黄津辉

1.       加拿大土木工程学会（CSCE）会士（Fellow），国际事务委员会委员，主席

2.       世界工程组织联合会（WFEO）水专委会委员

3.       中国水利学会流域发展战略委员会委员

4.       中国城镇供水排水协会，海绵城市建设专业委员会委员

5.       中国地质学会水文地质专业委员委员

6.       “水资源保护”期刊（EI）编委

7.       Journal of Water Management Modelling  编委

8.       Journal of Groundwater Science and Engineering 编委

9.       天津市时空信息工程技术实验室  学术委员会委员

10.   SRC城市街景设计研究中心公园城市专业委员会副主任

11.   加拿大注册工程师协会会员

12.   加拿大水技术交流中心副理事长

在中国，加拿大，美国，阿拉伯地区，南美洲完成生态水文及生态修复等多项科研及咨询项目

（一）国际项目（代表性项目）

1）  美国加利福尼亚州Sears Point Bay湿地修复重建研究

2）  加拿大新斯科舍省Halifax城市CSO（Combined Sewer Outflow）研究

3）  加拿大安大略省Barrie市Lover’s Creek 流域水文研究 

4）  加拿大大多伦多地区（TRCA）防洪预警系统开发研究

5）  加拿大安大略省Oakville城市北部开发中的低影响开发方式研究（BMP/LID Study for North Oakville Development, Town of Oakville, Ontario）

6）  加拿大安大略省Don River 水质监测及模拟研究

7）  南美厄瓜多尔首都基多国际机场暴雨管理系统研究及设计

8）  美国绿色建筑LEED认证项目（20多项） 

（二）国内项目

1）  2021-2024：深圳市科技计划面上项目（JCYJ20210324120807021）：深圳快速城市化进程对城市区域土壤蒸发及植被蒸腾影响机理研究（课题负责人）

2）  2016-2020：国家重点研发计划（2016YFC0400709）：西部地区农村供排水水质智能化监测评估技术研究与示范（课题负责人）

3）  2017-2020：水体污染控制与治理科技重大专项（2017 ZX 07106001）：天津中心城区海绵城市建设运行管理技术体系构建与示范（参与人）

4）  2018: 中国市政工程华北设计研究总院有限公司：呼和浩特市水系连通及湿地修复方案（项目负责人）

5）  2018：中国城市规划设计研究院：鹤壁市淇水春天小区海绵城市改造设计--软件模拟（项目负责人）

6）  2016-2017: 中加科技合作：智慧海绵城市决策预警系统研发（项目负责人）

7）  2016-2017：中国城市规划设计研究院：河南汝州市海绵城市建设专项规划-城市排水防涝体系模拟评估专题研究（项目负责人）

8）  2015-2016：中国城市规划设计研究院：鹤壁市海绵城市建设专项规划-城市排水防涝体系模拟评估专题研究（项目负责人）

9）  2015-2015：天津市科委：天津市暴雨内涝监测预警系统研究（项目负责人）

10）  2016-2017：国家自然科学基金委（41561124015）：气候变化对中国华北平原和加拿大魁北克地区水资源的影响（项目负责人）

11）  2012-2014：新加坡国立大学“湄公河流域防洪减灾与气候变化研究”（项目负责人）

12）  2013-2014：天津空港经济区，天津空港经济区西四道景观湖入河河水生态修复-人工湿地设计及研究 (5.7万平米潜流+表流人工湿地) （项目负责人）

13）  2012-2012 天津空港经济区，天津空港经济区环河北路河水生态修复-人工湿地设计及研究 (4万平米表流人工湿地) （项目负责人）

14）  2012-2013：水利部海河水利委员会：水资源保护规划内源及外源污染控制技术研究（项目负责人）

15）  2012-2014：水利部公益性项目（201201114）：黄河河口地区水资源利用与水生态修复技术（子课题负责人）

16）  2011-2011：水利部水资源费项目：漳河平原段生态治理与修复方案研究（项目负责人）

17）  2011-2011：国家气象局气象关键技术集成与应用项目（CMAGJ2011M05）：设计暴雨和城市雨涝风险预估技术研究与示范（项目负责人）

18）  2011-2011：天津空港经济区生态水系水质提升方案研究（项目负责人）

19）  2010-2012：教育部新世纪优秀人才（NCET-09-0586），气候变化与饮用水水源安全（项目负责人）。

20）  2007-2010：科技部国际合作项目（2007DFA70860）中加合作项目石羊河生态修复与示范（于2011 年获水利部大禹科学技术奖一等奖，证书号DYJ20110308-G08，项目参与人）

Selected Publications:

[1]     Zhang, H; Huang, J.J.*; (2025). A Transferable Remote Sensing Framework Using Enhanced Tasseled Cap Transformation for Global Classification of Aquatic and Terrestrial Vegetation Across Freshwater and Coastal Environments, IEEE Transactions on Geoscience and Remote Sensing, Under Review (IF =8.2)

[2]     Fathi,S.; Vakili, A. T.; Kantoush, S. A.; Huang, J.J.*; Nourani, V.; *(2025). System Dynamics and Novel Z-Number Based TOPSIS Method for Uncertainty Assessment of Water Resource Carrying Capacity Under Different Environment Change Scenarios，Expert Systems With Applications, Under Review (IF = 7.5)

[3]     Najafi, H., and Huang, J.J.*,(2025). Advancing Group Decision-Making in Sustainable Water Resource Management: A Z-number Enhanced Framework for Wastewater Reuse，Journal of Hydrology, Under Review (IF =6.708)

