ABSTRACT
1
ABSTRACT Much recent work has suggested that nitrogen fluxes to the coastal zone depend on interactions between input loading rates, climate, and landscape processes. Direct relationships between nitrogen inputs and riverine fluxes have been shown with a relatively simple nitrogen accounting methodology for 16 large watersheds in the northeastern US (Boyer et al., 2002). More recently, statistical models have shown that the average response of these watersheds per unit nitrogen load is strongly related to precipitation or hydrology (Howarth et al., in press). To extend this approach to examine the temporal response of these systems in response to climate and land use change, we are developing a simple Regional Nutrient Management model (ReNuMa) based on watershed-scale water balances and statistical relationships between N loads and responses. For the 6-year period examined so far, interannual discharge is well predicted over the range of watersheds studied. Nitrogen fluxes vary across watersheds in response to anthropogenic sources, including point sources, atmospheric deposition and fertilizer use. MODELLING DISCHARGE AND NITROGEN FLUXES FROM LARGE WATERSHEDS IN THE NORTHEASTERN UNITED STATES D. P. Swaney 1 *, R. W. Howarth 1 , A. E. Galford 1 , E.W. Boyer 2 , C.L. Goodale 1 and R.M. Marino 1 1 Cornell University, Ithaca, NY USA 2 University of California at Berkeley, Berkeley, CA USA *(email: [email protected]) References The predecessor of ReNuMa is the Generalized Watershed Loading Function Model (GWLF): Haith, D. A., Shoemaker, L. L. 1987. Generalized watershed loading functions for stream flow nutrients. Water Resources Bulletin 23(3):471-478. A spreadsheet-based version of the model can be found on the web at: http://cfe.cornell.edu/biogeo/USGSWRI.htm. Other references Acknowledgements This work has been supported by an EPA STAR grant, “Developing regional- scale stressor models for managing eutrophication in coastal marine ecosystems, including interactions of nutrients, sediments, land-use change, and climate variability and change,” EPA Grant Number R830882, R.W. Howarth, P.I. Ongoing work and future directions Our work to date has focused on developing parameterizations of biogeochemical responses related to landuse/landcover: •Atmospheric deposition •Landscape level N retention of agricultural N sources (fertilizer, manure, N-fixation) •Nitrogen retention and losses (DIN) from forests •In-stream and landscape denitrification We are currently working on refining the model parameters for individual watersheds to reduce bias at this scale, as well as developing alternative parameterizations of processes which incorporate results from smaller-scale models. Additional processes to be considered will include: •Phosphorus losses from P-saturated soils •Soil erosion and sediment transport Water & wetland Forest & shrubland Urban & barren ReNuMa: Nitrogen Dynamics Human Waste Direct addition (load) to streams In-stream denitrification Threshold response in DIN concentrations following Aber et al (2003) Direct addition (load) to streams Direct addition to streams Riverine DIN flux Threshold response in DIN concentrations similar to Billen &Garnier (2000) Onsite treatment Wastewater Treatment Plants Atmos Deposition Manure Fertilizer Agricultural N-Fixation Agricultural Landuses Landscape denitrification & other losses Annual DIN flux in 16 large Northeastern US watersheds ReNuMa: Hydrological Dynamics Barren Wetland Vineyards/ orchards Row crops Open Water Forest Shrubland Unsaturated zone Saturated zone Evapotranspiration Snowpack Urban Daily Precipitation Daily Temperature Snowmelt Baseflow Shallow flow/runoff Streamflow 16 watersheds in the Northeastern USA in which Net Anthropogenic Nitrogen Inputs (NANI) have been related to average riverine N fluxes over the period 1988-93 (Boyer et al., 2002). We are extending the analysis to simulate seasonal and annual streamflow and nitrogen fluxes using the ReNuMa model. Annual streamflow in 16 large Northeastern US watersheds M easured vs sim ulated annualstream flow 1988-93 16 NE US w atersheds y = 0.96x + 1.45 R 2 = 0.87 0 20 40 60 80 100 0 20 40 60 80 100 O bserved stream flow (cm /yr)-USG S Sim ulated stream flow (cm /yr) pen ken sac cha conn m oh del sch sus rap jam m er and Bla Hud Pot The 2928 weather stations in the National Climate Data Center network for Northeastern states were identified (http://www.ncdc.noaa.gov/oa/ncdc.html). To select candidate stations for each watershed, Thiessen polygons for the network were generated using ArcView™ 3.2. Stations with polygons intersecting a watershed and with >95% complete records (daily temperature and precipitation) were averaged to obtain representative weather data for each watershed. Missing temperature data for each station were replaced with averages of the records preceding and following the missing interval; missing precipitation values were replaced with zero. Minor adjustments to evaporative cover factor for the Androscoggin and Susquehanna rivers were the only changes made to baseline parameter values for the watersheds. While individual watersheds may exhibit some bias above or below observations (ie USGS annual streamflows