Shaojie ZHANG 




Associate Professor 


No. 9, Block 4, Renminnanlu Road, Chengdu, 610041, People’s Republic of China 




Dr. Shaojie Zhang is the associate professor of geotechnical engineering at Key Laboratory of Mountain Hazards and Earth Surface Process, Chinese Academy of Sciences. He has doctor degree of engineering from Sichuan University. His research focuses on the monitoring and predicting debris flow and landslides, especially the physics-based prediction model and fiber sensing-based monitoring technique. His interests are also related to slope and debris flow units extraction from Digital Elevation Model. 


2002-2006, geotechnical engineering, Sichuan University, Bachelor. 

2006-2011, geotechnical engineering, Sichuan University, PHD. 

Employment Record (including international working experience ) 

2020.07-Present, Associate Professor, Institute of Mountain Hazards and Environmemt, Chinese Academy of Sciences 

2012.07-2020.07, Assistant Professor, Institute of Mountain Hazards and Environmemt, Chinese Academy of Sciences 

2006-2011, geotechnical engineering, Sichuan University, PHD. 

Running Projects 

1. Measurement and calculation of boulder impact force within debris flow based on Fiber sensing technique, National Natural Science Foundation of China. 

2. Intelligent prediction model for debris flow and shallow landslide, National Key research and Development Program of China. 

Academic Society Activities 

Reviewer for the Science of the Total Environment, Georisk, and Sensor review, Sensors, and Geotechnique. 



Zhang SJWei FQ, Xu H, Yang HJ, Liu DL, Wang K, Shen Y, Yang Y, Liu HZ. National Meteorological Center Award for Science and Technology Achievement Conversion and Application. Mechanism-based forecast system of landslide and debris flow in southwest China. 2019. 





[1] Shaojie Zhang, Changxue Xu, Fangqiang Wei, Kaiheng Hu, Hui Xu, Luqiang Zhao, Guoping Zhang. A physics-based model to derive rainfall intensity-duration threshold for debris flow, Geomorphology, 2020, 351: 106930. 

[2] Shaojie Zhang, Kai Wang, Kaiheng Hu, Heqi Xu, Changxue Xu, Dunlong Liu, Jun Lv, Fangqiang Wei. Model test: Infrasonic features of porous soil masses as applied to landslide monitoring. Engineering Geology, 2020, 265: 105454. 

[3] Shaojie Zhang, Changxue Xu, Jiang Chen, Jun Jiang. An experimental evaluation of impact force on a fiber Bragg grating-based device for debris flow warning. Landslides, 2019,16: 65-73. 

[4] Shaojie Zhang, Xiangping Xie, Fangqiang Wei, Sergey Chernomorets, Dmitry Petrakov, Irina Pavlova, Ricardo Delgado Tellez. A seismically triggered landslide dam in Honshiyan, Yunnan, China: from emergency management to hydropower potential. Landslides, 2015, 12: 1147-1157. 

[5] Shaojie Zhang, Luqiang Zhao, Ricardo Delgado-Tellez, and Hongjun Bao. A physics-based probabilistic forecasting model for rainfall-induced shallow landslides at regional scale. Natural Hazards and Earth System Sciences, 2018,18: 969-982. 

[6] Shaojie Zhang, Jiang Chen. An experimental study: Integration device of Fiber Bragg grating and reinforced concrete beam for measuring debris flow impact force. Journal of Mountain Science, 2017, 14(8): 1526-1536.

[7] Shaojie Zhang, Fangqiang Wei, Dunlong Liu, Hongjuan Yang, Yuhong Jiang. A regional-scale method of forecasting debris flow events based on water-soil coupling mechanism, Journal of Mountain Science, 2014, 11(6): 1531-1542. 

[8] Shaojie Zhang, Hongjuan Yang, Fangqiang Wei, Yuhong Jiang, Dunlong Liu. A model of debris flow forecast based on the water-soil coupling mechanism, Journal of Earth Science, 2014, 25(4): 757-763. 

[9] Kui Long, Shaojie Zhang*, Fangqiang Wei, Kaiheng Hu. A hydrology-process based method for correlating debris flow density to rainfall parameters and its application on debris flow prediction, Journal of Hydrology, 2020, 589: 125124. 

[10] Kai Wang, Shaojie Zhang*, Ricardo Delgado Tellez, Fangqiang Wei. A new slope unit extraction method for regional landslide analysis based on morphological image analysis, Bulletin of Engineering Geology and the Environment, 2019, 78: 4139-4151.