Understanding surface water storage using fused topobathy datasets of small agricultural ponds of the southern Coastal Plain of Georgia

Authors: Coffin, Alisa; ALBRIGHT, ANDREA - Orise Fellow; Bosch, David - Dave; Pisani, Oliva; Strickland, Timothy - Tim

Submitted to: Interagency Conference on Research in the Watersheds
Publication Type: Abstract Only
Publication Acceptance Date: 4/7/2023
Publication Date: 6/4/2023
Citation: Coffin, A.W., Albright, A., Bosch, D.D., Pisani, O., Strickland, T.C. 2023. Understanding surface water storage using fused topobathy datasets of small agricultural ponds of the southern Coastal Plain of Georgia. Interagency Conference on Research in the Watersheds. na.

Interpretive Summary: Irrigation ponds are a ubiquitous feature in agricultural landscapes as they allow for storage of pumped groundwater until it is needed for crop irrigation. Accurate estimates of surface water storage are needed for calculating and modeling landscape level water balance. However, researchers modeling surface water changes and groundwater usage do not often have access to bathymetry estimates of these ponds. Thus, accurate estimates of surface water volume are not available for many small water bodies without completing an in-situ bathymetry survey. Recently, a case study for measuring bathymetry of typical irrigation ponds was performed by the Southeast Watershed Research Laboratory (SEWRL) in South Georgia. In this case, measurements from in-situ surveys and remotely sensed surveys were fused into continuous topobathy surface models of the pond area. The data sources included depth measurements taken from a boat using a Depthmate SM-5 Portable Sounder, a permanent pond stage gage, precise shoreline locations surveyed using a Trimble Geo7X mapping grade GNSS, and high-resolution RGB imagery collected using an DJI Mavic 2 Pro Unoccupied Aerial System (UAS). All three data sets were used to derive volume and error estimates of the ponds. Additionally, a model shoreline was digitized from the UAS imagery and compared with the in-situ survey to investigate whether such time intensive shoreline surveys are necessary for accurate bathymetry modeling. Surface model data were combined with land use information to estimate areas of land use contributing to the runoff into the ponds.

Technical Abstract: Irrigation ponds are a ubiquitous feature in agricultural landscapes as they allow for storage of pumped groundwater until it is needed for crop irrigation. Accurate estimates of surface water storage are needed for calculating and modeling landscape level water balance. However, researchers modeling surface water changes and groundwater usage do not often have access to bathymetry estimates of these ponds. Thus, accurate estimates of surface water volume are not available for many small water bodies without completing an in-situ bathymetry survey. Recently, a case study for measuring bathymetry of typical irrigation ponds was performed by the Southeast Watershed Research Laboratory (SEWRL) in South Georgia. In this case, measurements from in-situ surveys and remotely sensed surveys were fused into continuous topobathy surface models of the pond area. The data sources included depth measurements taken from a boat using a Depthmate SM-5 Portable Sounder, a permanent pond stage gage, precise shoreline locations surveyed using a Trimble Geo7X mapping grade GNSS, and high-resolution RGB imagery collected using an DJI Mavic 2 Pro Unoccupied Aerial System (UAS). All three data sets were used to derive volume and error estimates of the ponds. Additionally, a model shoreline was digitized from the UAS imagery and compared with the in-situ survey to investigate whether such time intensive shoreline surveys are necessary for accurate bathymetry modeling. Surface model data were combined with land use information to estimate areas of land use contributing to the runoff into the ponds.