Articles | Volume 14, issue 10
https://doi.org/10.5194/essd-14-4667-2022
© Author(s) 2022. 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-14-4667-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The Surface Water Chemistry (SWatCh) database: a standardized global database of water chemistry to facilitate large-sample hydrological research
Lobke Rotteveel
Sterling Hydrology Research Group, Dalhousie University, Halifax, B3H
4R2, Canada
Franz Heubach
Department of Mechanical Engineering, Dalhousie University, Halifax,
B3H 4R2, Canada
Shannon M. Sterling
CORRESPONDING AUTHOR
Sterling Hydrology Research Group, Dalhousie University, Halifax, B3H
4R2, Canada
Related authors
Shannon M. Sterling, Sarah MacLeod, Lobke Rotteveel, Kristin Hart, Thomas A. Clair, Edmund A. Halfyard, and Nicole L. O'Brien
Hydrol. Earth Syst. Sci., 24, 4763–4775, https://doi.org/10.5194/hess-24-4763-2020, https://doi.org/10.5194/hess-24-4763-2020, 2020
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Wild salmon numbers in Nova Scotia, Canada, have been plummeting in recent decades. In 2014, we launched an ionic aluminium monitoring program in Nova Scotia to see if this toxic element was a threat to salmon populations. We found that all 10 monitored rivers had ionic aluminium concentrations that exceeded the threshold for aquatic health. Our results demonstrate that elevated aluminium still threatens aquatic ecosystems and that delays in recovery from acid rain remains a critical issue.
Shannon M. Sterling, Sarah MacLeod, Lobke Rotteveel, Kristin Hart, Thomas A. Clair, Edmund A. Halfyard, and Nicole L. O'Brien
Hydrol. Earth Syst. Sci., 24, 4763–4775, https://doi.org/10.5194/hess-24-4763-2020, https://doi.org/10.5194/hess-24-4763-2020, 2020
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Wild salmon numbers in Nova Scotia, Canada, have been plummeting in recent decades. In 2014, we launched an ionic aluminium monitoring program in Nova Scotia to see if this toxic element was a threat to salmon populations. We found that all 10 monitored rivers had ionic aluminium concentrations that exceeded the threshold for aquatic health. Our results demonstrate that elevated aluminium still threatens aquatic ecosystems and that delays in recovery from acid rain remains a critical issue.
Adriaan J. Teuling, Emile A. G. de Badts, Femke A. Jansen, Richard Fuchs, Joost Buitink, Anne J. Hoek van Dijke, and Shannon M. Sterling
Hydrol. Earth Syst. Sci., 23, 3631–3652, https://doi.org/10.5194/hess-23-3631-2019, https://doi.org/10.5194/hess-23-3631-2019, 2019
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Over the past decades, changes in land use and climate over Europe have impacted the average flow of water flowing through rivers and reservoirs (the so-called
water yield). We quantify these changes using a simple but widely tested modelling approach constrained by observations of lysimeters across Europe. Results show that the contribution of land use to changes in water yield are of the same order as changes in climate, showing that impacts of land use changes cannot be neglected.
Ronny Meier, Edouard L. Davin, Quentin Lejeune, Mathias Hauser, Yan Li, Brecht Martens, Natalie M. Schultz, Shannon Sterling, and Wim Thiery
Biogeosciences, 15, 4731–4757, https://doi.org/10.5194/bg-15-4731-2018, https://doi.org/10.5194/bg-15-4731-2018, 2018
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Deforestation not only releases carbon dioxide to the atmosphere but also affects local climatic conditions by altering energy fluxes at the land surface and thereby the local temperature. Here, we evaluate the local impact of deforestation in a widely used land surface model. We find that the model reproduces the daytime warming effect of deforestation well. On the other hand, the warmer temperatures observed during night in forests are not present in this model.
