Articles | Volume 13, issue 1
https://doi.org/10.5194/essd-13-1-2021
© Author(s) 2021. 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-13-1-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
05 Jan 2021
Data description paper |
| 05 Jan 2021
| 05 Jan 2021
An improved global remote-sensing-based surface soil moisture (RSSSM) dataset covering 2003–2018
Yongzhe Chen
State Key Laboratory of Urban and Regional Ecology, Research Center
for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085,
China
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049,
China
Xiaoming Feng
CORRESPONDING AUTHOR
State Key Laboratory of Urban and Regional Ecology, Research Center
for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085,
China
Bojie Fu
State Key Laboratory of Urban and Regional Ecology, Research Center
for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085,
China
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049,
China
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Soil freezing characteristic curves (SFCCs) relate the temperature of a soil to its ice content. SFCCs are needed in all physically based numerical models representing freezing and thawing soils, and they affect the movement of water in the subsurface, biogeochemical processes, soil mechanics, and ecology. Over a century of SFCC data exist, showing high variability in SFCCs based on soil texture, water content, and other factors. This repository summarizes all available SFCC data and metadata.
Hongru Sun, Zhenzhu Xu, and Bingrui Jia
Earth Syst. Sci. Data, 14, 2951–2961, https://doi.org/10.5194/essd-14-2951-2022, https://doi.org/10.5194/essd-14-2951-2022, 2022
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We compiled a new soil respiration (Rs) database of China's forests from 568 studies published up to 2018. The hourly, monthly, and annual samples were 8317, 5003, and 634, respectively. Most of the Rs data are shown in figures but were seldom exploited. For the first time, these data were digitized, accounting for 82 % of samples. Rs measured with common methods was selected (Li-6400, Li-8100, Li-8150, gas chromatography) and showed small differences of ~10 %. Bamboo had the highest Rs.
Yueli Chen, Xingwu Duan, Minghu Ding, Wei Qi, Ting Wei, Jianduo Li, and Yun Xie
Earth Syst. Sci. Data, 14, 2681–2695, https://doi.org/10.5194/essd-14-2681-2022, https://doi.org/10.5194/essd-14-2681-2022, 2022
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We reconstructed the first annual rainfall erosivity dataset for the Tibetan Plateau in China. The dataset covers 71 years in a 0.25° grid. The reanalysis precipitation data are employed in combination with the densely spaced in situ precipitation observations to generate the dataset. The dataset can supply fundamental data for quantifying the water erosion, and extend our knowledge of the rainfall-related hazard prediction on the Tibetan Plateau.
Alexander R. Groos, Janik Niederhauser, Bruk Lemma, Mekbib Fekadu, Wolfgang Zech, Falk Hänsel, Luise Wraase, Naki Akçar, and Heinz Veit
Earth Syst. Sci. Data, 14, 1043–1062, https://doi.org/10.5194/essd-14-1043-2022, https://doi.org/10.5194/essd-14-1043-2022, 2022
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Continuous observations and measurements from high elevations are necessary to monitor recent climate and environmental changes in the tropical mountains of eastern Africa, but meteorological and ground temperature data from above 3000 m are very rare. Here we present a comprehensive ground temperature monitoring network that has been established between 3493 and 4377 m in the Bale Mountains (Ethiopian Highlands) to monitor and study the afro-alpine climate and ecosystem in this region.
Tianyu Yue, Shuiqing Yin, Yun Xie, Bofu Yu, and Baoyuan Liu
Earth Syst. Sci. Data, 14, 665–682, https://doi.org/10.5194/essd-14-665-2022, https://doi.org/10.5194/essd-14-665-2022, 2022
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This paper provides new rainfall erosivity maps over mainland China based on hourly data from 2381 stations (available at https://doi.org/10.12275/bnu.clicia.rainfallerosivity.CN.001). The improvement from the previous work was also assessed. The improvement in the R-factor map occurred mainly in the western region, because of an increase in the number of stations and an increased temporal resolution from daily to hourly data.
