World's Best Scientists 2026 revealed!

D-Index & Metrics

Environmental Sciences

D-Index
61
Citations
10981
World Ranking
2818
National Ranking
104

De Li Liu 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 De Li Liu 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: 176 publications — 54th percentile

54% of scientists in this discipline score the same or lower.

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

De Li Liu 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 De Li Liu 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: 61 D-Index — 72nd percentile

72% of scientists in this discipline score the same or lower.

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

Overview

De Li Liu is affiliated with the University of New South Wales in Australia. Their research primarily focuses on the intersection of agricultural and biological sciences as well as environmental science, with a significant emphasis on climate change impacts related to agriculture.

Their work covers various subfields including global and planetary change, ecology and systematics, plant science, water science and technology, and soil science. The main topics addressed in their research include climate change impacts on agriculture, climate variability and models, plant water relations and carbon dynamics, hydrology and watershed management studies, rice cultivation and yield improvement, hydrology and drought analysis, and plant responses to elevated CO2.

Liu has contributed several recent papers to scientific literature, including:

  • Projecting heat-related excess mortality under climate change scenarios in China, 2021, Nature Communications
  • Dynamic wheat yield forecasts are improved by a hybrid approach using a biophysical model and machine learning technique, 2020, Agricultural and Forest Meteorology
  • Climate change impact on yields and water use of wheat and maize in the North China Plain under future climate change scenarios, 2020, Agricultural Water Management
  • Silver lining to a climate crisis in multiple prospects for alleviating crop waterlogging under future climates, 2023, Nature Communications
  • Using an improved SWAT model to simulate hydrological responses to land use change: A case study of a catchment in tropical Australia, 2020, Journal of Hydrology

Frequent co-authors collaborating with Liu include Puyu Feng, Bin Wang, Qiang Yu, Linchao Li, and Cathy Waters.

The scientist often publishes in journals known for agricultural and environmental research such as Agricultural Systems, SSRN Electronic Journal, Agricultural Water Management, Journal of Hydrology, and European Journal of Agronomy. They have produced multiple publications in each of these venues.

Best Publications

  • Silver lining to a climate crisis in multiple prospects for alleviating crop waterlogging under future climates

    Unknown

  • Projecting heat-related excess mortality under climate change scenarios in China.

    Jun Yang;Maigeng Zhou;Zhoupeng Ren;Mengmeng Li

  • Adapting agriculture to climate change: a review

    Muhuddin Rajin Anwar;De Li Liu;Ian Macadam;Georgina Kelly

  • Estimation of solar radiation in Australia from rainfall and temperature observations

    D.L Liu;B.J Scott

  • Statistical downscaling of daily climate variables for climate change impact assessment over New South Wales, Australia

    De Li Liu;Heping Zuo

  • Machine learning-based integration of remotely-sensed drought factors can improve the estimation of agricultural drought in South-Eastern Australia

    Puyu Feng;Puyu Feng;Bin Wang;De Li Liu;De Li Liu;Qiang Yu;Qiang Yu;Qiang Yu

  • Climate change impacts on phenology and yields of five broadacre crops at four climatologically distinct locations in Australia

    Muhuddin Rajin Anwar;Muhuddin Rajin Anwar;De Li Liu;De Li Liu;Robert Farquharson;Ian Macadam

  • High resolution mapping of soil organic carbon stocks using remote sensing variables in the semi-arid rangelands of eastern Australia

    Bin Wang;Cathy Waters;Susan Orgill;Jonathan Gray

  • Incorporating machine learning with biophysical model can improve the evaluation of climate extremes impacts on wheat yield in south-eastern Australia

    Puyu Feng;Puyu Feng;Bin Wang;De Li Liu;De Li Liu;Cathy Waters

  • Dynamic wheat yield forecasts are improved by a hybrid approach using a biophysical model and machine learning technique

    Puyu Feng;Puyu Feng;Bin Wang;De Li Liu;De Li Liu;Cathy Waters

  • Climate change impact on yields and water use of wheat and maize in the North China Plain under future climate change scenarios

    Dengpan Xiao;Dengpan Xiao;De Li Liu;De Li Liu;Bin Wang;Bin Wang;Puyu Feng;Puyu Feng

  • Projections of drought characteristics in China based on a standardized precipitation and evapotranspiration index and multiple GCMs.

    Ning Yao;Linchao Li;Puyu Feng;Hao Feng

  • Estimating soil organic carbon stocks using different modelling techniques in the semi-arid rangelands of eastern Australia

    Bin Wang;Cathy Waters;Susan Orgill;Annette Cowie

  • Using an improved SWAT model to simulate hydrological responses to land use change: A case study of a catchment in tropical Australia

    Hong Zhang;Hong Zhang;Bin Wang;De Li Liu;De Li Liu;Mingxi Zhang

  • China can be self-sufficient in maize production by 2030 with optimal crop management

    Unknown

  • Spatial Interpolation of Daily Rainfall Data for Local Climate Impact Assessment over Greater Sydney Region

    Xihua Yang;Xiaojin Xie;De Li Liu;Fei Ji

  • Biologically active secondary metabolites of barley. II. Phytotoxicity of barley allelochemicals.

    D. L. Liu;J. V. Lovett

  • Autotoxicity of wheat ( Triticum aestivum L.) as determined by laboratory bioassays

    Hanwen Wu;Jim Pratley;Deirdre Lemerle;Min An

  • Using multi-model ensembles of CMIP5 global climate models to reproduce observed monthly rainfall and temperature with machine learning methods in Australia.

    Bin Wang;Lihong Zheng;De Li Liu;De Li Liu;Fei Ji

  • Developing machine learning models with multi-source environmental data to predict wheat yield in China

    Unknown

  • Mathematical Modeling of Allelopathy. III. A Model for Curve-Fitting Allelochemical Dose Responses

    De Li Liu;Min An;Ian R. Johnson;John V. Lovett

  • Biologically active secondary metabolites of barley. I. Developing techniques and assessing allelopathy in barley.

    D. L. Liu;J. V. Lovett

  • Impact of climate change on wheat flowering time in eastern Australia

    Bin Wang;Bin Wang;Bin Wang;De Li Liu;De Li Liu;Senthold Asseng;Ian Macadam

Frequent Co-Authors

Bin Wang
Bin Wang University of Hawaii at Manoa
Annette Cowie
Annette Cowie University of New England
Garry O'Leary
Garry O'Leary University of Melbourne
Guangdi Li
Guangdi Li Central South University
Hao Feng
Hao Feng Northwest A&F University
Yonghui Yang
Yonghui Yang Chinese Academy of Sciences
Senthold Asseng
Senthold Asseng Technical University of Munich
Hanwen Wu
Hanwen Wu New South Wales Department of Primary Industries
James Cleverly
James Cleverly James Cook University
Yuming Guo
Yuming Guo Monash University

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