S. M. Ambrose and S. M. Sterling
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-11-12103-2014, https://doi.org/10.5194/hessd-11-12103-2014, 2014
Revised manuscript has not been submitted
S. M. Sterling, C. Angelidis, M. Armstrong, K. M. Biagi, T. A. Clair, N. Jackson, and A. Breen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-11-10117-2014, https://doi.org/10.5194/hessd-11-10117-2014, 2014
Revised manuscript has not been submitted
Related subject area
Domain: ESSD – Land | Subject: Hydrology
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
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
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
A gridded dataset of consumptive water footprints, evaporation, transpiration, and associated benchmarks related to crop production in China during 2000–2018
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
Lake surface temperature retrieved from Landsat satellite series (1984 to 2021) for the North Slave Region
A global 5 km monthly potential evapotranspiration dataset (1982–2015) estimated by the Shuttleworth-Wallace model
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
OpenMRG: Open data from Microwave links, Radar, and Gauges for rainfall quantification in Gothenburg, Sweden
A 1 km daily soil moisture dataset over China using in situ measurement and machine learning
Downscaled hyper-resolution (400 m) gridded datasets of daily precipitation and temperature (2008–2019) for the East–Taylor subbasin (western United States)
HRLT: a high-resolution (1 d, 1 km) and long-term (1961–2019) gridded dataset for surface temperature and precipitation across China
Hydrography90m: a new high-resolution global hydrographic dataset
GLOBMAP SWF: a global annual surface water cover frequency dataset during 2000–2020
Streamflow data availability in Europe: a detailed dataset of interpolated flow-duration curves
High-resolution streamflow and weather data (2013–2019) for seven small coastal watersheds in the northeast Pacific coastal temperate rainforest, Canada
A 500-year annual runoff reconstruction for 14 selected European catchments
A comprehensive geospatial database of nearly 100 000 reservoirs in China
Stable water isotope monitoring network of different water bodies in Shiyang River basin, a typical arid river in China
A dataset of lake-catchment characteristics for the Tibetan Plateau
QUADICA: water QUAlity, DIscharge and Catchment Attributes for large-sample studies in Germany
A global terrestrial evapotranspiration product based on the three-temperature model with fewer input parameters and no calibration requirement
A new snow depth data set over northern China derived using GNSS interferometric reflectometry from a continuously operating network (GSnow-CHINA v1.0, 2013–2022)
Microwave radiometry experiment for snow in Altay, China: time series of in situ data for electromagnetic and physical features of snowpack
An integrated dataset of daily lake surface water temperature over the Tibetan Plateau
Emma L. Robinson, Matthew J. Brown, Alison L. Kay, Rosanna A. Lane, Rhian Chapman, Victoria A. Bell, and Eleanor M. Blyth
Earth Syst. Sci. Data, 15, 4433–4461, https://doi.org/10.5194/essd-15-4433-2023, https://doi.org/10.5194/essd-15-4433-2023, 2023
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This work presents two new Penman–Monteith potential evaporation datasets for the UK, calculated with the same methodology applied to historical climate data (Hydro-PE HadUK-Grid) and an ensemble of future climate projections (Hydro-PE UKCP18 RCM). Both include an optional correction for evaporation of rain that lands on the surface of vegetation. The historical data are consistent with existing PE datasets, and the future projections include effects of rising atmospheric CO2 on vegetation.
Xinyu Chen, Liguang Jiang, Yuning Luo, and Junguo Liu
Earth Syst. Sci. Data, 15, 4463–4479, https://doi.org/10.5194/essd-15-4463-2023, https://doi.org/10.5194/essd-15-4463-2023, 2023
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River flow is experiencing changes under the impacts of climate change and human activities. For example, flood events are occurring more often and are more destructive in many places worldwide. To deal with such issues, hydrologists endeavor to understand the features of extreme events as well as other hydrological changes. One key approach is analyzing flow characteristics, represented by hydrological indices. Building such a comprehensive global large-sample dataset is essential.
