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

Validating an Operational Flood Forecast Model Using Citizen Science in Hampton Roads, VA, USA

Changes in the eustatic sea level have enhanced the impact of inundation events in the coastal zone, ranging in significance from tropical storm surges to pervasive nuisance flooding events. The increased frequency of these inundation events has stimulated the production of interactive web-map tracking tools to cope with changes in our changing coastal environment. Tidewatch Maps, developed by the Virginia Institute of Marine Science (VIMS), is an effective example of an emerging street-level inundation mapping tool. Leveraging the Semi-implicit Cross-scale Hydro-science Integrated System Model (SCHISM) as the engine, Tidewatch operationally disseminates 36-h inundation forecast maps with a 12-h update frequency. SCHISM’s storm tide forecasts provide surge guidance for the legacy VIMS Tidewatch Charts sensor-based tidal prediction platform, while simultaneously providing an interactive and operationally functional forecast mapping tool with hourly temporal resolution and a 5 m spatial resolution throughout the coastal plain of Virginia, USA. This manuscript delves into the hydrodynamic modeling and geospatial methods used at VIMS to automate the 36-h street-level flood forecasts currently available via Tidewatch Maps, and the paradigm-altering efforts involved in validating the spatial, vertical, and temporal accuracy of the model. Supplementary material: Catch the King Tide GPS data points were collected by volunteers to effectively breadcrumb their path tracing the tidal high water contour lines by pressing the \u27Save Data\u27 button in the free Sea Level Rise Mobile App every few steps along the water\u27s edge during the high tide on the morning of November 5th, 2017. https://doi.org/10.25773/276h-2b4

Integrated Ocean, Earth, and Atmospheric Observations for Resilience Planning in Hampton Roads, Virginia

Building flood resilience in coastal communities requires a precise understanding of the temporal and spatial scales of inundation and the ability to detect and predict changes in flooding. In Hampton Roads, the Intergovernmental Pilot Project’s Scientific Advisory Committee recommended an integrated network of ocean, earth, and atmospheric data collection from both private and public sector organizations that engage in active scientific monitoring and observing. Since its establishment, the network has grown to include monitoring of water levels, land subsidence, wave measurements, current measurements, and atmospheric conditions. High-resolution land elevation and land cover data sets have also been developed. These products have been incorporated into a number of portals and integrated tools to help support resilience planning. Significant challenges to building the network included establishing consistent data standards across organizations to allow for the integration of the data into multiple, unique products and funding the expansion of the network components. Recommendations to the network development in Hampton Roads include the need to continue to support and expand the publicly available network of sensors; enhance integration between ocean, earth, and atmospheric networks; and improve shallow water bathymetry data used in spatial flooding models

Integrated ocean, earth, and atmospheric observations for resilience planning in Hampton roads, Virginia

Building flood resilience in coastal communities requires a precise understanding of the temporal and spatial scales of inundation and the ability to detect and predict changes in flooding. In Hampton Roads, the Intergovernmental Pilot Project\u27s Scientific Advisory Committee recommended an integrated network of ocean, earth, and atmospheric data collection from both private and public sector organizations that engage in active scientific monitoring and observing. Since its establishment, the network has grown to include monitoring of water levels, land subsidence, wave measurements, current measurements, and atmospheric conditions. High-resolution land elevation and land cover data sets have also been developed. These products have been incorporated into a number of portals and integrated tools to help support resilience planning. Significant challenges to building the network included establishing consistent data standards across organizations to allow for the integration of the data into multiple, unique products and funding the expansion of the network components. Recommendations to the network development in Hampton Roads include the need to continue to support and expand the publicly available network of sensors; enhance integration between ocean, earth, and atmospheric networks; and improve shallow water bathymetry data used in spatial flooding models

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

Multiscale, Multiphysics Modelling of Coastal Ocean Processes: Paradigms and Approaches

