Articles | Volume 14, issue 6
https://doi.org/10.5194/essd-14-2681-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-14-2681-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
09 Jun 2022
Data description paper |
| 09 Jun 2022
| 09 Jun 2022
New gridded dataset of rainfall erosivity (1950–2020) on the Tibetan Plateau
Yueli Chen
State Key Laboratory of Severe Weather, Chinese Academy of
Meteorological Sciences, Beijing, 100081, China
Xingwu Duan
CORRESPONDING AUTHOR
Institute of International Rivers and Eco-security, Yunnan University,
Kunming, 650091, China
State Key Laboratory of Severe Weather, Chinese Academy of
Meteorological Sciences, Beijing, 100081, China
Wei Qi
State Key Laboratory of Severe Weather, Chinese Academy of
Meteorological Sciences, Beijing, 100081, China
Ting Wei
State Key Laboratory of Severe Weather, Chinese Academy of
Meteorological Sciences, Beijing, 100081, China
Jianduo Li
CMA Earth System Modeling and Prediction Centre, Beijing, 100081,
China
State Key Laboratory of Severe Weather, Chinese Academy of
Meteorological Sciences, Beijing, 100081, China
Yun Xie
State Key Laboratory of Earth Surface Processes and Resources Ecology,
Faculty of Geographic Science, Beijing Normal University, Beijing, 100875,
China
Related authors
No articles found.
Yuanyuan Xiao, Shuiqing Yin, Bofu Yu, Conghui Fan, Wenting Wang, and Yun Xie
Hydrol. Earth Syst. Sci., 27, 4563–4577, https://doi.org/10.5194/hess-27-4563-2023, https://doi.org/10.5194/hess-27-4563-2023, 2023
Short summary
Short summary
An exceptionally heavy rainfall event occurred on 20 July 2021 in central China (the 7.20 storm). The storm presents a rare opportunity to examine the extreme rainfall erosivity. The storm, with an average recurrence interval of at least 10 000 years, was the largest in terms of its rainfall erosivity on record over the past 70 years in China. The study suggests that extreme erosive events can occur anywhere in eastern China and are not necessarily concentrated in low latitudes.
Tianming Ma, Zhuang Jiang, Minghu Ding, Yuansheng Li, Wenqian Zhang, and Lei Geng
The Cryosphere Discuss., https://doi.org/10.5194/tc-2023-76, https://doi.org/10.5194/tc-2023-76, 2023
Preprint under review for TC
Short summary
Short summary
We constructed a box model to evaluate the isotope effects of atmosphere-snow water vapor exchange at Dome A, Antarctica. The results show a clear and invisible diurnal cycle in surface snow isotopes under summer and winter conditions, respectively. After a 24-hour period, the model predicts a depletion in snow δ18O and δD under winter conditions, opposite to those in summer. The results suggest that annually atmosphere-snow water vapor exchange causes little isotope changes at the study site.
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
Short summary
Short summary
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.
Minghu Ding, Xiaowei Zou, Qizhen Sun, Diyi Yang, Wenqian Zhang, Lingen Bian, Changgui Lu, Ian Allison, Petra Heil, and Cunde Xiao
Earth Syst. Sci. Data, 14, 5019–5035, https://doi.org/10.5194/essd-14-5019-2022, https://doi.org/10.5194/essd-14-5019-2022, 2022
Short summary
Short summary
The PANDA automatic weather station (AWS) network consists of 11 stations deployed along a transect from the coast (Zhongshan Station) to the summit of the East Antarctic Ice Sheet (Dome A). It covers the different climatic and topographic units of East Antarctica. All stations record hourly air temperature, relative humidity, air pressure, wind speed and direction at two or three heights. The PANDA AWS dataset commences from 1989 and is planned to be publicly available into the future.
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
Short summary
Short summary
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.
Minghu Ding, Tong Zhang, Diyi Yang, Ian Allison, Tingfeng Dou, and Cunde Xiao
The Cryosphere, 15, 4201–4206, https://doi.org/10.5194/tc-15-4201-2021, https://doi.org/10.5194/tc-15-4201-2021, 2021
Short summary
Short summary
Measurement of snow heat conductivity is essential to establish the energy balance between the atmosphere and firn, but it is still not clear in Antarctica. Here, we used data from three automatic weather stations located in different types of climate and evaluated nine schemes that were used to calculate the effective heat diffusivity of snow. The best solution was proposed. However, no conductivity–density relationship was optimal at all sites, and the performance of each varied with depth.
