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Duong Tran Anh

Msc. Duong Tran Anh

Technische Universität München

Lehrstuhl für Wasserbau und Wasserwirtschaft (Prof. Rutschmann)

Postadresse

Richard Wagner Straße 3

80333 München

Tel.: +49 (89) 289 - 24257

Raum: 503 (floor 5)

tran.duong@tum.de

Higher Education

  • Doctoral Candidate. Technical University of Munich, Germany, 2013-2018;
  • Master Degree. Asian Institute of Technology, Bangkok, Thailand, 2010-2012;
  • Bachelor Degree. Hanoi Water Resources University, Vietnam, 2000-2005.

Professional Experiences

  • Researcher, Institute of Hydraulic and Water Resources Engineering, Technical University of Munich, 2013-2018
  • Research Fellow, Department of Civil and Environmental Engineering, Colorado State University, Fort Collins, CO 80523, USA.
  • DAAD-Research Fellow, Leichtweiß-Institute for Hydraulic Engineering and Water Resources, TU Braunschweig, Germany, 2011-2012.
  • ASIAN-Scholar, Chulalongkorn University, Bangkok, Thailand, April - October. 2013.
  • APEC Research Fellow, APEC climate center, Busan, South Korea, July - October 2012.
  • Project Manager, Southern Regional Hydro-Meteorological Center, MONRE, Ho Chi Minh, 2010 - 2012.
  • Project: Strengthening capabilities of flood waring and monitoring in Mekong Delta River financed World Bank (Cr.4114-VN, WB4), 2008-2012
  • Project Manager, Thanh Hoa Project Management Unit, DARD, 2010 - 2013.
  • - Project: Cau Khai drainage system financed by World Bank (2.0 million USD); 2005-2010
  • - Project: Integrated Rural Development of the Central Province financed by ADB (8.4 million USD), 2006-2009;
  • - Project: Emergency Rehabilitation of Calamity Damage Project financed by ADB (16.8 million USD), 2007-2010.

A few selected publications

1. Duong, T.A., Long, P.H, Bui, M.D, Rutschmann, P. (2018). Modelling seasonal flows in the Vietnamese Mekong due to upstream discharge variation, climate change and sea level rise. Journal of River Basin Management. doi.org/10.1080/15715124.2018.1505735.

2. Duong, T.A., Long, P.H, Bui, M.D, Rutschmann, P. (2018). Simulating future flows and salinity intrusion using combined one- and two-dimensional hydrodynamic modelling–The case of the Hau river, Vietnamese Mekong Delta. Journal of Water 2018, 10(7), 897; doi.org/10.3390/w10070897.

3. Duong, T.A., Bui, M.D, Rutschmann, P. (2018). Application of Long Short Term memory in statistical downscaling in rainfall forecasting by climate change. Hydrological Sciences Journal - Manuscript ID HSJ-2018-0329 (under review).

4. Duong, T.A., Bui, M.D, Rutschmann, P. (2018). Data pre-processing combined with Artificial Neural Network to improve the performance of time series modelling. 5th IAHR Europe Congress, Trento University, Italy.

5. Duong, T.A., Bui, M.D, Rutschmann, P. (2018). A comparative study of three different models to predict monthly rainfall in Ca Mau; Vietnam. Proceeding of Wasserbau-Symposium 2018, TU Gräz, 18-20 Sept. 2018, Austria.

6. Duong, T.A., Bui, M.D, Rutschmann, P. (2016). Effect of Upstream Discharge and Climate Change on the Hydraulic Regime in Vietnamese Mekong Delta. Proceeding of Wasserbau-Symposium 2016, Wallgau, Oberbayern, Germany.

7. Duong, T.A., Bui, M.D, Rutschmann, P. (2015). Impact of climate change on salinity intrusion in Mekong delta. Proceeding of 14th International conference on Environmental Science and Technology, Rhodes, Greece.

Others:

1. Proloy, D., Duong, T.A, Parmeshwar, D. U. (2015). Assessment of the impacts of climate change and brackish irrigation water on rice productivity and evaluation of adaptation measures in Ca Mau province, Vietnam. Theoretical and Applied Climatory, pp 1 -16; doi.org/10.1007/s00704-015-1525-8.

2. Proloy D., Duong, T.A, Dang, NN. (2014). Assessment of rice productivity under climate change for Ca Mau province, Vietnam. 19th IAHR-APD 2014 Congress, Hanoi, Vietnam.

3. Duong, T.A., Dang N.N. (2014). New Approach to Rainfall Forecasting using Simulated Annealing Algorithms, 19th IAHR-APD 2014 Congress, Hanoi, Vietnam

Research Interest

  • Hydrodynamic modelling;
  • Climate change and Water Resources;
  • Statistical Downscaling and Bias Correction;
  • Rainfall and Runoff prediction;
  • Long Short Term Memory for sequential prediction;
  • Artificial Neural Network for time series forecasting.