Prof. Gordon Huang
Faculty of Engineering and Applied Science, University of Regina, Canada

Dr. Gordon Huang is a Tier 1 Canada Research Chair in Energy and Environment, and Executive Director of the Institute for Energy, Environment and Sustainable Communities at the University of Regina, Canada. He holds BSC from Peking University (China), MSc from Simon Fraser University (Canada) and PhD from McMaster University (Canada). Since the 1990s, Huang has led over 150 research projects, produced over 800 peer-refereed international journal papers (with an SCI-based H-index of 51 in Science Citation Index under Thomson Reuters' Web of Science), and supervised over 100 Master/PhD students (with degrees awarded). Over 20 Huang's PhD graduates were appointed as faculty members at universities in Canada, USA, China and Singapore. He is a Fellow of the Canadian Academy of Engineering, and the President of the International Society for Environmental Information Sciences. He also acts as editor-in-chief for Journal of Environmental Informatics (, and served the United Nations Development Programme as Chief Scientist for a program of Rural Water Resources Management and Drinking Water Safety. His pioneering work in environmental risk management has been recognized as a significant innovation, and has influenced government and business approaches for tackling environmental challenges and formulating related policies.



Prof. Yongping Li
Beijing Normal University, China

Yongping Li is a Changjiang Scholar Professor at Beijing Normal University, China. She receives her MSc and PhD Degrees from the University of Regina, Canada. Her research interests involve in energy and environmental systems analysis, environmental pollution control, and decision making under uncertainty. Dr. Li has led or involved in over 60 energy- and environment-related research projects supported by industrial, governmental and international organizations. She has produced more than 400 peer-refereed international journal papers (with a SCI-based H-index of 50). She has been continuously selected as a highly cited scholar in the field of “Environmental Science” (by Elsevier) since 2013. She supervised over 70 Master/PhD students. Dr. Li was received a number of awards such as Distinguished Young Scientist Award, New Century Excellent Talents in University, the National Natural Science Funds for Distinguished Young Scholar, the National Award for Youth in Science and Technology, and the National Award for Youth Female Scientist.


Speech Title "Optimization modeling of water resources management in the Aral Sea Basin"


Abstract—The constantly increasing demand for water in terms of both sufficient quantity and satisfied quality has forced engineers and planners to contemplate and propose ever more comprehensive, complex and ambitious plans for managing water resources systems. In water resources management, uncertainties that exist in many system parameters and their interrelationships could intensify the conflict-laden issue of water allocation among multiple competing interests. It is thus deemed necessary to develop effective optimization methods for supporting water resources management under such complexities. A set of inexact fractional programming methods are proposed for reflecting random variables under conflicting objectives and analyze the interrelationship between marginal benefit and system-failure risk, through introducing the techniques of fuzzy programming and stochastic programming into the fractional programming framework. The developed methods are applied to water resources management in the Aral Sea Basin, one of the most prominent areas in the world where the contradiction between supply and demand of water resources and the ecological environment problems. Compared to the conventional optimization approaches, the inexact fractional programming method can generate more flexible alternatives and achieve higher marginal effectiveness, which is more beneficial to water resources management in arid and semi-arid regions. Results can provide scientific policy support for water resources management, and promote economic development, food security and ecological restoration in the Aral Sea Basin.




Prof. Caterina Valeo
University of Victoria, Canada

Dr. Caterina Valeo is a Professor in Mechanical Engineering at the University of Victoria and a Professional Engineer in the Province of British Columbia. After receiving undergraduate degrees in Physics and later, a second one in Civil Engineering, both from the University of Toronto, she went to McMaster University to complete a Masters degree and eventually a PhD specializing in urban water resources in 1998. She worked as an academic at the University of Manitoba for 2 years then moved to Geomatics Engineering at the University of Calgary in 2000 where she began developing what has now become a prolific 20 year career conducting research and teaching in Environmental Information Sciences. She moved to the Department of Mechanical Engineering at the University of Victoria in 2011 to continue her interdisciplinary research that merges information science with environmental science and engineering. Her research interests and areas of application are wide and varied and range from researching the impacts of global scale changes on forestry and water supply to developing sensors and models to describe the role of bacteria and biofilm in treating polluted water. She has more than 200 publications including 3 co-authored books on topics as diverse as Environmental Hydraulics and Digital Terrain Modelling. She has collaborated with over 100 researchers across the globe, has received and participated in several millions of dollars in grants and is the recipient of numerous accolades including the 2014 Award of Distinguished Scientist from the International Society for Environmental Information Sciences. Today Dr. Valeo runs the Biofilm Research Laboratory and the HAL Research Site at the University of Victoria and continues to conduct multi-collaborative research that uses Environmental Informatics tools to create sustainable solutions to society’s modern problems.