[4]     Tian, S., Zhu, X. T., Guo, H. W., Zhang, H., Zhang, Z.J., Huang, J.J.* (2025). An Optimal Strategy for Estimating Chlorophyll-a Concentration in Case II Waters to Support Sustainable Development Goals, Advances-in-Space-Research, 75(29), https://doi.org/10.1016/j.asr.2025.03.003. (IF =2.8)

[5]     Nourani, V.*; Tosan,M.; Huang, J.J.*; Gebremichael, M.; Kantoush,S. A.;Dastourani, M.; (2025). Advances in Multi-Source Data Fusion for Precipitation Estimation: Remote Sensing and Machine Learning Perspectives, Earth-Science Reviews 270 (2025) 105253, https://doi.org/10.1016/j.earscirev.2025.105253. (IF =10.8)

[6]     Nourani, V.*, Paknezhad, N. J., Sharghi,E., Zhang, Y., Huang, J.J.* (2025). Coherent change of groundwater level and salinity under climate change and anthropogenic impacts: A modular framework，Journal of Hydrology 661 (2025) 133615, https://doi.org/10.1016/j.jhydrol.2025.133615. (IF =6.708)

[7]     Yan, H.K., Zhang, H., Huang, J.J.*(2025). Quantifying coastal water quality responses to pandemic-induced human mobility: Insights from Bohai Bay, Water Research 285 (2025) 124043, https://doi.org/10.1016/j.watres.2025.124043. (IF =13.4)

[8]     Xia, C., Chang, C., Yu, Z., Huang, J.J.*, Wang. Q.J. (2025) The role of air conditioning waste heat in shaping short-duration intense rainfall: Insights from coastal twin cities, Atmospheric Research 326 (2025) 108309, https://doi.org/10.1016/j.atmosres.2025.108309. (IF =4.24)

[9]     Najafi, H., He. Z., Huang, J.J.,(2025) A Climate-Informed Early Warning Framework for Urban Water Pipe Leakage: Integrating Environmental Drivers with LSTM Based Risk Prediction, https://doi.org/10.21203/rs.3.rs-7089419/v1. (IF =xX)

[10]  Dąbrowska, D., Vakili, A. T., Fathi, S., Huang, J.J., Nourani, V., (2025).Uncertainty Assessment of Extreme Precipitation Predictions under the Synergic Influence of Teleconnection and Local Events, Journal-of-Hydrometeorology, https://doi.org/10.1175/JHM-D-25-0013.1. (IF =5.6)

[11]  Chen, H., Wei, Y., Huang, J.J*., (2025). Urbanization diminishes net ecosystem productivity by changing the landscape pattern, Agriculture and Forest Meteorology, https://doi.org/10.1016/j.agrformet.2024.110369. (IF =5.6)

[12]  Zhou, S., Song, M., Shan, K., Razaqpur, A.G. & Huang, J.J. (2024b). Parametric and optimization analyses of a dynamic trombe wall incorporating PCM to save heating energy under cold climate zones. Renewable Energy, 237. https://doi.org/10.1016/j.renene.2024.121537. (IF = 9.0)

[13]  Zhou, S., Song, M., Shan, K., Razaqpur, A., Huang, J.J., Zhu, X. et al. (2024a). Passive application of PCMs for the Trombe wall: a review. Energy Storage and Saving. https://doi.org/10.1016/j.enss.2024.06.001.

[14]  Wei, Y., Chen, H. & Huang, J.J.* (2024). Dynamics of urban latent heat in response to climate change and urbanization: What would be a global threshold? Journal of Hydrology, 643. https://doi.org/10.1016/j.jhydrol.2024.132002. (IF = 5.9)

[15]  Wang, J., Chen, C., Huang, J.J*, Xiao, N. & Li, S. (2025). Synchronous or selective removal of nitrate and Cr(VI) by montmorillonite supported sulfidized nanoscale zerovalent iron: Role of Fe(II) and S0. Separation and Purification Technology, 354. https://doi.org/10.1016/j.seppur.2024.129006. (IF = 8.1)

[16]  Chen, H., Wei, Y. & Huang, J.J.* (2024). Divergent Drivers of Declining Urban Vegetation Productivity and Transpiration During Heatwaves. Journal of Geophysical Research: Atmospheres. https://doi.org/10.1029/2023JD040390 (IF = 3.8)

[17]  Guo, H. W., Huang, J. J.*, Zhu, X. T., Tian, S., & Wang, B. L. (2024). Spatiotemporal variation reconstruction of total phosphorus in the Great Lakes since 2002 using remote sensing and deep neural network. Water Research, 255, 15, Article 121493. https://doi.org/10.1016/j.watres.2024.121493 (IF = 11.4)

[18]  Li, H., Chen, H., & Huang, J. J.* (2024). Partitioning urban forest evapotranspiration based on integrating eddy covariance of water vapor and carbon dioxide fluxes. Science of The Total Environment, 935, 18, Article 173201. https://doi.org/10.1016/j.scitotenv.2024.173201 (IF = 8.2)

[19]  Li, H., Lan, Z. Q., Chen, H., & Huang, J. J.* (2024). How do non-halophyte locust trees thrive in temperate coastal regions: A study of salinity and multiple environmental factors on water uptake patterns. Hydrological Processes, 38(3), 14, Article e15122. https://doi.org/10.1002/hyp.15122. (IF = 2.8)

[20]  Nourani, V., Najafi, H., Maleki, S., Paknezad, N. J., Huang, J. J., Zhang, P. W., & Mohammadisepasi, S. (2024). Z-number based assessment of groundwater vulnerability to seawater intrusion. Journal of Hydrology, 632, 16, Article 130859. https://doi.org/10.1016/j.jhydrol.2024.130859. (IF = 5.9)