David Olefeldt, Mikael Hovemyr, McKenzie A. Kuhn, David Bastviken, Theodore J. Bohn, John Connolly, Patrick Crill, Eugénie S. Euskirchen, Sarah A. Finkelstein, Hélène Genet, Guido Grosse, Lorna I. Harris, Liam Heffernan, Manuel Helbig, Gustaf Hugelius, Ryan Hutchins, Sari Juutinen, Mark J. Lara, Avni Malhotra, Kristen Manies, A. David McGuire, Susan M. Natali, Jonathan A. O'Donnell, Frans-Jan W. Parmentier, Aleksi Räsänen, Christina Schädel, Oliver Sonnentag, Maria Strack, Suzanne E. Tank, Claire Treat, Ruth K. Varner, Tarmo Virtanen, Rebecca K. Warren, and Jennifer D. Watts
Earth Syst. Sci. Data, 13, 5127–5149, https://doi.org/10.5194/essd-13-5127-2021, https://doi.org/10.5194/essd-13-5127-2021, 2021
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Wetlands, lakes, and rivers are important sources of the greenhouse gas methane to the atmosphere. To understand current and future methane emissions from northern regions, we need maps that show the extent and distribution of specific types of wetlands, lakes, and rivers. The Boreal–Arctic Wetland and Lake Dataset (BAWLD) provides maps of five wetland types, seven lake types, and three river types for northern regions and will improve our ability to predict future methane emissions.
Mengna Li, Yijian Zeng, Maciek W. Lubczynski, Jean Roy, Lianyu Yu, Hui Qian, Zhenyu Li, Jie Chen, Lei Han, Han Zheng, Tom Veldkamp, Jeroen M. Schoorl, Harrie-Jan Hendricks Franssen, Kai Hou, Qiying Zhang, Panpan Xu, Fan Li, Kai Lu, Yulin Li, and Zhongbo Su
Earth Syst. Sci. Data, 13, 4727–4757, https://doi.org/10.5194/essd-13-4727-2021, https://doi.org/10.5194/essd-13-4727-2021, 2021
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The Tibetan Plateau is the source of most of Asia's major rivers and has been called the Asian Water Tower. Due to its remoteness and the harsh environment, there is a lack of field survey data to investigate its hydrogeology. Borehole core lithology analysis, an altitude survey, soil thickness measurement, hydrogeological surveys, and hydrogeophysical surveys were conducted in the Maqu catchment within the Yellow River source region to improve a full–picture understanding of the water cycle.
Olivier Evrard, Caroline Chartin, J. Patrick Laceby, Yuichi Onda, Yoshifumi Wakiyama, Atsushi Nakao, Olivier Cerdan, Hugo Lepage, Hugo Jaegler, Rosalie Vandromme, Irène Lefèvre, and Philippe Bonté
Earth Syst. Sci. Data, 13, 2555–2560, https://doi.org/10.5194/essd-13-2555-2021, https://doi.org/10.5194/essd-13-2555-2021, 2021
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This dataset provides an original compilation of radioactive dose rates and artificial radionuclide activities in sediment deposited after floods in the rivers draining the main radioactive pollution plume in Fukushuma, Japan, between November
2011 and November 2020. In total, 782 sediment samples collected from 27 to 71 locations during 16 fieldwork campaigns were analysed. This provides a unique post-accidental dataset to better understand the environmental fate of radionuclides.
Qiang Zhang, Qiangqiang Yuan, Jie Li, Yuan Wang, Fujun Sun, and Liangpei Zhang
Earth Syst. Sci. Data, 13, 1385–1401, https://doi.org/10.5194/essd-13-1385-2021, https://doi.org/10.5194/essd-13-1385-2021, 2021
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Acquired daily soil moisture products are always incomplete globally (just about 30 %–80 % coverage ratio) due to the satellite orbit coverage and the limitations of soil moisture retrieval algorithms. To solve this inevitable problem, we generate long-term seamless global daily (SGD) AMSR2 soil moisture productions from 2013 to 2019. These productions are significant for full-coverage global daily hydrologic monitoring, rather than averaging as the monthly–quarter–yearly results.