Tingfeng Dou, Cunde Xiao, Jiping Liu, Qiang Wang, Shifeng Pan, Jie Su, Xiaojun Yuan, Minghu Ding, Feng Zhang, Kai Xue, Peter A. Bieniek, and Hajo Eicken
The Cryosphere, 15, 883–895, https://doi.org/10.5194/tc-15-883-2021, https://doi.org/10.5194/tc-15-883-2021, 2021
Short summary
Short summary
Rain-on-snow (ROS) events can accelerate the surface ablation of sea ice, greatly influencing the ice–albedo feedback. We found that spring ROS events have shifted to earlier dates over the Arctic Ocean in recent decades, which is correlated with sea ice melt onset in the Pacific sector and most Eurasian marginal seas. There has been a clear transition from solid to liquid precipitation, leading to a reduction in spring snow depth on sea ice by more than −0.5 cm per decade since the 1980s.
Minghu Ding, Biao Tian, Michael C. B. Ashley, Davide Putero, Zhenxi Zhu, Lifan Wang, Shihai Yang, Chuanjin Li, and Cunde Xiao
Earth Syst. Sci. Data, 12, 3529–3544, https://doi.org/10.5194/essd-12-3529-2020, https://doi.org/10.5194/essd-12-3529-2020, 2020
Short summary
Short summary
Dome A, is one of the harshest environments on Earth.To evaluate the characteristics of near-surface O3, continuous observations were carried out in 2016. The results showed different patterns between coastal and inland Antarctic areas that were characterized by high concentrations in cold seasons and at night. Short-range transport accounted for the O3 enhancement events (OEEs) during summer at DA, rather than efficient local production, which is consistent with previous studies.
O3 enhancement events(OEEs) at Dome A, East Antarctica
Minghu Ding, Biao Tian, Michael Ashley, Zhenxi Zhu, Lifan Wang, Shihai Yang, Chuanjin Li, Cunde Xiao, and Dahe Qin
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2019-1042, https://doi.org/10.5194/acp-2019-1042, 2020
Revised manuscript not accepted
Short summary
Short summary
In 2016, the first observation of near-surface ozone was made at Dome A, the inaccessible pole. And based on the ERA-interim meteorological reanalysis data, we clearly found that there was strong transportation from stratosphere to troposphere during polar night at Dome A. This work provides unique information of ozone variation in Dome A and expands our knowledge in Antarctica.
Tingfeng Dou, Zhiheng Du, Shutong Li, Yulan Zhang, Qi Zhang, Mingju Hao, Chuanjin Li, Biao Tian, Minghu Ding, and Cunde Xiao
The Cryosphere, 13, 3309–3316, https://doi.org/10.5194/tc-13-3309-2019, https://doi.org/10.5194/tc-13-3309-2019, 2019
Short summary
Short summary
The meltwater scavenging coefficient (MSC) determines the BC enrichment in the surface layer of melting snow and therefore modulates the BC-snow-albedo feedbacks. This study presents a new method for MSC estimation over the sea-ice area in Arctic. Using this new method, we analyze the spatial variability of MSC in the western Arctic and demonstrate that the value in Canada Basin (23.6 % ± 2.1 %) ≈ that in Greenland (23.0 % ± 12.5 %) > that in Chukchi Sea (17.9 % ± 5.0 %) > that in Elson Lagoon (14.5 % ± 2.6 %).
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
Short summary
Short summary
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.
Wei Wei, Hongsheng Zhang, Bingui Wu, Yongxiang Huang, Xuhui Cai, Yu Song, and Jianduo Li
Atmos. Chem. Phys., 18, 12953–12967, https://doi.org/10.5194/acp-18-12953-2018, https://doi.org/10.5194/acp-18-12953-2018, 2018
Short summary
Short summary
Heavy particulate pollution events have frequently occurred in the North China Plain. Using the intermittency factor, we found that the turbulence during the transport stage is intermittent and not locally generated. Turbulence results from the wind shear of low-level jets and then transports downward, causing intermittent turbulence at lower levels. The intermittent turbulence contributes positively to the vertical dispersion of particulate matter and improves the air quality near the surface.
