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.
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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Nannan An, Nan Lu, Weiliang Chen, Yongzhe Chen, Hao Shi, Fuzhong Wu, and Bojie Fu
Earth Syst. Sci. Data, 16, 1771–1810, https://doi.org/10.5194/essd-16-1771-2024, https://doi.org/10.5194/essd-16-1771-2024, 2024
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This study generated a spatially continuous plant functional trait dataset (~1 km) in China in combination with field observations, environmental variables and vegetation indices using machine learning methods. Results showed that wood density, leaf P concentration and specific leaf area showed good accuracy with an average R2 of higher than 0.45. This dataset could provide data support for development of Earth system models to predict vegetation distribution and ecosystem functions.
Yongzhe Chen, Xiaoming Feng, Bojie Fu, Haozhi Ma, Constantin M. Zohner, Thomas W. Crowther, Yuanyuan Huang, Xutong Wu, and Fangli Wei
Earth Syst. Sci. Data, 15, 897–910, https://doi.org/10.5194/essd-15-897-2023, https://doi.org/10.5194/essd-15-897-2023, 2023
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This study presented a long-term (2002–2021) above- and belowground biomass dataset for woody vegetation in China at 1 km resolution. It was produced by combining various types of remote sensing observations with adequate plot measurements. Over 2002–2021, China’s woody biomass increased at a high rate, especially in the central and southern parts. This dataset can be applied to evaluate forest carbon sinks across China and the efficiency of ecological restoration programs in China.
Nannan An, Nan Lu, Weiliang Chen, Yongzhe Chen, Hao Shi, Fuzhong Wu, and Bojie Fu
Earth Syst. Sci. Data, 16, 1771–1810, https://doi.org/10.5194/essd-16-1771-2024, https://doi.org/10.5194/essd-16-1771-2024, 2024
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This study generated a spatially continuous plant functional trait dataset (~1 km) in China in combination with field observations, environmental variables and vegetation indices using machine learning methods. Results showed that wood density, leaf P concentration and specific leaf area showed good accuracy with an average R2 of higher than 0.45. This dataset could provide data support for development of Earth system models to predict vegetation distribution and ecosystem functions.
Yongzhe Chen, Xiaoming Feng, Bojie Fu, Haozhi Ma, Constantin M. Zohner, Thomas W. Crowther, Yuanyuan Huang, Xutong Wu, and Fangli Wei
Earth Syst. Sci. Data, 15, 897–910, https://doi.org/10.5194/essd-15-897-2023, https://doi.org/10.5194/essd-15-897-2023, 2023
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This study presented a long-term (2002–2021) above- and belowground biomass dataset for woody vegetation in China at 1 km resolution. It was produced by combining various types of remote sensing observations with adequate plot measurements. Over 2002–2021, China’s woody biomass increased at a high rate, especially in the central and southern parts. This dataset can be applied to evaluate forest carbon sinks across China and the efficiency of ecological restoration programs in China.
Jinxia An, Guangyao Gao, Chuan Yuan, Juan Pinos, and Bojie Fu
Hydrol. Earth Syst. Sci., 26, 3885–3900, https://doi.org/10.5194/hess-26-3885-2022, https://doi.org/10.5194/hess-26-3885-2022, 2022
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An in-depth investigation was conducted of all rainfall-partitioning components at inter- and intra-event scales for two xerophytic shrubs. Inter-event rainfall partitioning amount and percentage depended more on rainfall amount, and rainfall intensity and duration controlled intra-event rainfall-partitioning variables. One shrub has larger branch angle, small branch and smaller canopy area to produce stemflow more efficiently, and the other has larger biomass to intercept more rainfall.
Shuang Song, Shuai Wang, Xutong Wu, Yongyuan Huang, and Bojie Fu
Hydrol. Earth Syst. Sci., 26, 2035–2044, https://doi.org/10.5194/hess-26-2035-2022, https://doi.org/10.5194/hess-26-2035-2022, 2022
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A reasonable assessment of the contribution of the water resources in a river basin to domestic crops supplies will be the first step in balancing the water–food nexus. Our results showed that although the Yellow River basin had reduced its virtual water outflow, its importance to crop production in China had been increasing when water footprint networks were considered. Our complexity-based approach provides a new perspective for understanding changes in a basin with a severe water shortage.
