomorphological, climatological, extreme rainfall, land cover and soil-related attributes of their upstream catchments.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Keirnan J. A. Fowler, Ziqi Zhang, and Xue Hou
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-263, https://doi.org/10.5194/essd-2024-263, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
This paper presents Version 2 of the Australian edition of the Catchment Attributes and Meteorology for Large-sample Studies (CAMELS) series of datasets. CAMELS-AUS v2 comprises data for an increased number (561) of catchments, each with with long-term monitoring, combining hydrometeorological time series with attributes related to geology, soil, topography, land cover, anthropogenic influence and hydroclimatology. It is freely downloadable from https://zenodo.org/doi/10.5281/zenodo.12575680.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Pragnaditya Malakar, Aatish Anshuman, Mukesh Kumar, Georgios Boumis, T. Prabhakar Clement, Arik Tashie, Hitesh Thakur, Nagaraj Bhat, and Lokendra Rathore
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-324, https://doi.org/10.5194/essd-2024-324, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
Groundwater dynamics depend on groundwater recharge, but daily benchmark data of recharge is scarce. Here we present a daily groundwater recharge per unit specified yield (RpSy) data at 485 US groundwater monitoring wells. RpSy can be used to validate temporal consistency of recharge products from land surface and hydrologic models and facilitate assessment of recharge-driver functional relationships in them.
Jun Liu, Julian Koch, Simon Stisen, Lars Troldborg, Anker Lajer Højberg, Hans Thodsen, Mark F. T. Hansen, and Raphael J. M. Schneider
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-292, https://doi.org/10.5194/essd-2024-292, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
We developed a CAMELS-style dataset in Denmark, which contains hydrometeorological time series and landscape attributes for 3,330 catchments. Many of the catchments in CAMELS-DK are small and located at low elevations. The dataset provides information on groundwater characteristics and dynamics, as well as quantities related to human impact on the hydrological system in Denmark. The dataset is especially relevant for developing data-driven and hybrid physically-informed modeling frameworks.
Bernhard Lehner, Mira Anand, Etienne Fluet-Chouinard, Florence Tan, Filipe Aires, George H. Allen, Pilippe Bousquet, Josep G. Canadell, Nick Davidson, C. Max Finlayson, Thomas Gumbricht, Lammert Hilarides, Gustaf Hugelius, Robert B. Jackson, Maartje C. Korver, Peter B. McIntyre, Szabolcs Nagy, David Olefeldt, Tamlin M. Pavelsky, Jean-Francois Pekel, Benjamin Poulter, Catherine Prigent, Jida Wang, Thomas A. Worthington, Dai Yamazaki, and Michele Thieme
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-204, https://doi.org/10.5194/essd-2024-204, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
The Global Lakes and Wetlands Database (GLWD) version 2 distinguishes a total of 33 non-overlapping wetland classes, providing a static map of the world’s inland surface waters. It contains cell fractions of wetland extents per class at a grid cell resolution of ~500 m. The total combined extent of all classes including all inland and coastal waterbodies and wetlands of all inundation frequencies—that is, the maximum extent—covers 18.2 million km2, equivalent to 13.4 % of total global land area.
Yueli Chen, Yun Xie, Xingwu Duan, and Minghu Ding
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-195, https://doi.org/10.5194/essd-2024-195, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
Rainfall erosivity map is crucial for identifying key areas of water erosion. Due to the limited historical precipitation data, there are certain biases in rainfall erosivity estimates in China. This study develops a new rainfall erosivity map for mainland China using 1-minute precipitation data from 60,129 weather stations, revealing that areas exceeding 4000 MJ·mm·ha−1·h−1·yr−1 of annual rainfall erosivity mainly concentrated in the southern China and southern Tibetan Plateau.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Nehar Mandal, Prabal Das, and Kironmala Chanda
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-109, https://doi.org/10.5194/essd-2024-109, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
Optimal features among hydroclimatic variables and land surface model (LSM) outputs are selected using a novel Bayesian network (BN) approach for simulating Terrestrial Water Storage Anomalies (TWSA). TWSA is simulated using ML models (CNN, SVR, ETR, and Stacking Ensemble Regression), and gridwise leader models are identified globally. TWSA is reconstructed (BNML_TWSA) with the selected leader models from January 1960 to December 2022 to generate a continuous global gridded dataset.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Chang Liao, Darren Engwirda, Matthew Cooper, Mingke Li, and Yilin Fang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-398, https://doi.org/10.5194/essd-2023-398, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
Discrete Global Grid systems, or DGGs, are digital frameworks that help us organize information about our planet. Although scientists have used DGGs in areas like weather and nature, using them in the water cycle has been challenging because some core datasets are missing. We created a way to generate these datasets. We then developed the datasets in the Amazon Basin, which plays an important role in our planet's climate. These datasets may help us improve our water cycle models.
