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.
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.
Andreas R. Stokholm, Jørgen Buus-Hinkler, Tore Wulf, Anton Korosov, Roberto Saldo, Leif T. Pedersen, David Arthurs, Ionut Dragan, Iacopo Modica, Juan Pedro, Annekatrien Debien, Xinwei Chen, Muhammed Patel, Fernando J. P. Cantu, Javier N. Turnes, Jinman Park, Linlin Xu, Andrea K. Scott, David A. Clausi, Yuan Fang, Mingzhe Jiang, Saeid Taleghanidoozdoozan, Neil C. Brubacher, Armina Soleymani, Zacharie Gousseau, Michał Smaczny, Patryk Kowalski, Jacek Komorowski, David Rijlaarsdam, Jan N. van Rijn, Jens Jakobsen, Martin S. J. Rogers, Nick Hughes, Tom Zagon, Rune Solberg, Nicolas Longépé, and Matilde B. Kreiner
EGUsphere, https://doi.org/10.5194/egusphere-2023-2648, https://doi.org/10.5194/egusphere-2023-2648, 2023
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, the age and ice floe size using multiple sources of satellite and weather data across the Canadian and Greenlandic Arctic. To judge the solution, professionally drawn operational sea ice charts were used as reference. 179 students and sea ice and AI specialists participated and produced maps in broad agreement with the sea ice charts.
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
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
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
Simbi: historical hydro-meteorological time series and signatures for 24 catchments in Haiti
LamaH-Ice: LArge-SaMple Data for Hydrology and Environmental Sciences for Iceland
Hydro-PE: gridded datasets of historical and future Penman–Monteith potential evaporation for the United Kingdom
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
Evapotranspiration evaluation by 3 different protocols on a large green roof in the greater Paris area
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
A global database of historic glacier lake outburst floods
Past and future discharge and stream temperature at high spatial resolution in a large European basin (Loire basin, France)
Res-CN (Reservoir dataset in China): hydrometeorological time series and landscape attributes across 3254 Chinese reservoirs
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
The enhanced future Flows and Groundwater dataset: development and evaluation of nationally consistent hydrological projections based on UKCP18
RC4USCoast: a river chemistry dataset for regional ocean model applications in the US East Coast, Gulf of Mexico, and US West Coast
Generation of global 1 km daily soil moisture product from 2000 to 2020 using ensemble learning
Panta Rhei benchmark dataset: socio-hydrological data of paired events of floods and droughts
Twelve years of profile soil moisture and temperature measurements in Twente, the Netherlands
Shallow-groundwater-level time series and a groundwater chemistry survey from a boreal headwater catchment, Krycklan, Sweden
High-resolution mapping of monthly industrial water withdrawal in China from 1965 to 2020
Weekly high-resolution multi-spectral and thermal uncrewed-aerial-system mapping of an alpine catchment during summer snowmelt, Niwot Ridge, Colorado
Nunataryuk field campaigns: understanding the origin and fate of terrestrial organic matter in the coastal waters of the Mackenzie Delta region
Integrated ecohydrological hydrometric and stable water isotope data of a drought-sensitive mixed land use lowland catchment
Regional data sets of high-resolution (1 and 6 km) irrigation estimates from space
Global hourly, 5 km, all-sky land surface temperature data from 2011 to 2021 based on integrating geostationary and polar-orbiting satellite data
Flood detection using Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage and extreme precipitation data
The pan-Arctic catchment database (ARCADE)
Multi-hazard susceptibility mapping of cryospheric hazards in a high-Arctic environment: Svalbard Archipelago
High-resolution water level and storage variation datasets for 338 reservoirs in China during 2010–2021
WaterBench-Iowa: a large-scale benchmark dataset for data-driven streamflow forecasting
A dataset of 10-year regional-scale soil moisture and soil temperature measurements at multiple depths on the Tibetan Plateau
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.
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.
Ralph Bathelemy, Pierre Brigode, Vazken Andréassian, Charles Perrin, Vincent Moron, Cédric Gaucherel, Emmanuel Tric, and Dominique Boisson
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-259, https://doi.org/10.5194/essd-2023-259, 2023
Revised manuscript accepted for ESSD
Short summary
Short summary
The aim of this work is to provide the first hydro-climatic database for Haiti, a Caribbean country particularly vulnerable to meteorological and hydrological hazards. The resulting database, named SIMBI, provides hydro-climatic time series for around 150 stations and 24 catchment areas.