Bojie Fu, Xutong Wu, Zhuangzhuang Wang, Xilin Wu, and Shuai Wang
Earth Syst. Dynam., 13, 795–808, https://doi.org/10.5194/esd-13-795-2022, https://doi.org/10.5194/esd-13-795-2022, 2022
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To understand the dynamics of a coupled human and natural system (CHANS) and promote its sustainability, we propose a conceptual
pattern–process–service–sustainabilitycascade framework. The use of this framework is systematically illustrated by a review of CHANS research experience in China's Loess Plateau in terms of coupling landscape patterns and ecological processes, linking ecological processes to ecosystem services, and promoting social–ecological sustainability.
Maierdang Keyimu, Zongshan Li, Bojie Fu, Guohua Liu, Fanjiang Zeng, Weiliang Chen, Zexin Fan, Keyan Fang, Xiuchen Wu, and Xiaochun Wang
Clim. Past, 17, 2381–2392, https://doi.org/10.5194/cp-17-2381-2021, https://doi.org/10.5194/cp-17-2381-2021, 2021
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We created a residual tree-ring width chronology and reconstructed non-growth-season precipitation (NGSP) over the period spanning 1600–2005 in the southeastern Tibetan Plateau (SETP), China. Reconstruction model verification as well as similar variations of NGSP reconstruction and Palmer Drought Severity Index reconstructions from the surrounding region indicate the reliability of the present reconstruction. Our reconstruction is representative of NGSP variability of a large region in the SETP.
Xuejing Leng, Xiaoming Feng, Bojie Fu, and Yu Zhang
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-377, https://doi.org/10.5194/hess-2021-377, 2021
Manuscript not accepted for further review
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At present, there is a lack of time series of runoff generated by glacial regions in the world. In this paper, we quantified glacial runoff (including meltwater runoff and delayed runoff) in arid regions of China from 1961 to 2015 by using remote sensing datasets of glacier mass balance with high resolution. Glacier runoff is the water resource used by oases in arid regions of China. The long-term glacial runoff data can indicate the climate risk faced by different basins in arid regions.
Xianfeng Liu, Xiaoming Feng, Philippe Ciais, and Bojie Fu
Hydrol. Earth Syst. Sci., 24, 3663–3676, https://doi.org/10.5194/hess-24-3663-2020, https://doi.org/10.5194/hess-24-3663-2020, 2020
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Freshwater availability is crucial for sustainable development across the Asian and eastern European regions. Our results indicate widespread decline in terrestrial water storage (TWS) over the region during 2002–2017, primarily due to the intensive over-extraction of groundwater and warmth-induced surface water loss. The findings provide insights into changes in TWS and its components over the Asian and eastern European regions, where there is growing demand for food grains and water supplies.
Jianjun Zhang, Guangyao Gao, Bojie Fu, Cong Wang, Hoshin V. Gupta, Xiaoping Zhang, and Rui Li
Hydrol. Earth Syst. Sci., 24, 809–826, https://doi.org/10.5194/hess-24-809-2020, https://doi.org/10.5194/hess-24-809-2020, 2020
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We proposed an approach that integrates universal multifractals and a segmentation algorithm to precisely identify extreme precipitation (EP) and assess spatiotemporal EP variation over the Loess Plateau, using daily data. Our results explain how EP contributes to the widely distributed severe natural hazards. These findings are of great significance for ecological management in the Loess Plateau. Our approach is also helpful for spatiotemporal EP assessment at the regional scale.
Chuan Yuan, Guangyao Gao, Bojie Fu, Daming He, Xingwu Duan, and Xiaohua Wei
Hydrol. Earth Syst. Sci., 23, 4077–4095, https://doi.org/10.5194/hess-23-4077-2019, https://doi.org/10.5194/hess-23-4077-2019, 2019
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The stemflow dynamics of two xerophytic shrubs were investigated at the inter- and intra-event scales with high-temporal-resolution data in 54 rain events. Stemflow process was depicted by intensity, duration and time lags to rain events. Funneling ratio was calculated as the ratio of stemflow to rainfall intensities. Rainfall intensity and raindrop momentum controlled stemflow intensity and time lags. Influences of rainfall characteristics on stemflow variables showed temporal dependence.
