Articles | Volume 17, issue 11
https://doi.org/10.5194/essd-17-6315-2025
© Author(s) 2025. 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-17-6315-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
21 Nov 2025
Data description paper |
| 21 Nov 2025
| 21 Nov 2025
A 30 m resolution dataset of soil and water conservation terraces across China for 2000, 2010, and 2020
Enwei Zhang
Yunnan Key Laboratory of Soil Erosion Prevention and Green Development, Institute of International Rivers and Eco-Security, Yunnan University, Kunming, 650500, China
Yueli Chen
State Key Laboratory of Severe Weather Meteorological Science and Technology, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
Shengzhao Wei
Yunnan Key Laboratory of Soil Erosion Prevention and Green Development, Institute of International Rivers and Eco-Security, Yunnan University, Kunming, 650500, China
Chenli Liu
Yunnan Key Laboratory of Soil Erosion Prevention and Green Development, Institute of International Rivers and Eco-Security, Yunnan University, Kunming, 650500, China
Hongna Wang
Yunnan Key Laboratory of Soil Erosion Prevention and Green Development, Institute of International Rivers and Eco-Security, Yunnan University, Kunming, 650500, China
Bowen Deng
Yunnan Key Laboratory of Soil Erosion Prevention and Green Development, Institute of International Rivers and Eco-Security, Yunnan University, Kunming, 650500, China
Honghong Lin
Yunnan Key Laboratory of Soil Erosion Prevention and Green Development, Institute of International Rivers and Eco-Security, Yunnan University, Kunming, 650500, China
Xue Yang
Yunnan Key Laboratory of Soil Erosion Prevention and Green Development, Institute of International Rivers and Eco-Security, Yunnan University, Kunming, 650500, China
Yawen Li
Yunnan Key Laboratory of Soil Erosion Prevention and Green Development, Institute of International Rivers and Eco-Security, Yunnan University, Kunming, 650500, China
Xingwu Duan
CORRESPONDING AUTHOR
Yunnan Key Laboratory of Soil Erosion Prevention and Green Development, Institute of International Rivers and Eco-Security, Yunnan University, Kunming, 650500, China
State Key Laboratory of Vegetation Structure, Function and Construction (VegLab), Yunnan University, Kunming, 650500, China
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Earth Syst. Sci. Data, 17, 1265–1274, https://doi.org/10.5194/essd-17-1265-2025, https://doi.org/10.5194/essd-17-1265-2025, 2025
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Rainfall erosivity maps are crucial for identifying key areas of water erosion. Due to the limited historical precipitation data, there are certain biases in rainfall erosivity estimates in China. This study develops a new rainfall erosivity map for mainland China using 1 min precipitation data from 60 129 weather stations, revealing that areas exceeding 4000 MJ mm ha−1 h−1yr−1 of annual rainfall erosivity are mainly concentrated in southern China and on the southern Tibetan Plateau.
Fanyu Zhao, Di Long, Chenqi Fang, Yiming Wang, and Xingwu Duan
EGUsphere, https://doi.org/10.5194/egusphere-2025-652, https://doi.org/10.5194/egusphere-2025-652, 2025
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The heterogeneous surge behaviors in Karakoram reveal critical knowledge gaps in the underlying mechanism, urging detailed investigations. We integrate multisource remote sensing (satellite altimetry, DEMs, optical/SAR imagery) to holistically characterize surge phases of a Karakoram glacier, quantifying flow velocity, surface elevation, terminus position, and lake level variations. This integrated approach underscores the value of multi-sensor synergies in deciphering complex surge mechanisms.
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
Short summary
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.
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Short summary
We produced the first soil and water conservation terrace measures dataset with a fine classification system on Google Earth Engine platform. This dataset included terrace data and soil and water conservation measure factor values, covering the period from 2000 to 2020. The terraces are categorized into level terrace, slope terrace, zig terrace, and slope-separated terrace. The results showed that the average overall accuracy of the terrace was 91.7 % and the average F1 score was 83.3 %.
We produced the first soil and water conservation terrace measures dataset with a fine...
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