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HAN Feng
Research Associate Professor

Basic Introduction

Dr. Feng Han is currently an Research Associate Professor at the School of Environmental Science and Engineering, Southern University of Science and Technology, in collaboration with Professor Yi Zheng. He has long been engaged in research in the fields of eco-hydrological and water environmental simulation, specializing in numerical simulation of hydrological processes, ecological processes, and water quality processes at the watershed scale. His research includes the development of new computational models, exploration of efficient model-data fusion methods, and investigation into the coupling paradigms of deep learning and process-based models. He has published more than 40 papers (including 38 SCI papers) in domestic and international academic journals, such as Water Research, Water Resources Research, Journal of Hydrology, and Research of Environmental Sciences (In Chinese). He also authored one academic work, contributed chapters to two edited volumes, and obtained one software copyright. Dr. Han is one of the main developers of the three-dimensional distributed eco-hydrological model HEIFLOW (Hydrological-Ecological Integrated watershed-scale FLOW). The model has been applied in over a dozen basins including the Heihe River Basin, the Pearl River Basin, the Luanhe River Basin, the Miho Basin (South Korea), the Skjern Basin (Denmark) and the San Joaquin Basin (United States).

 

Professional Experience

2021-present: Research Associate Professor, School of Environmental Science and Engineering, Southern University of Science and Technology

2018-2021: Research Assistant Professor, School of Environmental Science and Engineering, Southern University of Science and Technology

2015-2018: Post-doctoral research fellow, School of Environmental Science and Engineering, Southern University of Science and Technology

 

Education

2008-2015: Ph.D., Mechanics (Energy and Resources Engineering), Peking University

2004-2008: Bachelor, Theoretical and Applied Mechanics, Peking University


Selected funded projects

1. Research on the integrated eco-hydrological modelling of the degradation and restoration of natural grassland in arid region (2019-2021), funded by NSFC (No. 41807164), PI.

2. Improving water quality to sustain watershed ecosystems and socio-economic development under climate change: a China-Chile comparative study (2020-2024), founded by NSFC-CONICYT (5191101522), main participant.

3. Prediction and allocation of mountain-water-forest-cropland-lake-grasse system in Qilian Mountains (2018-2023), founded by Chinese Academy of Sciences (No. XDA20100104), main participant.

4. Shenzhen municipal engineering lab of environmental IoT technologies (2018-2020), founded by Shenzhen Development and Reform Commission, key member.

5. Uncertainty analysis of integrated surface water-groundwater modelling based on multi-source data assimilation (2017-2018), funded by China Postdoctoral Science Foundation (No. 2017M612505), PI

6. System Behaviors and regulation of ecohydrological processes in the middle and lower Heihe River Basin (2013-2016), funded by NSFC (No. 91225301), main participant.

 

Research Interests

1. Eco-hydrological modeling

2. Non-point source pollution simulation

3. Data assimilation and uncertainty analysis

4. Machine learning applications


Published Works

Books

1. Zheng, Y., Han, F. and Tian, Y. (2021) Methods and applications of eco-hydrological simulation in the Heihe River Basin (In Chinese). Science Press, 1-265.

Academic papers in Chinese

2. Ding, J., Hu, Z., Liu, Z., Zhang, Q., Liu, W., Han, F.* and Zheng, Y. (2023) Assessment of non-point source load of heavy metals using a watershed water quality model. Research of Environmental Sciences 36(6), 1125-1134.

3. Ding, J.*, He, S., Huang, Y., Wang, S., Wang, K., Qiang, Y. and Han, F. (2022) Analysis on characteristics and sources of phosphorus pollution in the soil and water environment of the Maquekeng Watershed. Journal of Water Resources Research 11(6), 572-579.

4. Luo, X., Yin, C., Zhang, G.*, Liu, Y., Niu, C. and Han, F. (2021) Water environmentstatus and comprehensive management measures of watershed in Beijing. Water Resources Protection 37(5), 140-146.