http://waterdata.usgs.gov/nwis/ ), agreement over all years and across all watersheds was generally good. Preliminary comparison of simulated vs observed annual DIN fluxes for the 12 watersheds with adequate observations of DIN; E NS = Nash-Sutcliffe efficiency; n=6 years*12 watersheds =72) ------------------------------------------- ----------------------------------- Run# Run description Bias R 2 E NS ------------------------------------------- ----------------------------------- 1 Baseline (all sources) +6.4 .89 .88 2 Pt sources + agriculture -17.5 .86 .84 + N dep (no forest) 3 Pt sources + agriculture -82 .90 .78 4 Pt sources + agriculture -142 .83 .57 without load response 5 Pt sources only -225 .71 .13 Examples of threshold responses in agricultural and forest systems in the literature. Left: response of [NO3] to fertilizer loads in agricultural leachate (Billen & Garnier, 2000); Right: response of [NO3] to N deposition in forest leachate (Aber, et al., 2003). We use a similar parameterization to estimate landscape response from these land cover types. SCS runoff equation for each cover type (1 st order linear reservoir) Across all watersheds, simulated annual DIN fluxes also match observed values reasonably well. Some individual watersheds exhibit significant bias above or below observed fluxes, but generally correlate with annual changes variations reasonably well. Human waste contributes N through sewers and septic system effluent. N deposition traverses lakes and wetlands without retention, but exhibits a threshold landscape response in forests. Agricultural N sources (fertilizer, manure and fixation) also exhibit a threshold response due to retention (ie landscape denitrification, etc). The proportions of in-river denitrification are based on estimates in Van Breemen et al., 2002) Aber, J. D., C. L. Goodale, S. V. Ollinger, M.-L. Smith, A. H. Magill, M. E. Martin, R. A. Hallett, and J. L. Stoddard. 2003. Is Nitrogen Deposition Altering the Nitrogen Status of Northeastern Forests? Bioscience 54(4):375-389. Billen, G. and J. Garnier. 2000. Nitrogen transfers through the Seine drainage network: a budget based on the application of the ‘Riverstrahler’ model. Hydrobiologia. 410: 139–150. Boyer, E.W., C. L. Goodale, N. A. Jaworski and R. W. Howarth. 2002. Anthropogenic nitrogen sources and relationships to riverine nitrogen export in the northeastern U.S.A. Biogeochemistry 57/58:137-169. Howarth, R.W., D.P. Swaney, E.W. Boyer, R.M. Marino, N. Jaworski and C.L. Goodale. The influence of climate on average nitrogen export from large watersheds in the Northeastern United States. Accepted for publication in Biogeochemistry. Van Breemen, N., E.W. Boyer, C.L. Goodale, N.A. Jaworski, K. Paustian, S.P. Seitzinger, K. Lajtha, B. Mayer, D. Van Dam, R.W. Howarth, K.J. Nadelhoffer, M. Eve, and G. Billen. 2002. Where did all the nitrogen go? Fate of nitrogen inputs to large watersheds in the northeastern U.S.A. Biogeochemistry 57/58: 267–293. Simulated annual DIN fluxes improve as more sources are added. Here, the scenarios show the increase in several goodness-of-fit measures as more terms are included in the model. Point sources alone (#5) underpredict the DIN load, but still exhibit a significant R 2 (ie a linear relationship with observations). Adding a fixed contribution from agricultural lands greatly improves the agreement, and adding a load-dependent contribution improves it further. Direct N deposition and the response of forests also improves the agreement with observed fluxes across watersheds. AnnualD IN fluxes 1988-93 12 N E U S w atersheds y = 0.96x -12.68 R 2 = 0.88 0 500 1000 1500 2000 0 500 1000 1500 2000 O bserved D IN flux (kg/km 2/yr)(B oyer,pers com m) Sim ulated dissolved N flux (kg/km 2/yr) 1:1 pen ken sac cha (adjusted) conn m oh del sch sus rap jam m er
description
MODELLING DISCHARGE AND NITROGEN FLUXES FROM LARGE WATERSHEDS IN THE NORTHEASTERN UNITED STATES D. P. Swaney 1 * , R. W. Howarth 1 , A. E. Galford 1 , E.W. Boyer 2 , C.L. Goodale 1 and R.M. Marino 1 1 Cornell University, Ithaca, NY USA - PowerPoint PPT Presentation
Transcript of ABSTRACT
ABSTRACT
Much recent work has suggested that nitrogen fluxes to the coastal zone depend on interactions between input loading rates, climate, and landscape processes. Direct relationships between nitrogen inputs and riverine fluxes have been shown with a relatively simple nitrogen accounting methodology for 16 large watersheds in the northeastern US (Boyer et al., 2002). More recently, statistical models have shown that the average response of these watersheds per unit nitrogen load is strongly related to precipitation or hydrology (Howarth et al., in press). To extend this approach to examine the temporal response of these systems in response to climate and land use change, we are developing a simple Regional Nutrient Management model (ReNuMa) based on watershed-scale water balances and statistical relationships between N loads and responses. For the 6-year period examined so far, interannual discharge is well predicted over the range of watersheds studied. Nitrogen fluxes vary across watersheds in response to anthropogenic sources, including point sources, atmospheric deposition and fertilizer use.