Tobias L. Hohenbrink, Conrad Jackisch, Wolfgang Durner, Kai Germer, Sascha C. Iden, Janis Kreiselmeier, Frederic Leuther, Johanna C. Metzger, Mahyar Naseri, and Andre Peters
Earth Syst. Sci. Data, 15, 4417–4432, https://doi.org/10.5194/essd-15-4417-2023, https://doi.org/10.5194/essd-15-4417-2023, 2023
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The article describes a collection of 572 data sets of soil water retention and unsaturated hydraulic conductivity data measured with state-of-the-art laboratory methods. Furthermore, the data collection contains basic soil properties such as soil texture and organic carbon content. We expect that the data will be useful for various important purposes, for example, the development of soil hydraulic property models and related pedotransfer functions.
Sebastien Klotz, Caroline Le Bouteiller, Nicolle Mathys, Firmin Fontaine, Xavier Ravanat, Jean-Emmanuel Olivier, Frédéric Liébault, Hugo Jantzi, Patrick Coulmeau, Didier Richard, Jean-Pierre Cambon, and Maurice Meunier
Earth Syst. Sci. Data, 15, 4371–4388, https://doi.org/10.5194/essd-15-4371-2023, https://doi.org/10.5194/essd-15-4371-2023, 2023
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Mountain badlands are places of intense erosion. They deliver large amounts of sediment to river systems, with consequences for hydropower sustainability, habitat quality and biodiversity, and flood hazard and river management. Draix-Bleone Observatory was created in 1983 to understand and quantify sediment delivery from such badland areas. Our paper describes how water and sediment fluxes have been monitored for almost 40 years in the small mountain catchments of this observatory.
Gopi Goteti
Earth Syst. Sci. Data, 15, 4389–4415, https://doi.org/10.5194/essd-15-4389-2023, https://doi.org/10.5194/essd-15-4389-2023, 2023
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Data on river gauging stations, river basin boundaries and river flow paths are critical for hydrological analyses, but existing data for India's river basins have limited availability and reliability. This work fills the gap by building a new dataset. Data for 645 stations in 15 basins of India were compiled and checked against global data sources; data were supplemented with additional information where needed. This dataset will serve as a reliable building block in hydrological analyses.
Md Safat Sikder, Jida Wang, George H. Allen, Yongwei Sheng, Dai Yamazaki, Chunqiao Song, Meng Ding, Jean-François Crétaux, and Tamlin M. Pavelsky
Earth Syst. Sci. Data, 15, 3483–3511, https://doi.org/10.5194/essd-15-3483-2023, https://doi.org/10.5194/essd-15-3483-2023, 2023
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We introduce Lake-TopoCat to reveal detailed lake hydrography information. It contains the location of lake outlets, the boundary of lake catchments, and a wide suite of attributes that depict detailed lake drainage relationships. It was constructed using lake boundaries from a global lake dataset, with the help of high-resolution hydrography data. This database may facilitate a variety of applications including water quality, agriculture and fisheries, and integrated lake–river modeling.
Maik Heistermann, Till Francke, Lena Scheiffele, Katya Dimitrova Petrova, Christian Budach, Martin Schrön, Benjamin Trost, Daniel Rasche, Andreas Güntner, Veronika Döpper, Michael Förster, Markus Köhli, Lisa Angermann, Nikolaos Antonoglou, Manuela Zude-Sasse, and Sascha E. Oswald
Earth Syst. Sci. Data, 15, 3243–3262, https://doi.org/10.5194/essd-15-3243-2023, https://doi.org/10.5194/essd-15-3243-2023, 2023
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Cosmic-ray neutron sensing (CRNS) allows for the non-invasive estimation of root-zone soil water content (SWC). The signal observed by a single CRNS sensor is influenced by the SWC in a radius of around 150 m (the footprint). Here, we have put together a cluster of eight CRNS sensors with overlapping footprints at an agricultural research site in north-east Germany. That way, we hope to represent spatial SWC heterogeneity instead of retrieving just one average SWC estimate from a single sensor.
