Articles | Volume 12, issue 3
https://doi.org/10.5194/essd-12-1789-2020
© Author(s) 2020. 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-12-1789-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
17 Aug 2020
Data description paper |
| 17 Aug 2020
| 17 Aug 2020
An integration of gauge, satellite, and reanalysis precipitation datasets for the largest river basin of the Tibetan Plateau
Yuanwei Wang
Key Laboratory of Tibetan Environmental Changes and Land Surface
Processes,
Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing,
China
University of Chinese Academy of Sciences, Beijing, China
Key Laboratory of Tibetan Environmental Changes and Land Surface
Processes,
Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing,
China
CAS Center for Excellence in Tibetan Plateau Earth Sciences,
Beijing, China
University of Chinese Academy of Sciences, Beijing, China
Xiuping Li
Key Laboratory of Tibetan Environmental Changes and Land Surface
Processes,
Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing,
China
CAS Center for Excellence in Tibetan Plateau Earth Sciences,
Beijing, China
Jing Zhou
Key Laboratory of Tibetan Environmental Changes and Land Surface
Processes,
Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing,
China
Zhidan Hu
Information Center, Ministry of Water Resources, Beijing, China
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Hao Li, Baoying Shan, Liu Liu, Lei Wang, Akash Koppa, Feng Zhong, Dongfeng Li, Xuanxuan Wang, Wenfeng Liu, Xiuping Li, and Zongxue Xu
Hydrol. Earth Syst. Sci., 26, 6399–6412, https://doi.org/10.5194/hess-26-6399-2022, https://doi.org/10.5194/hess-26-6399-2022, 2022
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This study examines changes in water yield by determining turning points in the direction of yield changes and highlights that regime shifts in historical water yield occurred in the Upper Brahmaputra River basin, both the climate and cryosphere affect the magnitude of water yield increases, climate determined the declining trends in water yield, and meltwater has the potential to alleviate the water shortage. A repository for all source files is made available.
Chenhao Chai, Lei Wang, Deliang Chen, Jing Zhou, Hu Liu, Jingtian Zhang, Yuanwei Wang, Tao Chen, and Ruishun Liu
Hydrol. Earth Syst. Sci., 26, 4657–4683, https://doi.org/10.5194/hess-26-4657-2022, https://doi.org/10.5194/hess-26-4657-2022, 2022
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This work quantifies future snow changes and their impacts on hydrology in the upper Salween River (USR) under SSP126 and SSP585 using a cryosphere–hydrology model. Future warm–wet climate is not conducive to the development of snow. The rain–snow-dominated pattern of runoff will shift to a rain-dominated pattern after the 2040s under SSP585 but is unchanged under SSP126. The findings improve our understanding of cryosphere–hydrology processes and can assist water resource management in the USR.
Xiaowan Liu, Zongxue Xu, Hong Yang, Xiuping Li, and Dingzhi Peng
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2020-71, https://doi.org/10.5194/essd-2020-71, 2020
Revised manuscript not accepted
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The retreat of glaciers over the QTP is intensifying. To understand changes in glaciers, the two inventories (RGI 4.0 and GIC-Ⅱ) provide potential, but glacier volumes are not convincing. The study recalculated and compared glacier volumes in RGI 4.0 and GIC-Ⅱ for the QTP. The results indicate the slope-dependent algorithm performs better than area-volume-based equations. The northern QTP has a larger degree of fragmentation. An obvious offset of glacier volumes in different aspects is observed.
M. Shrestha, L. Wang, T. Koike, H. Tsutsui, Y. Xue, and Y. Hirabayashi
Hydrol. Earth Syst. Sci., 18, 747–761, https://doi.org/10.5194/hess-18-747-2014, https://doi.org/10.5194/hess-18-747-2014, 2014
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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 high-frequency, long-term data set of hydrology and sediment yield: The alpine badland catchments of Draix-Bléone Observatory
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
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
The Surface Water Chemistry (SWatCh) database: a standardized global database of water chemistry to facilitate large-sample hydrological research
Hydrography90m: a new high-resolution global hydrographic dataset
GLOBMAP SWF: a global annual surface water cover frequency dataset during 2000–2020
Hydro-PE: gridded datasets of historical and future Penman-Monteith potential evaporation for the United Kingdom
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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
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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.
