# Presentation: 129798

- Developing regional-scale stressor models for managing 	eutrophication in coastal marine ecosystems:
- 	Interactions of nutrients, sediments, land-use change,
- 	and climate variability and change.

**Robert W. Howarth**
**Cornell University **
**EPA/STAR grant:  1 year review**
**June 2004**

## NRC 2000:

**NRC 2000:**
**Nitrogen is now the largest pollution problem in the coastal waters of the United States.**
**Two thirds of coastal rivers and bays are moderately to severely degraded from nitrogen pollution.**

## NRC 2000:

**NRC 2000:**
_**Priority recommendations**_**:**
** ****Improve models for determining how management actions may affect nitrogen fluxes from watersheds, and how these may be affected by climate variability and change**
** ****Develop a classification scheme for the sensitivity of estuaries to nitrogen inputs, as an aid for management decisions**

## Principal Investigator:	
	Robert Howarth, Cornell (biogeochemistry, 			ecosystem science)

Key Personnel and consultants:	
	Roxanne Marino, Cornell (coastal marine 			biogeochemistry, ecosystem science)
	Dennis Swaney, Cornell (watershed modeling)
	Elizabeth Boyer, SUNY/Syracuse ( watershed 		hydrology)
	Merryl Alber, Univ. of Georgia (ecology of 			southeastern rivers and estuaries)
	Don Scavia, Univ. of Michigan (water quality 			modeling)
	David Jay, Oregon State (physical oceanography)

- 	Robert Howarth, Cornell (biogeochemistry, 			ecosystem science)
- Key Personnel and consultants:
- 	Roxanne Marino, Cornell (coastal marine 			biogeochemistry, ecosystem science)
- 	Dennis Swaney, Cornell (watershed modeling)
- 	Elizabeth Boyer, SUNY/Syracuse ( watershed 		hydrology)
- 	Merryl Alber, Univ. of Georgia (ecology of 			southeastern rivers and estuaries)
- 	Don Scavia, Univ. of Michigan (water quality 			modeling)
- 	David Jay, Oregon State (physical oceanography)

## Estuaries vary in sensitivity to nitrogen inputs.

- Examples:  Chesapeake vs. Delaware & San Francisco
- 	Bays, Hudson River estuary.
- For management, target nitrogen reductions for
- 	ecosystems that are most sensitive.
- Will climate change increase or decrease sensitivity?

## Residence time

- Mesohaline Hudson
-      River Estuary
- (Howarth et al. 2000)

- has other
- Influences on
- Sensitivity to
- eutrophication

## Water residence time as master variable controlling sensitivity?

- If so, highly responsive to climate variability and change,
- through change in freshwater runoff.

## Water residence time as master variable controlling sensitivity?

- 	Residence time has numerous influences on sensitivity,
- 	mediated through:
- 	-- flushing of phytoplankton relative to growth
- 	-- flushing and dilution of nutrients
- 	-- influence on denitrification
- 	-- flushing of zooplankton populations relative to growth

## Chl/N load

- Residence time

- Nutrient dilution effect

## Chl/N load

- Residence time

- Nutrient dilution effect

- Phytoplankton
- flushing

## Chl/N load

- Residence time

- Nutrient dilution effect

- Phytoplankton
- flushing

- Denitrification

## Chl/N load

- Residence time

- Nutrient dilution effect

- Phytoplankton
- flushing

- Denitrification

- Top-down
- Control by
- zooplankton

## Chl/N load

- Residence time

- Nutrient dilution effect

- Phytoplankton
- flushing

- Denitrification

- Top-down
- control by
- zooplankton

- Combined
- influences

## Chl/N load

- Residence time

- Potential classes of sensitivity
- to nitrogen pollution

## What next?	Use a simple simulation model of phytoplankton growth at 	different N loadings to evaluate potential interacting effects 	of residence time on sensitivity to eutrophication.	Develop data set on chlorophyll, N loading, and water	residence times in estuaries, using consistent approaches.	Use this data set for statistical analysis of response pattern.	Eventually, begin to consider factors other than water 	residence time (turbidity, stratification and depth of mixing, 	benthic grazing).

## ReNuMa:  Regional Nutrient Management model

**ReNuMa:  Regional Nutrient Management model**

## Flowchart of ReNuMa erosion, sediment, and adsorbed nutrient transport

**Flowchart of ReNuMa erosion, sediment, and adsorbed nutrient transport**

## The parent model (GWLF) does well with hydrology...  It also 

- Swaney et al., 1996)

**The parent model (GWLF) does well with hydrology...  It also **
**predicts erosion well, and so does well with phosphorus fluxes.**
**GWLF lacks some essential processes for nitrogen, particularly **
**atmospheric deposition and denitrification.  We are adding these, **
**plus more on agricultural management options, for ReNuMa.**

## Preliminary model runs to evaluate the response of a watershed to hypothetical scenarios of landuse or climate change...

- In this case, climate changes (an increase of 2 degrees C and 20% increase in precipitation over 10 years) are considered,
- together with a doubling of area  of urban and agricultural landuses...

## Slide 20

## Slide 21

## Anthropogenic nitrogen sources and relationships to riverine nitrogen export

**Anthropogenic nitrogen sources and relationships to riverine nitrogen export**
** ****in the northeastern USA**

**Boyer et al. 2002**

**Notes:**
We focused specifically on portions of the watersheds upstream from individual USGS gaging stations, where long-term measurements of streamflow and water quality exist.
Order of subsequent slides will show graphs with the data presented in longitudinal order from North to South.

## NE region: watershed nitrogen inputs

**NE region: watershed nitrogen inputs**

**Boyer et al. 2002**

**Notes:**
Nitrogen Inputs.  The importance of the relative sources varied widely by watershed and is related to land use.  Dep most important in northern New England.  F&F most important in highly populated basins CHA, BLA.  Ag sources most important in mid-Atlantic.
Although the watersheds are predominantly forested (remember land use graph), just small fractions of agricultural land use (19.3% across all watersheds) have profound impacts on the annual N budgets.  On average, the majority of N inputs to the region (61% of the total – across all watersheds) come from agricultural sources -- from fertilizers, fixation of leguminous crops, and imports of food and feed.  

## Moderate-sized Watersheds, Northeastern US (Boyer et al)

**Moderate-sized Watersheds, Northeastern US (Boyer et al)**

**Note slope = 0.26 and intercept = 107 kg km****-2**** yr****-1**

## Discharge (mm yr-1)

**Discharge (mm yr****-1****)**

**Residual ****(kg N m****-2**** yr****-1****)**

## (5 x 10-4 * Discharge) * (NANI) + 115

**(5 x 10****-4**** * Discharge) * (NANI) + 115**
**kg N km****-2**** yr****-1**

**Riverine N flux (kg N km****-2**** yr****-1****)**

**Riverine N fluxes very well predicted from net anthropogenic**
**N inputs, attenuated by discharge-predicted fractional delivery.**

## Next steps with ReNuMa watershed model:

-  add a module for atmospheric deposition of           	nitrogen onto the landscape
-  add denitrification sink terms, as a function of 	climate
-  improve modules for agricultural management 	options, with emphasis on nitrogen exports
-  work with stakeholders in Susquehanna 	drainage basin within New York State to 	make model more useful for decision makers

## Thanks to EPA STAR Program!