**3. Methodology**

From 2014 to the present, surface water and groundwater elevations in various areas of the course have been surveyed or measured during and after floods (**Figure 1**). Water-level loggers were installed in various configurations to examine (1) groundwater elevations on the former course and its fluctuation in response to streamflow and flooding, and (2) surface water elevations and head differences between Mad River and the former course during flood events (**Figure 1**). At any given time, between two and four Solinst Leveloggers were deployed during the course of the study at various locations to measure surface water and groundwater water depths at 15- to 60-min intervals. Depths were compensated for barometric pressure and converted to water-level elevations using surveyed water levels during the period of measurement. Shallow monitoring wells were hand-augured to depths of approximately 2 m. While some were equipped with water-level loggers, depth to water was periodically measured in others using a steel-measuring tape and converted to waterlevel elevations. Open bodies of water (i.e., water hazards on the former course) were considered to represent groundwater level because all were excavated in sand and gravel outwash.

During the initial stages of this study, I realized flooding from stormflow events on Mad River was more frequent than anticipated, presenting an opportunity to study flood storage potential. Immediately following many of these flood events, the elevations of high-water marks, indicated by the highest accumulations of organic debris or surface ice, were surveyed. Flood storage potential was estimated by two means, modeling culvert flow based on the head difference between the Mad River

#### **Figure 5.**

*To examine flood storage potential, water level was logged at 15-min intervals on either end of the culvert and converted to elevation. The difference in elevation, or head, was used in calculating culvert flow.*

### *Assessing the Potential Flood Mitigation Services of a Former Golf Course with a Focus on Flood… DOI: http://dx.doi.org/10.5772/intechopen.113107*

and surface water elevation on the course and calculating the volume difference between the golf course surface and high-water elevation of a given flood.

Under flood conditions on Mad River, the culverts connecting Mad River with the former Snyder Park Golf Course exhibit full barrel flow [8]. In this case, the culverts are in pressure flow throughout their length, driven by the positive head between the river and the golf course. For the floods modeled in this study, datalogger data confirm that the inlet and outlet are fully submerged. This condition is often assumed in calculations [8] and is the basis for the nomograph estimations of discharge presented here. They also note that the equations and nomographs for submerged, full flow can be reasonably applied to culverts with no slope or an adverse slope. The culvert in this study has an adverse slope (**Figure 4**). Culvert discharge was calculated at a 15-min interval using a spreadsheet solution to the flow equation in [8] based on the head difference (**Figure 5**), an entrance loss coefficient (Ke), and culvert length and diameter. A value of 0.9 for Ke, representing a corrugated metal pipe projecting on either side, was used.

Flood storage was also estimated using the Cut Fill tool in ArcGIS ArcMap 10.8.2. The Cut Fill tool is used to calculate a volume difference between two input raster surfaces at two different time periods, prior to flooding and at peak flood. The surface prior to flooding is the bare earth digital elevation model (DEM) based on LiDAR. The surface at peak flood is created for each flood based on high-water marks or peak surface water elevation. Flood surfaces for two events are shown in **Figure 6**. Peak flood elevation is assumed flat for calculation purposes, but there is a negligible slope from the culverts to distant points of flooding.

#### **Figure 6.**

*The lower elevations of the former course frequently flood. Two floods are depicted here from the sequence of floods used in the study to estimate flood storage. The November 2, 2018 and may 17, 2019 floods inundated 13 and 17 acres, respectively.*