Benjamin M. Kitambo, Fabrice Papa, Adrien Paris, Raphael M. Tshimanga, Frederic Frappart, Stephane Calmant, Omid Elmi, Ayan Santos Fleischmann, Melanie Becker, Mohammad J. Tourian, Rômulo A. Jucá Oliveira, and Sly Wongchuig
Earth Syst. Sci. Data, 15, 2957–2982, https://doi.org/10.5194/essd-15-2957-2023, https://doi.org/10.5194/essd-15-2957-2023, 2023
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The surface water storage (SWS) in the Congo River basin (CB) remains unknown. In this study, the multi-satellite and hypsometric curve approaches are used to estimate SWS in the CB over 1992–2015. The results provide monthly SWS characterized by strong variability with an annual mean amplitude of ~101 ± 23 km3. The evaluation of SWS against independent datasets performed well. This SWS dataset contributes to the better understanding of the Congo basin’s surface hydrology using remote sensing.
Natalie Lützow, Georg Veh, and Oliver Korup
Earth Syst. Sci. Data, 15, 2983–3000, https://doi.org/10.5194/essd-15-2983-2023, https://doi.org/10.5194/essd-15-2983-2023, 2023
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Glacier lake outburst floods (GLOFs) are a prominent natural hazard, and climate change may change their magnitude, frequency, and impacts. A global, literature-based GLOF inventory is introduced, entailing 3151 reported GLOFs. The reporting density varies temporally and regionally, with most cases occurring in NW North America. Since 1900, the number of yearly documented GLOFs has increased 6-fold. However, many GLOFs have incomplete records, and we call for a systematic reporting protocol.
Hanieh Seyedhashemi, Florentina Moatar, Jean-Philippe Vidal, and Dominique Thiéry
Earth Syst. Sci. Data, 15, 2827–2839, https://doi.org/10.5194/essd-15-2827-2023, https://doi.org/10.5194/essd-15-2827-2023, 2023
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This paper presents a past and future dataset of daily time series of discharge and stream temperature for 52 278 reaches over the Loire River basin (100 000 km2) in France, using thermal and hydrological models. Past data are provided over 1963–2019. Future data are available over the 1976–2100 period under different future climate change models (warm and wet, intermediate, and hot and dry) and scenarios (optimistic, intermediate, and pessimistic).
Youjiang Shen, Karina Nielsen, Menaka Revel, Dedi Liu, and Dai Yamazaki
Earth Syst. Sci. Data, 15, 2781–2808, https://doi.org/10.5194/essd-15-2781-2023, https://doi.org/10.5194/essd-15-2781-2023, 2023
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Res-CN fills a gap in a comprehensive and extensive dataset of reservoir-catchment characteristics for 3254 Chinese reservoirs with 512 catchment-level attributes and significantly enhanced spatial and temporal coverage (e.g., 67 % increase in water level and 225 % in storage anomaly) of time series of reservoir water level (data available for 20 % of 3254 reservoirs), water area (99 %), storage anomaly (92 %), and evaporation (98 %), supporting a wide range of applications and disciplines.
Hui Zheng, Wenli Fei, Zong-Liang Yang, Jiangfeng Wei, Long Zhao, Lingcheng Li, and Shu Wang
Earth Syst. Sci. Data, 15, 2755–2780, https://doi.org/10.5194/essd-15-2755-2023, https://doi.org/10.5194/essd-15-2755-2023, 2023
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An ensemble of evapotranspiration, runoff, and water storage is estimated here using the Noah-MP land surface model by perturbing model parameterization schemes. The data could be beneficial for monitoring and understanding the variability of water resources. Model developers could also gain insights by intercomparing the ensemble members.
Alison L. Kay, Victoria A. Bell, Helen N. Davies, Rosanna A. Lane, and Alison C. Rudd
Earth Syst. Sci. Data, 15, 2533–2546, https://doi.org/10.5194/essd-15-2533-2023, https://doi.org/10.5194/essd-15-2533-2023, 2023
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Climate change will affect the water cycle, including river flows and soil moisture. We have used both observational data (1980–2011) and the latest UK climate projections (1980–2080) to drive a national-scale grid-based hydrological model. The data, covering Great Britain and Northern Ireland, suggest potential future decreases in summer flows, low flows, and summer/autumn soil moisture, and possible future increases in winter and high flows. Society must plan how to adapt to such impacts.