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 Discuss., https://doi.org/10.5194/essd-2023-34, https://doi.org/10.5194/essd-2023-34, 2023
Revised manuscript accepted for ESSD
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Mountain badlands are places of intense erosion. They deliver large amounts of sediment to river systems, with consequences on hydropower sustainability, habitat quality and biodiversity, 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.
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).
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.
Lobke Rotteveel, Franz Heubach, and Shannon M. Sterling
Earth Syst. Sci. Data, 14, 4667–4680, https://doi.org/10.5194/essd-14-4667-2022, https://doi.org/10.5194/essd-14-4667-2022, 2022
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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.
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.
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 Discuss., https://doi.org/10.5194/essd-2022-288, https://doi.org/10.5194/essd-2022-288, 2022
Revised manuscript accepted for ESSD
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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.
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.
Andrew J. Wiebe and David L. Rudolph
Earth Syst. Sci. Data, 14, 3229–3248, https://doi.org/10.5194/essd-14-3229-2022, https://doi.org/10.5194/essd-14-3229-2022, 2022
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Multiple well fields in Waterloo Region, ON, Canada, draw water that enters the groundwater system from rainfall and snowmelt within the Alder Creek watershed. The rates of recharge of the underground aquifers and human impacts on streamflow are important issues that are typically addressed using computer models. Field observations such as groundwater and stream levels were collected between 2013 and 2018 to provide data for models. The data are available at https://doi.org/10.20383/101.0178
Pinzeng Rao, Yicheng Wang, Fang Wang, Yang Liu, Xiaoya Wang, and Zhu Wang
Earth Syst. Sci. Data, 14, 3053–3073, https://doi.org/10.5194/essd-14-3053-2022, https://doi.org/10.5194/essd-14-3053-2022, 2022
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It is urgent to obtain accurate soil moisture (SM) with high temporal and spatial resolution for areas affected by desertification in northern China. A combination of multiple machine learning methods, including multiple linear regression, support vector regression, artificial neural networks, random forest and extreme gradient boosting, has been applied to downscale the 36 km SMAP SM products and produce higher-spatial-resolution SM data based on related surface variables.
Emilio I. Mateo, Bryan G. Mark, Robert Å. Hellström, Michel Baraer, Jeffrey M. McKenzie, Thomas Condom, Alejo Cochachín Rapre, Gilber Gonzales, Joe Quijano Gómez, and Rolando Cesai Crúz Encarnación
Earth Syst. Sci. Data, 14, 2865–2882, https://doi.org/10.5194/essd-14-2865-2022, https://doi.org/10.5194/essd-14-2865-2022, 2022
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This article presents detailed and comprehensive hydrological and meteorological datasets collected over the past two decades throughout the Cordillera Blanca, Peru. With four weather stations and six streamflow gauges ranging from 3738 to 4750 m above sea level, this network displays a vertical breadth of data and enables detailed research of atmospheric and hydrological processes in a tropical high mountain region.
Laurie Boithias, Olivier Ribolzi, Emma Rochelle-Newall, Chanthanousone Thammahacksa, Paty Nakhle, Bounsamay Soulileuth, Anne Pando-Bahuon, Keooudone Latsachack, Norbert Silvera, Phabvilay Sounyafong, Khampaseuth Xayyathip, Rosalie Zimmermann, Sayaphet Rattanavong, Priscia Oliva, Thomas Pommier, Olivier Evrard, Sylvain Huon, Jean Causse, Thierry Henry-des-Tureaux, Oloth Sengtaheuanghoung, Nivong Sipaseuth, and Alain Pierret
Earth Syst. Sci. Data, 14, 2883–2894, https://doi.org/10.5194/essd-14-2883-2022, https://doi.org/10.5194/essd-14-2883-2022, 2022
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Fecal pathogens in surface waters may threaten human health, especially in developing countries. The Escherichia coli (E. coli) database is organized in three datasets and includes 1602 records from 31 sampling stations located within the Mekong River basin in Lao PDR. Data have been used to identify the drivers of E. coli dissemination across tropical catchments, including during floods. Data may be further used to interpret new variables or to map the health risk posed by fecal pathogens.
Cited articles
Ahrens, B.: Distance in spatial interpolation of daily rain gauge data, Hydrol. Earth Syst. Sci., 10, 197–208, https://doi.org/10.5194/hess-10-197-2006, 2006.
