# Validating an Operational Flood Forecast Model Using Citizen Science in Hampton Roads, VA, USA
## 4 Discussion
Aside from depths being directly validated via amplitude comparisons with automated water level sensors, surveyed points collected through _Catch the King_ were merged with a DEM to translate the collected data to contours. While most modern smart phones have an altitude sensor, its error on accuracy is not sufficient to accurately report flood depths or meaningfully report heights above a reference datum. The Sea Level Rise app does display one's altitude in the app interface and records this with each point, but not all phone models share these data with the app or possess the internal hardware to report this. Thus, for the most reliable elevations, the GPS high water marks were merged with the topobathymetric DEM used to build the SCHISM model and the Tidewatch Maps, developed by the USGS [45]. Many citizen scientists were likely to test the app before venturing out to collect data, and several data points that were nowhere near water were collected. Instead, these points appeared in houses, apartment complexes, or traced around isolated puddles in parking lots that were non-contiguous with neighboring estuaries. These locations were flagged for use in storm water studies, and removed from this tidal inundation model validation analysis for any points >0.91 m (3 ft) elevation above NAVD88 were not included in the model comparison, as the king tide from neither year exceeded this height at any water level sensor in the region, and there was no significant rainfall  
Figure 10: Map of radial positional accuracy (in meters) reported by the Sea Level Rise mobile app in Norfolk’s Hague during _Catch the King_ 2017. Points in red were not included in the spatial comparison. (\(>\)2 cm) accumulated during or preceding either _Catch the King_ tidal flood mapping event. In other cases, users mapped tidal-connected drainage ditches that became inundated during the king tides and these points were included in the analysis (Figures 11 and 12). The context through which the degree of inundation was monitored by citizen science data is made more useful through following proper training for data collection and appropriate data filtering. Data were collected by 722 volunteers in 2017 and 431 volunteers in 2018. These data were collected by over 20 different smart phone models, which each vary in terms of relative accuracy due to the number of antennae included in each phone model to aid in triangulation of positional accuracy and for general clarity of cellular broadband communications through the device. As such, citizen science surveys are inherently less precise than those conducted by professional scientists using industry-standard GPS receivers capable of real time kinematics (RTKs). Since the high variation in phone models introduces variable accuracy, as does the number of GPS satellites in range, an estimated radial error metric is reported by the Sea Level Rise app for each GPS measurement by assessing the incoming signals from the global navigation satellite systems along with a correction stream. However, unlike professional survey equipment operated by trained professionals, smart phones are presently unable to achieve the 1 cm positional accuracy that RTK GPS tools can. Thus, points with a radial accuracy metric \(>\)10 m were not included in the spatial comparison (Figure 10). Figure 11: Examples of obtaining aerial elevations from lidar and conducting hydro-correction to assure unobstructed ditch and creek channels persist for hydrologic transport of king tide inundation in the City of Hampton, VA. Red highlighted boxes correspond to areas depicted in Figure 12A,B. Upon filtering for these three things, it was found that the Tidewatch Map comparisons on 5 November 2017 during _Catch the King_ 2017 had an overall MHDD of 5.9 m (19.3 ft). This statistic was calculated from 57,986 of the 59,718 total high water marks collected after less than 3% of the citizen scientists' measurements were filtered out for any of the six reasons previously noted for relative error on duration, depth, or degree of flooding.