[21]  Wei, Y. Z., Chen, H., & Huang, J. J.* (2024). Response of surface energy components to urban heatwaves and its impact on human comfort in coastal city. Urban Climate, 54, 15, Article 101836. https://doi.org/10.1016/j.uclim.2024.101836. (IF = 6.0)

[22]  Zhang, Z. J., Zhang, H., Jin, Y. F., Guo, H. W., Tian, S., Huang, J. J.*, & Zhu, X. T. (2024). Analysing the spatiotemporal variation and influencing factors of Lake Chaohu's CDOM over the past 40 years using machine learning. Ecohydrology, 17(3), 12. https://doi.org/10.1002/eco.2639. (IF = 2.5)

[23]  Zhu, X. T., Guo, H. W., & Huang, J. J.* (2024). Urban flood susceptibility mapping using remote sensing, social sensing and an ensemble machine learning model. Sustainable Cities and Society, 108, 16, Article 105508. https://doi.org/10.1016/j.scs.2024.105508. (IF = 10.5)

[24]  Chen, H., Li, H., Wei, Y. Z., McBean, E., Liang, H., Wang, W. M., & Huang, J. J. *(2024). Partitioning eddy covariance CO2 fluxes into ecosystem respiration and gross primary productivity through a new hybrid four sub-deep neural network. Agriculture Ecosystems & Environment, 361, 16, Article 108810. https://doi.org/10.1016/j.agee.2023.108810. (IF = 6.0)

[25]  Chen, H., Wei, Y. Z., & Huang, J. J.* (2024). Widespread increase in plant transpiration driven by global greening. Global and Planetary Change, 235, 17, Article 104395, https://doi.org/10.1016/j.gloplacha.2024.104395. (IF = 4.0)

[26]  Feng, S. T., Zhang, B. C., Wang, J. S., & Huang, J. J.* (2024). Zero-valent iron in phosphate removal: Unraveling the role of particle size and dissolved oxygen. Journal of Water Process Engineering, 60, 10, Article 105180. https://doi.org/10.1016/j.jwpe.2024.105180. (IF = 6.3)

[27]  Chang, C., Chen, Y., & Huang, J. J.* (2023). A comparison study on the role of urbanization in altering the short-duration and long-duration intense rainfall. Science of The Total Environment, 857, 159290, https://doi.org/10.1016/j.scitotenv.2022.159290.(IF = 9.8)

[28]  Chang, C. C., Chen, Y. H., & Huang, J. J. *(2023). Variability of Rainfall Areal Reduction Factors for a Coastal City: A Case Study of Shenzhen, China. Journal of Hydrologic Engineering, 28(6), 12, Article 05023008. https://doi.org/10.1061/jhyeff.Heeng-5813. (IF = 2.4)

[29]  Chen, H., Huang, J. J.*, Dash, S. S., McBean, E., Singh, V. P., Li, H., Wei, Y. Z., Zhang, P. W., & Zhou, Z. Q. (2023). A non-linear theoretical dry/wet boundary-based two-source trapezoid model for estimation of land surface evapotranspiration. Hydrological Sciences Journal, 68(11), 1591-1609. https://doi.org/10.1080/02626667.2023.2224921. (IF = 3.5)

[30]  Chen, H., Huang, J. J.*, Li, H., Wei, Y. Z., & Zhu, X. T. (2023). Revealing the response of urban heat island effect to water body evaporation from main urban and suburb areas. Journal of Hydrology, 623, 21, Article 129687. https://doi.org/10.1016/j.jhydrol.2023.129687. (IF = 6.4)

[31]  Chen, H., Huang, J. J.*, Liang, H., Wang, W., Li, H., Wei, Y., Jiang, A. Z., & Zhang, P. (2023). Can evaporation from urban impervious surfaces be ignored? Journal of Hydrology, 616, 128582, https://doi.org/10.1016/j.jhydrol.2022.128582. (IF = 6.4)

[32]  Chen, H., Huang, J. J.*, Liang, H., Wang, W. M., Li, H., Wei, Y. Z., Jiang, A. Z., & Zhang, P. W. (2023). Integration of flux footprint and physical mechanism into convolutional neural network model for enhanced simulation of urban evapotranspiration. Journal of Hydrology, 619, 18, Article 129016. https://doi.org/10.1016/j.jhydrol.2022.129016. (IF = 6.4)

[33]  Chen, H., Razaqpur, A. G., Wei, Y. Z., Huang, J. J.*, Li, H., & McBean, E. (2023). Estimation of global land surface evapotranspiration and its trend using a surface energy balance constrained deep learning model. Journal of Hydrology, 627, 18, Article 130224. https://doi.org/10.1016/j.jhydrol.2023.130224. (IF = 6.4)

[34]  Chen, H., Wei, Y. Z., & Huang, J. J.* (2023). Altered landscape pattern dominates the declined urban evapotranspiration trend. Journal of Hydrology, 627, 11, Article 130296. https://doi.org/10.1016/j.jhydrol.2023.130296. (IF = 6.4)

[35]  Chen, H., Zhou, Z. Q., Li, H., Wei, Y. Z., Huang, J.J.*, H., Liang, H., & Wang, W. M. (2023). Evaluation the Performance of Three Types of Two-Source Evapotranspiration Models in Urban Woodland Areas. Sustainability, 15(12), 18, Article 9826. https://doi.org/10.3390/su15129826. (IF = 3.9)

