Building with nature has offered a paradigm shift in hydraulic engineering providing a new design philosophy where the dependence upon hard engineering structures (i.e. levees, seawalls, breakwaters) to provide coastal protection is giving way to hybridized solutions incorporating natural and nature-based features for coastal resilience. Nature-based defenses for coastal resilience are increasingly gaining popularity as an ecological engineering approach to protect coastal communities against flooding and erosion. However, there remains a considerable gap in accurately determining whether coastal communities can safely and cost-effectively rely on natural and nature-based features (NNBF) for parcel-level and community resilience against flooding under a changing climate, leading to a significant inertia towards unlocking the true potential of nature to increase society resilience.
While the results of the field-based data provide an accurate representation of the in-situ NNBFs capacity to attenuate storms surges and prevent coastal flooding, it is limited on the events that occur over the length of the monitoring period and also only represent current conditions. In order to extrapolate our capacity to evaluate the NNBFs capacity to serve as a reliable green infrastructure alternative for coastal protection under extreme weather and future climate change conditions, we rely on a numerical modeling framework capable of representing this process based on the measured data and state of the art computational tools. This framework is based on a multi-tier approach combining state of the art models to simulate hydrodynamic and waves at a regional scale (Atlantic Ocean and the Chesapeake Bay) and local-based scale (marshes and green infrastructure projects).
An accurate prediction of riverine-tidal-coastal flooding is essential for cost effective storm mitigation, emergency management plans, flood insurance and planning. While the National Weather Service (NWS) and the National Ocean Service (NOS) currently provide flood forecasts for almost the entire US, predicting flood levels on tidal areas where major rivers meet coastal and estuarine zones is extremely challenging. We are currently developing the next generation of flood forecast systems, capable of providing accurate, timely and reliable information to support emergency management and response in areas impacted by multi-flood hazards integrating coastal, urban and riverine flood hazards. The scientific challenge requires understanding the non-linear and complex dynamics of multi-flood hazards including storm surges, riverine flow, tidal oscillation and urban storm water systems. Our research seeks to develop a computational tool capable of predicting the total water level resulting from the interaction of these systems in real time and into the future.
Understanding the ecological-engineering relationship is one critical piece of information necessary to evaluate the potential of living shorelines and other NNBFs. However, property owners and government decision makers in coastal areas need to understand the dollar value of the services that the projects are providing and compare them to the costs. Furthermore, they need to understand how these natural infrastructure approaches compare to hard infrastructure alternatives. Construction costs for living shoreline projects vary widely depending on the length of shoreline under consideration, the level of desired protection, and the costs for materials and labor, which can vary across local areas. In a partnership with the Resources for the Future (RFF) institute, we are investigating the flood protection benefits of the marshes in the Chesapeake Bay in terms of economical services.
Non-stationarity has been largely recognized to impact engineering design, especially for water resources, hydrological and hydraulic structures. We are currently investigating the impact that the inherent non-stationarity of watershed systems, climate and sea-level will have on engineering design and developing alternatives methods for the engineering practice of the future. A series of papers from our student PhD Dissertation are providing insights into design considerations for Fairfax County watersheds.
Communities are in need of cost-effective and innovative strategies for stormwater management infrastructure investments. This need is driven by the fact that stormwater pollution is the only major increasing or fast-growing source of water pollution across much of the country including sensitive waterbodies such as the Chesapeake Bay and Puget Sound (U.S. EPA). The focus of this research is on the development of a methodology to analyze the use of investments of green stormwater infrastructure (GSI) on private property to address this growing problem.
Enabling effective data use and re-use in scientific investigations relies heavily not only on data availability but also on efficient data sharing discovery. Based on the CUAHSI-HIS framework concepts for hydrologic data sharing we developed a unique system devoted to the George Mason University scientific community to support university wide data sharing and discovery as well as real time data access for extreme events situational awareness. 
The Mason Water Data Information System (MWDIS) is also now on CUAHSI-HIS. You can access all our data directly on our CUAHSI-HIS portal.
Arc StormSurge is a data model that integrates Geographic Information Systems (GIS) and the hurricane wave and surge model SWAN+ADCIRC, which is the result of coupling the Simulating Waves Nearshore (SWAN) wave model and the Advanced Circulation (ADCIRC) hydrodynamic model. The Arc StormSurge data model is a geodatabase that includes feature classes (in feature datasets) and tables all related through relationship classes; it also includes raster catalogs and grids. In addition to the data model schema, Arc StormSurge includes a number of pre and post-processing tools that help integrate spatial data and numerical modeling. 
The coastal areas of Bangladesh are recognized by the United Nations as the most vulnerable country in the world to tropical cyclones and the sixth most vulnerable country to floods. During cyclone Sidr, mangrove forests in coastal areas played a crucial role in the mitigation of these deadly effects. To quantify the benefits of the mangrove forest to attenuate storm surge in this area, a framework was developed combining detailed characterizations of mangroves vegetation with numerical simulations. 