Hordur Bragi Helgason and Bart Nijssen
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-349, https://doi.org/10.5194/essd-2023-349, 2023
Revised manuscript accepted for ESSD
Short summary
Short summary
LamaH-Ice is a large-sample hydrology (LSH) dataset for Iceland. The dataset includes daily and hourly hydro-meteorological timeseries, including observed streamflow, and basin characteristics for 107 basins. LamaH-Ice offers most variables that are included in existing LSH datasets, as well as 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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Pierre-Antoine Versini, Leydy Alejandra Castellanos-Diaz, David Ramier, and Ioulia Tchiguirinskaia
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-324, https://doi.org/10.5194/essd-2023-324, 2023
Revised manuscript accepted for ESSD
Short summary
Short summary
Nature-Based Solutions, as green roofs, have appeared as relevant solutions to mitigate urban heat islands. The evapotranspiration process conducts the ability of NBS to cool the air. To improve our knowledge about evapotranspiration assessment, this paper presents some experimental measurement campaigns carried out during 3 consecutive summers. It makes the data available for 3 different spatial scales (large, small and punctual).
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Fabian A. Gomez, Sang-Ki Lee, Charles A. Stock, Andrew C. Ross, Laure Resplandy, Samantha A. Siedlecki, Filippos Tagklis, and Joseph E. Salisbury
Earth Syst. Sci. Data, 15, 2223–2234, https://doi.org/10.5194/essd-15-2223-2023, https://doi.org/10.5194/essd-15-2223-2023, 2023
Short summary
Short summary
We present a river chemistry and discharge dataset for 140 rivers in the United States, which integrates information from the Water Quality Database of the US Geological Survey (USGS), the USGS’s Surface-Water Monthly Statistics for the Nation, and the U.S. Army Corps of Engineers. This dataset includes dissolved inorganic carbon and alkalinity, two key properties to characterize the carbonate system, as well as nutrient concentrations, such as nitrate, phosphate, and silica.
Yufang Zhang, Shunlin Liang, Han Ma, Tao He, Qian Wang, Bing Li, Jianglei Xu, Guodong Zhang, Xiaobang Liu, and Changhao Xiong
Earth Syst. Sci. Data, 15, 2055–2079, https://doi.org/10.5194/essd-15-2055-2023, https://doi.org/10.5194/essd-15-2055-2023, 2023
Short summary
Short summary
Soil moisture observations are important for a range of earth system applications. This study generated a long-term (2000–2020) global seamless soil moisture product with both high spatial and temporal resolutions (1 km, daily) using an XGBoost model and multisource datasets. Evaluation of this product against dense in situ soil moisture datasets and microwave soil moisture products showed that this product has reliable accuracy and more complete spatial coverage.
Heidi Kreibich, Kai Schröter, Giuliano Di Baldassarre, Anne F. Van Loon, Maurizio Mazzoleni, Guta Wakbulcho Abeshu, Svetlana Agafonova, Amir AghaKouchak, Hafzullah Aksoy, Camila Alvarez-Garreton, Blanca Aznar, Laila Balkhi, Marlies H. Barendrecht, Sylvain Biancamaria, Liduin Bos-Burgering, Chris Bradley, Yus Budiyono, Wouter Buytaert, Lucinda Capewell, Hayley Carlson, Yonca Cavus, Anaïs Couasnon, Gemma Coxon, Ioannis Daliakopoulos, Marleen C. de Ruiter, Claire Delus, Mathilde Erfurt, Giuseppe Esposito, Didier François, Frédéric Frappart, Jim Freer, Natalia Frolova, Animesh K. Gain, Manolis Grillakis, Jordi Oriol Grima, Diego A. Guzmán, Laurie S. Huning, Monica Ionita, Maxim Kharlamov, Dao Nguyen Khoi, Natalie Kieboom, Maria Kireeva, Aristeidis Koutroulis, Waldo Lavado-Casimiro, Hong-Yi Li, Maria Carmen LLasat, David Macdonald, Johanna Mård, Hannah Mathew-Richards, Andrew McKenzie, Alfonso Mejia, Eduardo Mario Mendiondo, Marjolein Mens, Shifteh Mobini, Guilherme Samprogna Mohor, Viorica Nagavciuc, Thanh