Jamie Hannaford, Jonathan D. Mackay, Matthew Ascott, Victoria A. Bell, Thomas Chitson, Steven Cole, Christian Counsell, Mason Durant, Christopher R. Jackson, Alison L. Kay, Rosanna A. Lane, Majdi Mansour, Robert Moore, Simon Parry, Alison C. Rudd, Michael Simpson, Katie Facer-Childs, Stephen Turner, John R. Wallbank, Steven Wells, and Amy Wilcox
Earth Syst. Sci. Data, 15, 2391–2415, https://doi.org/10.5194/essd-15-2391-2023, https://doi.org/10.5194/essd-15-2391-2023, 2023
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The eFLaG dataset is a nationally consistent set of projections of future climate change impacts on hydrology. eFLaG uses the latest available UK climate projections (UKCP18) run through a series of computer simulation models which enable us to produce future projections of river flows, groundwater levels and groundwater recharge. These simulations are designed for use by water resource planners and managers but could also be used for a wide range of other purposes.
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
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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
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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
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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
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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
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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.
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
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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
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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.
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 Discuss., https://doi.org/10.5194/essd-2023-102, https://doi.org/10.5194/essd-2023-102, 2023
Revised manuscript accepted for ESSD
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The consumptive water footprint of crop production (WFCP) measures blue and green evapotranspiration of either irrigated or rainfed crops in time and space. A gridded monthly WFCP dataset for China is established. There are four improvements from existing datasets: (i) distinguishing water supply modes and irrigation techniques; (ii) distinguishing evaporation and transpiration; (iii) consisting of both total and unit WFCP, and (iv) providing benchmarks for unit WFCP by climatic zones.
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
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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
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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.
Gifty Attiah, Homa Kheyrollah Pour, and K. Andrea Scott
Earth Syst. Sci. Data, 15, 1329–1355, https://doi.org/10.5194/essd-15-1329-2023, https://doi.org/10.5194/essd-15-1329-2023, 2023
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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).
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 Discuss., https://doi.org/10.5194/essd-2023-38, https://doi.org/10.5194/essd-2023-38, 2023
Revised manuscript accepted for ESSD
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Based on various existing datasets, we comprehensively considered spatio-temporal differences in land surfaces and CO2 effects on plant stomatal resistance to parameterize the Shuttleworth-Wallace model, and 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.
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
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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
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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
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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
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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
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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
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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
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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.
Jafet C. M. Andersson, Jonas Olsson, Remco (C. Z.) van de Beek, and Jonas Hansryd
Earth Syst. Sci. Data, 14, 5411–5426, https://doi.org/10.5194/essd-14-5411-2022, https://doi.org/10.5194/essd-14-5411-2022, 2022
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This article presents data from three types of sensors for rain measurement, i.e. commercial microwave links (CMLs), gauges, and weather radar. Access to CML data is typically restricted, which limits research and applications. We openly share a large CML database (364 CMLs at 10 s resolution with true coordinates), along with 11 gauges and one radar composite. This opens up new opportunities to study CMLs, to benchmark algorithms, and to investigate how multiple sensors can best be combined.
Qingliang Li, Gaosong Shi, Wei Shangguan, Vahid Nourani, Jianduo Li, Lu Li, Feini Huang, Ye Zhang, Chunyan Wang, Dagang Wang, Jianxiu Qiu, Xingjie Lu, and Yongjiu Dai
Earth Syst. Sci. Data, 14, 5267–5286, https://doi.org/10.5194/essd-14-5267-2022, https://doi.org/10.5194/essd-14-5267-2022, 2022
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SMCI1.0 is a 1 km resolution dataset of daily soil moisture over China for 2000–2020 derived through machine learning trained with in situ measurements of 1789 stations, meteorological forcings, and land surface variables. It contains 10 soil layers with 10 cm intervals up to 100 cm deep. Evaluated by in situ data, the error (ubRMSE) ranges from 0.045 to 0.051, and the correlation (R) range is 0.866-0.893. Compared with ERA5-Land, SMAP-L4, and SoMo.ml, SIMI1.0 has higher accuracy and resolution.