[36]  Fan, L., Wu, R., Huang, J. J.*, & Selvaganapathy, P. R. (2023). One-step fabrication of the novel electrochemical sensing platform for the ultrasensitive determination of Microcystin-LR. Sensors and Actuators B-Chemical, 390, 9, Article 133961. https://doi.org/10.1016/j.snb.2023.133961. (IF = 8.4)

[37]  Fan, L., Wu, R., Patel, V., Huang, J. J.*, & Selvaganapathy, P. R. (2023). Solid-state, reagent-free and one-step laser-induced synthesis of graphene-supported metal nanocomposites from metal leaves and application to glucose sensing. Analytica Chimica Acta, 1264, 10, Article 341248. https://doi.org/10.1016/j.aca.2023.341248 (IF = 6.2)

[38]  Foroumandi, E., Nourani, V., Huang, J. J., & Moradkhani, H. (2023). Drought monitoring by downscaling GRACE-derived terrestrial water storage anomalies: A deep learning approach. Journal of Hydrology, 616, 16, Article 128838. https://doi.org/10.1016/j.jhydrol.2022.128838 (IF = 6.4)

[39]  Guo, H. W., Zhu, X. T., Huang, J. J.*, Zhang, Z. J., Tian, S., & Chen, Y. H. (2023). An enhanced deep learning approach to assessing inland lake water quality and its response to climate and anthropogenic factors. Journal of Hydrology, 620, 19, Article 129466. https://doi.org/10.1016/j.jhydrol.2023.129466 (IF = 6.4)

[40]  Nourani, V., Tapeh, A. H. G., Khodkar, K., & Huang, J. J. (2023). Assessing long-term climate change impact on spatiotemporal changes of groundwater level using autoregressive-based and ensemble machine learning models. Journal of Environmental Management, 336, 14, Article 117653. https://doi.org/10.1016/j.jenvman.2023.117653 (IF = 8.7)

[41]  Pan, L., He, X. P., Chen, J. H., Huang, J. J.*, Wang, Y. N., Liang, S. K., & Wang, B. D. (2023). Detection, occurrence, influencing factors and environmental risks of paralytic shellfish toxins in seawater in a typical mariculture bay. Chemosphere, 313, 11, Article 137372. https://doi.org/10.1016/j.chemosphere.2022.137372 (IF = 8.8)

[42]  Tian, S., Guo, H. W., Xu, W., Zhu, X. T., Wang, B., Zeng, Q. H., Mai, Y. Q., & Huang, J.J.* (2023). Remote sensing retrieval of inland water quality parameters using Sentinel-2 and multiple machine learning algorithms. Environmental Science and Pollution Research, 30(7), 18617-18630. https://doi.org/10.1007/s11356-022-23431-9 (IF = 5.8)

[43]  Yan, R., & Huang, J. J.* (2023). Confident learning-based Gaussian mixture model for leakage detection in water distribution networks. Water Research, 247, 15, Article 120773. https://doi.org/10.1016/j.watres.2023.120773 (IF = 12.8)

[44]  Zhang, B. C., Wang, J. S., Feng, S. T., Huang, J. J.*, & Han, X. Y. (2023). The roles of different Fe-based materials in alleviating the stress of Cr(VI) on anammox activity: Performance and mechanism. Chemical Engineering Journal, 475, 13, Article 145739. https://doi.org/10.1016/j.cej.2023.145739 (IF = 15.1)

[45]  Zhu, X. T., Guo, H. W., Huang, J. J.*, Tian, S., & Zhang, Z. J. (2023). A hybrid decomposition and Machine learning model for forecasting Chlorophyll-a and total nitrogen concentration in coastal waters. Journal of Hydrology, 619, 19, Article 129207. https://doi.org/10.1016/j.jhydrol.2023.129207 (IF = 6.4)

[46]  Pan, L., Huang, J. J.*, Chen, J. H., He, X. P., Wang, Y. N., Wang, J. M., & Wang, B. D. (2022). Trace determination of multiple hydrophilic cyanotoxins in freshwater by off- and on-line solid phase extraction coupled to liquid chromatography-tandem mass spectrometry. Science of The Total Environment, 853, 11, Article 158545. https://doi.org/10.1016/j.scitotenv.2022.158545

[47]  Wang, J. S., Huang, J. J.*, Zhou, Y., Liao, Y., Li, S., Zhang, B. C., & Feng, S. T. (2022). Synchronous N and P Removal in Carbon-Coated Nanoscale Zerovalent Iron Autotrophic Denitrification-The Synergy of the Carbon Shell and P Removal [; Early Access]. Environmental Science & Technology, 13. https://doi.org/10.1021/acs.est.2c02376

[48]  Yang, C., Xiao, N., Yang, S. S., & Huang, J. J.* (2022). Micro response mechanism of mini MFC sensor performance to temperature and its applicability to actual wastewater. Chemical Engineering Science, 263, 9, Article 118124. https://doi.org/10.1016/j.ces.2022.118124

[49]  Zhu, X. T., Guo, H. W., Huang, J. J.*, Tian, S., Xu, W., & Mai, Y. Q. (2022). An ensemble machine learning model for water quality estimation in coastal area based on remote sensing imagery. Journal of Environmental Management, 323, 12, Article 116187. https://doi.org/10.1016/j.jenvman.2022.116187

[50]  Wang, J., Zhang, B.,Huang J.* , Liao, Y., Xiao, N. (2022).Elucidating the Role of Carbon Shell in Autotrophic Denitrification Driven by Carbon-coated Nanoscale Zerovalent Iron,Chemical Engineering Journal,434(10). https://doi.org/10.1016/j.cej.2022.134656.

