World's Best Scientists 2026 revealed!
Yuefei Huang

Yuefei Huang

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Environmental Sciences 43 7174 6895 707 703 99 6380

Yuefei Huang publications per year

The chart shows the history of publications by Yuefei Huang between 2002 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Yuefei Huang published across 24 years, from 2002 to 2025, averaging 7 papers a year. Output peaked at 26 publications in 2025. 41 of the 168 publications appeared in the last two years.

No. of publications
5 10 15 20 25
Bar chart. Horizontal axis: year, 2002 to 2025. Vertical axis: number of publications, 0 to 26. Peak 26 publications in 2025. 2002: 2 publications 2003: 2 publications 2004: 3 publications 2005: 5 publications 2006: 2 publications 2007: 3 publications 2008: 1 publication 2009: 3 publications 2010: 1 publication 2011: 3 publications 2012: 0 publications 2013: 4 publications 2014: 7 publications 2015: 8 publications 2016: 8 publications 2017: 8 publications 2018: 10 publications 2019: 8 publications 2020: 5 publications 2021: 8 publications 2022: 17 publications 2023: 19 publications 2024: 15 publications 2025: 26 publications
2002 2025

168 publications in total across all disciplines

View publications per year as a table
Yuefei Huang: publications per year, 2002 to 2025
Year Publications
2002 2
2003 2
2004 3
2005 5
2006 2
2007 3
2008 1
2009 3
2010 1
2011 3
2012 0
2013 4
2014 7
2015 8
2016 8
2017 8
2018 10
2019 8
2020 5
2021 8
2022 17
2023 19
2024 15
2025 26
Total 168
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Yuefei Huang publication distribution in Environmental Sciences in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Environmental Sciences in 2026. The highlighted bar marks where Yuefei Huang sits on this spectrum.

No. of scientists
200 400 600
Bar chart with 66 bars. Horizontal axis: publications, 41–50 to 690+. Vertical axis: number of scientists, 0 to 617. Most scientists, 617, have 121–130 publications. The last bar groups every scientist with 690 publications or more. The highlighted bar, 91–100 publications, is where this scientist sits. 41–50 publications: 21 scientists 51–60 publications: 62 scientists 61–70 publications: 133 scientists 71–80 publications: 257 scientists 81–90 publications: 361 scientists 91–100 publications: 440 scientists 101–110 publications: 492 scientists 111–120 publications: 541 scientists 121–130 publications: 617 scientists 131–140 publications: 544 scientists 141–150 publications: 541 scientists 151–160 publications: 539 scientists 161–170 publications: 444 scientists 171–180 publications: 444 scientists 181–190 publications: 400 scientists 191–200 publications: 377 scientists 201–210 publications: 318 scientists 211–220 publications: 282 scientists 221–230 publications: 263 scientists 231–240 publications: 220 scientists 241–250 publications: 217 scientists 251–260 publications: 180 scientists 261–270 publications: 181 scientists 271–280 publications: 155 scientists 281–290 publications: 130 scientists 291–300 publications: 127 scientists 301–310 publications: 130 scientists 311–320 publications: 85 scientists 321–330 publications: 106 scientists 331–340 publications: 80 scientists 341–350 publications: 83 scientists 351–360 publications: 75 scientists 361–370 publications: 69 scientists 371–380 publications: 52 scientists 381–390 publications: 54 scientists 391–400 publications: 56 scientists 401–410 publications: 44 scientists 411–420 publications: 40 scientists 421–430 publications: 36 scientists 431–440 publications: 25 scientists 441–450 publications: 25 scientists 451–460 publications: 32 scientists 461–470 publications: 29 scientists 471–480 publications: 21 scientists 481–490 publications: 26 scientists 491–500 publications: 26 scientists 501–510 publications: 17 scientists 511–520 publications: 19 scientists 521–530 publications: 15 scientists 531–540 publications: 22 scientists 541–550 publications: 12 scientists 551–560 publications: 15 scientists 561–570 publications: 11 scientists 571–580 publications: 19 scientists 581–590 publications: 9 scientists 591–600 publications: 9 scientists 601–610 publications: 7 scientists 611–620 publications: 11 scientists 621–630 publications: 5 scientists 631–640 publications: 5 scientists 641–650 publications: 6 scientists 651–660 publications: 3 scientists 661–670 publications: 3 scientists 671–680 publications: 4 scientists 681–689 publications: 4 scientists 690+ publications: 100 scientists
41–50 publications 690+

This scientist: 99 publications — 13th percentile

13% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 690 publications or more.