Yuan Zhang, Xiaoming Feng, Xiaofeng Wang, and Bojie Fu
Hydrol. Earth Syst. Sci., 22, 1749–1766, https://doi.org/10.5194/hess-22-1749-2018, https://doi.org/10.5194/hess-22-1749-2018, 2018
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We characterized drought by linking climate anomalies with the change in precipitation–runoff relationships in China's Loess Plateau, where drought is of major concern for revegetation. Multi-year drought causes a change in the precipitation–runoff relationship in this water limited area. The drought causing a decrease in runoff ratio is vital to ecosystem management. The revegetation in the Loess Plateau should live with the spatially varied drought.
Guangyao Gao, Jianjun Zhang, Yu Liu, Zheng Ning, Bojie Fu, and Murugesu Sivapalan
Hydrol. Earth Syst. Sci., 21, 4363–4378, https://doi.org/10.5194/hess-21-4363-2017, https://doi.org/10.5194/hess-21-4363-2017, 2017
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This study extracted spatio-temporal patterns in the effects of LUCC and precipitation variability on sediment yield across the Loess Plateau during 1961–2011. The impacts of precipitation on sediment yield declined with time and the precipitation-sediment relationship showed a coherent spatial pattern. The sediment coefficient, representing the effect of LUCC, decreases linearly with fraction of area treated with erosion control measures and the slopes were highly variable among the catchments.
Yonggang Yang and Bojie Fu
Hydrol. Earth Syst. Sci., 21, 1757–1767, https://doi.org/10.5194/hess-21-1757-2017, https://doi.org/10.5194/hess-21-1757-2017, 2017
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This paper investigates soil water migration processes in the Loess Plateau using isotopes. The soil water migration is dominated by piston-type flow, but rarely preferential flow. Soil water from the soil lay (20–40 cm) contributed to 6–12% of plant xylem water, while soil water at the depth of 40–60 cm is the largest component (range from 60 to 66 %), soil water below 60 cm depth contributed 8–14 % to plant xylem water, and only 5–8 % is derived from precipitation.
Ji Zhou, Bojie Fu, Guangyao Gao, Yihe Lü, and Shuai Wang
Hydrol. Earth Syst. Sci., 21, 1491–1514, https://doi.org/10.5194/hess-21-1491-2017, https://doi.org/10.5194/hess-21-1491-2017, 2017
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We constructed an integrated probabilistic assessment to describe, simulate and evaluate the stochasticity of soil erosion in restoration vegetation in the Loess Plateau. We found that morphological structures in vegetation are the source of different stochasticities of soil erosion, and proved that the Poisson model is fit for predicting erosion stochasticity. This assessment could be an important complement to develop restoration strategies to improve understanding of stochasticity of erosion.
Chuan Yuan, Guangyao Gao, and Bojie Fu
Hydrol. Earth Syst. Sci., 21, 1421–1438, https://doi.org/10.5194/hess-21-1421-2017, https://doi.org/10.5194/hess-21-1421-2017, 2017
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We computed stemflow yield and efficiency, and analyzed the influential mechanism at smaller scales of leaf and raindrop. We found that precipitation was the most influential meteorological feature on stemflow. The smaller threshold precipitation to start stemflow and the more beneficial leaf traits might partly explain the larger and more efficient stemflow production. At defoliated period, the newly exposed stems replaced leaves to intercept raindrops and might really matter in stemflow yield.
