# Validating an Operational Flood Forecast Model Using Citizen Science in Hampton Roads, VA, USA
## 2 Methods
### Volunteer Coordination for Flood Extent Validation  
The volunteer coordination effort involved a hierarchical scheme led by an adept volunteer coordinator, [PERSON], from the Chesapeake Bay Foundation who has successfully led the 'Clean the Bay Day' litter and debris removal initiative in Chesapeake Bay for several years prior to _Catch the King_. Below the volunteer coordinator were over 120 volunteer \"Tide Captains,\" who led smaller organized groups of volunteers. In many cases, these tide captains were knowledgeable school teachers, volunteer organization leaders, and enthusiastic users of the Sea Level Rise mobile app, who trained neighbors, friends, and family in their community over a series of separate volunteer training events held all over Hampton Roads, VA, USA [16]. Citizen scientists were trained in the use of the 'Sea Level Rise' mobile application to capture three types of flood data useful for model validation:  
1. GPS locations for mapping high water contours during flooding (Figure 3);
2. Taking field notes for important observations or denoting errata; and
3. Uploading time-stamped, geo-tagged pictures, including directional facing information.  
Figure 2: Catch the King (CtK) citizen engagement time series chart corresponding to major news releases used to garner successful volunteer training participation and support leading up to the king 173 tide on November 5, from July 30–November 10, 2017. According to ArcGIS Online’s data metrics, the volunteer invitation story map received 10,137 page views, in little over 3 months for an average of 93 page views per day. Story Map at: [[http://arcg.is/1f8W1q](http://arcg.is/1f8W1q)]([http://arcg.is/1f8W1q](http://arcg.is/1f8W1q)).  
Training volunteers in proper, uniform data collection and appropriate geospatial filtering for these three data types is critical to recording an accurate location history for mapping tidal flooding and ensure the most effective approach for collecting error-free data for model validation. More than 45% of the volunteers were directly trained in a training session in 2017's event, while nearly 60% of the volunteers were trained in a training session.  
Figure 3: Comparison of GPS maximum flood extent observations (depicted as blue dots) in Hampton, VA, following debris lines remaining after Hurricane Irene 2011, used to geospatially verify model performance at (**A**) 00:00 UTC and (**B**) 01:00 UTC on 28 August 2011. GPS data collected by volunteers effectively illustrate the challenge with temporal matching for model comparison.  
attended a training in 2017 [35]. However, in both years, many volunteers were still able to register as users and meaningfully map flooding in their community through Catch the King without any formal training, partially owing to the relatively intuitive interface of the app.  
The 'Sea Level Rise' mobile app streamlined data collection and made model validation easier through a hierarchical internal quality assurance mechanism. This allowed the Catch the King event coordinator to limit participation to certain trusted registered users, and filter data permissions, such as photo uploads and GPS data collection, only to certain trained users (labeled as 'Champions' in the app interface). Post-event, tide captains and the volunteer coordinator could download their event data as csv files after the specified time window for their flood monitoring event expired, and even retroactively flag volunteer's data where consistently erroneous data points were measured. The resulting maps shown in the results and discussion sections present these dense data maps surveyed during the 2017 and 2018 king tide inundation events, and present the mean horizontal distance difference (MHDD) comparative spatial calculations between the modeled maximum flood extent contours and citizen science flood validation data sets for each king tide flood event, followed by the lessons learned.