Evaluation of Storm Event Inputs on Levels of Gross Primary Production and Respiration in a Drinking Water Reservoir
,
2
Staehr
Peter A.
Donald C. Pierson3 , Mark S. Zion3 , S. M. Pradhanang1, David G. Smith1
1 CUNY Institute for Sustainable Cities/Hunter College, New York USA
2 Institute of Bioscience, University of Aarhus, Roskilde, Denmark
3 Bureau of Water Supply, New York City Department of Environmental Protection, Kingston, New York, USA
ID No. : OS23A-1658
Contact: [email protected]
Presented at the 2013 AGU Fall Meeting,
9-13 December, San Francisco, USA.
Nihar R.
Samal1,
INTRODUCTION
RESULTS AND DISCUSSIONS:
Weather related episodic events and associated inputs of dissolved and particulate
material during storm events can have important effects on lake and reservoir
ecosystem function and also impact reservoir drinking water quality.
Hurricane Irene
Esopus Creek Inflow (m3 s-1) and Turbidity (NTU) input to Ashokan Reservoir
Storm Events
Storm Events
Significant vertical variability in GPP, R and NEP associated with changes in the depth of the mixed layer and
the euphotic zone
Storm Events
We evaluate the impacts of storm events using vertical profiles of temperature,
dissolved oxygen, and turbidity automatically collected at 6 hour intervals in West
basin of Ashokan Reservoir, which is a part of the New York City drinking water
supply.
Using data from before, during and after storm events, we examine how the balance
between GPP and R is influenced by storm related increases in turbidity and
dissolved organic matter, which would in turn influence light attenuation and bacterial
production.
R (mmol O2 m-3 d-1) for the year 2009
Storm driven inputs to the reservoir periodically resulted in large input of suspended
sediments raising water turbidity beyond 25 NTU. This reduced the euphotic depth,
light availability and thus GPP. Storm inputs stimulated R through elevated external
inputs of organic matter as well as internal inputs from upwelling???.
R (mmol O2 m-3 d-1) for the year 2010
R (mmol O2 m-3 d-1) for the year 2011
NEP (mmol O2 m-3 d-1) for the year 2010
NEP (mmol O2 m-3 d-1) for the year 2011
Daily areal metabolism (mmol m-2 d-1)
STUDY SITE AND DATA ACQUISITION
NEP (mmol O2 m-3 d-1) for the year 2009
Robotic
monitoring station
Temperature (0C) for the year 2009
Temperature (0C) for the year 2010
Temperature (0C) for the year 2011
Ashokan Reservoir Profiling Buoy.
Photo credit: Perri Paul & Tom Mills, NYC DEP
Data: YSI buoy in situ measurements of depth-water temperature,
dissolved oxygen and turbidity in every 6 hour interval and the above
surface measurement of meteorological data (air temperature, wind
speed, and surface PAR in every 15 min interval) for the period:
2009, 2010 & 2011
METHODOLOGY AND APPROACH:
Metabolic rates for each depth layer were calculated using a methodology that
includes biological fluxes (metabolism), air-water gas exchange and DO exchange
between depth layers driven by mixed-layer deepening and eddy diffusivity.
The basic model (Staehr et al. 2012; Obrador et al. 2013) assumes that the DO
change between two consecutive time steps in a given depth layer i (delO2(i)/delt, in
mmol m-3 h-1) is described by:
CONCLUSIONS: Impact of storm eventsDepth specific calculations of gross primary production (GPP), net ecosystem production (NEP), and
respiration (R) in lakes suggest significant variability associated with changes in the depth of the
mixed layer (Zmix) and the photic zone (Zeu).
In this system R often exceeds GPP, which suggest that external C loading plays an important role in
driving R.
Dissolved Oxygen (mg/l) for the year 2009 Dissolved Oxygen (mg/l) for the year 2010 Dissolved Oxygen (mg/l) for the year 2011
During this study extreme hydrological events strongly influenced mixing material transport and water
quality
NEP especially in the upper mixed layer becomes negative as a consequence of increased R
following:
Turbidity (NTU) for the year 2009
NEPi = net ecosystem production, (mmol m-3 h-1)
Dz(i) = flux between layers driven by mixed-layer deepening, (mmol m-3 h-1)
Dv(i) = flux between layers driven by eddy diffusivity, (mmol m-3 h-1)
Ds(i) = air-water gas exchange (mmol m-3 h-1);
Ds(i) = Ks (O2(i) – O2sat(i))/Zmix;
Ks is the gas transfer velocity at the in situ temperature (mh-1)
Turbidity (NTU) for the year 2010
Turbidity (NTU) for the year 2011
 Storm events as GPP is lowed by less available of light and R is likely elevated by allochthonous
C inputs
The decline of phytoplankton blooms as autochthonous C is used by respiration
Extreme events result in the disruption of lake thermal structure and ecosystem metabolism
REFERENCES
Metabolic rates are calculated using an inverse modeling procedure (Hanson et al. 2008)
which calucules NEPi from photosynthetically active radiation (PARi, µmol m-2 s-1) and
Biel Obrador, Peter A. Staehr, and Jesper P.C. Christensen, 2013.Light and mixing regime drive vertical patterns of metabolism in three contrasting lakes, Limnol. Oceanogr. (in press)
temperature (Ti, oC) at each specific depth i.
Klug, J.L., Richardson, D.C., Ewing, H.A., Hargreaves, B.R., Samal, N.R., Vachon, D., Pierson, D.C., Lindsey, A.E., Donnell, D. O', Effler, S.W. and Weathers, K.C. 2012. Ecosystem effects of a tropical cyclone on a network
of lakes in northeastern North America. Environmental Science and Technology: 46 (21), pp 11693–11701
Where Pmax is the maximum photosynthetic rate light (mmol m-3 h-1), alpha is the
photosynthetic efficiency, R20= respiration rate at 20 deg C, Theta is the coefficient
which stands for the thermal dependencies of respiration
Tsai, J.-W., Kratz, T.K., Hanson, P.C., Wu, J.-T., Chang, W.Y.B., Arzberger, P.W., Lin, B.-S., Lin, F.-P., Chou, H.-M., Chiu, C.-Y. 2008. Seasonal dynamics, typhoons and the regulation of lake metabolism in a subtropical humic
lake, Freshwater Biology, 53, 1929–1941