World's Best Scientists 2026 revealed!

D-Index & Metrics

Environmental Sciences

D-Index
48
Citations
7713
World Ranking
5592
National Ranking
45

Joon Ha Kim 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 Joon Ha Kim 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: 187 publications — 59th percentile

59% of scientists in this discipline score the same or lower.

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

Joon Ha Kim 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 Joon Ha Kim 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: 48 D-Index — 44th percentile

44% of scientists in this discipline score the same or lower.

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

Overview

Joon Ha Kim is affiliated with the Gwangju Institute of Science and Technology in South Korea. Their research primarily focuses on environmental science and engineering, with significant contributions in the fields of water science and technology, biomedical engineering, industrial and manufacturing engineering, environmental engineering, and electrical and electronic engineering.

Their work often centers on membrane separation technologies, membrane-based ion separation techniques, water quality monitoring technologies, hydrological forecasting using artificial intelligence, water quality monitoring and analysis, hydrology and watershed management studies, and membrane separation and gas transport.

Frequent publication venues for their research include:

  • Desalination and Water Treatment
  • Desalination
  • Membranes
  • Ecological Engineering

Selected recent papers authored or co-authored by Joon Ha Kim are:

  • "A comprehensive review of the feasibility of pressure retarded osmosis: Recent technological advances and industrial efforts towards commercialization," 2020, Desalination
  • "Analysis of the relation between pollutant loading and water depth flowrate changes in a constructed wetland for agricultural nonpoint source pollution management," 2020, Ecological Engineering
  • "Cost-based optimization, feasibility study, and sensitivity analysis of forward osmosis/crystallization/reverse osmosis with high-temperature operation for high-salinity seawater desalination," 2024, Desalination
  • "Prediction of permeate water flux in forward osmosis desalination system using tree-based ensemble machine learning models," 2022, Desalination and Water Treatment
  • "Theoretical Analysis of a Mathematical Relation between Driving Pressures in Membrane-Based Desalting Processes," 2021, Membranes

Their research collaborations include frequent co-authorship with Seo Jin Ki, Seung Ji Lim, Sung Ho Chae, Jeongwoo Moon, and Kwanho Jeong.

Best Publications

  • Decadal and shorter period variability of surf zone water quality at Huntington Beach, California.

    Boehm Ab;Grant Sb;Kim Jh;Mowbray Sl

  • A comprehensive review of hybrid forward osmosis systems: Performance, applications and future prospects

    Laura Chekli;Sherub Phuntsho;Jung Eun Kim;Jihye Kim

  • Prediction of effluent concentration in a wastewater treatment plant using machine learning models

    Hong Guo;Kwanho Jeong;Jiyeon Lim;Jeongwon Jo

  • Development of early-warning protocol for predicting chlorophyll-a concentration using machine learning models in freshwater and estuarine reservoirs, Korea

    Yongeun Park;Kyung Hwa Cho;Jihwan Park;Sung Min Cha

  • Generation of enterococci bacteria in a coastal saltwater marsh and its impact on surf zone water quality.

    S B Grant;B F Sanders;A B Boehm;J A Redman

  • Overview of systems engineering approaches for a large-scale seawater desalination plant with a reverse osmosis network

    Young M. Kim;Seung J. Kim;Yong S. Kim;Sangho Lee

  • Linking land-use type and stream water quality using spatial data of fecal indicator bacteria and heavy metals in the Yeongsan river basin.

    Joo-Hyon Kang;Seung Won Lee;Kyung Hwa Cho;Seo Jin Ki

  • Toward a combined system of forward osmosis and reverse osmosis for seawater desalination

    Yong Jun Choi;June Seok Choi;Hyun Je Oh;Sangho Lee

  • Gap‐filling approaches for eddy covariance methane fluxes: A comparison of three machine learning algorithms and a traditional method with principal component analysis

    Yeonuk Kim;Mark S. Johnson;Sara H. Knox;T. Andrew Black

  • Prediction of contamination potential of groundwater arsenic in Cambodia, Laos, and Thailand using artificial neural network.

    Kyung Hwa Cho;Suthipong Sthiannopkao;Yakov A. Pachepsky;Kyoung-Woong Kim

  • Surf zone entrainment, along-shore transport, and human health implications of pollution from tidal outlets

    S. B. Grant;J. H. Kim;B. H. Jones;S. A. Jenkins

  • The relative importance of water temperature and residence time in predicting cyanobacteria abundance in regulated rivers.

    YoonKyung Cha;Kyung Hwa Cho;Hyuk Lee;Taegu Kang

  • Smart water grid: the future water management platform

    Seung Won Lee;Sarper Sarp;Dong Jin Jeon;Joon Ha Kim

  • Use of barcoded pyrosequencing and shared OTUs to determine sources of fecal bacteria in watersheds.

    Tatsuya Unno;Jeonghwan Jang;Dukki Han;Joon Ha Kim

  • Release of Escherichia coli from the bottom sediment in a first-order creek: Experiment and reach-specific modeling

    Kyung Hwa Cho;Kyung Hwa Cho;Y.A. Pachepsky;Joon Ha Kim;A.K. Guber

  • Reverse osmosis (RO) and pressure retarded osmosis (PRO) hybrid processes: Model-based scenario study

    Jihye Kim;Minkyu Park;Shane A. Snyder;Joon Ha Kim

  • Mathematical model of flat sheet membrane modules for FO process: Plate-and-frame module and spiral-wound module

    B. Gu;D.Y. Kim;J.H. Kim;D.R. Yang

  • Simulation of forward osmosis membrane process: Effect of membrane orientation and flow direction of feed and draw solutions

    Da Hee Jung;Jijung Lee;Do Yeon Kim;Young Geun Lee

  • Molecular dynamics simulations in membrane-based water treatment processes: A systematic overview

    Hannah Ebro;Young Mi Kim;Joon Ha Kim

  • Meteorological effects on the levels of fecal indicator bacteria in an urban stream: a modeling approach.

    Kyung Hwa Cho;Sung Min Cha;Joo-Hyon Kang;Seung Won Lee

  • Determination of a constant membrane structure parameter in forward osmosis processes

    Minkyu Park;Ji Jung Lee;Sangho Lee;Joon Ha Kim

Frequent Co-Authors

Kyung Hwa Cho
Kyung Hwa Cho Korea University
In S. Kim
In S. Kim Gwangju Institute of Science and Technology
Stanley B. Grant
Stanley B. Grant Virginia Tech
Ho Kyong Shon
Ho Kyong Shon University of Technology Sydney
Yakov A. Pachepsky
Yakov A. Pachepsky Agricultural Research Service
Kyoung-Woong Kim
Kyoung-Woong Kim Gwangju Institute of Science and Technology
Michael J. Sadowsky
Michael J. Sadowsky University of Minnesota
Shane A. Snyder
Shane A. Snyder Georgia Institute of Technology
Seungkwan Hong
Seungkwan Hong Korea University
GwangPyo Ko
GwangPyo Ko Seoul National University

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