# Presentation: 024843

## Delaware River Basin SPARROW Model

- Mary Chepiga  	    609-771-3955    	mchepiga@usgs.govSusan Colarullo     609-771-3922     	colarull@usgs.govJeff Fischer	    609-771-3953    	fischer@usgs.gov

- US Geological Survey
- Delaware NAWQA

## Today’s Talk

-  The SPARROW model technique
- Delaware River Basin SPARROW results for Total Nitrogen (TN) and Total Phosphorus (TP) for 2000
- SPARROW and water-quality monitoring

**Notes:**
Concepts – most importantly what data is used and what information is produced
Results –Major objective of this study is to estimate the distribution of TN and TP in all streams in the DRB.
   -  Because of time constraints, today most of the examples of results for the DRB are shown for TN.
   - Some results for TP are attached to the end of the presentation if any one has question concerning them.
SPARROW and WQ monitoring -  Some aspects that will touch on include inconsistent data coverage, small basin monitoring, nested basins, and monitoring of parameter distributions not aerial distributions.

## SPARROW* Model Concept

- *_SPA_tially _R_eferenced _R_egression _O_n
-    _W_atershed Attributes

**Notes:**
Acronym
- Sparrow was developed by Rich Alexander, Dick Smith and Greg Schwarz, of the USGS in the late 1990’s.  They are stationed in Reston.
-The mathematical form of SPARROW is a non linear regression model in which monitored nutrient loads are the dependent variable which are related to the independent variables which are characterized into 3 groups: the source terms, land-to-water transport terms and in-stream and reservoir transport terms.
Source terms may include any direct, like fertilizer application rates or atmospheric deposition,  or indirect source estimates, like land use.  Source terms are weighted by the transport terms
Land-to-water- transport terms represent land characteristics that might increase or decrease the delivery of nutrients to a stream, like slope, precipitation, permeability
In-stream transport terms might represent denitrification , biological uptake, sedimentation 
Data for the source and transport terms are referenced to a digital stream network.
SPARROW is both statistical and deterministic in nature
   -  Statistical because the basis of it is a regression equation that relates monitored loads (dep var) to the three independent variables.
   - Deterministic in nature because the regression equation is determined through an iterative approach that that insures that both a flow and nutrient mass balance is maintained and because the dependent variable is described by a not linear equation where source terms are weighted by the transport and decay terms.  Equation slide is included after the talk slides.
- Retains advantages and disadvantages of deterministic models – simpler better/more usable error analysis. – but unknown error between model and physical world

## SPARROW relates measured loads at monitoring stations to stream and land attributes

- Sources

- Stream Network

- Landscape Features

- Monitoring Data

**Notes:**
4 elements comprise the input data to SPARROW. These components will be discussed in the order shown in relation to the DRB model.
Starting with the digital stream network, the scale of the network determines the scale of the results and reflects the scale of the input data parameters and management needs. 
In the DRB model we used the 1:24,000 scale NHD  - every stream reach or segment on a 1:24,000 scale topo is represented in the model.  
This scale was chose to represent details of streams, reservoirs, lakes and swamps.
Every input parameter was defined for each reach and its contributing basin, the equation for load is solved for each stream reach and you get predicted loads at every stream reach.
 How many in the DRB? -  about 61,580, about the same amount used to represent the US in the original SPARROW work.  Only simulated nutrients in the non-tidal portions of the DRB. Because of the difficulties in estimating mean Q.  Part of Delaware was not included because the NHD was not completed at the time of the study.

## Model predictions are made for every reach

- (not just monitored reaches)
-  Load, yield, concentration
-  Contribution from each source
-  In-stream and reservoir losses
-  Incremental and delivered         loads for stream reaches, basins and sub-basins
-  Statistical measures of uncertainty for predictors and predictions

**Stream reach**

**Reach basin**

**Notes:**
This is what the digital stream network looks like at the reach scale.
A stream reach runs between headwaters, points of convergence, points of divergence and terminal nodes.
Stream reaches range from 0.001 to 12.7 km , ave .5 km, total length of 31,300 km.
Basins range from .0001 to 22 sq km with and average size of .5 sq km and total size of 29,755 sq km.
Reach basins are the land surface areas directly adjacent to a stream reach. 
Input terms are summed over the reach basin areas.  For example, the sum of ATMDEP falling on this central pink basin is the one source term for that reach.
Of the 61580 stream reaches, 12266(17%) are designated as impoundments (reservoirs, lakes, ponds and marshes) that account for about 10% of the DRB area.
That’s what goes into the model, but what’s the output associated with the stream reaches? 

## Monitored/Calculated Loads

**Notes:**
The next aspect of the model data we will discuss is the Monitoring Data for TN and TP, 
Loads were estimated from monitored flow data from 1940-2001 and monitored water quality data from 1974 to 2001.
Stream flow was measured or by the USGS
TN and TP data was provided by the USGS (NY, NJ, MD/DE,  PA), NJDEP, PADEP, ACOEPA, NYCDEP, DRBC, DEDNREC

Sites that had measured WQ but no steam flow was estimated from nearby gages.

Monitored  (some times called observed load) loads are actually estimated loads calculated from measured stream flow and water quality measurements. 

This graph is the calculated loads in red for the DR at Trenton and the estimated daily loads in blue.  The grey band in the upper and lower 98% confidence interval on the calculated or estimated loads.  Generally load estimators underestimate the peaks and over estimates the lowest loads. 

