Development of a Large-Scale Storm Surge and High-Resolution Sub-Grid Inundation Model for Coastal Flooding Applications: A Case Study during Hurricane Sandy

Coastal inundation initiated via storm surge by hurricanes and nor\u27easters along the U.S. East Coast is a substantial threat to residential properties, community infrastructure, and human life. During and after the storm, compounding with heavy precipitation and upland drainage, inundation can be caused by the combination of storm surge and river-induced inland flooding in various locations throughout the coastal plain. Thus, coastal inundation can be expanded from the open coast upstream into the tributaries of the New York Bay including the Hudson and East River systems. Given the cross-disciplinary nature of the dynamics (encompassing hydraulics, oceanography, and hydrology), and the complexity of the atmospheric forcing, a numerical model is the optimal approach for a comprehensive study of the hydrodynamics of coastal inundation.;This study will utilize the large-scale parallel SELFE model to simulate the storm surge and inundation caused by 2012 Hurricane Sandy utilizing different forecast wind and pressure fields. The large-scale numerical model made use of multiple inputs for atmospheric forcing and spatially covered a large domain area to account for large-scale oceanographic processes and output accurate model simulation of water levels. In a simultaneous effort, a street-level sub-grid inundation model coupled with Lidar-derived topography (UnTRIM 2) was employed to simulate localized flooding events in the New York Harbor.;Sub-grid modeling is a novel method by which water level elevations are efficiently calculated on a coarse computational grid, with discretized bathymetric depths and topographic heights stored on a sub-grid nested within each base grid cell, capable of addressing local friction parameters without resorting to solve the full set of equations. Sub-grid technology essentially allows velocity to be rationally and efficiently determined at the sub-grid level. This salient feature enables coastal flooding to be addressed in a single cross-scale model from the ocean to the upstream river channel without overly refining the grid resolution. to this end, high-resolution Digital Elevation Models (DEMs) were developed utilizing GIS from Lidar-derived topography for incorporation into a sub-grid model, for research into the plethora of practical research applications related to urban inundation in New York City.;SELFE large-scale storm tide simulations were successfully conducted for 2012 Hurricane Sandy using both the North American Regional Reanalysis (NARR), and the Regional Atmospheric Modeling System (RAMS) atmospheric hindcast model results as atmospheric inputs. Overall statistics using the 24km resolution NARR inputs observed an average R2 value of 0.8994, a relative error of 11.77%, and a root-mean-squared error of 32.69cm for 10 NOAA observation stations. The 4km RAMS inputs performed noticeably better at all 10 stations with aggregate statistics yielding an average R2 value of 0.9402, a relative error of 4.08%, and a rootmean-squared error of 19.22 cm. Since the RAMS atmospheric inputs possessed a higher spatial and temporal resolution than the NARR inputs for air pressure and wind speed, it was concluded that generally superior storm tide predictions could be expected from utilizing more reliable or better resolution atmospheric forecast products.;UnTRIM2 results were obtained via sub-grid simulation of 2012 Hurricane Sandy in the New York Harbor with high-resolution topography and building heights embedded in the model sub-grid for New York City. Model performance was assessed via comparison with various verified field measurements: (1) Temporal comparison of NOAA and USGS permanent water level gauges, (2) USGS rapid deployment water level gauges, along with a spatial inundation comparison using (3) USGS-collected high water marks, (4) FEMA-collected data regarding inundated schools, (5) calculated area and distance differentials using FEMA\u27s maximum extent of inundation map, and (6) known locations of inundated subway entrances. Temporal results verified the effectiveness of the sub-grid model\u27s wetting and drying scheme via seven over land rapid deployment gauges installed and collected by the USGS with a mean R2 of 0.9568, a relative error of 3.83%, and a root-mean-squared error of 18.15cm.;Spatial verification of the inundation depths predicted by the UnTRIM 2 model were addressed by comparison with 73 high water mark measurements collected by the USGS and by 80 FEMA-reported water level thicknesses at inundated schools throughout the sub-grid domain separated by state. Average statistics for the 73 USGS-recorded high water marks for New York and New Jersey were: 0.120+/-0.085m and 0.347+/-0.256m for root-mean-squared error +/- standard deviation, respectively. The larger differences and errors reported in the point to point comparisons for New Jersey relative to New York were largely due to the lack building representation in the sub-grid DEM for the New Jersey side of the Hudson River, and was a significant indication that the representation of buildings as a physical impediment to fluid flow is critical to urban inundation modeling.;A maximum difference threshold was imposed for distance and area comparisons with FEMA\u27s Hurricane Sandy flood map using the average distance differential rounded to 40m. This was done to minimize the impact of missing or added infrastructure such as highway overpasses along with Lidar-derived data limitations of physical impediments to fluid flow not accounted for in the model\u27s DEM. The difference in the absolute mean distance between the maximum extent predicted by the street-level sub-grid model and the FEMA maximum inundation observation was 21.207m or ≈4 sub-grid pixels at 5m resolution for the entire sub-grid domain. The final area comparison resulted in an 85.17% area (49,253,687m 2) spatial match, with 7.57% area (4,376,726m2) representing model over-prediction, and under-prediction area accounting for 7.27% (4,202,376m 2), with differences being attributed to lack of building representation in the FEMA maximum inundation map. Additionally, the implementation of the FEMA\u27s spatial flood map data as a bathtub model derivative product of USGS interpolated high water marks and elevation data without regard for strong water current velocities or estuarine circulation can also account for regions with significant discrepancies.;Keywords: Sub-Grid, Stotul Surge, Inundation, New York Harbor, New York City, Jersey City, Conveyance Approach, Unstructured Grids, UnTRIM, SELFE, Lidar-Derived Topography