Ngo-Duc, Huynh Thi Thao Nguyen, Pham Thi Thao Nhi, Olga Petrucci, Nguyen Hong Quan, Pere Quintana-Seguí, Saman Razavi, Elena Ridolfi, Jannik Riegel, Md Shibly Sadik, Nivedita Sairam, Elisa Savelli, Alexey Sazonov, Sanjib Sharma, Johanna Sörensen, Felipe Augusto Arguello Souza, Kerstin Stahl, Max Steinhausen, Michael Stoelzle, Wiwiana Szalińska, Qiuhong Tang, Fuqiang Tian, Tamara Tokarczyk, Carolina Tovar, Thi Van Thu Tran, Marjolein H. J. van Huijgevoort, Michelle T. H. van Vliet, Sergiy Vorogushyn, Thorsten Wagener, Yueling Wang, Doris E. Wendt, Elliot Wickham, Long Yang, Mauricio Zambrano-Bigiarini, and Philip J. Ward
Earth Syst. Sci. Data, 15, 2009–2023, https://doi.org/10.5194/essd-15-2009-2023, https://doi.org/10.5194/essd-15-2009-2023, 2023
Short summary
Short summary
As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management. We present a dataset containing data of paired events, i.e. two floods or two droughts that occurred in the same area. The dataset enables comparative analyses and allows detailed context-specific assessments. Additionally, it supports the testing of socio-hydrological models.
Rogier van der Velde, Harm-Jan F. Benninga, Bas Retsios, Paul C. Vermunt, and M. Suhyb Salama
Earth Syst. Sci. Data, 15, 1889–1910, https://doi.org/10.5194/essd-15-1889-2023, https://doi.org/10.5194/essd-15-1889-2023, 2023
Short summary
Short summary
From 2009, a network of 20 profile soil moisture and temperature monitoring stations has been operational in the Twente region, east of the Netherlands. In addition, field campaigns have been conducted covering four growing seasons during which soil moisture was measured near 12 monitoring stations. We describe the monitoring network and field campaigns, and we provide an overview of open third-party datasets that may support the use of the Twente datasets.
Jana Erdbrügger, Ilja van Meerveld, Jan Seibert, and Kevin Bishop
Earth Syst. Sci. Data, 15, 1779–1800, https://doi.org/10.5194/essd-15-1779-2023, https://doi.org/10.5194/essd-15-1779-2023, 2023
Short summary
Short summary
Groundwater can respond quickly to precipitation and is the main source of streamflow in most catchments in humid, temperate climates. To better understand shallow groundwater dynamics, we installed a network of groundwater wells in two boreal headwater catchments in Sweden. We recorded groundwater levels in 75 wells for 2 years and sampled the water and analyzed its chemical composition in one summer. This paper describes these datasets.
Chengcheng Hou, Yan Li, Shan Sang, Xu Zhao, Yanxu Liu, Yinglu Liu, and Fang Zhao
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-66, https://doi.org/10.5194/essd-2023-66, 2023
Revised manuscript accepted for ESSD
Short summary
Short summary
The China Industrial Water Withdrawal Dataset help understand the human water use dynamics and support studies in hydrology, geography, environment, sustainability sciences, and regional water resources management and allocation in China. The transparent methodology and public availability of the source data allowed further adjustments and calibration to support the various applications by users. They also served as a reference for other countries to develop localized datasets of their own.
Oliver Wigmore and Noah P. Molotch
Earth Syst. Sci. Data, 15, 1733–1747, https://doi.org/10.5194/essd-15-1733-2023, https://doi.org/10.5194/essd-15-1733-2023, 2023
Short summary
Short summary
We flew a custom-built drone fitted with visible, near-infrared and thermal cameras every week over a summer season at Niwot Ridge in Colorado's alpine tundra. We processed these images into seamless orthomosaics that record changes in snow cover, vegetation health and the movement of water over the land surface. These novel datasets provide a unique centimetre resolution snapshot of ecohydrologic processes, connectivity and spatial and temporal heterogeneity in the alpine zone.