5. Zhang, Q., Han, F., Liu, Z. * and Xiang, R. (2018) Calculation of mercury non-point source pollution of Xiangjiang River Zhuzhou section based on the SWAT model. Sichuan Environment 37(2), 32-37.

6. Lin, Z., Zheng, Y.*, Xiang, R., Liu, Z., Zhang, Q. and Han, F. (2012) Simulation of the nonpoint sources load of heavy metals and its uncertainty analysis: a case study of cadmium pollution at the Xiangjiang River in the Zhuzhou city. Resources and Environment in the Yangtze Basin 21(09), 1112-1118.

7. Zheng, Y.*, Wang, X., Wu, B. and Han, F. (2010) Regulation, information and decision support for urban nonpoint source pollution management. Advances in Water Science 21(05), 726-732.

SCI papers

8. Han, F., Tian, Q., Chen, N.*, Hu, Z., Wang, Y., Xiong, R., Xu, P., Liu, W., Stehr, A., Barra, R.O. and Zheng, Y. (2024) Assessing ammonium pollution and mitigation measures through a modified watershed non-point source model. Water Research 254, 121372.

9. Ge, Y.*, Han, F., Wu, F., Zhao, Y., Li, H., Tian, Y., Zheng, Y., Luan, W., Zhang, L., Cai, X., Ma, C. and Li, X. (2024) Sustainable decision making based on systems integration and decision support system promoting endorheic basin sustainability. Decision Support Systems 179, 114169.

10. Wang, C., Jiang, S., Zheng, Y.*, Han, F., Kumar, R., Rakovec, O. and Li, S. (2024) Distributed hydrological modeling with physics‐encoded deep learning: A general framework and its application in the Amazon. Water Resources Research 60(4), e2023WR036170.

11. Han, F., Hu, Z., Chen, N., Wang, Y., Jiang, J. and Zheng, Y.* (2023) Assimilating low-cost high-frequency sensor data in watershed water quality modeling: A Bayesian approach. Water Resources Research, 59, e2022WR033673.

12. Han, F., Zheng, Y.*, Zhang, L.*, Xiong, R., Hu, Z., Tian, Y. and Li, X. (2023) Simulating drip irrigation in large-scale and high-resolution ecohydrological models: From emitters to the basin. Agricultural Water Management 289, 108500.

13. Li, S., Zheng, Y.*, Han, F., Xu, P. and Chen, A. (2023) Ecological flow management identified as leading driver of grassland greening in the gobi desert using deep learning. Geophysical Research Letters 50(11), e2023GL103369.

14. Wang, M., Xu, B.*, Li, Y., Han, F., Du, X., Zhang, J., Zhang, C. and Peng, Y. (2023) A surface and ground‐water integrated investigation of streamflow drying up in semi‐arid regions. Hydrological Processes 37(6), e14903.

15. Chen, X., Zheng, Y.*, Wang, L., Han, F., Zeng, Z., Xu, P., Fu, G. and Zhang, C. (2022) Climate change may neutralize the sediment starvation in mega deltas caused by hydropower dams. Sustainable Horizons 4, 100041.

16. Du, E., Tian, Y., Cai, X., Zheng, Y., Han, F., Li, X., Zhao, M., Yang, Y. and Zheng, C.* (2022) Evaluating distributed policies for conjunctive surface water‐groundwater management in large river basins: Water uses versus hydrological impacts. Water Resources Research 58(1), e2021WR031352.

17. Xiong, R., Zheng, Y.*, Chen, N., Tian, Q., Liu, W., Han, F., Jiang, S., Lu, M. and Zheng, Y. (2022) Predicting Dynamic Riverine Nitrogen Export in Unmonitored Watersheds: Leveraging Insights of AI from Data-Rich Regions. Environmental Science & Technology 56(14), 10530-10542.