Ali, S., Tong, D., Xu, Z., Henchiri, M., Wilson, K., Shi, S., and Zhang, J.: Characterization of drought monitoring events through MODIS- and TRMM-based
DSI and TVDI over south Asia during 2001–2017, Environ. Sci. Pollut. R.,
26, 33568–33581, 2019.
Anders, A. M., Roe, G. H., Hallet, B., Montgomery, D. R., and Putkonen, J.:
Spatial patterns of precipitation and topography in the himalaya, Geol. Soc.
Am. Spec. Pap., 398, 39–53, 2006.
Angelidis, P., Maris, F., Kotsovinos, N., and Hrissanthou, V.: Computation
of Drought Index SPI with Alternative Distribution Functions, Water Resour.
Manag., 26, 2453–2473, 2012.
Bai, P. and Liu, X.: Evaluation of Five Satellite-Based Precipitation
Products in Two Gauge-Scarce Basins on the Tibetan Plateau, Remote Sensing,
10, 1316, https://doi.org/10.3390/rs10081316, 2018.
Bibi, S., Wang, L., Li, X., Zhang, X., and Chen, D.: Response of groundwater
storage and recharge in the Qaidam Basin (Tibetan Plateau) to climate
variations from 2002 to 2016, J. Geophys. Res.-Atmos., 124,
9918–9934, 2019.
Chen, Y., Yang, K., He, J., Qin, J., Shi, J., Du, J., and He, Q.: Improving
land surface temperature modeling for dry land of China, J. Geophys. Res.-Atmos., 116, D20104, https://doi.org/10.1029/2011JD015921, 2011.
Chen, Y., Yang, K., Qin, J., Zhao, L., Tang, W., and Han, M.: Evaluation of
AMSR-E retrievals and GLDAS simulations against observations of a soil
moisture network on the central Tibetan Plateau, J. Geophys. Res.-Atmos.,
118, 4466–4475, 2013.
Cuo, L., Li, N., Liu, Z., Ding, J., Liang, L., Zhang, Y., and Gong, T.:
Warming and human activities induced changes in the Yarlung Tsangpo basin of
the Tibetan plateau and their influences on streamflow, J. Hydrol., 25, 100625, https://doi.org/10.1016/j.ejrh.2019.100625, 2019.
Deng, M., Meng, X., Li, Z., Lyv, Y., Lei, H., Zhao, L., Zhao, S., Ge, J.,
and Jing, H.: Responses of soil moisture to regional climate change over the
Three Rivers Source Region on the Tibetan plateau, Int. J. Climatol., 40, 2403–2417,
https://doi.org/10.1002/joc.6341, 2019.
Fang, J., Yang, W., Luan, Y., Du, J., Lin, A., and Zhao, L.: Evaluation of
the TRMM 3B42 and GPM IMERG products for extreme precipitation analysis over
China, Atmos. Res., 223, 24–38, 2019.
Ferraro, R. R., Weng, F., Grody, N. C., and Zhao, L.: Precipitation
characteristics over land from the NOAA-15 AMSU sensor, Geophys. Res. Lett.,
27, 2669–2672, 2000.
Funk, C., Peterson, P., Landsfeld, M., Pedreros, D., Verdin, J., Shukla, S.,
Husak, G., Rowland, J., Harrison, L., Hoell, A., and Michaelsen, J.: The
climate hazards infrared precipitation with stations-a new environmental
record for monitoring extremes, Scientific Data, 2, 1–21, 2015.
Gelaro, R., McCarty, W., Suárez, M. J., Todling, R., Molod, A., Takacs,
L., Randles, C.A., Darmenova, A., Bosilovicha, M. G., Reichlea, R., Wargan,
K., Coya, L., Cullather, R., Draper, C., Akella, S., Buchard, V., Conaty,
A., Silva, A. M., Gu, W., Kima, G.-K., Koster, R., Lucchesi, R., Merkova, D.,
Nielsen, J. E., Partyka, G., Pawsona, S., Putman, W., Rienecker, M.,
Schubert, S. D., Sienkiewicz, M., and Zhao, B.: The modern-era retrospective
analysis for research and applications, version 2 (MERRA-2), J. Climate,
30, 5419–5454, 2017.