[51]  Guo, H., Huang, J*.,Tian, S., Zhu, X., Wang, B., Zhang, Z. (2022).Performance of deep learning in mapping water quality of Lake Simcoe with long-term Landsat archive,ISPRS Journal of Photogrammetry and Remote Sensing,183,451-469. https://doi.org/10.1016/j.isprsjprs.2021.11.023.

[52]  Chen, H., Huang, J*., McBean, E., Singh, V. (2022). Assessing the effects of end-members determination on regional latent heat flux simulation in trapezoidal framework based model. Agricultural and Forest Meteorology, 312,108734.https://doi.org/10.1016/j.agrformet.2021.108734.

[53]  Chen, H., Huang, J*., McBean, E., Sandeep, S.D., Lan, Z.Z., Jiawei Zhang., Gao, J,J., McBean, E., Singh, V. (2022). Development of a Three-Source Remote Sensing Model for Estimation of Urban Evapotranspiration, Advances in Water Resources 2022, 161,104126.https://doi.org/10.1016/j.advwatres.161.104126.

[54]  Chen, H., Huang, J*., Jiang,A.Z., Han Li., McBean, E., Singh, V. Jiawei Zhang., Lan, Z.Z., Gao, J,J. (2022). An Enhanced Shuttleworth-Wallace Model for Simulation of Evapotranspiration and its Components, Agricultural and Forest Meteorology,313,108769.https://doi.org/10.1016/j.agrformet.2021.108769.

[55]  Chen, H., Huang, J*., Sandeep, S.D., McBean, E., Singh, V., Wei, Y., Han Li. (2022). Assessing the impact of urbanization on urban evapotranspiration and its components using a novel four-source energy balance model, Agricultural and Forest Meteorology,316,108853. https://doi.org/10.1016/j.agrformet.2022.108853.

[56]  Chen, H., Huang, J*., Sandeep, S.D., Wei, Y., Han Li. (2022). A hybrid deep learning framework with physical process description for simulation of evapotranspiration, Journal of Hydrology,606,127422. https://doi.org/10.1016/j.jhydrol.2021.127422.

[57]  Xiao, N., Wang, B., Huang J.* ,Huang, Z., Shi, L. (2022). Aeration strategy based on numerical modelling and the response mechanism of microbial communities under various operating conditions, Journal of Environmental Management ,310,114752. https://doi.org/10.1016/j.jenvman.2022.114752.

[58]  Huang, J*., Xiao, M., Li, Y., Ran,Y., Qian, Z. (2022).The optimization of Low Impact Development placement considering life cycle cost using Genetic Algorithm, Journal of Environmental Management,309,114700.https://doi.org/10.1016/j.jenvman.2022.114700.

[59]  Mei, X., Huang, J*., Jue, H. (2022). Impacts of hydrophobic, hydrophilic, superhydrophobic and superhydrophilic nanofibrous substrates on the thin film composite forward osmosis membranes, Journal of Environmental Chemical Engineering, 10(7). https://doi.org/10.1016/j.jece.2021.106958.

[60]  Liang Fan, Jinhui Jeanne Huang *, Ching Y. Lo, Bin Zhou and Xujin Fu. (2022). Ultrasensitive Photoelectrochemical Microcystin-LR Immunosensor Using Carboxyl-Functionalized Graphene Oxide Enhanced Gold Nanoclusters for Signal Amplification, Analytica Chimica Acta,1185, https://doi.org/10.1016/j.aca.2021.339078.

[61]  Xiao, N., Huang J.*, Catherine, N, M. (2022). The dynamics of soil microbial community structure and nitrogen metabolism influenced by agriculture practices and rainfall, Applied Soil Ecology,172, 104351,https://doi.org/10.1016/j.apsoil.2021.104351.

[62]  Liang Fan, Jinhui Jeanne Huang *, Ching Y. Lo, Bin Zhou and Xujin Fu. (2022). Simplified validation of the ELISA kit determination of Microcystins in surface water. Water Science & Technology,85(3):900-913.https://doi.org/10.2166/wst.2021.640.

[63]  Vahid Nourani, Nardin Jabbarian Paknezhad, Jinhui Jeanne Huang. (2022) .Application of PPIE method to assess the uncertainty and accuracy of multi-climate model-based temperature and precipitation downscaling, Theoretical and Applied Climatology,147(2).https://doi.org/10.1007/s00704-021-03884-7.

[64]  Wang, J., Huang J.* , Catherine, N. M. (2022).Seasonal source identification and source-specific health risk assessment of pollutants in road dust. Environmental Science and Pollution, Research,29(37). https://doi.org/10.1007/s11356-021-16326-8.

[65]  Chen, H., Huang, J*., McBean, E., Sandeep, S.D., Han Li., Jiawei Zhang., Lan, Z.Z., Gao, J,J. (2022). Evapotranspiration partitioning based on field-stable oxygen isotope observations for an urban locust forest land. Ecohydrology, https://doi.org/10.1002/eco.2431

[66]  Guo, H., Huang, J*., Zhu, X., Wang, B., Tian, S., Wang, X., Mai, Y. (2021). A generalized machine learning approach for dissolved oxygen estimation at multiple spatiotemporal scales using remote sensing, Environmental Pollution,288,117734.https://doi.org/10.1016/j.envpol.2021.117734.

[67]  Chen, H., Huang, J*., McBean, E., Singh, V. (2021). Evaluation of alternative two-source remote sensing models in partitioning of land evapotranspiration. Journal of Hydrology. https://doi.org/10.1016/j.jhydrol.2021.126029.