Speech title"Quantifying Uncertainty in Ocean Currents: Using Fuzzy Mathematics for Oil Spill Tracking and Emergency Response"


Abstract—Predicting how floating objects move around on the ocean surface is challenging. However, there is significant activity and interest in this prediction particularly for optimizing marine emergency responses to oil spills, search and rescue, etc. The movement of surface floating objects is governed by currents, winds, and waves at the surface, as well as physical characteristics of the floating mass, such as geometry if the object is solid. Today, predicting ocean spill extent and deploying emergency response is supported by sophisticated hydrodynamic models that combine relevant forces to model and predict the drift of objects. These models are verified and calibrated with in situ observations of wind and currents through networks of solid floating objects such as instrumented buoys. In spite of all these data and the sophistication of the models used, the range of errors arising from the hydrodynamic models as well as from the observed data can lead to questionable outcomes with large uncertainties. Quantifying the uncertainties can become intractable for a modeler unless several assumptions are made. This presentation will provide insights from research being conducted by collaborators at the University of Victoria and the Department of Fisheries and Oceans Canada that explores the use of fuzzy mathematics to quantify uncertainty in predicting particle or object movement (drift) in nearshore ocean areas. Uncertainty can be quantified as fuzzy numbers representing a portion of instrument observations of currents and winds collected from buoys or stationary platforms. This uncertainty can be propagated through time-series simulations of particle trajectories from the hydrodynamic model to predict possible endpoint locations in space. An application to buoys in the straits along the western shore of Vancouver Island shows how fuzzy mathematics is able to correctly identify the area where a buoy is expected to be found for targeted simulations. Furthermore, the impact of uncertainty in varying velocity fields on particle movement is explored numerically in a simple domain where steady uncertainty is described as a fuzzy number. The modelling shows that good results can be produced with reasonable computational effort and that using fuzzy mathematics for such a complex simulation is possible and advantageous.




Prof. Xi Chen
Tianjin University, China

Xi Chen is currently a chair professor at the Institute of Surface Earth System Sciences of Tianjin University, director of the Ecohydrology and Water Resources Research Center of the School of Earth System Science of Tianjin University, graduated from Hohai University. He received his Bachelor's degree, Master's degree and Doctor's degree in Hydrology and water resources from Hohai University in July 1984, March 1990 and November 1999 respectively. Mainly engaged in research on groundwater development, utilization and management, basin hydrological process simulation, and response of hydrological and water resources to global changes. Hosted major projects of the National Natural Science Foundation of China, major international cooperation projects, major national basic research projects, major science and technology research projects of the Ministry of Education, key projects of the National Natural Science Foundation of China, etc.



Speech title"Coupled Hydrological and Biogeochemical Modelling of Nitrogen Transport in the Karst Critical Zone"


Abstract—Transport of nitrogen (N) in karst areas is more complex than in non-karst areas due to marked heterogeneity of hydrodynamic behaviour in the karst critical zone. Here, we present a novel, distributed, coupled hydrological-biogeochemical model that can simulate water and nitrogen transport in the critical zone of karst catchments. This new model was calibrated using integrated hydrometric, water stable isotope, and nitrogen-N concentration data at the outflow of Houzhai catchment in Guizhou province of Southwest China. Hydrological dynamics appears to control N load from the study catchment. Combining flow discharge and water stable isotopes significantly constrained model parameterisation and mitigate the equifinality effects of parameters on the simulated results. Karst geomorphology and land use have functional effects on spatiotemporal variations of hydrological processes and nitrogen transport. In the study catchment, agricultural fertilizer was the largest input source of N, accounting for 86 % of the total. Plant uptake consumed about 45 % of inputs, primarily in the low-lying valley bottom areas and the plain covered by relatively thick soils. Thus, a large amount of N released from soil reservoirs to the epikarst (via fractures or sinkholes) is then exported to the underground channel in the limestone area to the south. This N draining into groundwater could lead to extensive, potentially long-term contamination of the karst system. Therefore, improving the efficiency of fertilization and agricultural management in valleys/depressions is an urgent need to reduce N losses and contamination risk.





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