Guo, H., Chen, S., Bao, A., Behrangi, A., Hong, Y., Ndayisaba, F., Hu, J.,
and Stepanian, P. M.: Early assessment of integrated multi-satellite
retrievals for global precipitation measurement over China, Atmos. Res.,
176, 121–133, 2016.
Haiden, T. and Pistotnik, G.: Intensity-dependent parameterization of elevation effects in precipitation analysis, Adv. Geosci., 20, 33–38, https://doi.org/10.5194/adgeo-20-33-2009, 2009.
Hashemi, H., Fayne, J. V., Lakshmi, V., and Huffman, G. J.: Very high
resolution, altitude-corrected, TMPA-based monthly satellite precipitation
product over the CONUS, Scientific Data, 7, 74, https://doi.org/10.1038/s41597-020-0411-0, 2020.
He, J.: Development of surface meteorological dataset of China with high
temporal and spatial resolution, Master dissertation, Institute of Tibetan
Plateau Research, Chinese Academy of Science, 2010.
Huffman, G. J., Adler, R. F., Rudolf, B., Schneider, U., and Keehn, P. R.:
Global precipitation estimates based on a technique for combining
satellite-based estimates, rain gauge analysis, and NWP model precipitation
information, J. Climate, 8, 1284–1295, 1995.
Huffman, G. J., Bolvin, D. T., Nelkin, E. J., Wolff, D. B., Adler, R. F., Gu, G.,
Hong, Y., Bowman, K. P., and Stocker, E. F.: The TRMM multisatellite
precipitation analysis (TMPA): Quasi-global, multiyear, combined-sensor
precipitation estimates at fine scales, J. Hydrometeorol., 8, 38–55,
2007.
Joyce, R. J., Janowiak, J. E., Arkin, P. A., and Xie, P.: CMORPH: A method that
produces global precipitation estimates from passive microwave and infrared
data at high spatial and temporal resolution, J. Hydrometeorol., 5,
487–503, 2004.
Kato, H., Rodell, M., Beyrich, F., Cleugh, H., Gorsel, E. V., Liu, H., and
Meyers, T. P.: Sensitivity of land surface simulations to model physics, land
characteristics, and forcings, at four CEOP sites, J. Meteorol. Soc. Jpn.,
85, 187–204, 2007.
Kidd, C., Becker, A., Huffman, G. J., Muller, C. L., Joe, P.,
Skofronick-Jackson, G., and Kirschbaum, D. B.: So, how much of the Earth's
surface is covered by rain gauges?, B. Am. Meteorol. Soc., 98, 69–78,
2017.
Kumar, M. N., Murthy, C. S., Sai, M. V., and Roy, P. S.: On the use of
Standardized Precipitation Index (SPI) for drought intensity assessment,
Meteorol. Appl., 16, 381–389, 2009.
Li, X., Long, D., Han, Z., Scanlon, B. R., Sun, Z., Han, P., and Hou, A.:
Evapotranspiration Estimation for Tibetan Plateau Headwaters using Conjoint
Terrestrial and Atmospheric Water Balances and Multisource Remote Sensing,
Water Resour. Res., 55, 8608–8630, https://doi.org/10.1029/2019WR025196,
2019a.
Li, X., Long, D., Huang, Q., Han, P., Zhao, F., and Wada, Y.: High-temporal-resolution water level and storage change data sets for lakes on the Tibetan Plateau during 2000–2017 using multiple altimetric missions and Landsat-derived lake shoreline positions, Earth Syst. Sci. Data, 11, 1603–1627, https://doi.org/10.5194/essd-11-1603-2019, 2019b.
Li, Z., Yang, D., Gao, B., Jiao, Y., Hong, Y., and Xu, T.: Multiscale
hydrologic applications of the latest satellite precipitation products in
the Yangtze River Basin using a distributed hydrologic model, J.
Hydrometeorol., 16, 407–426, 2015.
Liu, X. and Chen, B.: Climatic warming in the Tibetan Plateau during recent
decades, Int. J. Climatol., 20, 1729–1742, 2000.
Lu, N., Trenberth, K. E., Qin, J., Yang, K., and Yao, L.: Detecting long-term
trends in precipitable water over the Tibetan Plateau by synthesis of
station and MODIS observations, J. Climate, 28, 1707–1722, 2015.