Alexander Kmoch, Arno Kanal, Alar Astover, Ain Kull, Holger Virro, Aveliina Helm, Meelis Pärtel, Ivika Ostonen, and Evelyn Uuemaa
Earth Syst. Sci. Data, 13, 83–97, https://doi.org/10.5194/essd-13-83-2021, https://doi.org/10.5194/essd-13-83-2021, 2021
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The Soil Map of Estonia is the most detailed and information-rich dataset for soils in Estonia. But its information is not immediately usable for analyses or modelling. We derived parameters including soil layering, soil texture (clay, silt, and sand content), coarse fragments, and rock content and aggregated and predicted physical variables related to water and carbon cycles (bulk density, hydraulic conductivity, organic carbon content, available water capacity).
Xavier Morel, Birger Hansen, Christine Delire, Per Ambus, Mikhail Mastepanov, and Bertrand Decharme
Earth Syst. Sci. Data, 12, 2365–2380, https://doi.org/10.5194/essd-12-2365-2020, https://doi.org/10.5194/essd-12-2365-2020, 2020
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Nuuk fen site is a well-instrumented Greenlandic site where soil physical variables and greenhouse gas fluxes are monitored. But knowledge of soil carbon stocks and profiles is missing. This is a crucial shortcoming for a complete evaluation of models. For the first time we measured soil carbon and nitrogen density, profiles, and stocks in the Nuuk peatland. This new dataset can contribute to further develop joint modeling of greenhouse gas emissions and soil carbon in land-surface models.
Valery Kashparov, Sviatoslav Levchuk, Marina Zhurba, Valentyn Protsak, Nicholas A. Beresford, and Jacqueline S. Chaplow
Earth Syst. Sci. Data, 12, 1861–1875, https://doi.org/10.5194/essd-12-1861-2020, https://doi.org/10.5194/essd-12-1861-2020, 2020
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Sampling and analysis methodology and spatial radionuclide deposition data from the 60 km area around the Chernobyl Nuclear Power Plant, sampled in 1987 by the Ukrainian Institute of Agricultural Radiology, are useful for reconstructing doses to human and wildlife populations, answering the current lack of scientific consensus on the effects of radiation on wildlife in the Chernobyl Exclusion Zone and evaluating future management options for the Chernobyl-impacted areas of Ukraine and Belarus.
Kristen Manies, Mark Waldrop, and Jennifer Harden
Earth Syst. Sci. Data, 12, 1745–1757, https://doi.org/10.5194/essd-12-1745-2020, https://doi.org/10.5194/essd-12-1745-2020, 2020
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Boreal ecosystems are unique in that their mineral soil is covered by what can be quite thick layers of organic soil. Layers within this organic soil have different bulk densities, carbon composition, and nitrogen composition. We summarize these properties by soil layer and examine if and how they are affected by soil drainage and stand age. These values can be used to initialize and validate models as well as gap fill when these important soil properties are not measured.
Conrad Jackisch, Kai Germer, Thomas Graeff, Ines Andrä, Katrin Schulz, Marcus Schiedung, Jaqueline Haller-Jans, Jonas Schneider, Julia Jaquemotte, Philipp Helmer, Leander Lotz, Andreas Bauer, Irene Hahn, Martin Šanda, Monika Kumpan, Johann Dorner, Gerrit de Rooij, Stefan Wessel-Bothe, Lorenz Kottmann, Siegfried Schittenhelm, and Wolfgang Durner
Earth Syst. Sci. Data, 12, 683–697, https://doi.org/10.5194/essd-12-683-2020, https://doi.org/10.5194/essd-12-683-2020, 2020
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Soil water content and matric potential are central hydrological state variables. A large variety of automated probes and sensor systems for field monitoring exist. In a field experiment under idealised conditions we compared 15 systems for soil moisture and 14 systems for matric potential. The individual records of one system agree well with the others. Most records are also plausible. However, the absolute values of the different measuring systems span a very large range of possible truths.