Yuzhe Wang, Tong Zhang, Jiawen Ren, Xiang Qin, Yushuo Liu, Weijun Sun, Jizu Chen, Minghu Ding, Wentao Du, and Dahe Qin
The Cryosphere, 12, 851–866, https://doi.org/10.5194/tc-12-851-2018, https://doi.org/10.5194/tc-12-851-2018, 2018
Short summary
Short summary
We combine in situ measurements and an ice flow model to study the thermomechanical features of Laohugou Glacier No. 12, the largest valley glacier on Qilian Shan. We reveal that this glacier, once considered to be extremely continental or cold, is actually polythermal with a lower temperate ice layer over a large region of the ablation area. Strain heating and latent heat due to meltwater refreezing in the firn zone play critical roles in controlling the thermal regime of this glacier.
Related subject area
Pedology
The patterns of soil nitrogen stocks and C : N stoichiometry under impervious surfaces in China
Mapping of peatlands in the forested landscape of Sweden using lidar-based terrain indices
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
SGD-SM 2.0: an improved seamless global daily soil moisture long-term dataset from 2002 to 2022
Improving Latin American Soil Information Database for Digital Soil Mapping enhances its usability and scalability
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
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
The Boreal–Arctic Wetland and Lake Dataset (BAWLD)
A first investigation of hydrogeology and hydrogeophysics of the Maqu catchment in the Yellow River source region
Radionuclide contamination in flood sediment deposits in the coastal rivers draining the main radioactive pollution plume of Fukushima Prefecture, Japan (2011–2020)
Generating seamless global daily AMSR2 soil moisture (SGD-SM) long-term products for the years 2013–2019
EstSoil-EH: a high-resolution eco-hydrological modelling parameters dataset for Estonia
An improved global remote-sensing-based surface soil moisture (RSSSM) dataset covering 2003–2018
A new dataset of soil carbon and nitrogen stocks and profiles from an instrumented Greenlandic fen designed to evaluate land-surface models
Spatial radionuclide deposition data from the 60 km radial area around the Chernobyl Nuclear Power Plant: results from a sampling survey in 1987
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
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Sergio Díaz-Guadarrama, 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 Aqua, Arnulfo Encina, Hernán Figueredo, Fernando Fontes, Joan S. Gutiérrez-Diaz, 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. Rodríguez, Darío M. Rodríguez, Albán Rosales, Kenset Rosales, Guillermo Schulz, Victor Sevilla, Leonardo M. Tenti, Ronald Vargas, Viviana M. Varón-Ramírez, Gustavo M. Vasques, Yusuf Yigini, and Yolanda Rubiano
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-291, https://doi.org/10.5194/essd-2022-291, 2022
Revised manuscript accepted for ESSD
Short summary
Short summary
In this work, the SISLAC database was revised to generate an improved version of the data. Then, through a practical exercise of digital soil mapping we show the potential of the data to generate spatial information of soil organic carbon. The results (R2 > 0.5) show the suitability and usability of the data to generate information that can help mitigate problems such as food security and global warming.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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).
Yongzhe Chen, Xiaoming Feng, and Bojie Fu
Earth Syst. Sci. Data, 13, 1–31, https://doi.org/10.5194/essd-13-1-2021, https://doi.org/10.5194/essd-13-1-2021, 2021
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Cited articles
Agnese, C., Bagarello, V., Corrao, C., D Agostino, L., and D'Asaro, F.:
Influence of the rainfall measurement interval on the erosivity
determinations in the Mediterranean area, J. Hydrol., 329, 39–48, https://doi.org/10.1016/j.jhydrol.2006.02.002, 2006.
Angulo-Martínez, M. and Beguería, S.: Estimating rainfall
erosivity from daily precipitation records: A comparison among methods using
data from the Ebro Basin (NE Spain), J. Hydrol., 379, 111–121, https://doi.org/10.1016/j.jhydrol.2009.09.051, 2009.
Beck, H. E., Vergopolan, N., Pan, M., Levizzani, V., van Dijk, A. I. J. M., Weedon, G. P., Brocca, L., Pappenberger, F., Huffman, G. J., and Wood, E. F.: Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling, Hydrol. Earth Syst. Sci., 21, 6201–6217, https://doi.org/10.5194/hess-21-6201-2017, 2017.
Brown, C. L. and Foster, R. G.: Storm erosivity using idealized intensity distributions, T. ASAE, 30, 379–386, https://doi.org/10.13031/2013.31957,
1987.
Cao, Y., Wang, S. J., Bai, X. Y., and Li, H. W.: Inversion calculation and
spatial-temporal pattern of rainfall erosivity in southwestern China over
one hundred years, Acta Ecologica Sinica, 38, 8766–8773, https://doi.org/10.5846/stxb201805241142, 2018 (in Chinese).
