Interpreting outputs from the sonar analysis tool

The Benthomap sonar analysis tool is a robust application designed to transform Lowrance sonar datasets into maps and summary statistics, aiding in the effective management of aquatic resources. This post will outline the limitations of the sonar analysis tool and provide guidance on how to accurately interpret its outputs.

The first output we will discuss is the bathymetry map. A bathymetry map is made up of depth estimates made using geostatistical modeling that are based on the data points that were collected. The further these estimates are from actual data points, the less trustworthy they will be and vice versa. These depth estimates are then applied to individual raster pixels to create a smooth surface. How smooth a bathymetry map looks depends on the resolution setting used in data input. The example below shows an example bathymetry map created using a 0.5-m resolution and its corresponding raw sonar data points.

An additional map generated by the sonar analysis tool provides estimates of aquatic vegetation density. When interpreting these maps, it is crucial to understand what the sonar unit measures and how the tool generates vegetation density estimates. Sonar units emit sound waves through the water column and record the intensity of the return signal as it reflects back to the unit after encountering the bottom or other objects. Higher intensity returns can indicate the presence of objects, while lower intensity returns suggest empty water. However, it is not possible to differentiate between high intensity returns caused by vegetation and those caused by other objects. Therefore, it is important to consider information about other structures that are present when interpreting vegetation density maps.

Below is an example of a vegetation density map generated by the sonar analysis tool. Density estimates correspond to the proportion of the total water column where higher intensity sonar returns (potential vegetation or other objects) were measured.

The final type of map we will discuss is of the intensity of the sonar return from the bottom of the waterbody. As the relative hardness of an object or surface increases, the intensity at which a sonar ping returns also increases. Therefore, the intensity of the return from the bottom can be used to estimate the relative hardness of the bottom substrate in a waterbody.

The results table tab in the sonar analysis tool contains tables of summary statistics for both the bathymetry and submerged aquatic vegetation analyses.

The initial bathymetry summary table presents the total area, average depth, and volume estimates of the waterbody. The subsequent table details the surface area corresponding to each specific depth contour.

• Area: surface area of the waterbody, calculated by multiplying the known area of each raster pixel by the total number of raster pixels in the dataset.

• Average depth: the mean of all depths in the dataset, given in the units selected by user input.

• Max depth: the deepest depth estimate in the dataset, given in the units selected by user input.

• Volume: the product of the average depth multiplied by the surface area.

The initial submerged aquatic vegetation (SAV) table presents the average and standard deviation of the SAV density, the percent area covered by SAV, and the total area covered by SAV. The subsequent table details the same summary statistics corresponding to each specific depth contour.

• Average SAV Density: the mean of all SAV density estimates in the dataset.

• % Area Covered: the percentage of the total surface area of the pond that has any vegetation. This metric does not consider height of the vegetation.

• SAV Area: the area of the waterbody that has any vegetation. Similar to % area covered, this metric does not consider height of the vegetation.