World's Best Scientists 2026 revealed!

D-Index & Metrics

Environmental Sciences

D-Index
68
Citations
12456
World Ranking
1904
National Ranking
180

Fanghua Hao 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 Fanghua Hao sits on this spectrum.

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: 283 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: 25 scientists 501–510 publications: 17 scientists 511–520 publications: 18 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 681–686 publications: 3 scientists 687+ publications: 100 scientists
41 publications 687+

This scientist: 214 publications — 69th percentile

69% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 687 publications or more.

Fanghua Hao 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 Fanghua Hao sits on this spectrum.

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: 199 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: 19 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: 99 scientists
30 D-Index 125+

This scientist: 68 D-Index — 81st percentile

81% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 125 D-Index or more.

Overview

Fanghua Hao is affiliated with Beijing Normal University in China, focusing primarily on environmental science with a substantial body of work in global and planetary change.

Their research encompasses several subfields including:

  • Global and Planetary Change
  • Water Science and Technology
  • Ecology
  • Ecology, Evolution, Behavior and Systematics
  • Soil Science

Main topics studied by Fanghua Hao cover a wide range of environmental and agricultural concerns such as:

  • Climate variability and models
  • Hydrology and Drought Analysis
  • Hydrology and Watershed Management Studies
  • Plant Water Relations and Carbon Dynamics
  • Remote Sensing in Agriculture
  • Climate change impacts on agriculture
  • Soil erosion and sediment transport

Among the recent publications, key papers address drought dynamics, machine learning applications in agriculture, and climate extremes:

  • "Drought propagation under global warming: Characteristics, approaches, processes, and controlling factors" (2022, The Science of The Total Environment)
  • "Integrated phenology and climate in rice yields prediction using machine learning methods" (2020, Ecological Indicators)
  • "Compound droughts and hot extremes: Characteristics, drivers, changes, and impacts" (2022, Earth-Science Reviews)
  • "Agricultural drought prediction in China based on drought propagation and large-scale drivers" (2021, Agricultural Water Management)
  • "Characterization of agricultural drought propagation over China based on bivariate probabilistic quantification" (2021, Journal of Hydrology)

Fanghua Hao frequently collaborates with several co-authors, notably:

  • Xuan Zhang
  • Zengchao Hao
  • Yongshuo H. Fu
  • Sifang Feng
  • Yang Xu

The scientist has published extensively in academic journals, with a notable presence in:

  • Journal of Hydrology
  • International Journal of Climatology
  • The Science of The Total Environment
  • Agricultural Water Management
  • Water

Best Publications

  • Drought propagation under global warming: Characteristics, approaches, processes, and controlling factors.

    Unknown

  • Heavy metal loss from agricultural watershed to aquatic system: A scientometrics review.

    Wei Ouyang;Yidi Wang;Chunye Lin;Mengchang He

  • Integrated phenology and climate in rice yields prediction using machine learning methods

    Yahui Guo;Yongshuo Fu;Fanghua Hao;Xuan Zhang

  • Compound droughts and hot extremes: Characteristics, drivers, changes, and impacts

    Unknown

  • Propagation from meteorological drought to hydrological drought under the impact of human activities: A case study in northern China

    Yang Xu;Xuan Zhang;Xiao Wang;Zengchao Hao

  • Changes in the severity of compound drought and hot extremes over global land areas

    Zengchao Hao;Fanghua Hao;Vijay P Singh;Xuan Zhang

  • Predicting hydrologic response to climate change in the Luohe River Basin using the SWAT model

    X. Zhang;R. Srinivasan;F. Hao

  • Properties comparison of biochars from corn straw with different pretreatment and sorption behaviour of atrazine.

    Xuchen Zhao;Wei Ouyang;Fanghua Hao;Chunye Lin

  • Soil erosion dynamics response to landscape pattern

    Wei Ouyang;Andrew K. Skidmore;Fanghua Hao;Tiejun Wang

  • Identification of sources of heavy metals in agricultural soils using multivariate analysis and GIS

    Yushu Shan;Yushu Shan;Mats Tysklind;Fanghua Hao;Wei Ouyang

  • Soil erosion and sediment yield and their relationships with vegetation cover in upper stream of the Yellow River

    Wei Ouyang;Fanghua Hao;Andrew K. Skidmore;A.G. Toxopeus

  • Larger temperature response of autumn leaf senescence than spring leaf-out phenology.

    Yongshuo H. Fu;Yongshuo H. Fu;Shilong Piao;Shilong Piao;Nicolas Delpierre;Fanghua Hao

  • Runoff Simulation of the Headwaters of the Yellow River Using The SWAT Model With Three Snowmelt Algorithms1

    Xuesong Zhang;Raghavan Srinivasan;Bekele Debele;Fanghua Hao

  • Exploring the application of artificial intelligence technology for identification of water pollution characteristics and tracing the source of water quality pollutants.

    Puze Wang;Jiping Yao;Guoqiang Wang;Fanghua Hao

  • Long-term vegetation landscape pattern with non-point source nutrient pollution in upper stream of Yellow River basin

    Wei Ouyang;Wei Ouyang;Andrew K. Skidmore;A.G. Toxopeus;Fanghua Hao

  • An Overview of Drought Monitoring and Prediction Systems at Regional and Global Scales

    Zengchao Hao;Xing Yuan;Youlong Xia;Fanghua Hao

  • Agricultural drought prediction in China based on drought propagation and large-scale drivers

    Yu Zhang;Zengchao Hao;Sifang Feng;Xuan Zhang

  • Characterization of agricultural drought propagation over China based on bivariate probabilistic quantification

    Yang Xu;Xuan Zhang;Zengchao Hao;Vijay P. Singh

  • Compound Extremes in Hydroclimatology: A Review

    Zengchao Hao;Vijay P. Singh;Fanghua Hao

  • Variations of compound precipitation and temperature extremes in China during 1961-2014.

    Xinying Wu;Zengchao Hao;Fanghua Hao;Xuan Zhang

  • Probabilistic evaluation of the impact of compound dry-hot events on global maize yields

    Sifang Feng;Zengchao Hao;Xuan Zhang;Fanghua Hao

  • Daylength helps temperate deciduous trees to leaf-out at the optimal time.

    Yongshuo H. Fu;Yongshuo H. Fu;Xuan Zhang;Shilong Piao;Shilong Piao;Fanghua Hao

  • Vegetation NDVI Linked to Temperature and Precipitation in the Upper Catchments of Yellow River

    Fanghua Hao;Xuan Zhang;Wei Ouyang;Andrew K. Skidmore

Frequent Co-Authors

Wei Ouyang
Wei Ouyang Beijing Normal University
Zengchao Hao
Zengchao Hao Beijing Normal University
Yongshuo H. Fu
Yongshuo H. Fu Beijing Normal University
Vijay P. Singh
Vijay P. Singh Texas A&M University
Chunye Lin
Chunye Lin Beijing Normal University
Shilong Piao
Shilong Piao Peking University
Youlong Xia
Youlong Xia M-Systems
Andrew K. Skidmore
Andrew K. Skidmore University of Twente
Ivan A. Janssens
Ivan A. Janssens University of Antwerp
Mats Tysklind
Mats Tysklind Umeå University

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