Researchers installed environmental sensors near an eddy flux tower to measure variables needed to quantify the water budget of a mixed pine forest over multiple years. This included installing two understory meteorological stations and 28 groundwater wells. Preliminary results showed the stations successfully measured rainfall, soil moisture, evapotranspiration and groundwater levels. The data will help understand differences between longleaf and loblolly pine species and their impacts on the local environment and water availability.

1.  To investigate the sub canopy of a mixed pine forest, two sub
stations capable of measuring meteorological variables (MET
stations) were installed in the footprint of an eddy flux tower.
Jenkins, J.P., Richardson, A.D., Braswell, B.H.,Ollinger, S. V., Hollinger D. Y., Smith, M.-L. (2006). Refining light-use
efficiency calculations for deciduous forest canopy using simultaneous tower-based carbon flux and radiometric
measurements. Elsevier. pp. Pages 66-65.
South Carolina’s Forest Resource Assessment and Strategy (2010). Conserving South Carolina’s Working Forests.
Retrieved from https://www.state.sc.us/forest/fra-cons.htm
 Climate change impacts water availability in South Carolina. 67% of
South Carolina (13 million acres) is forest, so it is important to
understand the water budgets of the forest to comprehend how it
affects water availability
 There is interest in restoring longleaf pines in South Carolina;
therefore, it is important to understand differences between longleaf
and other pine species and how each species impacts its environment.
INTRODUCTION PRELIMINARY RESULTS
 A flume will be constructed in the coming weeks to capture and
measure the water runoff and drainage in the tower footprint. This will
contribute to completing the hydrological budget of the tower footprint.
 Sensors will collect data continuously over the next few years to
capture the seasonal dynamics of the forest in order to model the
complete water budget of the stand.
MOVING FOWARD
We are grateful for support from the Baruch Institute of Coastal
Ecology and Forest Science, the South Carolina Water Resources
Center, and the Clemson University UPIC Program.
ACKNOWLEDGEMENTS
Figure 1. Components of a low-gradient watershed. Water enters the forest as rainfall and is
either intercepted by vegetation, absorbed into the soil, or directed into drainage basins as runoff.
Water can escape back into the atmosphere by evaporation or evapotranspiration.
 Installation of 28 groundwater
wells to measure depth of water
table of the forest
 To install each well a 10 ft. hole
was augured in the ground.
 Soil samples were taken every 6
in. during the auguring procedure.
 A well shaft constructed from
PVC pipe was driven into the
hole.
 Water was pumped in and out of
the installed wells to clear any
loose sediment surrounding the
well.
 Calibrating the MET station PAR sensors with the tall tower’s
PAR sensors
Figure 7. Initial comparison (left) and corrected comparison (right) of PAR data from MET station
vs the Tall Tower (all PAR sensor measure in units of umol photons m-2 s-1). Upon correction,
RMSE error was reduced by approximately 50%, and a 1:1 relation in the data set was
established with zero offset.
Figure 3. (Left) Well
#4 collecting date in
the field.
Figure 4. Diagram of MET Stations, which are located in the footprint of a 37m tall eddy flux
tower. Each MET Station has a rain gauge, PAR sensor, temperature and relative humidity
sensor, soil moisture probe, and a datalogger. Each MET station also has two sub platforms
~10m in opposing directions that have an additional rain gauge and PAR sensor.
Figure 8. (Left) Hydrological data figures.
The top graph shows precipitation in mm
per minute as well as total precipitation.
The middle graph shows soil moisture
measured by the MET stations at various
depths along with the weather table depth
from well 15. The bottom graph shows
rate of evapotranspiration calculated from
measurements from the tall tower.
Figure 9. (Above) Scans of soils extracted
during well excavation. These scans illustrate
the soil texture and color. These examples
show aquifer material representative of the
two major soils in the tower footprint. Well 7
features sandy soils stained with iron oxide.
Well 20 contains spodosols over organic-
stained sand down to about 8 ft.
Figure 2. (Right) Dr.
Williams and Michael
Kline working on a
well installation.
Figure 5. (Above) The eddy flux tower
seen from above the canopy of a mixed
pine forest.
PRELIMINARY RESULTS
ACKNOWLEDGEMENTS
INTRODUCTION
METHODS
Figure 6. (Left)
Hunter Morgan
and the
completed
longleaf MET
understory
station collecting
data in the field.
36.5 m
18 m
21 m
batteries
log
2 m
12 m
24 m
30 m
33 m SPN1 PRI PAR NET RAD
Cell GPS
CO2, H2O and heat fluxes
Tair, RH
Tair, RH
Tair, RH
Longleaf Pine Loblolly Pine
Tair, RH
MET STATION MET STATION
Tair, RH Tair, RH
PAR
PAR
Rain gauge Rain gauge
Soil moisture
Soil moisture
log log
REFERENCES
 My goal for the summer of 2019 was to complete a network of
environmental sensors, focused around a 37m tall eddy covariance
tower, to measure the variables needed to quantify and model
(forecast) the water budget of the forest (Figure 1). This includes:
 Understory sensors for measuring light interception, which can be
used to model leaf area index as a biological model input
 Understory sensors for measuring rain throughfall and soil moisture
in predominantly loblolly vs. longleaf areas for comparing differences
in water use by species
 A network of 28 groundwater wells
OBJECTIVES