Data from: A pilot study for water storage and carbon variability in an irrigation pond of the Southeastern Plains, USA

Farm ponds are a common feature of agricultural landscapes for irrigation of crops. Yet small water bodies have been ignored as reservoirs and carbon balance features despite ubiquity in the global landscape. These ponds contain surface water from precipitation and runoff, but in South Georgia, USA, groundwater supplementation is required to maintain a supply for irrigation. As part of a project to characterize water balance and quality of irrigation ponds in this landscape, data were collected describing terrain, bathymetry, inputs and outputs, and water quality from October 2021 through October 2023. The pond described in this study was located on a farm near Ty Ty, GA (Ty Ty Cooperator Farm, TCF; 31.5086980, -83.6167862). The TCF is a rotational cropping system, alternating among corn, cotton, and peanuts. During the 2022 growing season, the fields adjacent to the pond were planted with corn. Datasets include georeferenced image files (.tif) and tabular files (.csv). Image data were obtained on 27 SEP 2022 at approximately 0915 local time using a commercial, off-the-shelf unmanned aircraft system (UAS; DJI Mavic 2 Pro L1P) with an integrated digital RGB camera (Hasselblad L1D-20c_10.3 RGB with 20MP 1" CMOS sensor). The UAS was flown at 107 meters above ground level with 75% front and side overlap to capture an area of 12.99 ha. The images were used to produce an orthorectified mosaic (RMS error = 0.001 m) with 2.5 cm average ground sample distance (GSD), and a digital terrain model (DTM) with 12.5 cm GSD using 5 surveyed ground control points. A derived topobathymetric surface (12.5 cm GSD) was created by fusing bathymetric and topographic survey data. All geospatial data were projected in WGS84 / UTMZone 17N (EGM96 Geoid). Tabular data include GPS survey data points of the bathymetry and shoreline, and log files of daily water pumping into and out of the pond (acre-inches), 5-minute staff gauge levels within the pond (US feet), and 1-minute precipitation data (inches) at the farm. Water pumping, pond level and precipitation data were measured using instrumentation and data loggers operated by the USDA ARS Southeast Watershed Research Laboratory. Relevant water chemistry data were also recorded for this study, are flagged (Flag = 4) and are published separately by Pisani et al (2025) in the USDA Ag Data Commons repository, as "Water chemistry data for three agricultural ponds in the southern Coastal Plain of Georgia, USA".

Datasets provided here include:

1. A georeferenced orthomosaic (.tif) of aerial imagery of the study site from 27SEP2022 (1_TyTyCooperatorFarm_RGB_mosaic_20220927.tif)

2. A digital terrain model (.tif) of the study site, produced from provided orthomosaic from 27SEP2022 (2_TyTyCooperatorFarm_DTM_20220927.tif)

3. A fused topobathymetric surface model (.tif) of the study site (3_TyTyCooperatorFarm_DTM_20220927.tif)

4. Survey data points from a bathymetric survey providing global positioning system (GPS) outputs (4_TyTyCooperatorFarm_Bathymetry_Survey_20220923_20220927.csv) NOTE: Field values for Tables 4 and 6 are nearly identical. Refer to Table 4 for values in Table 6.

5. Water amounts pumped into and out of the study site pond in 2022 (5_TyTyCooperatorFarm_InOut_Pumping_Data_2022.csv)

6. Survey data points from a shoreline survey providing global positioning system (GPS) outputs (6_TyTyCooperatorFarm_Shoreline_Survey_20220922.csv) NOTE: Field values for Tables 4 and 6 are nearly identical. Refer to Table 4 for values in Table 6.

7. Water elevation readings from a staff gauge in the pond at the study site 2021 through 2023 (7_TyTyCooperatorFarm_Staff_Gauge_Pressure_Readings_2021_2023.csv)

8. Rainfall precipitation measured at the study site during 2022 (8_TyTyCooperatorFarm_Precipitation_Rainfall_2022.csv)

9. Dataset dictionary: Tabular data field values for tables 4 – 9 (9_TyTyCooperatorFarm_Data_Dictionary_Pond_Study_2022.xlsx). NOTE: Field values for Tables 4 and 6 are nearly identical. Refer to Table 4 for values in Table 6.al. Refer to Table 4 for values in Table 6.