# Validating an Operational Flood Forecast Model Using Citizen Science in Hampton Roads, VA, USA
## 3 Results
While the areas shown in Figure 8 were surveyed by few citizen scientists, the area shown in Figure 6B is one of the most frequently monitored areas in the Sea Level Rise app's history. During 2017's _Catch the King_, the area featured in Figure 6B was monitored by 27 different volunteers at different times (not all during the flood peak period) to form 27 king tide inundation contours for The Hague. These were mosaicked into a composite maximum extent contour map comprised of 1134 GPS points stretching 2.17 km to form a maximum extent contour for VIMS to compare with its Tidewatch Maps modeled inundation. The total distance walked and recorded using the Sea Level Rise app by all 27 volunteers for The Hague alone in 2017's _Catch the King_ was 22.58 km (Figure 6B). This is 10.39\(\times\) the composite's distance at this king tide inundation site, meaning \(>\)10\(\times\) the actual effort, or about a 10\(\times\) greater distance was walked than represented by the composite 0 m flood depth contour. As a result, these distances along the waterways that were travelled as effort expended by volunteers was significantly greater than needed to efficiently validate the flooding extents (by 10\(\times\)), and this is not counting a volunteer's travel to and from each reported flood site. Figure 7: Illustrative comparison of mean distance difference of 112 GPS data points collected in Larchmont, Norfolk (2.67 m), compared with the 2018 king tide peak inundation forecast in blue. Figure 8: Model comparison of forecasts and data from 13:00 to 13:59 UTC at left, and 14:00 to 14:59 UTC used to show varying flooding conditions during the 2017 king tide at four sites ranging from residential, commercial, and industrial land uses throughout Norfolk, VA.  
For perspective, the grand total for over 1000 volunteers to map inundation distances across both _Catch the King_ years was 631.35 km, with the total number of unique king tide contours travelled in Hampton Roads across both years adding up to 173.65 km (Table 1). Therefore, significantly more effort was used than needed to effectively map the site, with Norfolk's Hague experiencing the greatest duplicated effort. This was also indicative of overlapping efforts among other high-density monitoring areas at public beaches in Norfolk, Virginia Beach, and Hampton representing the other greatest density GPS data density areas with >6\(\times\) overlap. As noted previously, the increased density of GPS data proved to be a boon towards supporting the development of data-driven area maps, which was useful in The Hague, but were less useful on public coastal beaches where the water was not surrounded by land, with transient sand elevations that may vary from those embedded in the hydrodynamic model via the latest lidar elevation surveys. Thus, in 2018's _Catch the King_, greater emphasis was placed on coordinating volunteers at registration to commit to mapping unique locations when communicating with volunteers via training events, and through print and social media to best value their time commitment and most efficiently validate the model. Aside from the horizontal GPS surveys reported through _Catch the King_, Tidewatch is routinely validated through automated water level monitoring sites. An overview of the water level sensor data extracted from sensors through Tidewatch Charts during _Catch the King_ 2018 across all data points revealed a favorable average vertical accuracy assessment of 3.7 cm via the root mean squared error (RMSE). This metric was drawn from 28 StormSense water level sensors, and 16 tidal USGS Sensors and 4 NOAA sensors. Six of these sensors, including three NOAA, two StormSense, and one USGS sensor, are shown in Figure 9 from VIMS' Tidewatch Charts, as an example comparison of hydrodynamic model performance during 2018's _Catch the King_.