Baoyuan Liu

Prof. Baoyuan Liu


Research Focus & Metrics

Academic Career Length

25Years (2002-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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12 June 2009 in Science in China Series D: Earth Sciences
Verified
Journal Article
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ZWZhiQiang Wang
ZhiQiang Wang
BLBaoyuan Liu
Baoyuan Liu
GLGang Liu
Gang Liu
YZYongXuan Zhang
YongXuan Zhang

31 July 2012 in Environmental Earth Sciences
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Journal Article
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HLHonghu Liu
Honghu Liu
TZTianyu Zhang
Tianyu Zhang
BLBaoyuan Liu
Baoyuan Liu
GLGang Liu
Gang Liu
GWG. V. Wilson
G. V. Wilson

11 December 2009 in Journal of Geographical Sciences
Verified
Journal Article
Closed access
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ZWZhiqiang Wang
Zhiqiang Wang
BLBaoyuan Liu
Baoyuan Liu
YZYan Zhang
Yan Zhang

8 March 2018 in Hydrology and Earth System Sciences
Verified
Journal Article
Open access
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SYShuiqing Yin
Shuiqing Yin
ZZZhengyuan Zhu
Zhengyuan Zhu
LWLi Wang
Li Wang
BLBaoyuan Liu
Baoyuan Liu
YXYun Xie
Yun Xie
YLYishan Li
Yishan Li
Soil erosion is one of the most significant environmental problems in China. From 2010 to 2012, the fourth national census for soil erosion sampled 32 364 PSUs (Primary Sampling Units, small watersheds) with the areas of 0.2–3 km2. Land use and soil erosion controlling factors including rainfall erosivity, soil erodibility, slope length, slope steepness, biological practice, engineering practice, and tillage practice for the PSUs were surveyed, and the soil loss rate for each land use in the PSUs was estimated using an empirical model, the Chinese Soil Loss Equation (CSLE). Though the information collected from the sample units can be aggregated to estimate soil erosion conditions on a large scale; the problem of estimating soil erosion condition on a regional scale has not been addressed well. The aim of this study is to introduce a new model-based regional soil erosion assessment method combining a sample survey and geostatistics. We compared seven spatial interpolation models based on the bivariate penalized spline over triangulation (BPST) method to generate a regional soil erosion assessment from the PSUs. Shaanxi Province (3116 PSUs) in China was selected for the comparison and assessment as it is one of the areas with the most serious erosion problem. Ten-fold cross-validation based on the PSU data showed the model assisted by the land use, rainfall erosivity factor (R), soil erodibility factor (K), slope steepness factor (S), and slope length factor (L) derived from a 1 : 10 000 topography map is the best one, with the model efficiency coefficient (ME) being 0.75 and the MSE being 55.8 % of that for the model assisted by the land use alone. Among four erosion factors as the covariates, the S factor contributed the most information, followed by K and L factors, and R factor made almost no contribution to the spatial estimation of soil loss. The LS factor derived from 30 or 90 m Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) data worsened the estimation when used as the covariates for the interpolation of soil loss. Due to the unavailability of a 1 : 10 000 topography map for the entire area in this study, the model assisted by the land use, R, and K factors, with a resolution of 250 m, was used to generate the regional assessment of the soil erosion for Shaanxi Province. It demonstrated that 54.3 % of total land in Shaanxi Province had annual soil loss equal to or greater than 5 t ha−1 yr−1. High (20–40 t ha−1 yr−1), severe (40–80 t ha−1 yr−1), and extreme ( > 80 t ha−1 yr−1) erosion occupied 14.0 % of the total land. The dry land and irrigated land, forest, shrubland, and grassland in Shaanxi Province had mean soil loss rates of 21.77, 3.51, 10.00, and 7.27 t ha−1 yr−1, respectively. Annual soil loss was about 207.3 Mt in Shaanxi Province, with 68.9 % of soil loss originating from the farmlands and grasslands in Yan'an and Yulin districts in the northern Loess Plateau region and Ankang and Hanzhong districts in the southern Qingba mountainous region. This methodology provides a more accurate regional soil erosion assessment and can help policymakers to take effective measures to mediate soil erosion risks.

26 February 2023 in Agriculture, Ecosystems & Environment
Verified
Journal Article
Closed access
QPQiong Peng
Qiong Peng
BLBaoyuan Liu
Baoyuan Liu
YHYaxian Hu
Yaxian Hu
AWAijuan Wang
Aijuan Wang
QGQiankun Guo
Qiankun Guo
LHLiang He
Liang He

18 September 2013 in Environmental Monitoring and Assessment
Verified
Journal Article
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PDF file
YYYang Yang
Yang Yang
ZYZhihan Ye
Zhihan Ye
BLBaoyuan Liu
Baoyuan Liu
XZXianqin Zeng
Xianqin Zeng
SFSuhua Fu
Suhua Fu
BLBingjun Lu
Bingjun Lu