My researches focus on the water and nutrient cycling at catchment-scale, and to assess the impacts of climate change and anthropogenic managements by modelling the key nutrient transport and transformation processes (e.g., denitrification). I also use tracer-aided ecohydrological model to identify the water pathways in peatland ecosystems. The methodology involves the application and development of tracer-aided distributed hydrological and water quality models, sensitivity and uncertainty analysis, Unmanned-Aerial-Vehicle technology and machine learning. Moreover, a new calibration framework (DREAMLoAX; https://github.com/songjun-wu/DREAM_LoAX) was developed specially for ecohydrological modelling, which is capable of simultaneous calibration and real-time diagnosis of deficiencies in data and model structural.