Ma, J., Ding, Y., Cheng, J. C. P., Jiang, F., and Wan, Z.: A temporal-spatial
interpolation and extrapolation method based on geographic Long Short-Term
Memory neural network for PM2.5, J. Clean. Prod., 237, 117729, https://doi.org/10.1016/j.jclepro.2019.117729, 2019.
Marquardt Collow, A. B., Bosilovich, M. G., and Koster, R. D.: Large-scale
influences on summertime extreme precipitation in the northeastern United
States, J. Hydrometeorol., 17, 3045–3061, 2016.
Mazzoleni, M., Brandimarte, L., and Amaranto, A.: Evaluating precipitation
datasets for large-scale distributed hydrological modelling, J. Hydrol.,
578, 124076, https://doi.org/10.1016/j.jhydrol.2019.124076, 2019.
Meng, J., Li, L., Hao, Z., Wang, J., and Shao, Q.: Suitability of TRMM
satellite rainfall in driving a distributed hydrological model in the source
region of Yellow River, J. Hydrol., 509, 320–332, 2014.
Miri, M., Masoudi, R., and Raziei, T.: Performance Evaluation of Three
Satellites-Based Precipitation Data Sets Over Iran, J. Indian Soc. Remot.,
47, 2073–2084, 2019.
Qi, W., Zhang, C., Fu, G., and Zhou H.: Global Land Data Assimilation System
data assessment using a distributed biosphere hydrological model, J.
Hydrol., 528, 652–667, 2015.
Qi, W., Zhang, C., Fu, G., Sweetapple, C., and Zhou, H.: Evaluation of global fine-resolution precipitation products and their uncertainty quantification in ensemble discharge simulations, Hydrol. Earth Syst. Sci., 20, 903–920, https://doi.org/10.5194/hess-20-903-2016, 2016.
Qi, W., Liu, J., and Chen, D.: Evaluations and improvements of GLDAS2.0 and
GLDAS2.1 forcing data's applicability for basin scale hydrological
simulations in the Tibetan Plateau, J. Geophys. Res.-Atmos., 123,
13128–13148, 2018.
Qiao, P., Li, P., Cheng, Y., Wei, W., Yang, S., Lei, M., and Chen, T.:
Comparison of common spatial interpolation methods for analyzing pollutant
spatial distributions at contaminated sites, Environ. Geochem. Hlth., 41,
2709–2730, 2019.
Reichle, R. H., Draper, C. S., Liu, Q., Girotto, M., Mahanama, S. P. P., Koster,
R. D., and De Lannoy, G. J. M.: Assessment of MERRA-2 land surface hydrology
estimates, J. Climate, 30, 2937–2960, 2017a.
Reichle, R. H., Liu, Q., Koster, R. D., Draper, C. S., Mahanama, S. P. P., and
Partyka, G. S.: Land surface precipitation in MERRA-2, J. Climate, 30,
1643–1664, 2017b.
Roca, R., Alexander, L. V., Potter, G., Bador, M., Jucá, R., Contractor, S., Bosilovich, M. G., and Cloché, S.: FROGS: a daily
Rodell, M., Houser, P. R., Jambor, U., Gottschalck, J., Mitchell, K., Meng,
C.-J., Arsenault, K., Cosgrove, B., Radakovich, J., Bosilovich, M., Entin,
J. K., Walker, J. P., Lohmann, D., and Toll, D.: The Global Land Data
Assimilation System, B. Am. Meteorol. Soc., 85, 381–394, 2004.
Ruhi, A., Messager, M. L., and Olden, J. D.: Tracking the pulse of the Earth's
fresh waters, Nature Sustainability, 1, 198–203, 2018.
Sang, Y., Singh, V. P., Gong, T., Xu, K., Sun, F., Liu, C., Liu, W., and
Chen, R.: Precipitation variability and response to changing climatic
condition in the Yarlung Tsangpo River basin, China, J. Geophys. Res.-Atmos., 121, 8820–8831, https://doi.org/10.1002/2016JD025370, 2016.
Sangani, M. F., Khojasteh, D. N., and Owens, G.: Dataset characteristics
influence the performance of different interpolation methods for soil
salinity spatial mapping, Environ. Monit. Assess., 191, 684, https://doi.org/10.1007/s10661-019-7844-y, 2019.
Savtchenko, A. K., Huffman, G., and Vollmer, B.: Assessment of precipitation
anomalies in California using TRMM and MERRA data, J. Geophys. Res.-Atmos.,
120, 8206–8215, 2015.