View publications distribution as a table
Number of Environmental Sciences scientists by publication count, Research.com 2026 ranking edition. Based on 9,676 ranked scientists.
Publications Scientists This scientist
41–50 21
51–60 62
61–70 133
71–80 257
81–90 361
91–100 440 99
101–110 492
111–120 541
121–130 617
131–140 544
141–150 541
151–160 539
161–170 444
171–180 444
181–190 400
191–200 377
201–210 318
211–220 282
221–230 263
231–240 220
241–250 217
251–260 180
261–270 181
271–280 155
281–290 130
291–300 127
301–310 130
311–320 85
321–330 106
331–340 80
341–350 83
351–360 75
361–370 69
371–380 52
381–390 54
391–400 56
401–410 44
411–420 40
421–430 36
431–440 25
441–450 25
451–460 32
461–470 29
471–480 21
481–490 26
491–500 26
501–510 17
511–520 19
521–530 15
531–540 22
541–550 12
551–560 15
561–570 11
571–580 19
581–590 9
591–600 9
601–610 7
611–620 11
621–630 5
631–640 5
641–650 6
651–660 3
661–670 3
671–680 4
681–689 4
690+ 100
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Yuefei Huang D-index placement in Environmental Sciences in 2026

The chart shows the D-index (discipline H-index) distribution of Environmental Sciences scientists ranked by Research.com in 2026. The highlighted bar marks where Yuefei Huang sits on this spectrum.

No. of scientists
100 200 300
Bar chart with 97 bars. Horizontal axis: D-Index, 30 to 126+. Vertical axis: number of scientists, 0 to 348. Most scientists, 348, have 45 D-Index. The last bar groups every scientist with 126 D-Index or more. The highlighted bar, 43 D-Index, is where this scientist sits. 30 D-Index: 12 scientists 31 D-Index: 26 scientists 32 D-Index: 51 scientists 33 D-Index: 88 scientists 34 D-Index: 123 scientists 35 D-Index: 163 scientists 36 D-Index: 206 scientists 37 D-Index: 267 scientists 38 D-Index: 265 scientists 39 D-Index: 275 scientists 40 D-Index: 321 scientists 41 D-Index: 343 scientists 42 D-Index: 305 scientists 43 D-Index: 336 scientists 44 D-Index: 330 scientists 45 D-Index: 348 scientists 46 D-Index: 291 scientists 47 D-Index: 275 scientists 48 D-Index: 272 scientists 49 D-Index: 273 scientists 50 D-Index: 263 scientists 51 D-Index: 232 scientists 52 D-Index: 266 scientists 53 D-Index: 217 scientists 54 D-Index: 198 scientists 55 D-Index: 177 scientists 56 D-Index: 202 scientists 57 D-Index: 204 scientists 58 D-Index: 166 scientists 59 D-Index: 177 scientists 60 D-Index: 166 scientists 61 D-Index: 152 scientists 62 D-Index: 143 scientists 63 D-Index: 150 scientists 64 D-Index: 124 scientists 65 D-Index: 119 scientists 66 D-Index: 120 scientists 67 D-Index: 118 scientists 68 D-Index: 82 scientists 69 D-Index: 98 scientists 70 D-Index: 94 scientists 71 D-Index: 105 scientists 72 D-Index: 74 scientists 73 D-Index: 84 scientists 74 D-Index: 70 scientists 75 D-Index: 67 scientists 76 D-Index: 78 scientists 77 D-Index: 60 scientists 78 D-Index: 59 scientists 79 D-Index: 52 scientists 80 D-Index: 47 scientists 81 D-Index: 38 scientists 82 D-Index: 48 scientists 83 D-Index: 42 scientists 84 D-Index: 42 scientists 85 D-Index: 43 scientists 86 D-Index: 29 scientists 87 D-Index: 37 scientists 88 D-Index: 29 scientists 89 D-Index: 30 scientists 90 D-Index: 34 scientists 91 D-Index: 20 scientists 92 D-Index: 22 scientists 93 D-Index: 17 scientists 94 D-Index: 19 scientists 95 D-Index: 24 scientists 96 D-Index: 21 scientists 97 D-Index: 20 scientists 98 D-Index: 24 scientists 99 D-Index: 17 scientists 100 D-Index: 17 scientists 101 D-Index: 21 scientists 102 D-Index: 25 scientists 103 D-Index: 18 scientists 104 D-Index: 26 scientists 105 D-Index: 20 scientists 106 D-Index: 15 scientists 107 D-Index: 10 scientists 108 D-Index: 13 scientists 109 D-Index: 15 scientists 110 D-Index: 12 scientists 111 D-Index: 8 scientists 112 D-Index: 7 scientists 113 D-Index: 9 scientists 114 D-Index: 6 scientists 115 D-Index: 12 scientists 116 D-Index: 7 scientists 117 D-Index: 8 scientists 118 D-Index: 3 scientists 119 D-Index: 5 scientists 120 D-Index: 7 scientists 121 D-Index: 2 scientists 122 D-Index: 4 scientists 123 D-Index: 8 scientists 124 D-Index: 7 scientists 125 D-Index: 9 scientists 126+ D-Index: 92 scientists
30 D-Index 126+