Lingbo Li, Hong-Yi Li, Guta Abeshu, Jinyun Tang, L. Ruby Leung, Chang Liao, Zeli Tan, Hanqin Tian, Peter Thornton, and Xiaojuan Yang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-43, https://doi.org/10.5194/essd-2024-43, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
We have developed a new map that reveals how organic carbon from soil leaches into headwater streams over the contiguous United States. We use advanced artificial intelligence techniques and a massive amount of data, including observations at over 2,500 gauges and a wealth of climate and environmental information. The map is a critical step in understanding and predicting how carbon moves through our environment, hence a useful tool for tackling climate challenges.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Cited articles
Attiah, G., Kheyrollah Pour, H., and Scott, K. A.: North Slave Lake Surface
Temperature Retrieved from Landsat Archives from 1984 to 2021, Borealis [data set],
https://doi.org/10.5683/SP3/J4GMC2, 2022.
Austin, J. A. and Colman, S. M.: Lake Superior summer water temperatures are
increasing more rapidly than regional temperatures: A positive ice-albedo
feedback, Geophys. Res. Lett., 34, L06604,
https://doi.org/10.1029/2006GL029021, 2007.
Chander, G. and Markham, B.: Revised Landsat-5 TM Radiometrie Calibration
Procedures and Postcalibration Dynamic Ranges, IEEE T. Geosci. Remote, 41, 2674–2677, https://doi.org/10.1109/TGRS.2003.818464, 2003.
Chen, Y., Zhao, C., and Ming, Y.: Potential impacts of Arctic warming on
Northern Hemisphere mid-latitude aerosol optical depth, Clim. Dynam., 53, 1637–1651,
https://doi.org/10.1007/s00382-019-04706-3, 2019.
Collingsworth, P. D., Bunnell, D. B., Murray, M. W., Kao, Y. C., Feiner, Z.
S., Claramunt, R. M., Lofgren, B. M., Höök, T. O., and Ludsin, S.
A.: Climate change as a long-term stressor for the fisheries of the
Laurentian Great Lakes of North America, Rev. Fish Biol. Fish., 27,
363–391, https://doi.org/10.1007/s11160-017-9480-3, 2017.
Crosman, E. T. and Horel, J. D.: Remote Sensing of Environment MODIS-derived
surface temperature of the Great Salt Lake, Remote Sens. Environ., 113,
73–81, https://doi.org/10.1016/j.rse.2008.08.013, 2009.
Desai, A. R., Austin, J. A., Bennington, V., and McKinley, G. A.: Stronger
winds over a large lake in response to weakening air-to-lake temperature
gradient, Nat. Geosci., 2, 855–858, https://doi.org/10.1038/ngeo693, 2009.
Eerola, K., Rontu, L., Kourzeneva, E., Pour, H. K., and Duguay, C.: Impact
of partly ice-free Lake Ladoga on temperature and cloudiness in an
anticyclonic winter situation – a case study using a limited area model,
Tellus A, 66, 23929,
https://doi.org/10.3402/tellusa.v66.23929, 2014.
Environment and Climate Change Canada, Université de Montréal: CIMP 161_Legacy arsenic pollution in Yellowknife Bay sediments, 1.0.0, DataStream [data set], https://doi.org/10.25976/gm49-2a19, 2020.
Fichot, C. G., Matsumoto, K., Holt, B., Gierach, M. M., and Tokos, K. S.:
Assessing change in the overturning behavior of the Laurentian Great Lakes
using remotely sensed lake surface water temperatures, Remote Sens.
Environ., 235, 111427, https://doi.org/10.1016/j.rse.2019.111427, 2019.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on single levels from 1959 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.adbb2d47, 2018.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A.,
Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D.,
Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P.,
Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D.,
Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer,
A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková,
M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., De Rosnay,
P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5
global reanalysis, Q. J. Roy. Meteorol. Soc., 146, 1999–2049,
https://doi.org/10.1002/qj.3803, 2020.
Huang, Y., Liu, H., Hinkel, K., Yu, B., Beck, R., and Wu, J.: Analysis of
Thermal Structure of Arctic Lakes at Local and Regional Scales Using in Situ
and Multidate Landsat-8 Data, Water Resour. Res., 53, 9642–9658,
https://doi.org/10.1002/2017WR021335, 2017.