18. Han, F., Zheng, Y.*, Tian, Y., Li, X., Zheng, C. and Li, X. (2021) Accounting for field-scale heterogeneity in the ecohydrological modeling of large arid river basins: Strategies and relevance. Journal of Hydrology 595, 126045.

19. Han, J., Xin, Z.*, Han, F.*, Xu, B., Wang, L., Zhang, C. and Zheng, Y. (2021) Source contribution analysis of nutrient pollution in a P-rich watershed: Implications for integrated water quality management. Environmental Pollution 279, 116885.

20. Li, X.*, Zhang, L.*, Zheng, Y., Yang, D., Wu, F., Tian, Y., Han, F., Gao, B., Li, H., Zhang, Y., Ge, Y., Cheng, G., Fu, B., Xia, J., Song, C. and Zheng, C. (2021) Novel hybrid coupling of ecohydrology and socioeconomy at river basin scale: A watershed system model for the Heihe River basin. Environmental Modelling & Software 141, 105058.

21. Xiong, R., Zheng, Y.*, Han, F. and Tian, Y. (2021) Improving the Scientific Understanding of the Paradox of Irrigation Efficiency: An Integrated Modeling Approach to Assessing Basin‐Scale Irrigation Efficiency. Water Resources Research 57(11), e2020WR029397.

22. Zhang, Z., Zheng, Y.*, Han, F., Xiong, R. and Feng, L. (2021) Recovery of an endorheic lake after a decade of conservation efforts: Mediating the water conflict between agriculture and ecosystems. Agricultural Water Management 256, 107107.

23. Chen, X., Zheng, Y.*, Xu, B., Wang, L., Han, F. and Zhang, C.* (2020) Balancing competing interests in the Mekong River Basin via the operation of cascade hydropower reservoirs in China: Insights from system modeling. Journal of Cleaner Production 254, 119967.

24. Mao, G., Liu, J.*, Han, F., Meng, Y., Tian, Y., Zheng, Y. and Zheng, C. (2020) Assessing the interlinkage of green and blue water in an arid catchment in Northwest China. Environmental Geochemistry and Health 42(3), 933-953.

25. Xu, B., Li, Y.*, Han, F., Zheng, Y., Ding, W., Zhang, C., Wallington, K. and Zhang, Z. (2020) The transborder flux of phosphorus in the Lancang-Mekong River Basin: Magnitude, patterns and impacts from the cascade hydropower dams in China. Journal of Hydrology 590, 125201.

26. Zheng, Y., Tian, Y.*, Du, E., Han, F., Wu, Y., Zheng, C. and Li, X. (2020) Addressing the water conflict between agriculture and ecosystems under environmental flow regulation: An integrated modeling study. Environmental Modelling & Software 134, 104874.

27. Niu, G., Zheng, Y.*, Han, F. and Qin, H. (2019) The nexus of water, ecosystems and agriculture in arid areas: A multiobjective optimization study on system efficiencies. Agricultural Water Management 223, 105697.

28. Chen, C., Tian, Y., Zhang, Y.-K., He, X., Yang, X., Liang, X., Zheng, Y., Han, F., Zheng, C. and Yang, C.* (2019) Effects of agricultural activities on the temporal variations of streamflow: trends and long memory. Stochastic Environmental Research and Risk Assessment 33(8-9), 1553-1564.

29. Han, F. and Zheng, Y.* (2018) Joint analysis of input and parametric uncertainties in watershed water quality modeling: A formal Bayesian approach. Advances in Water Resources 116, 77-94.

30. Jiang, J.*, Han, F., Zheng, Y., Wang, N. and Yuan, Y. (2018) Inverse uncertainty characteristics of pollution source identification for river chemical spill incidents by stochastic analysis. Frontiers of Environmental Science & Engineering 12(5), 6-21.

31. Jiang, S., Zheng, Y.*, Babovic, V., Tian, Y. and Han, F. (2018) A computer vision-based approach to fusing spatiotemporal data for hydrological modeling. Journal of Hydrology 567, 25-40.

