Kelin Hu

Dr. Kelin Hu

College of Land Science and Technology, China Agricultural University, Beijing 100193, China
orcid

Research Focus & Metrics

Academic Career Length

16Years (2011-Present)

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

Representative Publications

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16 May 2016 in Scientific Reports
Verified
Journal Article
Open access
HLHao Liang
Hao Liang
KHKelin Hu
Kelin Hu
WBWilliam D. Batchelor
William D. Batchelor
ZQZhiming Qi
Zhiming Qi
BLBaoguo Li
Baoguo Li
An integrated model WHCNS (soil Water Heat Carbon Nitrogen Simulator) was developed to assess water and nitrogen (N) management in North China. It included five main modules: soil water, soil temperature, soil carbon (C), soil N, and crop growth. The model integrated some features of several widely used crop and soil models, and some modifications were made in order to apply the WHCNS model under the complex conditions of intensive cropping systems in North China. The WHCNS model was evaluated using an open access dataset from the European International Conference on Modeling Soil Water and N Dynamics. WHCNS gave better estimations of soil water and N dynamics, dry matter accumulation and N uptake than 14 other models. The model was tested against data from four experimental sites in North China under various soil, crop, climate, and management practices. Simulated soil water content, soil nitrate concentrations, crop dry matter, leaf area index and grain yields all agreed well with measured values. This study indicates that the WHCNS model can be used to analyze and evaluate the effects of various field management practices on crop yield, fate of N, and water and N use efficiencies in North China.

22 March 2024 in Journal of Hydrology
Verified
Journal Article
Closed access
XXXinlei Xu
Xinlei Xu
FCFangzheng Chen
Fangzheng Chen
BWBin Wang
Bin Wang
MHMatthew Tom Harrison
Matthew Tom Harrison
YCYong Chen
Yong Chen
KHKelin Hu
Kelin Hu

28 July 2017 in Journal of Soils and Sediments
Verified
Journal Article
Closed access
PDF file
HSHongyan Song
Hongyan Song
KHKelin Hu
Kelin Hu
YAYi An
Yi An
CCChong Chen
Chong Chen
GLGuangde Li
Guangde Li

1 February 2022 in Science of The Total Environment
Verified
Journal Article
Closed access
HZHuayan Zhang
Huayan Zhang
EHErik A. Hobbie
Erik A. Hobbie
PFPuyu Feng
Puyu Feng
LNLing'An Niu
Ling'An Niu
KHKelin Hu
Kelin Hu

13 October 2022 in Nature Food
Verified
Journal Article
Closed access
PDF file
PFPuyu Feng
Puyu Feng
Bin WangBin Wang
Bin Wang
IMIan Macadam
Ian Macadam
ATAndréa S. Taschetto
Andréa S. Taschetto
NANerilie J. Abram
Nerilie J. Abram
KHKelin Hu
Kelin Hu

5 June 2015 in PLOS ONE
Verified
Journal Article
Open access
PDF file
CCChong Chen
Chong Chen
KHKelin Hu
Kelin Hu
HLHong Li
Hong Li
AYAnping Yun
Anping Yun
BLBaoguo Li
Baoguo Li
Understanding spatial variation of soil organic carbon (SOC) in three-dimensional direction is helpful for land use management. Due to the effect of profile depths and soil texture on vertical distribution of SOC, the stationary assumption for SOC cannot be met in the vertical direction. Therefore the three-dimensional (3D) ordinary kriging technique cannot be directly used to map the distribution of SOC at a regional scale. The objectives of this study were to map the 3D distribution of SOC at a regional scale by combining kriging method with the profile depth function of SOC (KPDF), and to explore the effects of soil texture and land use type on vertical distribution of SOC in a fluvial plain. A total of 605 samples were collected from 121 soil profiles (0.0 to 1.0 m, 0.20 m increment) in Quzhou County, China and SOC contents were determined for each soil sample. The KPDF method was used to obtain the 3D map of SOC at the county scale. The results showed that the exponential equation well described the vertical distribution of mean values of the SOC contents. The coefficients of determination, root mean squared error and mean prediction error between the measured and the predicted SOC contents were 0.52, 1.82 and -0.24 g kg-1 respectively, suggesting that the KPDF method could be used to produce a 3D map of SOC content. The surface SOC contents were high in the mid-west and south regions, and low values lay in the southeast corner. The SOC contents showed significant positive correlations between the five different depths and the correlations of SOC contents were larger in adjacent layers than in non-adjacent layers. Soil texture and land use type had significant effects on the spatial distribution of SOC. The influence of land use type was more important than that of soil texture in the surface soil, and soil texture played a more important role in influencing the SOC levels for 0.2-0.4 m layer.