HydroSheds: HydroLAKES, Hydrosheds [data set], https://www.hydrosheds.org/products/hydrolakes, last access: 20 May 2022.
Ihlen, V. and Zanter, K.: Landsat 7 (L7) Data Users Handbook, USGS Landsat
User Serv., 7, 151, https://d9-wret.s3.us-west-2.amazonaws.com/assets/palladium/production/s3fs-public/atoms/files/LSDS-1927_L7_Data_Users_Handbook-v2.pdf (last access: 6 March 2023), 2019.
Irons, J. R., Dwyer, J. L., and Barsi, J. A.: The next Landsat satellite:
The Landsat Data Continuity Mission, Remote Sens. Environ., 122, 11–21,
https://doi.org/10.1016/j.rse.2011.08.026, 2012.
Jiménez-Muñoz, J. C. and Sobrino, J. A.: A generalized
single-channel method for retrieving land surface temperature from
remote sensing data, J. Geophys. Res, 108, 4688,
https://doi.org/10.1029/2003JD003480, 2003.
Jimenez-Munoz, J. C., Cristobal, J., Sobrino, J. A., Sòria, G.,
Ninyerola, M., and Pons, X.: Revision of the single-channel algorithm for
land surface temperature retrieval from landsat thermal-infrared data, IEEE
T. Geosci. Remote, 47, 339–349,
https://doi.org/10.1109/TGRS.2008.2007125, 2009.
Jimenez-Munoz, J. C., Sobrino, J. A., Skokovic, D., Mattar, C., and
Cristobal, J.: Land surface temperature retrieval methods from landsat-8
thermal infrared sensor data, IEEE Geosci. Remote Sens. Lett., 11,
1840–1843, https://doi.org/10.1109/LGRS.2014.2312032, 2014.
Kheyrollah Pour, H., Duguay, C. R., Solberg, R., and Rudjord, Ø.: Impact
of satellite-based lake surface observations on the initial state of HIRLAM.
Part I: Evaluation of remotelysensed lake surface water temperature
observations, Tellus A, 66, 21534,
https://doi.org/10.3402/tellusa.v66.21534, 2014a.
Kheyrollah Pour, H., Rontu, L., Duguay, C., Eerola, K., and Kourzeneva, E.:
Impact of satellite-based lake surface observations on the initial state of
HIRLAM. Part II: Analysis of lake surface temperature and ice cover, Tellus
A, 66, 21395,
https://doi.org/10.3402/tellusa.v66.21395, 2014b.
Kheyrollah Pour, H., Duguay, C. R., Scott, K. A., and Kang, K. K.:
Improvement of Lake Ice Thickness Retrieval from MODIS Satellite Data Using
a Thermodynamic Model, IEEE T. Geosci. Remote, 55, 5956–5965,
https://doi.org/10.1109/TGRS.2017.2718533, 2017.
Kraemer, B. M., Anneville, O., Chandra, S., Dix, M., Kuusisto, E.,
Livingstone, D. M., Rimmer, A., Schladow, S. G., Silow, E., Sitoki, L. M.,
Tamatamah, R., Vadeboncoeur, Y., and McIntyre, P. B.: Morphometry and average temperature affect lake stratification responses to climate change, Geophys. Res. Lett., 42, 4981–4988,
https://doi.org/10.1002/2015GL064097, 2015.
Livingstone, D. M., Lotter, F., and Kettle, H.: Altitude-dependent
differences in the primary physical response of mountain lakes to climatic
forcing, Limnol. Oceanogr., 50, 1313–1325, 2005.
Magnuson, J. J., Robertson, D. M., Benson, B. J., Wynne, R. H., Livingstone,
D. M., Arai, T., Assel, R. A., Barry, R. G., Card, V., Kuusisto, E., Granin,
N. G., Prowse, T. D., Stewart, K. M., and Vuglinski, V. S.: Historical
trends in lake and river ice cover in the Northern Hemisphere, Science, 289, 1743–1746, https://doi.org/10.1126/science.289.5485.1743, 2000.
Markham, B., Barsi, J., Kvaran, G., Ong, L., Kaita, E., Biggar, S.,
Czapla-Myers, J., Mishra, N., and Helder, D.: Landsat-8 operational land
imager radiometric calibration and stability, Remote Sensing, 6, 12275–12308,
https://doi.org/10.3390/rs61212275, 2014.
