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D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Environmental Sciences 66 2098 2001 207 204 405 15784

Jichun Wu publications per year

The chart shows the history of publications by Jichun Wu between 1970 and 2026, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Jichun Wu published across 57 years, from 1970 to 2026, averaging 9.8 papers a year. Output peaked at 53 publications in 2025. 54 of the 557 publications appeared in the last two years.

No. of publications
10 20 30 40 50
Bar chart. Horizontal axis: year, 1970 to 2026. Vertical axis: number of publications, 0 to 53. Peak 53 publications in 2025. 1970: 1 publication 1971: 0 publications 1972: 0 publications 1973: 0 publications 1974: 0 publications 1975: 0 publications 1976: 0 publications 1977: 0 publications 1978: 0 publications 1979: 0 publications 1980: 0 publications 1981: 0 publications 1982: 0 publications 1983: 0 publications 1984: 0 publications 1985: 0 publications 1986: 0 publications 1987: 0 publications 1988: 0 publications 1989: 0 publications 1990: 0 publications 1991: 0 publications 1992: 0 publications 1993: 2 publications 1994: 1 publication 1995: 1 publication 1996: 1 publication 1997: 0 publications 1998: 1 publication 1999: 0 publications 2000: 1 publication 2001: 0 publications 2002: 1 publication 2003: 5 publications 2004: 9 publications 2005: 6 publications 2006: 10 publications 2007: 8 publications 2008: 10 publications 2009: 12 publications 2010: 10 publications 2011: 21 publications 2012: 10 publications 2013: 13 publications 2014: 15 publications 2015: 20 publications 2016: 29 publications 2017: 31 publications 2018: 46 publications 2019: 45 publications 2020: 40 publications 2021: 41 publications 2022: 41 publications 2023: 36 publications 2024: 36 publications 2025: 53 publications 2026: 1 publication
1970 2026

557 publications in total across all disciplines

View publications per year as a table
Jichun Wu: publications per year, 1970 to 2026
Year Publications
1970 1
1971 0
1972 0
1973 0
1974 0
1975 0
1976 0
1977 0
1978 0
1979 0
1980 0
1981 0
1982 0
1983 0
1984 0
1985 0
1986 0
1987 0
1988 0
1989 0
1990 0
1991 0
1992 0
1993 2
1994 1
1995 1
1996 1
1997 0
1998 1
1999 0
2000 1
2001 0
2002 1
2003 5
2004 9
2005 6
2006 10
2007 8
2008 10
2009 12
2010 10
2011 21
2012 10
2013 13
2014 15
2015 20
2016 29
2017 31
2018 46
2019 45
2020 40
2021 41
2022 41
2023 36
2024 36
2025 53
2026 1
Total 557
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Jichun Wu 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 Jichun Wu 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, 401–410 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: 405 publications — 94th percentile

94% 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
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 44 405
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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Jichun Wu 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 Jichun Wu 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, 66 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: 66 D-Index — 79th percentile

79% 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
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 66
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

Jichun Wu is affiliated with Nanjing University in China and focuses research efforts on environmental science and engineering, with a significant emphasis on hydrology and related subfields. Their scholarly contributions span a broad range of topics within these disciplines.

The scientist's research extensively covers several main topics, including:

  • Groundwater flow and contamination studies
  • Hydrology and Watershed Management Studies
  • Groundwater and Isotope Geochemistry
  • Geophysical and Geoelectrical Methods
  • Hydraulic Fracturing and Reservoir Analysis
  • Reservoir Engineering and Simulation Methods
  • Hydrology and Drought Analysis

The main fields of study for Jichun Wu are Environmental Science and Engineering, with notable subfields comprising Environmental Engineering, Water Science and Technology, Ocean Engineering, Global and Planetary Change, and Geophysics.

The frequent venues for publication include journals with a focus on hydrology and water resources, showing a consistent presence in:

  • Journal of Hydrology
  • Water Resources Research
  • SSRN Electronic Journal
  • Water Research
  • Zenodo (CERN European Organization for Nuclear Research)

Coauthor collaborations are a prominent aspect of Jichun Wu's network, with recurrent partnerships involving:

  • Jianfeng Wu
  • Xiaoqing Shi
  • Yuanyuan Sun
  • Dong Wang
  • Xiankui Zeng

Key recent publications demonstrate the scientist's focus on water temperature forecasting, hydraulic conductivity estimation, and the application of neural networks and deep learning methods in hydrological studies. Selected recent works include:

  • "Integration of Adversarial Autoencoders With Residual Dense Convolutional Networks for Estimation of Non-Gaussian Hydraulic Conductivities" (2020), Water Resources Research
  • "River water temperature forecasting using a deep learning method" (2021), Journal of Hydrology
  • "Impacts of cascade reservoirs on Yangtze River water temperature: Assessment and ecological implications" (2020), Journal of Hydrology
  • "Water temperature forecasting based on modified artificial neural network methods: Two cases of the Yangtze River" (2020), The Science of The Total Environment
  • "Bayesian convolutional neural networks for predicting the terrestrial water storage anomalies during GRACE and GRACE-FO gap" (2021), Journal of Hydrology

Best Publications

  • Bioaccessibility and health risk of arsenic and heavy metals (Cd, Co, Cr, Cu, Ni, Pb, Zn and Mn) in TSP and PM2.5 in Nanjing, China

    Xin Hu;Yun Zhang;Zhuhong Ding;Tijian Wang

  • TiO2 and ZnO nanoparticles negatively affect wheat growth and soil enzyme activities in agricultural soil

    Wenchao Du;Yuanyuan Sun;Rong Ji;Jianguo Zhu

  • Effects of chronic exposure of 2,4-dichlorophenol on the antioxidant system in liver of freshwater fish Carassius auratus.

