Xu Liang, PhD

Professor

Land Surface Hydrology and Modeling Advanced Informatics Environmental Monitoring via WSN

728 Benedum Hall | 3700 O’Hara Street | Pittsburgh, PA 15261 P: 412-624-9872

xuliang@pitt.edu www.engineering.pitt.edu/XuLiang/

Liang’s primary research interests are to discover and reveal fundamental laws that govern water and energy cycles, and to investigate how the water and energy cycles affect the health of our environment and ecological systems, and how they influence the transport and cycling of nutrients and pollutants at different spatial scales, such as at local, regional, continental, and global scales. Liang’s research work includes (1) land surface hydrology and modeling, (2) advanced hydroinformatics, and (3) environmental monitoring via wireless sensors and sensor network (WSN).

Advanced Informatics

Due to significant advancements in information and communication technologies, hydroinformatics, an emerging cross-disciplinary field, could change the way of hydrological and environmental research profoundly. Liang and her team have been developing new methodology to conduct data fusion and data assimilation by making good and effective use of various heterogeneous data sources. They have also been investigating decades-long difficult problems on improving prediction accuracies for ungauged basins by combining machine learning approaches.

Land Surface Hydrology and Modeling

The fields of surface water hydrology and atmospheric sciences were developed as two independent fields in the past. With the evolvement of the new interdisciplines, the atmosphere, land surface, and soil zone below the land surface are now viewed as one integrated system. Such new view provides great opportunities to understand the nature which have never been possible before, such as, how to connect climate change of global warming at different scales in order to conduct impact studies on flooding, drought, agricultural yields, water resources, human welfare, etc. One of the outstanding and difficult problems in resolving these connections is to effectively deal with different spatial scales associated with the climatemodel predictions of various physical variables, such as rainfall, snowfall, soil moisture, etc. from large spatial domains in atmospheric models to much smaller spatial domains associated with hydrological models. Liang and her team are developing a new modeling strategy to address some of the emerging challenges in the field of land surface modeling.

Environmental Monitoring via WSN

Wireless sensor networks (WSNs) enable the continuous monitoring of various hydrological phenomena at unprecedented high spatial densities and long time durations and hence, open new exciting opportunities for numerous scientific endeavors. It is of paramount importance to deploy large scale monitoring WSNs for environmental monitoring. Because sensor nodes are battery-powered, one of the most critical challenges in WSNs is to minimize the use of power for data gathering. Liang and her team have worked on building their own sensors to significantly reduce the cost for making a large number of field deployment possible. In addition, collaborating with computer scientists, they have been investigating the energy characteristics of different types of sensors in environmental wireless sensor networks, and developing an innovative framework to significantly improve energy efficiency for large scale environmental monitoring using WSNs.