MODELLING DISCHARGE AND NITROGEN FLUXES FROM LARGE WATERSHEDS IN THE NORTHEASTERN UNITED STATES
D. P. Swaney1*, R. W. Howarth1 , A. E. Galford1, E.W. Boyer2, C.L. Goodale1 and R.M. Marino1
1Cornell University, Ithaca, NY USA
2University of California at Berkeley, Berkeley, CA USA*(email: [email protected])
ReferencesThe predecessor of ReNuMa is the Generalized Watershed Loading Function Model (GWLF): Haith, D. A., Shoemaker, L. L. 1987. Generalized watershed loading functions for stream flow nutrients. Water Resources Bulletin 23(3):471-478. A spreadsheet-based version of the model can be found on the web at: http://cfe.cornell.edu/biogeo/USGSWRI.htm.
Other references
Acknowledgements
This work has been supported by an EPA STAR grant, “Developing regional-scale stressor models for managing eutrophication in coastal marine ecosystems, including interactions of nutrients, sediments, land-use change, and climate variability and change,” EPA Grant Number R830882, R.W. Howarth, P.I.
Ongoing work and future directions
Our work to date has focused on developing parameterizations of biogeochemical responses related to landuse/landcover:
•Atmospheric deposition
•Landscape level N retention of agricultural N sources (fertilizer, manure, N-fixation)
•Nitrogen retention and losses (DIN) from forests
•In-stream and landscape denitrification
We are currently working on refining the model parameters for individual watersheds to reduce bias at this scale, as well as developing alternative parameterizations of processes which incorporate results from smaller-scale models. Additional processes to be considered will include:
•Phosphorus losses from P-saturated soils
•Soil erosion and sediment transport
Water & wetland
Forest &shrubland
Urban & barren
ReNuMa: Nitrogen Dynamics
Human Waste
Direct addition (load) to streams
In-streamdenitrification
Threshold response in DIN
concentrations following Aber et al (2003)
Direct addition (load) to streams
Direct addition to streams
Riverine DIN flux
Threshold response in DIN concentrations similar to
Billen &Garnier (2000)
Onsite treatment
WastewaterTreatment
Plants
AtmosDeposition
Manure
Fertilizer
Agricultural N-Fixation
AgriculturalLanduses
Landscapedenitrification& other losses
Annual DIN flux in 16 large Northeastern US watersheds
ReNuMa: Hydrological Dynamics
Barren WetlandVineyards/orchards
Row cropsOpen Water Forest Shrubland
Unsaturated zone
Saturated zone
EvapotranspirationSnowpack
Urban
DailyPrecipitation
Daily Temperature
Snowmelt
Baseflow
Shallow flow/runoff
Streamflow
16 watersheds in the NortheasternUSA in which Net AnthropogenicNitrogen Inputs (NANI) have beenrelated to average riverine N fluxes overthe period 1988-93 (Boyer et al., 2002). We are extending the analysis to simulateseasonal and annual streamflow andnitrogen fluxes using the ReNuMa model.
Annual streamflow in 16 large Northeastern US watersheds
Measured vs simulated annual streamflow 1988-9316 NE US watersheds
y = 0.96x + 1.45
R2 = 0.87
0
20
40
60
80
100
0 20 40 60 80 100
Observed streamflow (cm/yr) -USGS
Sim
ula
ted
str
eam
flo
w
(cm
/yr)
pen
ken
sac
cha
conn
moh
del
sch
sus
rap
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and
Bla
Hud
Pot
The 2928 weather stations in the National Climate DataCenter network for Northeastern states were identified(http://www.ncdc.noaa.gov/oa/ncdc.html). To select candidate stations for each watershed, Thiessen polygonsfor the network were generated using ArcView™ 3.2. Stations with polygons intersecting a watershed and with >95% complete records (daily temperature and precipitation) were averaged to obtain representative weather data for each watershed. Missing temperaturedata for each station were replaced with averages of the records preceding and following the missing interval; missing precipitation values were replaced with zero.