Martine Lizotte, Bennet Juhls, Atsushi Matsuoka, Philippe Massicotte, Gaëlle Mével, David Obie James Anikina, Sofia Antonova, Guislain Bécu, Marine Béguin, Simon Bélanger, Thomas Bossé-Demers, Lisa Bröder, Flavienne Bruyant, Gwénaëlle Chaillou, Jérôme Comte, Raoul-Marie Couture, Emmanuel Devred, Gabrièle Deslongchamps, Thibaud Dezutter, Miles Dillon, David Doxaran, Aude Flamand, Frank Fell, Joannie Ferland, Marie-Hélène Forget, Michael Fritz, Thomas J. Gordon, Caroline Guilmette, Andrea Hilborn, Rachel Hussherr, Charlotte Irish, Fabien Joux, Lauren Kipp, Audrey Laberge-Carignan, Hugues Lantuit, Edouard Leymarie, Antonio Mannino, Juliette Maury, Paul Overduin, Laurent Oziel, Colin Stedmon, Crystal Thomas, Lucas Tisserand, Jean-Éric Tremblay, Jorien Vonk, Dustin Whalen, and Marcel Babin
Earth Syst. Sci. Data, 15, 1617–1653, https://doi.org/10.5194/essd-15-1617-2023, https://doi.org/10.5194/essd-15-1617-2023, 2023
Short summary
Short summary
Permafrost thaw in the Mackenzie Delta region results in the release of organic matter into the coastal marine environment. What happens to this carbon-rich organic matter as it transits along the fresh to salty aquatic environments is still underdocumented. Four expeditions were conducted from April to September 2019 in the coastal area of the Beaufort Sea to study the fate of organic matter. This paper describes a rich set of data characterizing the composition and sources of organic matter.
Doerthe Tetzlaff, Aaron Smith, Lukas Kleine, Hauke Daempfling, Jonas Freymueller, and Chris Soulsby
Earth Syst. Sci. Data, 15, 1543–1554, https://doi.org/10.5194/essd-15-1543-2023, https://doi.org/10.5194/essd-15-1543-2023, 2023
Short summary
Short summary
We present a comprehensive set of ecohydrological hydrometric and stable water isotope data of 2 years of data. The data set is unique as the different compartments of the landscape were sampled and the effects of a prolonged drought (2018–2020) captured by a marked negative rainfall anomaly (the most severe regional drought of the 21st century). Thus, the data allow the drought effects on water storage, flux and age dynamics, and persistence of lowland landscapes to be investigated.
Jacopo Dari, Luca Brocca, Sara Modanesi, Christian Massari, Angelica Tarpanelli, Silvia Barbetta, Raphael Quast, Mariette Vreugdenhil, Vahid Freeman, Anaïs Barella-Ortiz, Pere Quintana-Seguí, David Bretreger, and Espen Volden
Earth Syst. Sci. Data, 15, 1555–1575, https://doi.org/10.5194/essd-15-1555-2023, https://doi.org/10.5194/essd-15-1555-2023, 2023
Short summary
Short summary
Irrigation is the main source of global freshwater consumption. Despite this, a detailed knowledge of irrigation dynamics (i.e., timing, extent of irrigated areas, and amounts of water used) are generally lacking worldwide. Satellites represent a useful tool to fill this knowledge gap and monitor irrigation water from space. In this study, three regional-scale and high-resolution (1 and 6 km) products of irrigation amounts estimated by inverting the satellite soil moisture signals are presented.
Aolin Jia, Shunlin Liang, Dongdong Wang, Lei Ma, Zhihao Wang, and Shuo Xu
Earth Syst. Sci. Data, 15, 869–895, https://doi.org/10.5194/essd-15-869-2023, https://doi.org/10.5194/essd-15-869-2023, 2023
Short summary
Short summary
Satellites are now producing multiple global land surface temperature (LST) products; however, they suffer from data gaps caused by cloud cover, seriously restricting the applications, and few products provide gap-free global hourly LST. We produced global hourly, 5 km, all-sky LST data from 2011 to 2021 using geostationary and polar-orbiting satellite data. Based on the assessment, it has high accuracy and can be used to estimate evapotranspiration, drought, etc.