Comparison of Electrochemical Polishing Treatments between Phosphoric Acid and a Deep Eutectic Solvent for High-Purity Copper

This study investigated and compared the acid-free electropolishing of copper with the state-of-the-art acidic electropolishing process. The acid-free medium used in this study is based on a deep eutectic solvent comprised of 2:1 ethylene glycol and choline chloride. The electrochemical study included voltammetry and chronoamperometry tests during the electropolishing process. The characterization techniques used were atomic force microscopy (AFM) and digital microscopy, and surface morphology comparisons summarized the electropolishing efficiency of phosphoric acid and acid-free deep eutectic solvent treatments for high-purity copper. Electropolishing copper with a deep eutectic solvent resulted in a mirror finish and a post-treatment surface that was 8× smoother than the original metal surface prior to electropolishing treatments with a smoothing efficiency of 91.1 ± 1.5%. This eco-friendly solution produced polished surfaces superior to those surfaces treated with industry standard acid electrochemistry treatments of 1 M H3PO4

Comparison of Electropolishing of Aluminum in a Deep Eutectic Medium and Acidic Electrolyte

Research advances in electropolishing, with respect to the field of metalworking, have afforded significant improvements in the surface roughness and conductivity properties of aluminum polished surfaces in ways that machine polishing and simple chemical polishing cannot. The effects of a deep eutectic medium as an acid-free electrolyte were tested to determine the potential energy thresholds during electropolishing treatments based upon temperature, experiment duration, current, and voltage. Using voltammetry and chronoamperometry tests during electropolishing to supplement representative recordings via atomic force microscopy (AFM), surface morphology comparisons were performed regarding the electropolishing efficiency of phosphoric acid and acid-free ionic liquid treatments for aluminum. This eco-friendly solution produced polished surfaces superior to those surfaces treated with industry standard acid electrochemistry treatments of 1 M phosphoric acid. The roughness average of the as-received sample became 6.11 times smoother, improving from 159 nm to 26 nm when electropolished with the deep eutectic solvent. This result was accompanied by a mass loss of 0.039 g and a 7.2 µm change in step height along the edge of the electropolishing interface, whereas the acid treatment resulted in a slight improvement in surface roughness, becoming 1.63 times smoother with an average post-electropolishing roughness of 97.7 nm, yielding a mass loss of 0.0458 g and a step height of 8.1 µm

StormSense: A Blueprint for Coastal Flood Forecast Information & Automated Alert Messaging Systems