Utkarsh Mital, Dipankar Dwivedi, James B. Brown, and Carl I. Steefel
Earth Syst. Sci. Data, 14, 4949–4966, https://doi.org/10.5194/essd-14-4949-2022, https://doi.org/10.5194/essd-14-4949-2022, 2022
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We present a new dataset that estimates small-scale variations in precipitation and temperature in mountainous terrain. The dataset is generated using a new machine learning framework that extracts relationships between climate and topography from existing coarse-scale datasets. The generated dataset is shown to capture small-scale variations more reliably than existing datasets and constitutes a valuable resource to model the water cycle in the mountains of Colorado, western United States.
Rongzhu Qin, Zeyu Zhao, Jia Xu, Jian-Sheng Ye, Feng-Min Li, and Feng Zhang
Earth Syst. Sci. Data, 14, 4793–4810, https://doi.org/10.5194/essd-14-4793-2022, https://doi.org/10.5194/essd-14-4793-2022, 2022
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This work presents a new high-resolution daily gridded maximum temperature, minimum temperature, and precipitation dataset for China (HRLT) with a spatial resolution of 1 × 1 km for the period 1961 to 2019. This dataset is valuable for crop modelers and climate change studies. We created the HRLT dataset using comprehensive statistical analyses, which included machine learning, the generalized additive model, and thin-plate splines.
Giuseppe Amatulli, Jaime Garcia Marquez, Tushar Sethi, Jens Kiesel, Afroditi Grigoropoulou, Maria M. Üblacker, Longzhu Q. Shen, and Sami Domisch
Earth Syst. Sci. Data, 14, 4525–4550, https://doi.org/10.5194/essd-14-4525-2022, https://doi.org/10.5194/essd-14-4525-2022, 2022
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Streams and rivers drive several processes in hydrology, geomorphology, geography, and ecology. A hydrographic network that accurately delineates streams and rivers, along with their topographic and topological properties, is needed for environmental applications. Using the MERIT Hydro Digital Elevation Model at 90 m resolution, we derived a globally seamless, standardised hydrographic network: Hydrography90m. The validation demonstrates improved accuracy compared to other datasets.
Yang Liu, Ronggao Liu, and Rong Shang
Earth Syst. Sci. Data, 14, 4505–4523, https://doi.org/10.5194/essd-14-4505-2022, https://doi.org/10.5194/essd-14-4505-2022, 2022
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Surface water has been changing significantly with high seasonal variation and abrupt change, making it hard to capture its interannual trend. Here we generated a global annual surface water cover frequency dataset during 2000–2020. The percentage of the time period when a pixel is covered by water in a year was estimated to describe the seasonal dynamics of surface water. This dataset can be used to analyze the interannual variation and change trend of highly dynamic inland water extent.
Simone Persiano, Alessio Pugliese, Alberto Aloe, Jon Olav Skøien, Attilio Castellarin, and Alberto Pistocchi
Earth Syst. Sci. Data, 14, 4435–4443, https://doi.org/10.5194/essd-14-4435-2022, https://doi.org/10.5194/essd-14-4435-2022, 2022
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For about 24000 river basins across Europe, this study provides a continuous representation of the streamflow regime in terms of empirical flow–duration curves (FDCs), which are key signatures of the hydrological behaviour of a catchment and are widely used for supporting decisions on water resource management as well as for assessing hydrologic change. FDCs at ungauged sites are estimated by means of a geostatistical procedure starting from data observed at about 3000 sites across Europe.