Marco Pfeiffer, José Padarian, Rodrigo Osorio, Nelson Bustamante, Guillermo Federico Olmedo, Mario Guevara, Felipe Aburto, Francisco Albornoz, Monica Antilén, Elías Araya, Eduardo Arellano, Maialen Barret, Juan Barrera, Pascal Boeckx, Margarita Briceño, Sally Bunning, Lea Cabrol, Manuel Casanova, Pablo Cornejo, Fabio Corradini, Gustavo Curaqueo, Sebastian Doetterl, Paola Duran, Mauricio Escudey, Angelina Espinoza, Samuel Francke, Juan Pablo Fuentes, Marcel Fuentes, Gonzalo Gajardo, Rafael García, Audrey Gallaud, Mauricio Galleguillos, Andrés Gomez, Marcela Hidalgo, Jorge Ivelic-Sáez, Lwando Mashalaba, Francisco Matus, Francisco Meza, Maria de la Luz Mora, Jorge Mora, Cristina Muñoz, Pablo Norambuena, Carolina Olivera, Carlos Ovalle, Marcelo Panichini, Aníbal Pauchard, Jorge F. Pérez-Quezada, Sergio Radic, José Ramirez, Nicolás Riveras, Germán Ruiz, Osvaldo Salazar, Iván Salgado, Oscar Seguel, Maria Sepúlveda, Carlos Sierra, Yasna Tapia, Francisco Tapia, Balfredo Toledo, José Miguel Torrico, Susana Valle, Ronald Vargas, Michael Wolff, and Erick Zagal
Earth Syst. Sci. Data, 12, 457–468, https://doi.org/10.5194/essd-12-457-2020, https://doi.org/10.5194/essd-12-457-2020, 2020
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The CHLSOC database is the biggest soil organic carbon (SOC) database that has been compiled for Chile yet, comprising 13 612 data points. This database is the product of the compilation of numerous sources including unpublished and difficult-to-access data, allowing us to fill numerous spatial gaps where no SOC estimates were publicly available before. The values of SOC compiled in CHLSOC have a wide range, reflecting the variety of ecosystems that exists in Chile.
Corey R. Lawrence, Jeffrey Beem-Miller, Alison M. Hoyt, Grey Monroe, Carlos A. Sierra, Shane Stoner, Katherine Heckman, Joseph C. Blankinship, Susan E. Crow, Gavin McNicol, Susan Trumbore, Paul A. Levine, Olga Vindušková, Katherine Todd-Brown, Craig Rasmussen, Caitlin E. Hicks Pries, Christina Schädel, Karis McFarlane, Sebastian Doetterl, Christine Hatté, Yujie He, Claire Treat, Jennifer W. Harden, Margaret S. Torn, Cristian Estop-Aragonés, Asmeret Asefaw Berhe, Marco Keiluweit, Ágatha Della Rosa Kuhnen, Erika Marin-Spiotta, Alain F. Plante, Aaron Thompson, Zheng Shi, Joshua P. Schimel, Lydia J. S. Vaughn, Sophie F. von Fromm, and Rota Wagai
Earth Syst. Sci. Data, 12, 61–76, https://doi.org/10.5194/essd-12-61-2020, https://doi.org/10.5194/essd-12-61-2020, 2020
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The International Soil Radiocarbon Database (ISRaD) is an an open-source archive of soil data focused on datasets including radiocarbon measurements. ISRaD includes data from bulk or
whole soils, distinct soil carbon pools isolated in the laboratory by a variety of soil fractionation methods, samples of soil gas or water collected interstitially from within an intact soil profile, CO2 gas isolated from laboratory soil incubations, and fluxes collected in situ from a soil surface.
Hong Zhao, Yijian Zeng, Shaoning Lv, and Zhongbo Su
Earth Syst. Sci. Data, 10, 1031–1061, https://doi.org/10.5194/essd-10-1031-2018, https://doi.org/10.5194/essd-10-1031-2018, 2018
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The Tibet-Obs soil properties dataset was compiled based on in situ and laboratory measurements of soil profiles across three climate zones on the Tibetan Plateau. The appropriate parameterization schemes of soil hydraulic and thermal properties were discussed for their applicability in land surface modeling. The uncertainties of existing soil datasets were evaluated. This paper contributes to land surface modeling and hydro-climatology communities for their studies of the third pole region.