Increased availability of low-cost water level sensors communicating through the Internet of Things (IoT) has expanded the horizons of publicly-ingestible data streams available to modern smart cities. StormSense is an IoT-enabled inundation forecasting research initiative and an active participant in the Global City Teams Challenge seeking to enhance flood preparedness in the smart cities of Hampton Roads, VA for flooding resulting from storm surge, rain, and tides. In this study, we present the a blueprint and series of applicable protocols through the use of the new StormSense water level sensors to help establish a regional resilience monitoring network. In furtherance of this effort, the Virginia Commonwealth Center for Recurrent Flooding Resiliency\u27s Tidewatch tidal forecast system is being used as a starting point to integrate the extant (NOAA) and new (USGS and StormSense) water level sensors throughout the region, and demonstrate replicability of the solution across the cities of Newport News, Norfolk, and Virginia Beach within Hampton Roads, VA. StormSense\u27s network employs a mix of ultrasonic sonar and radar remote sensing technologies to record water levels and develop autonomous alert messaging systems through the use of three separate cloud environments. One to manage the water level monitoring sensors and alert messaging, one to run the model and interface with the post-processed results, and one to geospatially present the flood results

Using Lidar Elevation Data to Develop a Topobathymetric Digital Elevation Model for Sub-Grid Inundation Modeling at Langley Research Center

Technological progression in light detection and ranging permits the production of highly detailed digital elevation models, which are useful in sub-grid hydrodynamic modeling applications. Sub-grid modeling technology is capable of incorporating these high-resolution lidar-derived elevation measurements into the conventional hydrodynamic modeling framework to resolve detailed topographic features for inclusion in a hydrological transport model for runoff simulations. The horizontal resolution and vertical accuracy of the digital elevation model is augmented via inclusion of these lidar elevation values on a nested 5-m sub-grid within each coarse computational grid cell. This aids in resolving ditches and overland drainage infrastructure at Langley Research Center to calculate runoff induced by the heavy precipitation often accompanied with tropical storm systems, such as Hurricane Irene (2011) and Hurricane Isabel (2003). Temporal comparisons of model results with a NASA tide gauge during Hurricane Irene yielded a good R-2 correlation of 0.97, and root mean squared error statistic of 0.079 m. A rigorous point-to-point comparison between model results and wrack line observations collected at several sites after Hurricane Irene revealed that when soil infiltration was not accounted for in the model, the mean difference between modeled and observed maximum water levels was approximately 10%. This difference was reduced to 2-5% when infiltration was considered in the model formulation, ultimately resulting in the sub-grid model more accurately predicting the horizontal maximum inundation extents within 1.0-8.5 m of flood sites surveyed. Finally, sea-level rise scenarios using Hurricane Isabel as a base case revealed future storm-induced inundation could extend 0.5-2.5 km inland corresponding to increases in mean sea level of 37.5-150 cm

The Floodwater Depth Estimation Tool (FwDET v2.0) for improved remote sensing analysis of coastal flooding

Remote sensing analysis is routinely used to map flooding extent either retrospectively or in near-real time. For flood emergency response, remote-sensing-based flood mapping is highly valuable as it can offer continued observational information about the flood extent over large geographical domains. Information about the floodwater depth across the inundated domain is important for damage assessment, rescue, and prioritizing of relief resource allocation, but cannot be readily estimated from remote sensing analysis. The Floodwater Depth Estimation Tool (FwDET) was developed to augment remote sensing analysis by calculating water depth based solely on an inundation map with an associated digital elevation model (DEM). The tool was shown to be accurate and was used in flood response activations by the Global Flood Partnership. Here we present a new version of the tool, FwDET v2.0, which enables water depth estimation for coastal flooding. FwDET v2.0 features a new flood boundary identification scheme which accounts for the lack of confinement of coastal flood domains at the shoreline. A new algorithm is used to calculate the local floodwater elevation for each cell, which improves the tool\u27s runtime by a factor of 15 and alleviates inaccurate local boundary assignment across permanent water bodies. FwDET v2.0 is evaluated against physically based hydrodynamic simulations in both riverine and coastal case studies. The results show good correspondence, with an average difference of 0.18 and 0.31 m for the coastal (using a 1 m DEM) and riverine (using a 10 m DEM) case studies, respectively. A FwDET v2.0 application of using remote-sensing-derived flood maps is presented for three case studies. These case studies showcase FwDET v2.0 ability to efficiently provide a synoptic assessment of floodwater. Limitations include challenges in obtaining high-resolution DEMs and increases in uncertainty when applied for highly fragmented flood inundation domains