Chen, Y.: A new gridded dataset of rainfall erosivity (1950–2020) in the
Tibetan Plateau, National Tibetan Plateau Data Center [dataset],
https://doi.org/10.11888/Terre.tpdc.271833, 2021.
Chen, Y., Duan, X., Zhang, G., Ding, M., and Lu, S.: Rainfall erosivity estimation over the Tibetan Plateau based on high spatial-temporal resolution rainfall records, Int. Soil Water Conse., https://doi.org/10.1016/j.iswcr.2022.01.004, in press, 2022.
Cucchi, M., Weedon, G. P., Amici, A., Bellouin, N., Lange, S., Müller Schmied, H., Hersbach, H., and Buontempo, C.: WFDE5: bias-adjusted ERA5 reanalysis data for impact studies, Earth Syst. Sci. Data, 12, 2097–2120, https://doi.org/10.5194/essd-12-2097-2020, 2020.
Fick, S. E. and Hijmans, R. J.: WorldClim 2: new 1km spatial resolution climate
surfaces for global land areas, Int. J. Climatol., 37, 4302–4315,
https://doi.org/10.1002/joc.5086, 2017.
Freitas, E. D. S., Coelho, V. H. R., Xuan, Y., Melo, D. D. C. D., Gadelha, A. N.,
Santos, E. A., Galvão, C. D. O., Ramos Filho, G. M., Barbosa, L. R., Huffman,
G. J., Petersen, W. A., and Almeida, C. D. N.: The performance of the IMERG
satellite-based product in identifying sub-daily rainfall events and their
properties, J. Hydrol., 589, 125128, https://doi.org/10.1016/j.jhydrol.2020.125128, 2020.
Gu, Z., Feng, D., Duan, X., Gong, K., Li, Y., and Yue, T.: Spatial and
temporal patterns of rainfall erosivity in the Tibetan Plateau, Water, 12,
200, https://doi.org/10.3390/w12010200, 2020.
He, J., Yang, K., Tang, W., Lu, H., Qin, J., Chen, Y., and Li, X.: The first
high-resolution meteorological forcing dataset for land process studies over
China, Sci. Data, 7, 25, https://doi.org/10.1038/s41597-020-0369-y, 2020.
Hersbach, H., Bell, W., Berrisford, P., Horányi, A., J., M.-S., Nicolas, J., Radu, R., Schepers, D., Simmons, A., Soci, C., and Dee, D.: Global reanalysis: goodbye ERA-Interim, hello, https://doi.org/10.21957/VF291HEHD7, 2019.
Jiang, Q., Li, W., Fan, Z., He, X, Sun, W., Chen, S., Wen, J., Gao, J., and Wang, J.:
Evaluation of the ERA5 reanalysis precipitation dataset over Chinese
Mainland, J. Hydrol., 595, 125660,
https://doi.org/10.1016/j.jhydrol.2020.125660, 2021.
Jiao D., Xu N., Yang F., and Xu K.: Evaluation of spatial-temporal variation
performance of ERA5 precipitation data in China, Sci. Rep.-UK, 11, 17956,
https://doi.org/10.1038/s41598-021-97432-y, 2021.
Kim, J., Han, H., Kim, B., Chen, H., and Lee, J.: Use of a
high-resolution-satellite-based precipitation product in mapping
continental-scale rainfall erosivity: A case study of the United States,
Catena, 193, 104602, https://doi.org/10.1016/j.catena.2020.104602, 2020.
Li, D., Yang, K., Tang, W., Li, X., Zhou, X., and Guo, D.: Characterizing
precipitation in high altitudes of the western Tibetan plateau with a focus
on major glacier areas, Int. J. Climatol., 40, 5114–5127, https://doi.org/10.1002/joc.6509, 2020.
Liu, B., Tao, H., Song, C., Guo, B., Shi, Z., Zhang, C., Kong, F., and He,
B.: Temporal and spatial variations of rainfall erosivity in China during
1960 to 2009, Geogr. Res., 32, 245–256, 2013 (in Chinese).
Liu, B., Xie, Y., Li, Z., Liang, Y., Zhang, W., Fu, S., Yin, S., Wei, X.,
Zhang, K., Wang, Z., Liu, Y., Zhao, Y., and Guo, Q.: The assessment of soil
loss by water erosion in China, Int. Soil Water Conse., 8, 430–439, https://doi.org/10.1016/j.iswcr.2020.07.002, 2020.
Liu, B. Y., Zhang, K. L., and Xie, Y.: An empirical soil loss equation//Proceedings-Process of soil erosion and its environment effect, 12th international soil conservation organization conference, 26–31 May 2002, Beijing, China, Tsinghua University Press,
Beijing, China, ISBN 7-5046-3189-2, 2002.