This scientist: 43 D-Index — 29th percentile

29% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 126 D-Index or more.

View D-Index distribution as a table
Number of Environmental Sciences scientists by D-index, Research.com 2026 ranking edition. Based on 9,676 ranked scientists.
D-Index Scientists This scientist
30 12
31 26
32 51
33 88
34 123
35 163
36 206
37 267
38 265
39 275
40 321
41 343
42 305
43 336 43
44 330
45 348
46 291
47 275
48 272
49 273
50 263
51 232
52 266
53 217
54 198
55 177
56 202
57 204
58 166
59 177
60 166
61 152
62 143
63 150
64 124
65 119
66 120
67 118
68 82
69 98
70 94
71 105
72 74
73 84
74 70
75 67
76 78
77 60
78 59
79 52
80 47
81 38
82 48
83 42
84 42
85 43
86 29
87 37
88 29
89 30
90 34
91 20
92 22
93 17
94 19
95 24
96 21
97 20
98 24
99 17
100 17
101 21
102 25
103 18
104 26
105 20
106 15
107 10
108 13
109 15
110 12
111 8
112 7
113 9
114 6
115 12
116 7
117 8
118 3
119 5
120 7
121 2
122 4
123 8
124 7
125 9
126+ 92
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Overview

Yuefei Huang is affiliated with Tsinghua University in China and works primarily in the field of Environmental Science. Their research extensively covers several subfields, including Water Science and Technology, Global and Planetary Change, Industrial and Manufacturing Engineering, Ecology, and Environmental Engineering.

The topics that form the core of Huang's research include:

  • Phosphorus and nutrient management
  • Hydrology and watershed management studies
  • Flood risk assessment and management
  • Plant water relations and carbon dynamics
  • Coastal wetland ecosystem dynamics
  • Adsorption and biosorption for pollutant removal
  • Hydrological forecasting using AI

Huang has contributed to notable recent publications. These include:

  • Short-term runoff prediction with GRU and LSTM networks without requiring time step optimization during sample generation, 2020, Journal of Hydrology
  • Artificial neural network based hybrid modeling approach for flood inundation modeling, 2020, Journal of Hydrology
  • A long-term reconstructed TROPOMI solar-induced fluorescence dataset using machine learning algorithms, 2022, Scientific Data
  • Effects of soil water content on forest ecosystem water use efficiency through changes in transpiration/evapotranspiration ratio, 2021, Agricultural and Forest Meteorology
  • Detecting drought-induced GPP spatiotemporal variabilities with sun-induced chlorophyll fluorescence during the 2009/2010 droughts in China, 2020, Ecological Indicators

Frequent coauthors in Huang's research collaborations include:

  • Jing-Cheng Han
  • Bing Li
  • Xiaofeng Wu
  • Guangqian Wang
  • Yang Zhou

Huang commonly publishes in several academic journals, among them:

  • The Science of The Total Environment
  • Chemical Engineering Journal
  • Journal of Hydrology
  • Journal of Cleaner Production
  • Journal of Hazardous Materials

Best Publications

  • Partitioning evapotranspiration based on the concept of underlying water use efficiency

    Sha Zhou;Bofu Yu;Yao Zhang;Yuefei Huang

  • An integrated fuzzy-stochastic modeling approach for risk assessment of groundwater contamination.

    Jianbing Li;Gordon H. Huang;Gordon H. Huang;Guangming Zeng;Imran Maqsood

  • A multistage fuzzy-stochastic programming model for supporting sustainable water-resources allocation and management

    Y. P. Li;G. H. Huang;Y. F. Huang;H. D. Zhou

  • The effect of vapor pressure deficit on water use efficiency at the subdaily time scale

    Sha Zhou;Bofu Yu;Yuefei Huang;Guangqian Wang

  • AN INTERVAL-PARAMETER FUZZY NONLINEAR OPTIMIZATION MODEL FOR STREAM WATER QUALITY MANAGEMENT UNDER UNCERTAINTY

    Xiao-Sheng Qin;Xiao-Sheng Qin;Guo H. Huang;Guo H. Huang;Guang-Ming Zeng;A. Chakma

  • Effects of vegetation stems on hydraulics of overland flow under varying water discharges.