    Jingfei Zhang;Hua Shen;Xiaorong Wang;Jichun Wu

  • Deep Convolutional Encoder-Decoder Networks for Uncertainty Quantification of Dynamic Multiphase Flow in Heterogeneous Media

    Shaoxing Mo;Shaoxing Mo;Yinhao Zhu;Nicholas Zabaras;Xiaoqing Shi

  • Land subsidence in China

    Yu-Qun Xue;Yun Zhang;Shu-Jun Ye;Ji-Chun Wu

  • Transport of polystyrene nanoplastics in natural soils: Effect of soil properties, ionic strength and cation type.

    Xiaoli Wu;Xueyan Lyu;Zhengyu Li;Bin Gao

  • Streamflow forecasting using extreme gradient boosting model coupled with Gaussian mixture model

    Lingling Ni;Dong Wang;Jianfeng Wu;Yuankun Wang

  • Suspect and Nontarget Screening of Per- and Polyfluoroalkyl Substances in Wastewater from a Fluorochemical Manufacturing Park

    Yi Wang;Nanyang Yu;Xiaobin Zhu;Huiwei Guo

  • Hydroxyl Radical Based Photocatalytic Degradation of Halogenated Organic Contaminants and Paraffin on Silica Gel

    Ruijuan Qu;Chenguang Li;Jiaoqin Liu;Ruiyang Xiao

  • Transport, retention, and size perturbation of graphene oxide in saturated porous media: effects of input concentration and grain size.

    Yuanyuan Sun;Bin Gao;Scott A. Bradford;Lei Wu

  • Removal of levofloxacin from aqueous solution using rice-husk and wood-chip biochars

    Shengze Yi;Bin Gao;Yuanyuan Sun;Jichun Wu

  • Progression and mitigation of land subsidence in China

    Shujun Ye;Yuqun Xue;Jichun Wu;Xuexin Yan

  • Fractionation and health risks of atmospheric particle-bound As and heavy metals in summer and winter.

    Yuanyuan Sun;Xin Hu;Jichun Wu;Hongzhen Lian

  • Cost-effective sampling network design for contaminant plume monitoring under general hydrogeological conditions

    Jianfeng Wu;Chunmiao Zheng;Calvin C. Chien

  • A modeling study of seawater intrusion in Alabama Gulf Coast, USA

    Jin Lin;Jin Lin;Jin Lin;J. Blake Snodsmith;Chunmiao Zheng;Jianfeng Wu

  • Responses of the antioxidant defenses of the Goldfish Carassius auratus, exposed to 2,4-dichlorophenol.

    J.F. Zhang;H. Liu;Y.Y. Sun;Y.Y. Sun;X.R. Wang

  • Integration of Adversarial Autoencoders With Residual Dense Convolutional Networks for Estimation of Non-Gaussian Hydraulic Conductivities

    Shaoxing Mo;Shaoxing Mo;Nicholas Zabaras;Xiaoqing Shi;Jichun Wu

  • A cloud model-based approach for water quality assessment

    Dong Wang;Dengfeng Liu;Hao Ding;Vijay P. Singh

  • River water temperature forecasting using a deep learning method

    Rujian Qiu;Yuankun Wang;Bruce Rhoads;Dong Wang

  • Bioaccumulation and ROS generation in liver of Carassius auratus, exposed to phenanthrene

    Ying Yin;Haixia Jia;Yuanyuan Sun;Hongxia Yu

  • Deep Autoregressive Neural Networks for High-Dimensional Inverse Problems in Groundwater Contaminant Source Identification

    Shaoxing Mo;Shaoxing Mo;Nicholas Zabaras;Xiaoqing Shi;Jichun Wu

Frequent Co-Authors

Bin Gao
Bin Gao University of Florida
Vijay P. Singh
Vijay P. Singh Texas A&M University
Dong Wang
Dong Wang Peking University
Rong Ji
Rong Ji Nanjing University
Dongxiao Zhang
Dongxiao Zhang Southern University of Science and Technology
Nicholas Zabaras
Nicholas Zabaras University of Notre Dame
Chunmiao Zheng
Chunmiao Zheng Southern University of Science and Technology
Ming Ye
Ming Ye Florida State University
André Revil
André Revil Université Savoie Mont Blanc
Hongxia Yu
Hongxia Yu Nanjing University

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