Valery Kashparov, Sviatoslav Levchuk, Marina Zhurba, Valentyn Protsak, Yuri Khomutinin, Nicholas A. Beresford, and Jacqueline S. Chaplow
Earth Syst. Sci. Data, 10, 339–353, https://doi.org/10.5194/essd-10-339-2018, https://doi.org/10.5194/essd-10-339-2018, 2018
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Spatial datasets of radionuclide contamination in the Ukrainian Chernobyl Exclusion Zone describe data from analysis of samples collected by the Ukrainian Institute of Agricultural Radiology after the Chernobyl nuclear accident between May 1986 and 2014 at sites inside the Chernobyl Exclusion Zone and other areas of interest. The data and supporting documentation are freely available from the Environmental Information Data Centre: https://doi.org/10.5285/782ec845-2135-4698-8881-b38823e533bf.
Carsten Montzka, Michael Herbst, Lutz Weihermüller, Anne Verhoef, and Harry Vereecken
Earth Syst. Sci. Data, 9, 529–543, https://doi.org/10.5194/essd-9-529-2017, https://doi.org/10.5194/essd-9-529-2017, 2017
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Global climate models require adequate parameterization of soil hydraulic properties, but typical resampling to the model grid introduces uncertainties. Here we present a method to scale hydraulic parameters to individual model grids and provide a global data set that overcomes the problems. It preserves the information of sub-grid variability of the water retention curve by deriving local scaling parameters that enables modellers to perturb hydraulic parameters for model ensemble generation.
Niels H. Batjes, Eloi Ribeiro, Ad van Oostrum, Johan Leenaars, Tom Hengl, and Jorge Mendes de Jesus
Earth Syst. Sci. Data, 9, 1–14, https://doi.org/10.5194/essd-9-1-2017, https://doi.org/10.5194/essd-9-1-2017, 2017
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Soil is an important provider of ecosystem services. Yet this natural resource is being threatened. Professionals, scientists, and decision makers require quality-assessed soil data to address issues such as food security, land degradation, and climate change. Procedures for safeguarding, standardising, and subsequently serving of consistent soil data to underpin broad-scale mapping and modelling are described. The data are freely accessible at doi:10.17027/isric-wdcsoils.20160003.
J. S. Chaplow, N. A. Beresford, and C. L. Barnett
Earth Syst. Sci. Data, 7, 215–221, https://doi.org/10.5194/essd-7-215-2015, https://doi.org/10.5194/essd-7-215-2015, 2015
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The data set ‘Post Chernobyl surveys of radiocaesium in soil, vegetation, wildlife and fungi in Great Britain’ was developed to enable data collected by the Natural Environment Research Council after the Chernobyl accident to be made publicly available. Data for samples collected between May 1986 (immediately after Chernobyl) to spring 1997 are freely available for non-commercial use under Open Government Licence terms and conditions. doi: 10.5285/d0a6a8bf-68f0-4935-8b43-4e597c3bf251.
G. Hugelius, J. G. Bockheim, P. Camill, B. Elberling, G. Grosse, J. W. Harden, K. Johnson, T. Jorgenson, C. D. Koven, P. Kuhry, G. Michaelson, U. Mishra, J. Palmtag, C.-L. Ping, J. O'Donnell, L. Schirrmeister, E. A. G. Schuur, Y. Sheng, L. C. Smith, J. Strauss, and Z. Yu
Earth Syst. Sci. Data, 5, 393–402, https://doi.org/10.5194/essd-5-393-2013, https://doi.org/10.5194/essd-5-393-2013, 2013
G. Hugelius, C. Tarnocai, G. Broll, J. G. Canadell, P. Kuhry, and D. K. Swanson
Earth Syst. Sci. Data, 5, 3–13, https://doi.org/10.5194/essd-5-3-2013, https://doi.org/10.5194/essd-5-3-2013, 2013
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Short summary
Soil moisture can greatly influence the ecosystem but is hard to monitor at the global scale. By calibrating and combining 11 different products derived from satellite observation, we developed a new global surface soil moisture dataset spanning from 2003 to 2018 with high accuracy. Using this new dataset, not only can the global long-term trends be derived, but also the seasonal variation and spatial distribution of surface soil moisture at different latitudes can be better studied.
Soil moisture can greatly influence the ecosystem but is hard to monitor at the global scale. By...
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