Merchant, C. J., Paul, F., Popp, T., Ablain, M., Bontemps, S., Defourny, P., Hollmann, R., Lavergne, T., Laeng, A., de Leeuw, G., Mittaz, J., Poulsen, C., Povey, A. C., Reuter, M., Sathyendranath, S., Sandven, S., Sofieva, V. F., and Wagner, W.: Uncertainty information in climate data records from Earth observation, Earth Syst. Sci. Data, 9, 511–527, https://doi.org/10.5194/essd-9-511-2017, 2017.
Messager, M. L., Lehner, B., Grill, G., Nedeva, I., and Schmitt, O.:
Estimating the volume and age of water stored in global lakes using a
geo-statistical approach, Nat. Commun., 7, 13603,
https://doi.org/10.1038/ncomms13603, 2016.
Le Moigne, P., Colin, J., and Decharme, B.: Impact of lake surface temperatures simulated by the FLake scheme in the CNRM-CM5 climate model, Tellus A, 68, 31274, https://doi.org/10.3402/tellusa.v68.31274, 2016.
Natural Resources Canada: Lakes, Rivers and Glaciers in Canada – CanVec Series – Hydrographic Features, Government of Canada [data set], https://open.canada.ca/data/en/dataset/9d96e8c9-22fe-4ad2-b5e8-94a6991b744b (last access: 28 March 2022), 2019.
O'Reilly, C. M., Rowley, R. J., Schneider, P., Lenters, J. D., Mcintyre, P.
B., and Kraemer, B. M.: Rapid and highly variable warming of lake surface
waters around the globe, Geophys. Res. Lett., 42, 10773–10781, https://doi.org/10.1002/2015GL066235, 2015.
Pekel, J. F., Cottam, A., Gorelick, N., and Belward, A. S.: High-resolution
mapping of global surface water and its long-term changes, Nature, 540,
418–422, https://doi.org/10.1038/nature20584, 2016.
Prats, J., Reynaud, N., Rebière, D., Peroux, T., Tormos, T., and Danis, P.-A.: LakeSST: Lake Skin Surface Temperature in French inland water bodies for 1999–2016 from Landsat archives, Earth Syst. Sci. Data, 10, 727–743, https://doi.org/10.5194/essd-10-727-2018, 2018.
Reinart, A. and Reinhold, M.: Mapping surface temperature in large lakes
with MODIS data, Remote Sens. Environ., 112, 603–611, https://doi.org/10.1016/j.rse.2007.05.015,
2008.
Roy, D. P., Wulder, M. A., Loveland, T. R., C. E., W., Allen, R. G.,
Anderson, M. C., Helder, D., Irons, J. R., Johnson, D. M., Kennedy, R.,
Scambos, T. A., Schaaf, C. B., Schott, J. R., Sheng, Y., Vermote, E. F.,
Belward, A. S., Bindschadler, R., Cohen, W. B., Gao, F., Hipple, J. D.,
Hostert, P., Huntington, J., Justice, C. O., Kilic, A., Kovalskyy, V., Lee,
Z. P., Lymburner, L., Masek, J. G., McCorkel, J., Shuai, Y., Trezza, R.,
Vogelmann, J., Wynne, R. H., and Zhu, Z.: Landsat-8: Science and product
vision for terrestrial global change research, Remote Sens. Environ., 145,
154–172, https://doi.org/10.1016/j.rse.2014.02.001, 2014.
Schneider, P. and Hook, S. J.: Space observations of inland water bodies
show rapid surface warming since 1985, Geophys. Res. Lett., 37, L22405,
https://doi.org/10.1029/2010GL045059, 2010.
Sentlinger, G. I., Hook, S. J., and Laval, B.: Sub-pixel water temperature
estimation from thermal-infrared imagery using vectorized lake features,
Remote Sens. Environ., 112, 1678–1688,
https://doi.org/10.1016/j.rse.2007.08.019, 2008.
Shi, Q. and Xie, P.: Impact of lake
surface temperature variations on lake
effect snow over the great lakes region, J. Geophys. Res.-Atmos., 124, 12553–12567, https://doi.org/10.1029/2019JD031261, 2019.
Sima, S., Ahmadalipour, A., and Tajrishy, M.: Mapping surface temperature in
a hyper-saline lake and investigating the effect of temperature distribution
on the lake evaporation, Remote Sens. Environ., 136, 374–385,
https://doi.org/10.1016/j.rse.2013.05.014, 2013.
Slater, J. A., Garvey, G., Johnston, C., Haase, J., Heady, B., Kroenung, G.,
and Little, J.: The SRTM data “finishing” process and products,
Photogramm. Eng. Remote Sensing, 72, 237–247,
https://doi.org/10.14358/PERS.72.3.237, 2006.