This Special Issue includes papers on physical phenomena, such as wind-driven flows, coastal flooding, and turbidity currents, and modeling techniques, such as model comparison, model coupling, parallel computation, and domain decomposition. These papers illustrate the need for modeling coastal ocean flows with multiple physical processes at different scales. Additionally, these papers reflect the current status of such modeling of coastal ocean flows, and they present a roadmap with numerical methods, data collection, and artificial intelligence as future endeavors

Effects of tidal flooding on estuarine biogeochemistry: Quantifying flood-driven nitrogen inputs in an urban, lower Chesapeake Bay sub-tributary

Sea level rise has increased the frequency of tidal flooding even without accompanying precipitation in many coastal areas worldwide. As the tide rises, inundates the landscape, and then recedes, it can transport organic and inorganic matter between terrestrial systems and adjacent aquatic environments. However, the chemical and biological effects of tidal flooding on urban estuarine systems remain poorly constrained. Here, we provide the first extensive quantification of floodwater nutrient concentrations during a tidal flooding event and estimate the nitrogen (N) loading to the Lafayette River, an urban tidal sub-tributary of the lower Chesapeake Bay (USA). To enable the scale of synoptic sampling necessary to accomplish this, we trained citizen-scientist volunteers to collect 190 flood water samples during a perigean spring tide to measure total dissolved N (TDN), dissolved inorganic N (DIN) and phosphate concentrations, and Enterococcus abundance from the retreating ebb tide while using a phone application to measure the extent of tidal inundation. Almost 95% of Enterococcus results had concentrations that exceeded the standard established for recreational waters (104 MPN 100 mL−1). Floodwater dissolved nutrient concentrations were higher than concentrations measured in natural estuarine waters, suggesting floodwater as a source of dissolved nutrients to the estuary. However, only DIN concentrations were statistically higher in floodwater samples than in the estuary. Using a hydrodynamic model to calculate the volume of water inundating the landscape, and the differences between the median DIN concentrations in floodwaters and the estuary, we estimate that 1,145 kg of DIN entered the Lafayette River during this single, blue sky, tidal flooding event. This amount exceeds the annual N load allocation for overland flow established by federal regulations for this segment of the Chesapeake Bay by 30%. Because tidal flooding is projected to increase in the future as sea levels continue to rise, it is crucial we quantify nutrient loading from tidal flooding in order to set realistic water quality restoration targets for tidally influenced water bodies

Dynamic Modeling of Inland Flooding and Storm Surge on Coastal Cities Under Climate Change Scenarios: Transportation Infrastructure Impacts in Norfolk, Virginia USA as a Case Study

Low-lying coastal cities across the world are vulnerable to the combined impact of rainfall and storm tide. However, existing approaches lack the ability to model the combined effect of these flood mechanisms, especially under climate change and sea level rise (SLR). Thus, to increase flood resilience of coastal cities, modeling techniques to improve the understanding and prediction of the combined effect of these flood hazards are critical. To address this need, this study presents a modeling system for assessing the combined flood impact on coastal cities under selected future climate scenarios that leverages ocean modeling with land surface modeling capable of resolving urban drainage infrastructure within the city. The modeling approach is demonstrated in quantifying the impact of possible future climate scenarios on transportation infrastructure within Norfolk, Virginia, USA. A series of combined storm events are modeled for current (2020) and projected future (2070) climate scenarios. The results show that pluvial flooding causes a larger interruption to the transportation network compared to tidal flooding under current climate conditions. By 2070, however, tidal flooding will be the dominant flooding mechanism with even nuisance flooding expected to happen daily due to SLR. In 2070, nuisance flooding is expected to cause a 4.6% total link close time (TLC), which is more than two times that of a 50-year storm surge (1.8% TLC) in 2020. The coupled flood model was compared with a widely used but physically simplistic bathtub method to assess the difference resulting from the more complex modeling presented in this study. The results show that the bathtub method overestimated the flooded area near the shoreline by 9.5% and 3.1% for a 10-year storm surge event in 2020 and 2070, respectively, but underestimated the flooded area in the inland region by 9.0% and 4.0% for the same events. The findings demonstrate the benefit of sophisticated modeling methods compared to more simplistic bathtub approaches, in climate adaptive planning and policy in coastal communities