[68]  Chenchao Chang, Yu Li, Yiheng Chen, Jinhui Jeanne Huang*, Ya Zhang. (2021). Advanced statistical analyses of urbanization impacts on heavy rainfall in the Beijing metropolitan area. Urban Climate. https://doi.org/10.1016/j.uclim.2021.100987.

[69]  Yang, C., Xiao, N., Chang, Z., Huang, J.*, Zeng, W. (2021). Biodegradation of TOC by Nano-Fe2O3 modified SMFC and its potential environmental effects, Chemistry Select.,6(22). https://doi.org/10.1002/slct. 202101125.

[70]  Xiao, N., Wang, B., Huang J.* (2021). Hydrodynamic optimization for design and operating parameters of an innovative continuous-flow miniaturized MFC biosensor, Chemical Engineering Science,235:116505.https://doi.org/10.1016/j.ces.2021.116505.

[71]  Huang, J., Chen, S., Liao, Y., Chen, Y., You X., Wang. R. (2021). Performance, fouling and Cleaning of a thin film composite hollow fiber membrane during fertiliser-drawn forward osmosis process for micro-polluted water, Environmental Science Water Research and Technology.2021,7:1279-1291.https://doi.org/10.1016/j.jece.2021.106958.

[72]  Wang, J., Huang J.*,Iseult, L. (2021). Seasonal and short-term variations of bacteria and pathogenic bacteria on road deposited sediments, Environmental Research 204(8):111903. https://doi.org/10.1016/j.envres.2021.111903.

[73]  Zeng, X., Huang, J.*, Hua, B. (2021). Efficient phosphorus removal by a novel halotolerant fungus Aureobasidium sp. MSP8 and the application potential in saline industrial wastewater treatment. Bioresource Technology,334,125237.https://doi.org/10.1016/j.biortech.2021.125237.

[74]  Xiao, N., Wang, B., Huang J.* (2021). Optimization of a continuous-flow miniaturized MFC biosensor by hydrodynamic computational modelling and experimental investigation, Chemical Engineering Journal , https://doi.org/10.1016/j.ces.2021.116505.(IF=8.355)

[75]  Chen, H., Huang, J*., McBean, E. (2020).Development of a Trapezoidal Framework-Based Model (PCALEP) for Partition of Land Evapotranspiration, Journal of Hydrology, 124994, 0022-1694. https://doi.org/10.1016/j.jhydrol.2020.124994.

[76]  Zhao, W., Huang, J.*, Hua, B., Droste, R. (2020). Photosynthetic bioaugmentation strategy for releasing recovering volatile fatty acid inhibition of the anaerobic digestion system, Bioresources Technology, 2020, 311:123501https://doi.org/10.1016/j.biortech.2020.123501.

[77]  Chen, L., Huang, J.*, Hua, B., Droste, R. Salman, M., Zhao, W.; (2020). Effect of steel slag on the anaerobic granulation in recycling waste activated sludge to produce anaerobic granular sludge, Chemosphere,2020, 257, 127291.https://doi.org/10.1016/j.chemosphere.2020.127291.

[78]  Huang, J*., Chen, H., Li, T., McBean, E., Singh V. (2020), A Modified Trapezoidal Framework Model for Partitioning Regional Evapotranspiration, Hydrological Processes, https://doi.org/10.22541/au.158602500.05780501.

[79]  Guo, H., Huang, J.*, Chen, B., McBean, E. (2020).Machine learning based strategy to retrieve water quality for small scale urban waterbody by Sentinel-2, Remote Sensing https://doi.org/10.1080/01431161.2020.1846222.

[80]  Xiao, N., Wu, R., Huang J.*and Selvaganapathy, P. (2020). Influence of wastewater microbial community on the performance of miniaturized microbial fuel cell biosensor, Bioresource Technology，https://doi.org/10.1016/j.biortech.2020.122777.

[81]  Chen, H., Huang, J*., McBean, E. (2020).Quantitative Assessment of Agriculture Practices on Farmland Evapotranspiration Using Eddy Covariance Method and Numeric Modelling, Water Resources Management, https://doi.org/10.1007/s11269-019-02448-9.

[82]  Chen, H., Huang, J*., McBean, E. (2020). Partitioning of Daily Evapotranspiration using a Modified Shuttleworth-Wallace Model and Artificial Intelligence Model for a Cabbage Farmland, Agricultural Water Managemen , https://doi.org/10.1016/j.agwat.2019.105923.

[83]  Zeng, X., Huang, J.*, Hua, B., Champagne P. (2020). Nitrogen removal bacterial strains, MSNA-1 and MSD4, with wide ranges of salinity and pH resistances, Bioresources Technology, https://doi.org/10.1016/j.biortech.2020.123309.

[84]  Kuang, D.. Weichao Kong, Yuxiang Wen, Mengxian Zhao; Jinhui Huang*, Chen Yang (2020) Solution classification with portable smartphone-based spectrometer system under variant shooting conditions by using convolutional neural network, IEEE Sensors Journal, https://doi.org/10.1109/JSEN.2020.2983733.

[85]  Wang, J., Huang, J.J.* and Li, J. (2020); Characterization of the Pollutant Build-up Processes and Concentration/Mass Load in Road Deposited Sediments over a Long Dry Period, Science of the Total Environment, https://doi.org/10.1016/j.scitotenv.2020.137282.

