Big Data and Model Supported Environmental Decision Making under Uncertainty

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Today’s environmental problems including climate changes are getting exponentially more complex. Accordingly, huge volumes of information and data are involved in both daily and strategic environmental management. Based on data, environmental modeling and assessment tools have been playing an essential role in understanding those complex environmental problems and in helping vital decision-making processes. However, the critical gap between the data and the state of the art models has significantly limited the applicability of modeling tools due to data availability and data management issues. For example, the applicant has put forward the following environmental models with reported field applications in the past decade: a multiphase multicomponent chemical fate and transport model for the petroleum-contaminated soil and groundwater, a coupled near- and far- field numerical model for modeling contaminant's dispersion in Canadian offshore water, and a GIS-supported spatial multi-source air quality model with application to California. Data processing costs half or more of the time and efforts for the above-mentioned model developments and applications.