N. Lu, J. Liski, R. Y. Chang, A. Akujärvi, X. Wu, T. T. Jin, Y. F. Wang, and B. J. Fu
Biogeosciences, 10, 7053–7063, https://doi.org/10.5194/bg-10-7053-2013, https://doi.org/10.5194/bg-10-7053-2013, 2013
J. Zhou, B. J. Fu, N. Lü, G. Y. Gao, Y. H. Lü, and S. Wang
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-10-10083-2013, https://doi.org/10.5194/hessd-10-10083-2013, 2013
Revised manuscript not accepted
Y. D. Xu, B. J. Fu, and C. S. He
Hydrol. Earth Syst. Sci., 17, 2185–2193, https://doi.org/10.5194/hess-17-2185-2013, https://doi.org/10.5194/hess-17-2185-2013, 2013
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European topsoil bulk density and organic carbon stock database (0–20 cm) using machine-learning-based pedotransfer functions
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Improving the Latin America and Caribbean Soil Information System (SISLAC) database enhances its usability and scalability
The patterns of soil nitrogen stocks and C : N stoichiometry under impervious surfaces in China
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Harmonized Soil Database of Ecuador (HESD): data from 2009 to 2015
ChinaCropSM1 km: a fine 1 km daily soil moisture dataset for dryland wheat and maize across China during 1993–2018
Colombian soil texture: building a spatial ensemble model
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A high spatial resolution soil carbon and nitrogen dataset for the northern permafrost region based on circumpolar land cover upscaling
A repository of measured soil freezing characteristic curves: 1921 to 2021
A compiled soil respiration dataset at different time scales for forest ecosystems across China from 2000 to 2018
New gridded dataset of rainfall erosivity (1950–2020) on the Tibetan Plateau
An hourly ground temperature dataset for 16 high-elevation sites (3493–4377 m a.s.l.) in the Bale Mountains, Ethiopia (2017–2020)
Rainfall erosivity mapping over mainland China based on high-density hourly rainfall records
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Radionuclide contamination in flood sediment deposits in the coastal rivers draining the main radioactive pollution plume of Fukushima Prefecture, Japan (2011–2020)
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EstSoil-EH: a high-resolution eco-hydrological modelling parameters dataset for Estonia
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Generalized models to estimate carbon and nitrogen stocks of organic soil horizons in Interior Alaska
Soil moisture and matric potential – an open field comparison of sensor systems
CHLSOC: the Chilean Soil Organic Carbon database, a multi-institutional collaborative effort
An open-source database for the synthesis of soil radiocarbon data: International Soil Radiocarbon Database (ISRaD) version 1.0
Analysis of soil hydraulic and thermal properties for land surface modeling over the Tibetan Plateau
Spatial datasets of radionuclide contamination in the Ukrainian Chernobyl Exclusion Zone
A global data set of soil hydraulic properties and sub-grid variability of soil water retention and hydraulic conductivity curves
WoSIS: providing standardised soil profile data for the world
Post-Chernobyl surveys of radiocaesium in soil, vegetation, wildlife and fungi in Great Britain
A new data set for estimating organic carbon storage to 3 m depth in soils of the northern circumpolar permafrost region
The Northern Circumpolar Soil Carbon Database: spatially distributed datasets of soil coverage and soil carbon storage in the northern permafrost regions
Anatol Helfenstein, Vera L. Mulder, Mirjam J. D. Hack-ten Broeke, Maarten van Doorn, Kees Teuling, Dennis J. J. Walvoort, and Gerard B. M. Heuvelink
Earth Syst. Sci. Data, 16, 2941–2970, https://doi.org/10.5194/essd-16-2941-2024, https://doi.org/10.5194/essd-16-2941-2024, 2024
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Earth system models and decision support systems greatly benefit from high-resolution soil information with quantified accuracy. Here we introduce BIS-4D, a statistical modeling platform that predicts nine essential soil properties and their uncertainties at 25 m resolution in surface 2 m across the Netherlands. Using machine learning informed by up to 856 000 soil observations coupled with 366 spatially explicit environmental variables, prediction accuracy was the highest for clay, sand and pH.
Xiaoying Li, Huijun Jin, Qi Feng, Qingbai Wu, Hongwei Wang, Ruixia He, Dongliang Luo, Xiaoli Chang, Raul-David Șerban, and Tao Zhan
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-187, https://doi.org/10.5194/essd-2024-187, 2024
Preprint under review for ESSD
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In Northeast China, the permafrost is more sensitive to climate warming and fire disturbances than the boreal and Arctic permafrost. Since 2016, a continuous observation system has been gradually established for ground hydrothermal regimes and soil nutrient contents in Northeast China. The integrated dataset includes soil moisture content, soil organic carbon, total nitrogen, total phosphorus, total potassium, ground temperatures at depths of 0–20 m and active layer thickness from 2016 to 2022.
