Dr.-Ing. Ye Tuo


Picture of Ye Tuo
Place of employment

Chair of Hydrology and River Basin Management (Prof. Disse )

Work:
Arcisstr. 21(0507)/I
80333 München

  • Phone: +49 (89) 289 - 23258
  • Room: 0507.01.761B
  • ye.tuo(at)tum.de

Research focus

  • Catchment scale hydrological modeling
  • Satellite remote sensing in hydrology
  • Machine learning and deep learning in hydrology
  • Long-term drought and flash drought

Professional Career

  • Since 2019 | Lecturer at Technical University of Munich | Courses: “Remote Sensing in Hydrology”, “Hydrological and Environmental River Basin Modelling” and “Rainfall runoff modeling”.
  • Since 2018 | Post-Doctoral researcher and lecturer at Technical University of Munich | Projects: Hios, PROMOS and Danube floodplain.
  • 2015 – 2018 | Ph.D. Research associate for EU project-GLOBAQUA.
  • 2015 – 2017 | Teaching assistant at Technical University of Munich, Germany.

Research Achievements

  • Lu, M., Sun, H., Yan, D., Xue, J., Yi, S., Gui, D., Tuo, Y., & Zhang, W. (2021). Projections of thermal growing season indices over China under global warming of 1.5° C and 2.0° C. Science of The Total Environment, 781, 146774.
  • Arias-Rodriguez, L. F., Duan, Z., Díaz-Torres, J. d. J., Basilio Hazas, M., Huang, J., Kumar, B. U., Tuo, Y., & Disse, M. (2021). Integration of remote sensing and Mexican water quality monitoring system using an extreme learning machine. Sensors, 21(12), 4118.
  • Sun, H., Bai, Y., Lu, M., Wang, J., Tuo, Y., Yan, D., & Zhang, W. (2021). Drivers of the water use efficiency changes in China during 1982–2015. Science of The Total Environment, 799, 149145.
  • Song, Z., & Tuo, Y. (2021). Automated flood depth estimates from online traffic sign images: explorations of a convolutional neural network-based method. Sensors, 21(16), 5614.
  • Ho, S., Tian, L., Disse, M., & Tuo, Y. (2021). A new approach to quantify propagation time from meteorological to hydrological drought. Journal of Hydrology, 603, 127056.
  • Duan, Z., Tuo, Y., Liu, J., Gao, H., Song, X., Zhang, Z., Yang, L., & Mekonnen, D. F. (2019). Hydrological evaluation of open-access precipitation and air temperature datasets using SWAT in a poorly gauged basin in Ethiopia. Journal of Hydrology, 569, 612-626.
  • Wu, S., Zhang, X., Du, J., Zhou, X., Tuo, Y., Li, R., & Duan, Z. (2019). The vertical influence of temperature and precipitation on snow cover variability in the Central Tianshan Mountains, Northwest China. Hydrological Processes, 33(12), 1686-1697.
  • Kopp, M., Tuo, Y., & Disse, M. (2019). Fully automated snow depth measurements from time-lapse images applying a convolutional neural network. Science of The Total Environment, 697, 134213.
  • Vigiak, O., Lutz, S., Mentzafou, A., Chiogna, G., Tuo, Y., Majone, B., Beck, H., de Roo, A., Malagó, A., & Bouraoui, F. (2018). Uncertainty of modelled flow regime for flow-ecological assessment in Southern Europe. Science of The Total Environment, 615, 1028-1047.
  • Tuo, Y., Marcolini, G., Disse, M., & Chiogna, G. (2018). A multi-objective approach to improve SWAT model calibration in alpine catchments. Journal of Hydrology, 559, 347-360.
  • Tuo, Y. (2018). Application of the Soil Water Assessment Tool (SWAT) in alpine catchments: pitfalls and solutions Technische Universität München].
  • Tuo, Y., Marcolini, G., Disse, M., & Chiogna, G. (2018). Calibration of snow parameters in SWAT: Comparison of three approaches in the Upper Adige River basin (Italy). Hydrological Sciences Journal, 63(4), 657-678.
  • Chiogna, G., Marcolini, G., Liu, W., Ciria, T. P., & Tuo, Y. (2018). Coupling hydrological modeling and support vector regression to model hydropeaking in alpine catchments. Science of The Total Environment, 633, 220-229.
  • Tuo, Y., Disse, M., & Chiogna, G. (2017). Applying A Multi-Objective Based Procedure to SWAT Modelling in Alpine Catchments. AGU Fall Meeting Abstracts,
  • Duan, Z., Liu, J., Tuo, Y., Chiogna, G., & Disse, M. (2016). Evaluation of eight high spatial resolution gridded precipitation products in Adige Basin (Italy) at multiple temporal and spatial scales. Science of The Total Environment, 573, 1536-1553.
  • Tuo, Y., Duan, Z., Disse, M., & Chiogna, G. (2016). Evaluation of precipitation input for SWAT modeling in Alpine catchment: A case study in the Adige river basin (Italy). Science of The Total Environment, 573, 66-82.
  • Tuo, Y., Chiogna, G., & Disse, M. (2015). A multi-criteria model selection protocol for practical applications to nutrient transport at the catchment scale. Water, 7(6), 2851-2880