Anthropocene Sea Level Change: A History of Recent Trends Observed in the U.S. East, Gulf, and West Coast Regions

Relative sea level (RSL) observations since 1969 at U.S. tide stations exhibit trends in RSL rise rate and acceleration that vary in response to both global and regional processes. Trend histories display a high degree of similarity between locations in coastal regions that are experiencing similar processes. With the exception of the U.S. Northeast Coast and Alaska,every other coastal location in the continental U.S. has experienced an upturn in RSL rise rate since 2013-2014 despite wide differences in the magnitude and trending direction of RSL acceleration. High RSL acceleration along the U.S. Northeast Coast has trended downward since 2011 while low RSL acceleration along the U.S Southeast Coast has recently trended upward in response to changes likely associated with ocean dynamics and ice sheet loss. RSL change in the sedimentary basins of the central U.S. Gulf Coast region is highly dependent on local rates of vertical land movement (VLM). VLM here varies over relatively short time scales amid changing patterns of subsurface water and hydrocarbons extraction.RSL rise rates of 5 mm/year or more aided by weak acceleration in Louisiana and Texas project a total RSL rise of between 0.4 and 0.5 meters above 1992 MSL by the year 2050; other Gulf and East Coast locations will experience equal or greater rise if upward trends in acceleration continue. Low and mostly downward trends in RSL rise rate at central U.S. West Coast locations have recently reverted to a pattern of upward trends with higher rise rates. Rise rates prior to 2013 appear to have been restrained by deceleration now trending toward acceleration. A combination of tectonic plate convergence and glacial isostatic adjustment makes the non-contiguous U.S. coastal state of Alaska unique with regard to RSL trends. Land emergence, rather than subsidence, produces consistent trends of falling RSL in Alaska

Preferences for Modeling Scenarios and Parameters: The Perspective of Planners and Emergency Managers (Risk Communication and Public Engagement in Sea Level Rise Resilience Research Series, Paper No. 1)

The purpose of this study is to better inform research and practice in flood modeling by obtaining input from key end users on preferences for modeling approaches and model parameters, usability of flood models, and how information from flood models fit into decision making processes. We conducted a survey of stakeholders and end-users in the planning arena to identify their preferences for flood modeling scenarios and parameters. We also conducted a focus group with local emergency managers to understand how they would use predictive flood modeling for emergency management and planning

Anticipating and adapting to the future impacts of climate change on the health, security and welfare of low elevation coastal zone (LECZ) communities in southeastern USA

Low elevation coastal zones (LECZ) are extensive throughout the southeastern United States. LECZ communities are threatened by inundation from sea level rise, storm surge, wetland degradation, land subsidence, and hydrological flooding. Communication among scientists, stake-holders, policy makers and minority and poor residents must improve. We must predict processes spanning the ecological, physical, social, and health sciences. Communities need to address linkages of (1) human and socioeconomic vulnerabilities; (2) public health and safety; (3) economic concerns; (4) land loss; (5) wetland threats; and (6) coastal inundation. Essential capabilities must include a network to assemble and distribute data and model code to assess risk and its causes, support adaptive management, and improve the resiliency of communities. Better communication of information and understanding among residents and officials is essential. Here we review recent background literature on these matters and offer recommendations for integrating natural and social sciences. We advocate for a cyber-network of scientists, modelers, engineers, educators, and stakeholders from academia, federal state and local agencies, non-governmental organizations, residents, and the private sector. Our vision is to enhance future resilience of LECZ communities by offering approaches to mitigate hazards to human health, safety and welfare and reduce impacts to coastal residents and industrie