    Chunhong Zhao;Chunhong Zhao;Jian'en Gao;Yuefei Huang;Guangqian Wang

  • Development of an artificial neural network model for predicting minimum miscibility pressure in CO2 flooding

    Y.F. Huang;Y.F. Huang;G.H. Huang;G.H. Huang;M.Z. Dong;G.M. Feng;G.M. Feng

  • Phosphorus recovery through struvite crystallisation: Recent developments in the understanding of operational factors.

    Bing Li;Hai Ming Huang;Irina Boiarkina;Wei Yu

  • The complementary relationship and generation of the Budyko functions

    Sha Zhou;Bofu Yu;Yuefei Huang;Guangqian Wang

  • ITOM : an interval-parameter two-stage optimization model for stochastic planning of water resources systems

    Imran Maqsood;Guohe Huang;Yuefei Huang;Bing Chen

  • The contribution of reduction in evaporative cooling to higher surface air temperatures during drought

    Dongqin Yin;Dongqin Yin;Michael L. Roderick;Michael L. Roderick;Guy Leech;Fubao Sun;Fubao Sun

  • Explaining inter-annual variability of gross primary productivity from plant phenology and physiology

    Sha Zhou;Sha Zhou;Yao Zhang;Kelly K. Caylor;Yiqi Luo;Yiqi Luo

  • Violation analysis for solid waste management systems: an interval fuzzy programming approach

    Y.F. Huang;B.W. Baetz;B.W. Baetz;G.H. Huang;L. Liu;L. Liu

  • A Multi-objective Linear Programming Model with Interval Parameters for Water Resources Allocation in Dalian City

    Yan Han;Yue-Fei Huang;Guang-Qian Wang;Imran Maqsood

  • Artificial neural network based hybrid modeling approach for flood inundation modeling

    Shuai Xie;Wenyan Wu;Sebastian Mooser;Q.J. Wang

  • A long-term reconstructed TROPOMI solar-induced fluorescence dataset using machine learning algorithms

    Unknown

  • Daily underlying water use efficiency for AmeriFlux sites

    Sha Zhou;Bofu Yu;Yuefei Huang;Guangqian Wang

  • Effects of human activities on the eco-environment in the middle Heihe River Basin based on an extended environmental Kuznets curve model

    Sha Zhou;Yuefei Huang;Bofu Yu;Guangqian Wang

  • Diel ecosystem conductance response to vapor pressure deficit is suboptimal and independent of soil moisture

    Changjie Lin;Changjie Lin;Pierre Gentine;Yuefei Huang;Yuefei Huang;Kaiyu Guan

  • Water use efficiency and evapotranspiration partitioning for three typical ecosystems in the Heihe River Basin, northwestern China

    Sha Zhou;Bofu Yu;Yao Zhang;Yuefei Huang;Yuefei Huang

  • Vegetation response to climate conditions based on NDVI simulations using stepwise cluster analysis for the Three-River Headwaters region of China

    Yutong Zheng;Jingcheng Han;Yuefei Huang;Yuefei Huang;Steven R. Fassnacht

  • The Contribution of Astragalus adsurgens Roots and Canopy to Water Erosion Control in the Water–Wind Crisscrossed Erosion Region of the Loess Plateau, China

    Chunhong Zhao;Chunhong Zhao;Jian'en Gao;Jian'en Gao;Yuefei Huang;Guangqian Wang

Frequent Co-Authors

Guangqian Wang
Guangqian Wang Tsinghua University
Sha Zhou
Sha Zhou Columbia University
Guohe Huang
Guohe Huang University of Regina
Bofu Yu
Bofu Yu Griffith University
Songdong Shao
Songdong Shao University of Sheffield
Jianbing Li
Jianbing Li University of Northern British Columbia
Yao Zhang
Yao Zhang Peking University
Xiaosheng Qin
Xiaosheng Qin Nanyang Technological University
Yiqi Luo
Yiqi Luo Cornell University
Christopher R. Schwalm
Christopher R. Schwalm Woodwell Climate Research Center

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Additionally, professionals seeking further advancement can explore bridge programs such as the EdS to EdD bridge program, designed to transition educators from specialist certification to doctoral qualifications, enhancing expertise and career potential in environmental education.

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