Songchao Chen, Zhongxing Chen, Xianglin Zhang, Zhongkui Luo, Calogero Schillaci, Dominique Arrouays, Anne Christine Richer-de-Forges, and Zhou Shi
Earth Syst. Sci. Data, 16, 2367–2383, https://doi.org/10.5194/essd-16-2367-2024, https://doi.org/10.5194/essd-16-2367-2024, 2024
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A new dataset for topsoil bulk density (BD) and soil organic carbon (SOC) stock (0–20 cm) across Europe using machine learning was generated. The proposed approach performed better in BD prediction and slightly better in SOC stock prediction than earlier-published PTFs. The outcomes present a meaningful advancement in enhancing the accuracy of BD, and the resultant topsoil BD and SOC stock datasets across Europe enable more precise soil hydrological and biological modeling.
Niels Hindrik Batjes, Luis Calisto, and Luis Moreira de Sousa
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-14, https://doi.org/10.5194/essd-2024-14, 2024
Revised manuscript accepted for ESSD
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Soils are an important provider of ecosystem services. This dataset provides quality-assessed and standardised soil data to support digital soil mapping and environmental applications at a broad scale. The underpinning soil profiles were shared by a wide range of data providers. Special attention was paid to the standardisation of soil property definitions, analytical method descriptions and property values. We present three measures to assess “fitness-for-intended-use” of the standardised data.
Sergio Díaz-Guadarrama, Viviana M. Varón-Ramírez, Iván Lizarazo, Mario Guevara, Marcos Angelini, Gustavo A. Araujo-Carrillo, Jainer Argeñal, Daphne Armas, Rafael A. Balta, Adriana Bolivar, Nelson Bustamante, Ricardo O. Dart, Martin Dell Acqua, Arnulfo Encina, Hernán Figueredo, Fernando Fontes, Joan S. Gutiérrez-Díaz, Wilmer Jiménez, Raúl S. Lavado, Jesús F. Mansilla-Baca, Maria de Lourdes Mendonça-Santos, Lucas M. Moretti, Iván D. Muñoz, Carolina Olivera, Guillermo Olmedo, Christian Omuto, Sol Ortiz, Carla Pascale, Marco Pfeiffer, Iván A. Ramos, Danny Ríos, Rafael Rivera, Lady M. Rodriguez, Darío M. Rodríguez, Albán Rosales, Kenset Rosales, Guillermo Schulz, Víctor Sevilla, Leonardo M. Tenti, Ronald Vargas, Gustavo M. Vasques, Yusuf Yigini, and Yolanda Rubiano
Earth Syst. Sci. Data, 16, 1229–1246, https://doi.org/10.5194/essd-16-1229-2024, https://doi.org/10.5194/essd-16-1229-2024, 2024
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In this work, the Latin America and Caribbean Soil Information System (SISLAC) database (https://54.229.242.119/sislac/es) was revised to generate an improved version of the data. Rules for data enhancement were defined. In addition, other datasets available in the region were included. Subsequently, through a principal component analysis (PCA), the main soil characteristics for the region were analyzed. We hope this dataset can help mitigate problems such as food security and global warming.
Qian Ding, Hua Shao, Chi Zhang, and Xia Fang
Earth Syst. Sci. Data, 15, 4599–4612, https://doi.org/10.5194/essd-15-4599-2023, https://doi.org/10.5194/essd-15-4599-2023, 2023
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A soil survey in 41 Chinese cities showed the soil nitrogen (N) in impervious surface areas (ISA; NISA) was 0.59±0.35 kg m−2, lower than in pervious soils. Eastern China had the highest NISA but the lowest natural soil N in China. Soil N decreased linearly with depth in ISA but nonlinearly in natural ecosystems. Temperature was negatively correlated with C : NISA but positively correlated with natural soil C : N. The unique NISA patterns imply intensive disturbance in N cycle by soil sealing.
Lukas Rimondini, Thomas Gumbricht, Anders Ahlström, and Gustaf Hugelius
Earth Syst. Sci. Data, 15, 3473–3482, https://doi.org/10.5194/essd-15-3473-2023, https://doi.org/10.5194/essd-15-3473-2023, 2023
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Peatlands have historically sequestrated large amounts of carbon and contributed to atmospheric cooling. However, human activities and climate change may instead turn them into considerable carbon emitters. In this study, we produced high-quality maps showing the extent of peatlands in the forests of Sweden, one of the most peatland-dense countries in the world. The maps are publicly available and may be used to support work promoting sustainable peatland management and combat their degradation.