Semenov, M. A.: Simulation of extreme weather events by a stochastic weather
generator, Clim. Res., 35, 203–212, 2008.
Shen, Y., Xiong, A., Wang, Y., and Xie, P.: Performance of high-resolution
satellite precipitation products over China, J. Geophys. Res.-Atmos.,
115, D02114, https://doi.org/10.1029/2009JD012097, 2010.
Shen, Y., Zhao, P., Pan, Y., and Yu, J.: A high spatiotemporal
gauge-satellite merged precipitation analysis over China, J. Geophys. Res.-Atmos., 119, 3063–3075, 2014.
Shi, P., Bai, X., Kong, F., Fang, J., Gong, D., Zhou, T., Guo, Y., Liu, Y.,
Dong, W., Wei, Z., He, C., Yu, D., Wang, J., Ye, Q., Yu, R., and Chen, D.:
Urbanization and air quality as major drivers of altered spatiotemporal
patterns of heavy rainfall in China, Landscape Ecol., 32, 1723–1738,
2017.
Sloughter, J. M., Raftery, A. E., Gneiting, T., and Fraley, C.: Probabilistic
Quantitative Precipitation Forecasting Using Bayesian Model Averaging, Mon.
Weather Rev., 135, 3209–3220, 2007.
Su, F., Hong, Y., and Lettenmaier, D.P.: Evaluation of TRMM Multisatellite
Precipitation Analysis (TMPA) and its utility in hydrologic prediction in
the La Plata Basin, J. Hydrometeorol., 9, 622–640, 2008.
Sun, Q., Miao, C., Duan, Q., Ashouri, H., Soroosh, S., and Hsu, K.: A review
of global precipitation data sets: Data sources, estimation, and
intercomparisons, Rev. Geophys., 56, 79–107, 2018.
Tong, K., Su, F., Yang, D., and Hao, Z.: Evaluation of satellite
precipitation retrievals and their potential utilities in hydrologic
modeling over the Tibetan Plateau, J. Hydrol., 519, 423–437, 2014.
Verma, K. and Katpatal, Y. B.: Groundwater monitoring using GRACE and GLDAS
data after downscaling within basaltic aquifer system, Groundwater, 58, 143–151, https://doi.org/10.1111/gwat.12929, 2019.
Wang, F., Wang, L., Koike, T., Zhou, H., Yang, K., Wang, A., and Li, W.:
Evaluation and application of a fine-resolution global data set in a
semiarid mesoscale river basin with a distributed biosphere hydrological
model, J. Geophys. Res.-Atmos., 116, D21108, https://doi.org/10.1029/2011JD015990, 2011.
Wang, L. and Koike, T.: Comparison of a distributed biosphere hydrological
model with GBHM, Annual Journal of Hydraulic Engineering-JSCE, 53, 103–108,
2009a.
Wang, L., Koike, T., Yang, K., and Yeh, P. J.: Assessment of a distributed
biosphere hydrological model against streamflow and MODIS land surface
temperature in the upper Tone River Basin, J. Hydrol., 377, 21–34,
2009b.
Wang, L., Sun, L., Shrestha, M., Li, X., Liu, W., Zhou, J., Yang, K., Lu,
H., and Chen, D.: Improving snow process modeling with satellite-based
estimation of near-surface-air-temperature lapse rate, J. Geophys. Res.-Atmos., 121, 12005–12030, 2016.
Wang, L., Zhou, J., Qi, J., Sun, L., Yang, K., Tian, L., Lin, Y., Liu, W.,
Shrestha, M., Xue, Y., Koike, T., Ma, Y., Li, X., Chen, Y., Chen, D., Piao,
S., and Lu, H.: Development of a land surface model with coupled snow and
frozen soil physics, Water Resour. Res., 53, 5085–5103, 2017a.
Wang, S., Liu, J., Wang, J., Qiao, X., and Zhang, J.: Evaluation of GPM
IMERG V05B and TRMM 3B42V7 Precipitation products over high mountainous
tributaries in Lhasa with dense rain gauges, Remote Sensing, 11, 2080, https://doi.org/10.3390/rs11182080,
2019.
Wang, Y., Wang, L., Li, X., and Chen, D.: Temporal and spatial changes in
estimated near-surface air temperature lapse rates on Tibetan Plateau, Int.