[86]  Xiao, N., Wu, R., Huang J.*and Selvaganapathy, P. (2020). Anode surface modification regulates biofilm community population and the performance of micro-MFC based biochemical oxygen demand sensor, Chemical Engineering Science , https://doi.org/10.1016/j.ces.2020.115691.

[87]  Liao, Y., Zheng, G., Huang, J.*, Tian, M., Wang, R., (2020). Development of robust and superhydrophobic membranes to mitigate membrane scaling and fouling in membrane distillation, Journal of Membrane Science, https://doi.org/10.1016/j.memsci.2020.117962.

[88]  Li, Y.; Huang, J.*.; Hu, M.; Hong, Y.; Tanaka, K.; (2020) Design of low impact development in the urban context considering hydrological performance and life-cycle cost, Journal of Flood Risk Management.https://doi.org/10.1111/jfr3.12625

[89]  Wang, J., Huang, J.*, Li, J. (2019). The Study of Road Sediment Build-up Processes in a Long Dry Period in Semi-Arid Area of China, Science of the Total Environment, 696.https://doi.org/10.1016/j.scitotenv.2019.133788.

[90]  Liu, B., Huang, J*., and McBean, E. A. (2019). Risk Assessment of Hybrid Rain Harvesting System and Other Small Drinking Water Supply Systems by Game Theory and Fuzzy Logic Modelling, Science of Total Environment, https://doi.org/10.1016/j.scitotenv.2019.134436.

[91]  Xiao, N., Wu, R., Huang J.*and Selvaganapathy, P. (2019). Development of a xurographically fabricated miniaturized low-cost, high-performance microbial fuel cell and its application for sensing biological oxygen demand, Sensors & Actuators: B. Chemical, https://doi.org/10.1016/j.snb.2019.127432.

[92]  Ali, S., Hua, B., Huang, J.*, Droste., R, Zhou, Q., Zhao, W. (2019). Effect of different initial low pH conditions on biogas production, composition, and shift in the aceticlastic methanogenic population, Bioresources Technology, https://doi.org/10.1016/j.biortech.2019.121579.

[93]  Huang, J.*, Tian, Y., Wang, R. , Tian, M., Liao, Y (2019). Fabrication of bead-on-string polyacrylonitrile nanofibrous air filters with superior filtration efficiency and ultralow pressure drop, Separation and Purification Technology, https://doi.org/10.1016/j.seppur.2019.116377.

[94]  McBean, E., Salsali, H., Bhatti, M., and Huang, J. * (2019). Source Characterization of Disinfectants in Municipal Wastewaters, Acta Chimica and Pharmceutica Indica.

[95]  Huang, J. , Zhang, N., Choi, G., McBean, E. A., and Zhang, Q.(2018). Spatiotemporal Patterns and Trends of Precipitation and Their Correlations with Related Meteorological Factors by Two Sets of Reanalysis Data in China, Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-756.

[96]  McBean, E,, Hamid Salsali, Munir Bhatti and J Huang * (2018). Funeral Homes and Slaughterhouses: Contributions of Emerging Contaminants to Municipal Wastewaters, Acta Chimica and Pharmaceutica India, 2018,8(2).

[97]  Wen, Y., Kuang, D., Huang J. and Zhang, Yi. (2017). Microaxicave Colour Analysis System for Fluoride Concentration using a Smart Phone. RSC Advances, 2017,7,42339 (DOI: 10.1039/c7Ra07727k).

[98]  McBean, E., and Huang, J; (2017). Sustainability Risks of Coastal Cities from Climate Change, The Global Environmental Engineers, 2017, 4, 1-9.https://doi.org/10.15377/2410-3624.2017.04.01.1

[99]  Huang, J*., Li, Y.; Yin, J.; McBean, E.; (2016). Precipitation Regional Extreme Mapping as a Tool for Ungauged Areas and the Assessment of Climate Changes, Hydrological Processes, 30, 1940–1954  (https://doi.org/10.1002/hyp.10743).

[100]  Choulnard, A., Anderson, B., Wotton, B. and Huang, J. (2015). Comparative study of cold-climate constructed wetland technology in Canada and Northern China for water resource protection, Environmental Reviews (https://doi.org/10.1139/er-2014-0082)

[101]  Huang, J*., Lin, X., Wang, H., Wang, J. (2015). The precipitation driven correlation based mapping method (PCM) for identifying the critical source areas of non-point source pollution, Journal of Hydrology, 524:100–110，doi:10.1016/j.jhydrol.2015.02.011.

[102]  Zhang, Y., Huang, J*., Chen, L., Qi, L., (2015). Eutrophication Forecasting and Management by Artificial Neural Network: a Case Study at Yuqiao Reservoir in North China, Journal of Hydroinformatics, 17（4），Pages 679–695，doi:10.2166/hydro.2015.115.

[103]  Huang, J*., and Xiang, W.; (2015). Investigation of Point Source and Non-Point Source Pollution for Panjiakou Reservoir in North China by Modelling Approach, Water Quality Research Journal of Canada, V50 (2), pp 167–181,doi: 10.2166/wqrjc.2014.019.

[104]  Huang, J*., Du, M. , McBean, E., Wang, H., Wang, J-H. (2014). A coupled Bayesian and fault tree methodology to assess future groundwater conditions in light of climate change, Hydrology and Earth System Sciences (Discussion) 11, 9361–9397, 2014 , doi:10.5194/hessd-11-9361-2014.

[105]  Huang, J*., Gao, X.; Balch, G.; Wootton, B.; Jorgensen, S.; Anderson, B. (2014). Modelling of Vertical Flow Constructed Wetlands for Treatment of Domestic Sewage and Stormwater Runoff by SubWet 2.0, Ecological Engineering, 74, 8-12;http://dx.doi.org/10.1016/j.ecoleng.2014.10.027.