Minor adjustments to evaporative cover factor for the Androscoggin and Susquehanna rivers were the only changes made to baseline parameter values for the watersheds. While individual watersheds may exhibit some bias above or below observations (ie USGS annual streamflows http://waterdata.usgs.gov/nwis/ ), agreement over all years and across all watersheds was generally good.
Preliminary comparison of simulated vs observed annual DIN fluxes for the 12 watersheds with adequateobservations of DIN; ENS = Nash-Sutcliffe efficiency; n=6 years*12 watersheds =72)-----------------------------------------------------------------------------
-Run# Run description Bias R2
ENS
------------------------------------------------------------------------------
1 Baseline (all sources) +6.4 .89.88
2 Pt sources + agriculture -17.5 .86.84 + N dep (no forest)
3 Pt sources + agriculture -82 .90.78
4 Pt sources + agriculture -142 .83.57
without load response5 Pt sources only -225 .71
.13
Examples of threshold responses in agricultural and forest systems in the literature. Left: response of [NO3] to fertilizer loads in agricultural leachate (Billen & Garnier, 2000); Right: response of [NO3] to N deposition in forest leachate (Aber, et al., 2003). We use a similar parameterization to estimate landscape response from these land cover types.
SCS runoff equationfor each cover type
(1st orderlinear reservoir)
Across all watersheds, simulated annual DIN fluxes also match observed values reasonably well. Some individual watersheds exhibit significant bias above or belowobserved fluxes, but generallycorrelate with annual changes variations reasonably well.
Human waste contributes N through sewers and septic system effluent. N depositiontraverses lakes and wetlands without retention, but exhibits a threshold landscape response in forests. Agricultural N sources (fertilizer, manure and fixation) also exhibit a threshold response due to retention (ie landscape denitrification, etc). The proportions of in-river denitrification are based on estimates in Van Breemen et al., 2002)
Aber, J. D., C. L. Goodale, S. V. Ollinger, M.-L. Smith, A. H. Magill, M. E. Martin, R. A. Hallett, and J. L. Stoddard. 2003. Is Nitrogen Deposition Altering the Nitrogen Status of Northeastern Forests? Bioscience 54(4):375-389.
Billen, G. and J. Garnier. 2000. Nitrogen transfers through the Seine drainage network: a budget based on the application of the ‘Riverstrahler’ model. Hydrobiologia. 410: 139–150.
Boyer, E.W., C. L. Goodale, N. A. Jaworski and R. W. Howarth. 2002. Anthropogenic nitrogen sources and relationships to riverine nitrogen export in the northeastern U.S.A. Biogeochemistry 57/58:137-169. Howarth, R.W., D.P. Swaney, E.W. Boyer, R.M. Marino, N. Jaworski and C.L. Goodale. The influence of climate on average nitrogen export from large watersheds in the Northeastern United States. Accepted for publication in Biogeochemistry.
Van Breemen, N., E.W. Boyer, C.L. Goodale, N.A. Jaworski, K. Paustian, S.P. Seitzinger, K. Lajtha, B. Mayer, D. Van Dam, R.W. Howarth, K.J. Nadelhoffer, M. Eve, and G. Billen. 2002. Where did all the nitrogen go? Fate of nitrogen inputs to large watersheds in the northeastern U.S.A. Biogeochemistry 57/58: 267–293.
Simulated annual DIN fluxes improve as more sources areadded. Here, the scenariosshow the increase in severalgoodness-of-fit measuresas more terms are includedin the model. Point sources alone (#5) underpredict the DIN load, but still exhibit a significant R2 (ie a linearrelationship withobservations).Adding a fixedcontribution from
agricultural lands greatly improves the agreement, and adding a load-dependentcontribution improves it further. Direct N deposition and the response of forestsalso improves the agreement with observed fluxes across watersheds.
Annual DIN fluxes 1988-9312 NE US watersheds
y = 0.96x - 12.68
R2 = 0.88
0
500
1000
1500
2000
0 500 1000 1500 2000
Observed DIN flux (kg/km2/yr) (Boyer, pers comm)
Sim
ula
ted
dis
so
lve
d N
flu
x
(kg
/km
2/y
r)
1:1
pen
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cha (adjusted)
conn
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mer
