# Validating an Operational Flood Forecast Model Using Citizen Science in Hampton Roads, VA, USA
## 2 Methods
### Tidewatch Storm Tide Modeling  
Each year, prior to the king tide flood event, researchers at VIMS and the CCRFR design a web map to direct volunteers to public places that are forecasted to flood during the King Tide using VIMS' hydrodynamic models. This method proved impactful, as the 2017 _Catch the King_ volunteer recruitment story map reached over 10,000 page views before the king tide in less than 3 months (Figure 2). Thus, the story map effectively conveyed the value of inundation forecasting by showcasing flooding impacts during the last major storm event in the region, 2011 Hurricane Irene, and the importance of time-stamped GPS data for tidal calibration and event calibration of models for improvement purposes (Figure 3). This was valuable to visually explain the value of accurate data collection both temporally and spatially to the citizen scientists. As Figure 3A shows, on 28 August 2011 at 00:00 UTC after Hurricane Irene, 30 min before the storm surge peak was observed at the nearest sensor, the 14 GPS points that comprise this maximum extent contour compare well with an MHDD of 4 m to the nearest model grid cell center point. However, the model's prediction from an hour later, 30 min after the storm surge peak was observed at the nearest sensor shown in Figure 3B, the maximum flood extent compares less favorably, changing the MHDD to 6.5 m, and illustrating the burden of timing for reliable model comparison. Thus, during the king tides in 2017 and 2018, GPS data points were collected by each year's event's many volunteers to breadcrumb maximum inundation extents in public spaces and time-stamped (Figure 4). This approach was used to coordinate and validate the flooding extents across 17 coastal cities and counties in Virginia, USA, by enlisting the aid of over 1000 volunteers for approximately an hour once a year to walk outside and press the 'Save Data' button in the 'Sea Level Rise' app every few steps along the water's edge near them during the king tide. The approach to presenting time series information and inundation areas for a flood model at the street-level can be a difficult task for development and comprehension. To simplify the approach, the open-source SCHISM model was developed at VIMS and used to compute Tidewatch's temporal-spatial inundation maps [36]. SCHISM is an open-source community-supported modeling system, designed for the effective simulation of 3D baroclinic circulation across ocean-to-creek scales. The model incorporates a wide range of physical and biological processes in a comprehensive modeling system that has been validated in many world-wide applications, ranging from general circulation [37], tsunami inundation [38], storm surge inundation [39], ecology [40], sediment transport [41], and oil spills [42]. The model is uniquely capable of accurately representing physical structures (both nature-based and engineered) in an inundated area in the model computations, not simply in the output displays. Furthermore, the outputs from this model can be nested with other hydrodynamic grids to provide street-level (1-5 m scale) urban inundation predictions for individual land parcels [43]. The results may be presented as high-resolutionmovies of flooding scenarios over multi-day periods, including tidal cycle variations, or translated and converted into GIS mapping applications, as seen here with Tidewatch for added utility. SCHISM is used to drive VIMS' Tidewatch's storm tide inundation maps, and the automated workflow to accomplish this is sub-divided into three tasks: (1) Preprocessing of the model grid and retrieval of the hydrodynamic model inputs, (2) SCHISM model simulation, and (3) post-processing retrieval of SCHISM inundation model outputs for GIS mapping, as illustrated in Figure 5:  
2. 2. * Hydrodynamic model simulation along the US East Coast and Gulf of Mexico used a geometric model mesh consisting of 2,348,351 nodes and 1,565,567 elements (Figure 1).