Maartje C. Korver, Emily Haughton, William C. Floyd, and Ian J. W. Giesbrecht
Earth Syst. Sci. Data, 14, 4231–4250, https://doi.org/10.5194/essd-14-4231-2022, https://doi.org/10.5194/essd-14-4231-2022, 2022
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The central coastline of the northeast Pacific coastal temperate rainforest contains many small streams that are important for the ecology of the region but are sparsely monitored. Here we present the first 5 years (2013–2019) of streamflow and weather data from seven small streams, using novel automated methods with estimations of measurement uncertainties. These observations support regional climate change monitoring and provide a scientific basis for environmental management decisions.
Sadaf Nasreen, Markéta Součková, Mijael Rodrigo Vargas Godoy, Ujjwal Singh, Yannis Markonis, Rohini Kumar, Oldrich Rakovec, and Martin Hanel
Earth Syst. Sci. Data, 14, 4035–4056, https://doi.org/10.5194/essd-14-4035-2022, https://doi.org/10.5194/essd-14-4035-2022, 2022
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This article presents a 500-year reconstructed annual runoff dataset for several European catchments. Several data-driven and hydrological models were used to derive the runoff series using reconstructed precipitation and temperature and a set of proxy data. The simulated runoff was validated using independent observed runoff data and documentary evidence. The validation revealed a good fit between the observed and reconstructed series for 14 catchments, which are available for further analysis.
Chunqiao Song, Chenyu Fan, Jingying Zhu, Jida Wang, Yongwei Sheng, Kai Liu, Tan Chen, Pengfei Zhan, Shuangxiao Luo, Chunyu Yuan, and Linghong Ke
Earth Syst. Sci. Data, 14, 4017–4034, https://doi.org/10.5194/essd-14-4017-2022, https://doi.org/10.5194/essd-14-4017-2022, 2022
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Over the last century, many dams/reservoirs have been built globally to meet various needs. The official statistics reported more than 98 000 dams/reservoirs in China. Despite the availability of several global-scale dam/reservoir databases, these databases have insufficient coverage in China. Therefore, we present the China Reservoir Dataset (CRD), which contains 97 435 reservoir polygons. The CRD reservoirs have a total area of 50 085.21 km2 and total storage of about 979.62 Gt.
Guofeng Zhu, Yuwei Liu, Peiji Shi, Wenxiong Jia, Junju Zhou, Yuanfeng Liu, Xinggang Ma, Hanxiong Pan, Yu Zhang, Zhiyuan Zhang, Zhigang Sun, Leilei Yong, and Kailiang Zhao
Earth Syst. Sci. Data, 14, 3773–3789, https://doi.org/10.5194/essd-14-3773-2022, https://doi.org/10.5194/essd-14-3773-2022, 2022
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From 2015 to 2020, we studied the Shiyang River basin, which has the highest utilization rate of water resources and the most prominent contradiction of water use, as a typical demonstration basin to establish and improve the isotope hydrology observation system, including river source region, oasis region, reservoir channel system region, oasis farmland region, ecological engineering construction region, and salinization process region.
Junzhi Liu, Pengcheng Fang, Yefeng Que, Liang-Jun Zhu, Zheng Duan, Guoan Tang, Pengfei Liu, Mukan Ji, and Yongqin Liu
Earth Syst. Sci. Data, 14, 3791–3805, https://doi.org/10.5194/essd-14-3791-2022, https://doi.org/10.5194/essd-14-3791-2022, 2022
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The management and conservation of lakes should be conducted in the context of catchments because lakes collect water and materials from their upstream catchments. This study constructed the first dataset of lake-catchment characteristics for 1525 lakes with an area from 0.2 to 4503 km2 on the Tibetan Plateau (TP), which provides exciting opportunities for lake studies in a spatially explicit context and promotes the development of landscape limnology on the TP.
Pia Ebeling, Rohini Kumar, Stefanie R. Lutz, Tam Nguyen, Fanny Sarrazin, Michael Weber, Olaf Büttner, Sabine Attinger, and Andreas Musolff
Earth Syst. Sci. Data, 14, 3715–3741, https://doi.org/10.5194/essd-14-3715-2022, https://doi.org/10.5194/essd-14-3715-2022, 2022
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Environmental data are critical for understanding and managing ecosystems, including the mitigation of water quality degradation. To increase data availability, we present the first large-sample water quality data set (QUADICA) of riverine macronutrient concentrations combined with water quantity, meteorological, and nutrient forcing data as well as catchment attributes. QUADICA covers 1386 German catchments to facilitate large-sample data-driven and modeling water quality assessments.
