Jian Shen (Chair)
Virginia Institute of Marine Science, School of Marine Science, Gloucester Point VA 23062, USA
Title : Combining Data and Numerical Modeling for Improving the Predictive Ability of Ecosystem and Water Quality Model of the Chesapeake Bay and Virginia Tributaries
Abstract :

The Chesapeake Bay and its tributaries endure pollution stress from the air, water and land. Excessive nutrient pollution fuels algae blooms that affect water quality and aquatic life. Hypoxia and anoxia happen more often during the summer. Fish kill often occurs following high runoff and storm events. The ecosystem restoration is the top priority for the Chesapeake Bay. To assess and predict the status of the Bay restoration, the Estuarine and Coastal Modeling Group of the Virginia Institute of Marine Science (VIMS) is currently endeavoring to develop a water quality prediction modeling system for the Bay and its Virginia tributaries. The model links watershed loadings and inputs from the coastal sea and interfaces with the atmosphere and the bottom sediment To fulfill the requirement of high model resolution in the regions of complex geometry and shallow tributary estuaries and improve the modeling efficiency, the nested grid approach is implemented in the modeling system to provide the flexibility for using the model to access multiple scale problems. VIMS scientists are currently improving the predictive ability of the model by implementing data assimilation techniques to combine the wealth of newly available biological and pollutant observations with numerical models in order to constrain the rate parameters required for the quantification of key biogeochemical processes, and to determine poorly constrained discharges of point and nonpoint sources. Model test case studies indicate that model prediction ability can be improved substantially by combining of wealth of newly available observations with the numerical model. With the use of observations, the model has the potential to evaluate pollutant sources and their contributions for the attainment of water quality standards for the system.

Biography :

Prof. Shen received his BS in Mathematics from Shanghai Normal University and his MA and Ph.D in Marine Science from the College of William and Mary.  He has more than 20 years of experiences with the development and application of numerical models to solve environmental problems. His research has been directed at improving our ability to quantify and predict ecosystems and water quality in estuaries and coastal seas. He combines theoretical analysis and numerical model simulations to study estuarine dynamics, transport processes, and water quality. Dr. Shen has been engaged in many environmental model developments, studies, and trainings to support state and local governments for estuarine restoration in the Chesapeake Bay region, North Carolina and West Virginia.   He has been actively involved in interdisciplinary projects for estuarine restoration. He has incorporated data assimilation techniques in water quality modeling, which improves model prediction capabilities, and used models for tracking pollutant sources. Dr. Jian Shen has numerous peer-reviewed publications. The research topics cover a number of fields including: estuarine transport timescale, estuarine dynamics and front, larval dispersion, eutrophication processes, transport of toxic materials, storm surge in estuaries and coastal seas, data assimilation and inverse parameter estimation, and modeling watershed processes. Prior to joining the faculty at the Virginia Institute of Marine Science, The College of William and Mary, he was a senior environmental engineer at Tetra Tech, inc., an environmental consultant company for USEPA. He was the technical lead in the development of Mining Data Analysis System (MDAS) and Loading Simulation Program C++ (LSPC), and EFDC Toolkit for USEPA. These tools have been widely used by USEPA for pollutant control and aquatic restoration. He has been a technical lead and principle investigator for many USEPA projects and conducted both watershed and 3D modeling trainings for USEPA.

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