32. Li, X.*, Cheng, G., Ge, Y., Li, H., Han, F., Hu, X., Tian, W., Tian, Y., Pan, X., Nian, Y., Zhang, Y., Ran, Y., Zheng, Y., Gao, B., Yang, D., Zheng, C., Wang, X., Liu, S. and Cai, X. (2018) Hydrological cycle in the Heihe River Basin and its implication for water resource management in endorheic basins. Journal of Geophysical Research: Atmospheres 123(2), 890-914.

33. Sun, Z., Zheng, Y.*, Li, X., Tian, Y.*, Han, F., Zhong, Y., Liu, J. and Zheng, C. (2018) The nexus of water, ecosystems, and agriculture in endorheic river basins: A system analysis based on integrated ecohydrological modeling. Water Resources Research 54(10), 7534-7556.

34. Tian, Y., Xiong, J., He, X., Pi, X., Jiang, S., Han, F. and Zheng, Y.* (2018) Joint operation of surface water and groundwater reservoirs to address water conflicts in arid regions: An integrated modeling study. Water 10(8), w10081105.

35. Tian, Y., Zheng, Y.*, Han, F., Zheng, C. and Li, X. (2018) A comprehensive graphical modeling platform designed for integrated hydrological simulation. Environmental Modelling & Software 108, 154-173.

36. Han, F. and Zheng, Y.* (2016) Multiple-response Bayesian calibration of watershed water quality models with significant input and model structure errors. Advances in Water Resources 88, 109-123.

37. Wu, X., Zheng, Y.*, Wu, B., Tian, Y., Han, F. and Zheng, C. (2016) Optimizing conjunctive use of surface water and groundwater for irrigation to address human-nature water conflicts: A surrogate modeling approach. Agricultural Water Management 163, 380-392.

38. Zheng, Y.*, Luo, X., Zhang, W., Wu, X., Zhang, J. and Han, F. (2016) Transport mechanisms of soil-bound mercury in the erosion process during rainfall-runoff events. Environmental Pollution 215, 10-17.

39. Zheng, Y.* and Han, F. (2015) Markov Chain Monte Carlo (MCMC) uncertainty analysis for watershed water quality modeling and management. Stochastic Environmental Research and Risk Assessment 30(1), 293-308.

40. Luo, X., Zheng, Y.*, Lin, Z., Wu, B., Han, F., Tian, Y., Zhang, W. and Wang, X. (2015) Evaluating potential non-point source loading of PAHs from contaminated soils: a fugacity-based modeling approach. Environmental Pollution 196, 1-11.

41. Wu, B., Zheng, Y.*, Wu, X., Tian, Y., Han, F., Liu, J. and Zheng, C. (2015) Optimizing water resources management in large river basins with integrated surface water‐groundwater modeling: A surrogate‐based approach. Water Resources Research 51(4), 2153-2173.

42. Wu, B., Zheng, Y.*, Tian, Y., Wu, X., Yao, Y., Han, F., Liu, J. and Zheng, C. (2014) Systematic assessment of the uncertainty in integrated surface water-groundwater modeling based on the probabilistic collocation method. Water Resources Research 50(7), 5848-5865.

43. Luo, X., Zheng, Y.*, Wu, B., Lin, Z., Han, F., Zhang, W. and Wang, X. (2013) Impact of carbonaceous materials in soil on the transport of soil-bound PAHs during rainfall-runoff events. Environmental Pollution 182, 233-241.

44. Zheng, Y.*, Luo, X., Zhang, W., Wu, B., Han, F., Lin, Z. and Wang, X. (2012) Enrichment behavior and transport mechanism of soil-bound PAHs during rainfall-runoff events. Environmental Pollution 171, 85-92.

45. Zheng, Y.*, Wang, W., Han, F. and Ping, J. (2011) Uncertainty assessment for watershed water quality modeling: A Probabilistic Collocation Method based approach. Advances in Water Resources 34(7), 887-898.