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Other influential variables considered for the analyzes included precipitation (mm), obtained in the databases of the National Meteorological Service of Mexico, and bottom type detected by the side-scan sonar and coded as: mangrove (1), dense grasses (2), scattered grasses (3) and silt substrate (4) (González-Socoloske and Olivera-Gómez 2012 McLarty et al. Each selected water body was named in accordance to the nomenclature of the Mexican water network (INEGI 2017a), by the closest locality, or according to the references provided by local people: Boca (mouth), Four Mile, López (Subteniente López), Chac (Estero Chac), Ucum, Diablo (river of the Curva del Diablo) and Román (river of the village of San Román). A bathymetric map was also created from the sonar recordings.

Sparse seagrass was the least accurately identified. Dense seagrass was most accurately identified. A manually zoned benthic substrate map was created from the sonar recordings. Unidentifiable substrates were classified as unknown. Five substrate types were identified: dense seagrass, sparse seagrass, mangrove soil, mangrove soil with rock, and silt. Videos and pictures were taken at various points to groundtruth the sonar images and provide a measure of accuracy. A total area of 11.55 km ² was surveyed with the sonar. In this study, the reliability of the side-scan sonar to accurately identify softer substrates such as grass and mud was tested in a large, brackish lagoon system. Previous research has demonstrated that low cost side-scan sonar is a reliable way to identify hard substrates, such as rock and gravel, in a small, freshwater stream. Benthic substrates are often not visible from the surface making it necessary to find another method to gather these data. Identifying benthic substrates is important to researchers studying aquatic organisms in fresh and salt water systems.