Jianxin Zhang, Kai Liu, and Ming Wang
Earth Syst. Sci. Data, 15, 521–540, https://doi.org/10.5194/essd-15-521-2023, https://doi.org/10.5194/essd-15-521-2023, 2023
Short summary
Short summary
This study successfully extracted global flood days based on gravity satellite and precipitation data between 60° S and 60° N from 1 April 2002 to 31 August 2016. Our flood days data performed well compared with current available observations. This provides an important data foundation for analyzing the spatiotemporal distribution of large-scale floods and exploring the impact of ocean–atmosphere oscillations on floods in different regions.
Niek Jesse Speetjens, Gustaf Hugelius, Thomas Gumbricht, Hugues Lantuit, Wouter R. Berghuijs, Philip A. Pika, Amanda Poste, and Jorien E. Vonk
Earth Syst. Sci. Data, 15, 541–554, https://doi.org/10.5194/essd-15-541-2023, https://doi.org/10.5194/essd-15-541-2023, 2023
Short summary
Short summary
The Arctic is rapidly changing. Outside the Arctic, large databases changed how researchers look at river systems and land-to-ocean processes. We present the first integrated pan-ARctic CAtchments summary DatabasE (ARCADE) (> 40 000 river catchments draining into the Arctic Ocean). It incorporates information about the drainage area with 103 geospatial, environmental, climatic, and physiographic properties and covers small watersheds , which are especially subject to change, at a high resolution
Ionut Cristi Nicu, Letizia Elia, Lena Rubensdotter, Hakan Tanyaş, and Luigi Lombardo
Earth Syst. Sci. Data, 15, 447–464, https://doi.org/10.5194/essd-15-447-2023, https://doi.org/10.5194/essd-15-447-2023, 2023
Short summary
Short summary
Thaw slumps and thermo-erosion gullies are cryospheric hazards that are widely encountered in Nordenskiöld Land, the largest and most compact ice-free area of the Svalbard Archipelago. By statistically analysing the landscape characteristics of locations where these processes occurred, we can estimate where they may occur in the future. We mapped 562 thaw slumps and 908 thermo-erosion gullies and used them to create the first multi-hazard susceptibility map in a high-Arctic environment.
Youjiang Shen, Dedi Liu, Liguang Jiang, Karina Nielsen, Jiabo Yin, Jun Liu, and Peter Bauer-Gottwein
Earth Syst. Sci. Data, 14, 5671–5694, https://doi.org/10.5194/essd-14-5671-2022, https://doi.org/10.5194/essd-14-5671-2022, 2022
Short summary
Short summary
A data gap of 338 Chinese reservoirs with their surface water area (SWA), water surface elevation (WSE), and reservoir water storage change (RWSC) during 2010–2021. Validation against the in situ observations of 93 reservoirs indicates the relatively high accuracy and reliability of the datasets. The unique and novel remotely sensed dataset would benefit studies involving many aspects (e.g., hydrological models, water resources related studies, and more).
Ibrahim Demir, Zhongrun Xiang, Bekir Demiray, and Muhammed Sit
Earth Syst. Sci. Data, 14, 5605–5616, https://doi.org/10.5194/essd-14-5605-2022, https://doi.org/10.5194/essd-14-5605-2022, 2022
Short summary
Short summary
We provide a large benchmark dataset, WaterBench-Iowa, with valuable features for hydrological modeling. This dataset is designed to support cutting-edge deep learning studies for a more accurate streamflow forecast model. We also propose a modeling task for comparative model studies and provide sample models with codes and results as the benchmark for reference. This makes up for the lack of benchmarks in earth science research.
Pei Zhang, Donghai Zheng, Rogier van der Velde, Jun Wen, Yaoming Ma, Yijian Zeng, Xin Wang, Zuoliang Wang, Jiali Chen, and Zhongbo Su
Earth Syst. Sci. Data, 14, 5513–5542, https://doi.org/10.5194/essd-14-5513-2022, https://doi.org/10.5194/essd-14-5513-2022, 2022
Short summary
Short summary
Soil moisture and soil temperature (SMST) are important state variables for quantifying the heat–water exchange between land and atmosphere. Yet, long-term, regional-scale in situ SMST measurements at multiple depths are scarce on the Tibetan Plateau (TP). The presented dataset would be valuable for the evaluation and improvement of long-term satellite- and model-based SMST products on the TP, enhancing the understanding of TP hydrometeorological processes and their response to climate change.
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