Leiyu Yu, Guo Yu Qiu, Chunhua Yan, Wenli Zhao, Zhendong Zou, Jinshan Ding, Longjun Qin, and Yujiu Xiong
Earth Syst. Sci. Data, 14, 3673–3693, https://doi.org/10.5194/essd-14-3673-2022, https://doi.org/10.5194/essd-14-3673-2022, 2022
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Accurate evapotranspiration (ET) estimation is essential to better understand Earth’s energy and water cycles. We estimate global terrestrial ET with a simple three-temperature model, without calibration and resistance parameterization requirements. Results show the ET estimates agree well with FLUXNET EC data, water balance ET, and other global ET products. The proposed daily and 0.25° ET product from 2001 to 2020 could provide large-scale information to support water-cycle-related studies.
Wei Wan, Jie Zhang, Liyun Dai, Hong Liang, Ting Yang, Baojian Liu, Zhizhou Guo, Heng Hu, and Limin Zhao
Earth Syst. Sci. Data, 14, 3549–3571, https://doi.org/10.5194/essd-14-3549-2022, https://doi.org/10.5194/essd-14-3549-2022, 2022
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The GSnow-CHINA data set is a snow depth data set developed using the two Global Navigation Satellite System station networks in China. It includes snow depth of 24, 12, and 2/3/6 h records, if possible, for 80 sites from 2013–2022 over northern China (25–55° N, 70–140° E). The footprint of the data set is ~ 1000 m2, and it can be used as an independent data source for validation purposes. It is also useful for regional climate research and other meteorological and hydrological applications.
Liyun Dai, Tao Che, Yang Zhang, Zhiguo Ren, Junlei Tan, Meerzhan Akynbekkyzy, Lin Xiao, Shengnan Zhou, Yuna Yan, Yan Liu, Hongyi Li, and Lifu Wang
Earth Syst. Sci. Data, 14, 3509–3530, https://doi.org/10.5194/essd-14-3509-2022, https://doi.org/10.5194/essd-14-3509-2022, 2022
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An Integrated Microwave Radiometry Campaign for Snow (IMCS) was conducted to collect ground-based passive microwave and optical remote-sensing data, snow pit and underlying soil data, and meteorological parameters. The dataset is unique in continuously providing electromagnetic and physical features of snowpack and environment. The dataset is expected to serve the evaluation and development of microwave radiative transfer models and snow process models, along with land surface process models.
Linan Guo, Hongxing Zheng, Yanhong Wu, Lanxin Fan, Mengxuan Wen, Junsheng Li, Fangfang Zhang, Liping Zhu, and Bing Zhang
Earth Syst. Sci. Data, 14, 3411–3422, https://doi.org/10.5194/essd-14-3411-2022, https://doi.org/10.5194/essd-14-3411-2022, 2022
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Lake surface water temperature (LSWT) is a critical physical property of the aquatic ecosystem and an indicator of climate change. By combining the strengths of satellites and models, we produced an integrated dataset on daily LSWT of 160 large lakes across the Tibetan Plateau (TP) for the period 1978–2017. LSWT increased significantly at a rate of 0.01–0.47° per 10 years. The dataset can contribute to research on water and heat balance changes and their ecological effects in the TP.
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Short summary
Data are needed to detect environmental problems, find their solutions, and identify knowledge gaps. Existing datasets have limited availability, sample size and/or frequency, or geographic scope. Here, we begin to address these limitations by collecting, cleaning, standardizing, and compiling the Surface Water Chemistry (SWatCh) database. SWatCh contains global surface water chemistry data for seven continents, 24 variables, 33 722 sites, and > 5 million samples collected between 1960 and 2022.
Data are needed to detect environmental problems, find their solutions, and identify knowledge...
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