J. Climatol., 38, 2907–2921, 2018.
Wang, Y., Chen, J., and Yang, D.: Bayesian assimilation of multiscale
precipitation data and sparse ground gauge observations in mountainous
areas, J. Hydrometeorol., 20, 1473–1494, 2019.
Wang, Y., Wang, L., Li, X., and Zhou, J.: High temporal and spatial
resolution precipitation data of Upper Brahmaputra River Basin (1981–2016),
Zenodo, https://doi.org/10.5281/zenodo.3711155, 2020.
Xia, T., Wang, Z., and Zheng, H.: Topography and data mining based methods
for improving satellite precipitation in mountainous areas of China,
Atmosphere, 6, 983–1005, 2015.
Xia, Y., Hao, Z., Shi, C., Li, Y., Meng, J., Xu T., Wu, X., and Zhang, B.:
Regional and Global Land Data Assimilation Systems: Innovations, Challenges,
and Prospects, J. Meteorol. Res., 33, 159–189, 2019.
Xu, R., Tian, F., Yang, L., Hu, H., Lu, H., and Hou, A.: Ground validation
of GPM IMERG and TRMM 3B42V7 rainfall products over southern Tibetan Plateau
based on a high-density rain gauge network, J. Geophys. Res.-Atmos.,
122, 910–924, 2017.
Xue, B., Wang, L., Yang, K., Tian, L., Qin, J., Chen, Y., Zhao, L., Ma, Y.,
Koike, T., Hu, Z., and Li, X.: Modeling the land surface water and energy
cycles of a mesoscale watershed in the central Tibetan Plateau during summer
with a distributed hydrological model, J. Geophys. Res.-Atmos., 118,
8857–8868, 2013.
Yang, K., He, J., Tang, W., Qin, J., and Chen, C. C. K.: On downward shortwave
and longwave radiations over high altitude regions: observation and modeling
in the Tibetan Plateau, Agr. Forest Meteorol., 150, 38–46, 2010.
Yang, K., Wu, H., Qin, J., Lin, C., Tang, W., and Chen, Y.: Recent climate
changes over the Tibetan Plateau and their impacts on energy and water
cycle: A review, Global Planet. Change, 112, 79–91, 2014.
Yi, X., Li, G., and Yin, Y.: Spatio-temporal variation of precipitation in
the Three-River Headwater Region from 1961 to 2010, J. Geogr. Sci., 23,
447–464, 2013.
Yong, B., Liu, D., Gourley, J. J., Tian, Y., Huffman, G. J., Ren, L., and
Hong, Y.: Global view of real-time TRMM multisatellite precipitation
analysis: Implications for its successor global precipitation measurement
mission, B. Am. Meteorol. Soc., 96, 283–296, 2015.
Zaitchik, B. F., Rodell, M., and Olivera, F.: Evaluation of the Global Land
Data Assimilation System using global river discharge data and a
source-to-sink routing scheme, Water Resour. Res., 46, W06507, https://doi.org/10.1029/2009WR007811, 2010.
Zhang, Q., Shi, P., Singh, V. P., Fan, K., and Huang, J.: Spatial downscaling
of TRMM-based precipitation data using vegetative response in Xinjiang,
China, Int. J. Climatol., 37, 3895–3909, 2017.
Zhou, J., Wang, L., Zhang, Y., Guo, Y., Li, X., and Liu, W.: Exploring the
water storage changes in the largest lake (Selin Co) over the Tibetan
Plateau during 2003–2012 from a basin-wide hydrological modeling, Water
Resour. Res., 51, 8060–8086, 2015a.
Zhou, Y., Lau, W. K. M., and Huffman, G. J.: Mapping TRMM TMPA into average
recurrence interval for monitoring extreme precipitation events, J. Appl.
Meteorol. Clim., 54, 979–995, 2015b.
Short summary
This article is to provide a better precipitation product for the largest river basin of the Tibetan Plateau, the upper Brahmaputra River basin, suitable for use in hydrological simulations and other climate change studies. We integrate gauge, satellite, and reanalysis precipitation datasets to generate a new dataset. The new product has been rigorously validated at various temporal and spatial scales with gauge precipitation observations as well as in cryosphere hydrological simulations.
This article is to provide a better precipitation product for the largest river basin of the...
