World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
54
Citations
11013
World Ranking
3187
National Ranking
205

Guangtao Fu publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Guangtao Fu sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 166 publications — 34th percentile

34% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Guangtao Fu D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Guangtao Fu sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 54 D-Index — 68th percentile

68% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

Guangtao Fu is affiliated with the University of Exeter in the United Kingdom. Their research primarily focuses on environmental science and engineering, with a strong emphasis on water-related challenges and solutions.

The main fields of study associated with Guangtao Fu include:

  • Environmental Science
  • Engineering

Within these fields, they have contributed extensively to several subfields, notably:

  • Water Science and Technology
  • Environmental Engineering
  • Civil and Structural Engineering
  • Global and Planetary Change
  • Ocean Engineering

Their research topics cover areas such as:

  • Flood Risk Assessment and Management
  • Water Systems and Optimization
  • Urban Stormwater Management Solutions
  • Water resources management and optimization
  • Hydrological Forecasting Using AI
  • Water-Energy-Food Nexus Studies
  • Hydrology and Watershed Management Studies

Guangtao Fu has contributed numerous papers, with recent publications including:

  • "The role of deep learning in urban water management: A critical review", 2022, Water Research
  • "Unraveling the effect of inter-basin water transfer on reducing water scarcity and its inequality in China", 2021, Water Research
  • "Pollution exacerbates China's water scarcity and its regional inequality", 2020, Nature Communications
  • "Sponge city practice in China: A review of construction, assessment, operational and maintenance", 2020, Journal of Cleaner Production
  • "A comprehensive review on the design and optimization of surface water quality monitoring networks", 2020, Environmental Modelling & Software

Key frequent co-authors in their work include:

  • David Butler
  • Haixing Liu
  • Siao Sun
  • Zhiguo Yuan
  • Dragan Savić

Guangtao Fu frequently publishes in journals such as:

  • Water Research
  • Journal of Water Resources Planning and Management
  • Journal of Hydrology
  • Journal of Environmental Management
  • SSRN Electronic Journal

In addition to journal articles, Guangtao Fu has authored books published by UWA Publishing, including:

  • "Quantification and Modelling of Fugitive Greenhouse Gas Emissions from Urban Water Systems", 2022
  • "Water-Wise Cities and Sustainable Water Systems: Concepts, Technologies, and Applications", 2020

Best Publications

  • Two-Archive Evolutionary Algorithm for Constrained Multiobjective Optimization

    Ke Li;Renzhi Chen;Guangtao Fu;Xin Yao

  • The effects of low impact development on urban flooding under different rainfall characteristics.

    Hua-peng Qin;Zhuo-xi Li;Guangtao Fu

  • Water-energy-food nexus: Concepts, questions and methodologies

    Chi Zhang;Xiaoxian Chen;Yu Li;Wei Ding

  • A global analysis approach for investigating structural resilience in urban drainage systems

    Seith N. Mugume;Diego E. Gomez;Guangtao Fu;Raziyeh Farmani

  • Reliable, resilient and sustainable water management: the Safe & SuRe approach

    David Butler;Sarah Ward;Chris Sweetapple;Maryam Astaraie-Imani

  • A fuzzy optimization method for multicriteria decision making: An application to reservoir flood control operation

    Guangtao Fu

  • An integrated framework for high-resolution urban flood modelling considering multiple information sources and urban features

    Yuntao Wang;Yuntao Wang;Albert S. Chen;Guangtao Fu;Slobodan Djordjević

  • Global resilience analysis of water distribution systems

    Kegong Diao;Kegong Diao;Chris Sweetapple;Raziyeh Farmani;Guangtao Fu

  • Multiple objective optimal control of integrated urban wastewater systems

    Guangtao Fu;David Butler;Soon-Thiam Khu

  • Deep learning identifies accurate burst locations in water distribution networks.

    Xiao Zhou;Zhenheng Tang;Weirong Xu;Fanlin Meng

  • Optimal Design of Water Distribution Systems Using Many-Objective Visual Analytics

    Guangtao Fu;Zoran Kapelan;Joseph R. Kasprzyk;Patrick Reed

  • Unraveling the effect of inter-basin water transfer on reducing water scarcity and its inequality in China.

    Siao Sun;Xian Zhou;Haixing Liu;Yunzhong Jiang

  • A new approach to urban water management: Safe and sure

    David Butler;Raziyeh Farmani;Guangtao Fu;Sarah Ward

  • Topological attributes of network resilience: A study in water distribution systems.

    Fanlin Meng;Guangtao Fu;Raziyeh Farmani;Chris Sweetapple

  • Sobol′’s sensitivity analysis for a distributed hydrological model of Yichun River Basin, China

    Chi Zhang;Jinggang Chu;Guangtao Fu

  • Assessing the combined effects of urbanisation and climate change on the river water quality in an integrated urban wastewater system in the UK.

    Maryam Astaraie-Imani;Zoran Kapelan;Guangtao Fu;David Butler

  • An Integrated Environmental Assessment of Green and Gray Infrastructure Strategies for Robust Decision Making

    Arturo Casal-Campos;Guangtao Fu;David Butler;Andrew Moore

  • Multi-objective optimisation of wastewater treatment plant control to reduce greenhouse gas emissions.

    Christine Sweetapple;Guangtao Fu;David Butler

  • Spatiotemporal patterns and source attribution of nitrogen load in a river basin with complex pollution sources.

    Xiaoying Yang;Qun Liu;Guangtao Fu;Yi He

  • Battle of the Water Networks II

    Angela Marchi;Elad Salomons;Avi Ostfeld;Zoran Kapelan

  • Two-Archive Evolutionary Algorithm for Constrained Multi-Objective Optimization

    Ke Li;Renzhi Chen;Guangtao Fu;Xin Yao

Frequent Co-Authors

David Butler
David Butler University of Exeter
Zoran Kapelan
Zoran Kapelan Delft University of Technology
Soon-Thiam Khu
Soon-Thiam Khu Tianjin University
Chi Zhang
Chi Zhang Hohai University
Dragan Savic
Dragan Savic University of Exeter
Patrick M. Reed
Patrick M. Reed Cornell University
Weisi Guo
Weisi Guo Cranfield University
Jim W. Hall
Jim W. Hall University of Oxford
Zhiguo Yuan
Zhiguo Yuan City University of Hong Kong
Giorgio Mannina
Giorgio Mannina University of Palermo

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