[106]  Huang, J*., Li, Y.; Niu, S.; Zhou, S. (2014). Assessing the Performances of LID Alternatives by Long Term Simulation for Semi-Arid Area in Tianjin, Northern China, Water Science and Technology. 2014;69(3):566-572. doi:10.2166/wst.2014.228.

[107]  Zhang, C, McBean, E., and Huang, J. (2014). “A Virtual Water Assessment Methodology For Cropping Pattern Investigation”, Water Resources Management, June 2014, Volume 28, Issue 8, pp 2331-2349 (SCI, IF2.463), DOI 10.1007/s11269-014-0618-y.

[108]  Qi, L., Zhang, Y., Peng, J., Qi, C., Huang, J. and Liu, D. (2014). Water requirement of vegetation and infiltration method to determine ecological water requirement of dried up, Water Science and Technology 2014;69(3):566-572. doi: 10.2166/wst.2013.743.

[109]  Huang, J*.(2014). The Development of a Design and Modelling Framework for Grey Water Reuse in Tianjin, China, ASCE International Conference on Sustainable Infrastructure 2014, Long Beach, USA, November 6-8, 2014. (Keynotes Speech). http://dx.doi.org/10.1061/9780784478745.050 EI.

[110]  Li, T. and Huang, J*. (2014). Separation of Soil Evaporation And Vegetation Transpiration By MODIS Data For Central And Northern China. CUNY Academic Works. http://academicworks.cuny.edu/cc_conf_hic/172.

[111]  Li, H., Huang, J*, Zhou, X., Lin, C., Luo, Y. (2012).Isolation and Identification of Two Psychrotrophs Strains and Preliminary Research on Their Application. Meteorological and Environment Research.

[112]  Cheng, H., Huang, J. and McBean, E. (2011). Reply to comment on “Using Bayesian Statistics to Estimate the Coefficients Of a Two-Component Second-order Chlorine Bulk Decay Model for a Water Distribution System”. Water Research, 2011,45(6), 2355-2357.

[113]  Huang, J., and McBean, E. (2009). Data Mining to Identify Contaminant Intrusion Events into Water Distribution Systems. ASCE Journal of Water Resources Planning and Management, 2009,135(6), 466-474.

[114]  Lee, M., McBean, E., Schuster, C., and Huang, J., (2009). A Fault Tree and Fuzzy Logic Methodology for Risk Assessment of Drinking Water Supply Failures, ASCE Journal of Water Resources Planning and Management, 135(6), 547-552.

[115]  Huang, J. and McBean, E. A. (2008). Using Bayesian Statistics to Estimate the Chlorine Wall Decay Coefficients for a Water Supply System, ASCE Journal of Water Resources Planning and Management, 134(2), 129-137.

[116]  Huang, J., McBean, E. A. and Shen, H.(2008).  Data Mining as a Tool to Identify Contaminant Sources in Water Distribution Systems, 10th International Water Distribution System Analysis conference, Kruger National Park, South Africa. August 17-20, 2008, www.uj.ac.za/wdsa2008 EI, http://dx.doi.org/10.1061/41024(340)97 EI

[117]  Huang, J. and McBean, E. A. (2007). Using Bayesian Statistics to Estimate the Coefficients of a Two- Component Second-Order Chlorine Decay Model for a Water Distribution System, Water Research, 41(2), 287-294.

[118]  Ostfeld et al; (2008). The Battle of Water Sensor Networks (BWSN): A Design Challenge for Engineers and Algorithms, ASCE Journal of Water Resources Planning and Management, 134(6), 556-558.

[119]  Huang, J. and McBean E A.; (2007). Chapter 19, Water Quality Modeling using Fault Tree Method. Contemporary Modeling of Urban Water Systems, Monograph15. Published by CHI, Guelph, ISBN: 139780973671636.

[120]  Huang, J. and McBean, E. A. (2006). Chapter 11, Comparison of Analytical and Simulation Approaches for Assessing Robustness of Reliability for Water Distribution Systems. Intelligent Modeling of Urban Water Systems, Monograph 14, Published by CHI, Guelph, ISBN: 0973671629.

[121]  Huang, J. and McBean, E. A. (2006). Use of Bayesian Statistics to Study Chlorine Decay for a Water Distribution System, Water Distribution System Analysis 2006, Cincinnati, Ohio USA. August 27-29, 2006, www.eng.uc.edu/wdsa2006/ EI. http://dx.doi.org/10.1061/40941(247)148 EI.

[122]  Huang, J., McBean, E. A., and James, W. (2006). Multi-objective Optimization Approach for Monitoring Sensor Placement in Water Distribution Systems, Water Distribution System Analysis 2006, Cincinnati, Ohio USA. August 27-29, 2006, www.eng.uc.edu/wdsa2006/ EI, http://dx.doi.org/10.1061/40941(247)113.

[123]  Huang, J., McBean, E., and James, W. (2005). Chapter 7, A Review of Reliability Analysis for Water Quality in Water Distribution Systems, Urban Water Systems, James, et al. (editors), Monograph 13, Published by CHI, Guelph, ISBN: 0973671602.

[124]   Huang, J.; James, W. and James, W. R. C. (2005). Chapter 3, A Lifecycle Cost Based Design Optimization Model for Stormwater Management System. Effective Modelling of Urban Water Systems, Monograph 13, Published by CHI, Guelph, ISBN: 0973671602.