Liu, X. and Chen, B.: Climatic warming in the Tibetan Plateau during recent
decades, Int. J. Climatol., 20, 1729–1742, https://doi.org/10.1002/1097-0088(20001130)20:14<1729::AID-JOC556>3.0.CO;2-Y, 2000.
Lobo, G. P. and Bonilla, C. A.: Sensitivity analysis of kinetic
energy-intensity relationships and maximum rainfall intensities on rainfall
erosivity using a long-term precipitation dataset, J. Hydrol., 527, 788–793,
https://doi.org/10.1016/j.jhydrol.2015.05.045, 2015.
Ma, X., He, Y., Xu, J., van Noordwijk, M., and Lu, X.: Spatial and temporal
variation in rainfall erosivity in a Himalayan watershed, Catena, 121,
248–259, https://doi.org/10.1016/j.catena.2014.05.017, 2014.
Panagos, P., Meusburger, K., Ballabio, C., Borrelli, P., Beguería, S.,
Klik, A., Rymszewicz, A., Michaelides, S., Olsen, P., Tadić, M. P.,
Aalto, J., Lakatos, M., Dumitrescu, A., Rousseva, S., Montanarella, L., and
Alewell, C.: Reply to the comment on “Rainfall erosivity in Europe” by
Auerswald et al., Sci. Total Environ., 532, 853–857, https://doi.org/10.1016/j.scitotenv.2015.05.020, 2015.
Panagos, P., Borrelli, P., Meusburger, K., Yu, B., Klik, A., Jae Lim, K.,
Yang, J. E., Ni, J., Miao, C., Chattopadhyay, N., Sadeghi, S. H., Hazbavi, Z.,
Zabihi, M., Larionov, G. A., Krasnov, S. F., Gorobets, A. V., Levi, Y., Erpul,
G., Birkel, C., Hoyos, N., Naipal, V., Oliveira, P. T. S., Bonilla, C. A.,
Meddi, M., Nel, W., Al Dashti, H., Boni, M., Diodato, N., Van Oost, K.,
Nearing, M., and Ballabio, C.: Global rainfall erosivity assessment based on
high-temporal resolution rainfall records, Sci. Rep.-UK, 7, 4175, https://doi.org/10.1038/s41598-017-04282-8, 2017.
Qin, W., Guo, Q., Zuo, C., Shan, Z., Ma, L., and Sun, G.: Spatial
distribution and temporal trends of rainfall erosivity in mainland China for
1951–2010, Catena, 147, 177–186, https://doi.org/10.1016/j.catena.2016.07.006,
2016.
Renard, K. G., Foster, G. A., Weesies, D. K., McCool, D. K., and Yoder, D. C.:
Predicting soil erosion by water: a guide to conservation planning with the
revised universal soil loss equation (RUSLE), U.S. Department of
Agriculture, Agriculture Handbook No. 703, ISBN 0-16-048938-5, 1997.
Risal, A., Lim, K. J., Bhattarai, R., Yang, J. E., Noh, H., Pathak, R., and
Kim, J.: Development of web-based WERM-S module for estimating spatially
distributed rainfall erosivity index (EI30) using RADAR rainfall data,
Catena, 161, 37–49, https://doi.org/10.1016/j.catena.2017.10.015, 2018.
Shin, J., Kim, T., Heo, J., and Lee, J.: Spatial and temporal variations in
rainfall erosivity and erosivity density in South Korea, Catena, 176,
125–144, https://doi.org/10.1016/j.catena.2019.01.005, 2019.
Sun, Q., Miao C., Duan Q., Ashouri H., Sorooshian S., and Hsu K.: A Review
of Global Precipitation Data Sets: Data Sources, Estimation, and
Intercomparisons, Rev. Geophys., 56, 79–107,
https://doi.org/10.1002/2017RG000574, 2018.
Teng, H., Ma, Z., Chappell, A., Shi, Z., Liang, Z., and Yu, W.: Improving rainfall erosivity estimates using merged TRMM and gauge data, Remote Sens., 9, 1134, https://doi.org/10.3390/rs9111134, 2017.
Teng, H., Liang, Z., Chen, S., Liu, Y., Viscarra Rossel, R. A., Chappell, A.,
Yu, W., and Shi, Z.: Current and future assessments of soil erosion by water
on the Tibetan Plateau based on RUSLE and CMIP5 climate models, Sci. Total
Environ., 635, 673–686, https://doi.org/10.1016/j.scitotenv.2018.04.146, 2018.