Statistics Canada: 2016 Census-Boundary files, Statistics Canada [data set], https://www12.statcan.gc.ca/census-recensement/2011/geo/bound-limit/files-fichiers/ghy_000c06a_e.zip, last access: 30 March 2022.
U.S. Geological Survey: Landsat 8 Data Users Handbook, Nasa, 8, 97, 2016.
USGS: landsat-level-1-processing-details,
https://www.usgs.gov/landsat-missions/landsat-level-1-processing-details,
last access: 11 March 2022.
Wan, Z., Zhang, Y., Zhang, Q., and Li, Z. L.: Validation of the
land-surface temperature products retrieved from terra moderate resolution
imaging spectroradiometer data, Remote Sens. Environ., 83, 163–180,
https://doi.org/10.1016/S0034-4257(02)00093-7, 2002.
Wang, J., Xue, P., Pringle, W., Yang, Z., and Qian, Y.: Impacts of lake
surface temperature on the summer
climate over the Great Lakes Region,
J. Geophys. Res.-Atmos., 127, e2021JD036231,
https://doi.org/10.1029/2021JD036231, 2022.
Wloczyk, C., Richter, R., Borg, E., and Neubert, W.: Sea and lake surface
temperature retrieval from Landsat thermal data in Northern Germany, Journal of Remote Sensing, 27, 2489–2502,
https://doi.org/10.1080/01431160500300206, 2006.
Woolway, R. I., Merchant, C. J., Van Den Hoek, J., Azorin-Molina, C.,
Nõges, P., Laas, A., Mackay, E. B., and Jones, I. D.: Northern
Hemisphere Atmospheric Stilling Accelerates Lake Thermal Responses to a
Warming World, Geophys. Res. Lett., 46, 11983–11992,
https://doi.org/10.1029/2019GL082752, 2019.
Woolway, R. I., Kraemer, B. M., Lenters, J. D., Merchant, C. J., O'Reilly,
C. M., and Sharma, S.: Global lake responses to climate change, Nat. Rev.
Earth Environ., 1, 388–403, https://doi.org/10.1038/s43017-020-0067-5,
2020.
Xie, C., Zhang, X., Zhuang, L., Zhu, R., and Guo, J.: Analysis of surface
temperature variation of lakes in China using MODIS land surface temperature
data, Scientific Reports, 12, 2415, https://doi.org/10.1038/s41598-022-06363-9, 2022.
Yang, K., Yu, Z., and Luo, Y.: Analysis on driving factors of lake surface
water temperature for major lakes in Yunnan-Guizhou Plateau, Water Res.,
184, 116018, https://doi.org/10.1016/j.watres.2020.116018, 2020.
Young, N. E., Anderson, R. S., Chignell, S. M., Vorster, A. G., Lawrence,
R., and Evangelista, P. H.: A survival guide to Landsat preprocessing,
Ecology, 98, 920–932, https://doi.org/10.1002/ecy.1730, 2017.
Zhang, G., Yao, T., Chen, W., Zheng, G., Shum, C. K., Yang, K., Piao, S.,
Sheng, Y., Yi, S., Li, J., O'Reilly, C. M., Qi, S., Shen, S. S. P., Zhang,
H., and Jia, Y.: Regional differences of lake evolution across China during
1960s–2015 and its natural and anthropogenic causes, Remote Sens. Environ.,
221, 386–404, https://doi.org/10.1016/j.rse.2018.11.038, 2019.
Zhang, X., Duan, K. Q., Shi, P. H., and Yang, J. H.: Effect of lake
surface temperature on the summer precipitation over the Tibetan Plateau, J.
Mt. Sci., 13, 802–810, https://doi.org/10.1007/s11629-015-3743-z, 2016.
Zhao, G., Gao, H., and Cai, X.: Estimating lake temperature profile and
evaporation losses by leveraging MODIS LST data, Remote Sens. Environ., 251,
112104, https://doi.org/10.1016/j.rse.2020.112104, 2020.
Short summary
Lake surface temperature (LST) is a significant indicator of climate change and influences local weather and climate. This study developed a LST dataset retrieved from Landsat archives for 535 lakes across the North Slave Region, NWT, Canada. The data consist of individual NetCDF files for all observed days for each lake. The North Slave LST dataset will provide communities, scientists, and stakeholders with the changing spatiotemporal trends of LST for the past 38 years (1984–2021).
Lake surface temperature (LST) is a significant indicator of climate change and influences local...
Altmetrics
Final-revised paper
Preprint