Daphne Armas, Mario Guevara, Fernando Bezares, Rodrigo Vargas, Pilar Durante, Víctor Osorio, Wilmer Jiménez, and Cecilio Oyonarte
Earth Syst. Sci. Data, 15, 431–445, https://doi.org/10.5194/essd-15-431-2023, https://doi.org/10.5194/essd-15-431-2023, 2023
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The global need for updated soil datasets has increased. Our main objective was to synthesize and harmonize soil profile information collected by two different projects in Ecuador between 2009 and 2015.The main result was the development of the Harmonized Soil Database of Ecuador (HESD) that includes information from 13 542 soil profiles with over 51 713 measured soil horizons, including 92 different edaphic variables, and follows international standards for archiving and sharing soil data.
Fei Cheng, Zhao Zhang, Huimin Zhuang, Jichong Han, Yuchuan Luo, Juan Cao, Liangliang Zhang, Jing Zhang, Jialu Xu, and Fulu Tao
Earth Syst. Sci. Data, 15, 395–409, https://doi.org/10.5194/essd-15-395-2023, https://doi.org/10.5194/essd-15-395-2023, 2023
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We generated a 1 km daily soil moisture dataset for dryland wheat and maize across China (ChinaCropSM1 km) over 1993–2018 through random forest regression, based on in situ observations. Our improved products have a remarkably better quality compared with the public global products in terms of both spatial and time dimensions by integrating an irrigation module (crop type, phenology, soil depth). The dataset may be useful for agriculture drought monitoring and crop yield forecasting studies.
Viviana Marcela Varón-Ramírez, Gustavo Alfonso Araujo-Carrillo, and Mario Antonio Guevara Santamaría
Earth Syst. Sci. Data, 14, 4719–4741, https://doi.org/10.5194/essd-14-4719-2022, https://doi.org/10.5194/essd-14-4719-2022, 2022
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These are the first national soil texture maps obtained via digital soil mapping. We built clay, sand, and silt maps using spatial assembling with the best possible predictions at different depths. Also, we identified the better model for each pixel. This work was done to address the lack of soil texture maps in Colombia, and it can provide soil information for water-related applications, ecosystem services, and agricultural and crop modeling.
Qiang Zhang, Qiangqiang Yuan, Taoyong Jin, Meiping Song, and Fujun Sun
Earth Syst. Sci. Data, 14, 4473–4488, https://doi.org/10.5194/essd-14-4473-2022, https://doi.org/10.5194/essd-14-4473-2022, 2022
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Compared to previous seamless global daily soil moisture (SGD-SM 1.0) products, SGD-SM 2.0 enlarges the temporal scope from 2002 to 2022. By fusing auxiliary precipitation information with the long short-term memory convolutional neural network (LSTM-CNN) model, SGD-SM 2.0 can consider sudden extreme weather conditions for 1 d in global daily soil moisture products and is significant for full-coverage global daily hydrologic monitoring, rather than averaging monthly–quarterly–yearly results.
Juri Palmtag, Jaroslav Obu, Peter Kuhry, Andreas Richter, Matthias B. Siewert, Niels Weiss, Sebastian Westermann, and Gustaf Hugelius
Earth Syst. Sci. Data, 14, 4095–4110, https://doi.org/10.5194/essd-14-4095-2022, https://doi.org/10.5194/essd-14-4095-2022, 2022
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The northern permafrost region covers 22 % of the Northern Hemisphere and holds almost twice as much carbon as the atmosphere. This paper presents data from 651 soil pedons encompassing more than 6500 samples from 16 different study areas across the northern permafrost region. We use this dataset together with ESA's global land cover dataset to estimate soil organic carbon and total nitrogen storage up to 300 cm soil depth, with estimated values of 813 Pg for carbon and 55 Pg for nitrogen.
Élise G. Devoie, Stephan Gruber, and Jeffrey M. McKenzie
Earth Syst. Sci. Data, 14, 3365–3377, https://doi.org/10.5194/essd-14-3365-2022, https://doi.org/10.5194/essd-14-3365-2022, 2022
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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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