Teng, H., Hu, J., Zhou, Y., Zhou, L., and Shi, Z.: Modelling and mapping
soil erosion potential in China, J. Integr. Agr., 18, 251–264, https://doi.org/10.1016/S2095-3119(18)62045-3, 2019.
Vrieling, A., Sterk, G., and de Jong, S. M.: Satellite-based estimation of
rainfall erosivity for Africa, J. Hydrol., 395, 235–241, https://doi.org/10.1016/j.jhydrol.2010.10.035, 2010.
Wang, Y., Cheng, C., Xie, Y., Liu, B., Yin, S., Liu, Y., and Hao, Y.:
Increasing trends in rainfall-runoff erosivity in the Source Region of the
Three Rivers, Sci. Total. Environ., 592, 639–648,
https://doi.org/10.1016/j.scitotenv.2017.02.235, 2017.
Wischmeier, W. H. and Smith, D. D.: Predicting rainfall-erosion
losses from cropland east of the Rocky Mountains: Guide for selection of
practices for soil and water conservation, US Department of Agriculture, Agriculture Handbook No. 282, https://handle.nal.usda.gov/10113/CAT87208342 (last access: 6 June 2022), 1965.
Wischmeier, W. H. and Smith, D. D.: Predicting rainfall erosion
losses: a guide to conservation planning, Department of Agriculture, Science
and Education Administration, US Department of Agriculture, Agriculture
Handbook No. 537, Stock Number 001-000-03903-2, 1978.
Xie, Y., Liu, B. Y., and Zhang, W. B.: Study on standard of erosive
rainfall, J. Soil Water Conserv., 14, 6–11, https://doi.org/10.3321/j.issn:1009-2242.2000.04.002, 2000 (in Chinese).
Yan, D., Fan, J., Guo, F., Guo, X., and Gong, K.F.: Spatiotemporal
distribution of precipitation erosivity in Tibet autonomous region,
Bulletin of Soil and Water Conservation, 30, 17–21, https://doi.org/10.13961/j.cnki.stbctb.2010.04.025, 2010 (in Chinese).
Yang, F. and Lu, C.: Spatiotemporal variation and trends in rainfall
erosivity in China's dryland region during 1961–2012, Catena, 133, 362–372,
https://doi.org/10.1016/j.catena.2015.06.005, 2015.
Yao, T., Thompson, L., Yang, W., Yu, W., Gao, Y., Guo, X., Yang, X., Duan,
K., Zhao, H., Xu, B., Pu, J., Lu, A., Xiang, Y., Kattel, D. B., and Joswiak,
D.: Different glacier status with atmospheric circulations in Tibetan
Plateau and surroundings, Nat. Clim. Change, 2, 663–667, https://doi.org/10.1038/nclimate1580, 2012.
Yin, S., Xie, Y., Liu, B., and Nearing, M. A.: Rainfall erosivity estimation based on rainfall data collected over a range of temporal resolutions, Hydrol. Earth Syst. Sci., 19, 4113–4126, https://doi.org/10.5194/hess-19-4113-2015, 2015.
Yuan, X., Yang, K., Lu, H., He, J., Sun, J., and Wang, Y.: Characterizing the
features of precipitation for the Tibetan Plateau among four gridded
datasets: Detection accuracy and spatio-temporal variabilities, Atmos. Res.,
264, 105875, https://doi.org/10.1016/j.atmosres.2021.105875, 2021.
Yue, T., Yin, S., Xie, Y., Yu, B., and Liu, B.: Rainfall erosivity mapping over mainland China based on high-density hourly rainfall records, Earth Syst. Sci. Data, 14, 665–682, https://doi.org/10.5194/essd-14-665-2022, 2022.
Zhang, W., Xie, Y., and Liu, B.: Spatial distribution of rainfall erosivity
in China, J. Mountain Sci., 21, 33–40, 2003 (in Chinese).
Zhou, X., Yang, K., Ouyang, L., Wang, Y., Jiang, Y., Li, X., Chen, D.,
and Prein, A.:
Added value of kilometer-scale modeling over the third pole region: a
CORDEXCPTP pilot study, Clim. Dynam., 57, 1673–1687,
https://doi.org/10.1007/s00382-021-05653-8, 2021.
Short summary
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.
We reconstructed the first annual rainfall erosivity dataset for the Tibetan Plateau in China....
Altmetrics
Final-revised paper
Preprint