The daily loads from the blue line is then used to calculate the mean load for the time period of the model . In the DRB SPARROW ave loads for the year 2000 were calculated and used as input into the model.

Calculations for load estimates were done using a version of  ESTIMATOR a statistical log-linear regression model which implements a minimum variance unbiased estimator and a  adjusted maximum likelihood estimator described by Helsel and Cohn (1988) and Cohn and others (1992b), which allows data containing censored values and multiple reporting limits. 

This version also used detrended flow estimates which provides for the computation of load trends that are not the results of trends in flow. 

Clarification of a point that confuses some users – monitored loads are a model input (the dependent variable) and are limited in number, about a 100 for the DRB.  

Predicted loads are made for every stream reach (10s of thousands) when the regression equation has been determined through trial and error.

## 2000 Total Nitrogen Yields

- 97 sites
- 50%  are  less than  700 kg/km2
- 10 % are  greater than 2,000 kg/km2

**       ****Kg/Km****2**** **
**         **_**>**_**2000**
**        ****>700 and  <2000**
**        **_**<**_** 700**
**Major Stream**

**Notes:**

This map is of yields (loads divided by the basin area) in the DRB (orient audience to  N-S, states, estuary and river)
97 sites
Range from 24? to 4,430? kg/km2/yr 
(Loads range from 92 kg/yr to 14.6 M kg/yr and are highest at the last monitoring station on the largest basins (Delaware, Schuylkill), Brandywine))
Half of the yields are < 700 kg/km2/yr, in green
10 sites >1600 kg/km2/yr, in red

The large area in the central part of the basin is in PA and is the result of The WQN until recently under the PADEP was not collecting data on organic N, so a TN value could not be calculated.
Recently the USGS took over this network and is now collecting all components of TN which will have a direct impact on the results of SPARROW modeling the includes PA 
Most TN sites had >70 WQ samples from 1970 to 2001.  In PA, samples were required to have only 50 WQ samples. 
Majority of sites had >15 years of QW.

## TP Loads

- Map here

- 2000 Total Phosphorus Yields

- 110 sites
- 50%  are  less than  25 kg/km2
- 10 % are  greater than 75 kg/km2

**       ****Kg/Km****2**** **
**         **_**>**_**75**
**        ****>25 and  <75**
**        **_**<**_** 25**
**Major Stream**

**Notes:**
110  sites
Yields range from 1.5 to 200 kg/km2/yr
(Loads range from 8.6 kg/yr to 828,000 kg/yr and are highest at the last monitoring station on the largest basins (Delaware, Schuylkill, & Lehigh))
Half of the yields are <25 kg/km2/yr, in green
12 sites exceed 70 kg/km2/yr, in red

## Total Nitrogen        Total Phosphorus

**Atmospheric deposition**
**Population**
**Fertilizer applied to ****	****agricultural land**
**Animal waste**
**Diffuse (forest, urban,  non-agricultural)***
**Water-holding capacity**
**Precipitation**
**Stream size**
**Reservoir size**

**Sources **

**Land-to-Water Delivery**

**Population**
**Fertilizer applied to **
**	****	****agricultural land**
**Animal waste**
**Diffuse (urban,  non-agricultural)***
** **
** **
**Stream size***
**Reservoir size**

**In-Stream Transport**

**Notes:**
Population is used as a indirect estimate of waste-water discharges from treatment plants

Initial estimates of waste-water discharges from EPA were  not a significant  predictor

The DRBC is working with us at this time to revaluate the location of the discharges and the amount of discharges to the tidal areas. 

## Delaware River Basin SPARROW Model Results

## DRB SPPARROW Results for entire basin

**DRB SPPARROW Results ****for entire basin**

**Total Nitrogen (TN) 57.8 million kg**

**Total Phosphorus (TP) 4.0 million kg**

**Atmospheric Deposition 14.5 kg**

**Population 11.6 kg**

**Fertilizer 12.7 kg**

**Waste 18.4 kg**

**Diffuse* 0.6 kg**

**Population 2.5 kg**

**Fertilizer 0.5 kg**

**Waste 0.7 kg**

**Diffuse 0.3 kg**

**Notes:**
                TN        TP
ATMDEP    25%      --
POP           20%     62.5%
FERT         22%      12.5%
WASTE      32%       17.5%
Diffuse       1%          7.5%

RMS err     .39            .71      % error associated with one std dev in the flux estimate in any given reach
Nat RMS   .43              .71
NE RMS      .16            .23  

R-sq           .96          .90     % variability in the measured /input loads that are described by the model
Nat R-sq      .88          .81
NE R-sq       .95          .94

Yield R-sq     .82          .48

The number here are presented for the entire DRB and any subbasin within the DRB will have a differing % from each source

## Total Nitrogen load, 
in kilograms per year

- Total Nitrogen load,
- in kilograms per year

- Total Nitrogen2000 Total Loads

**< 1,000**

**1,000  - 5,000**

**5,001 – 50,000**

**50,001 – 500,000**

**> 500,000**

## Total Nitrogen Incremental Load, 
in kilograms per year

- in kilograms per year

- Total Nitrogen2000 Incremental Loads

**< 200**

**201  - 500**

**500 – 1,000**

**1,000 – 10,000**

**> 10,000**

## Total Nitrogen Incremental Yield 
in kg per km2 per year

- in kg per km2 per year

- Total Nitrogen2000 Incremental Yields

**< 1,000**

**1,000 – 2,000**

**2,001 – 4,000**

**4,001 – 6,000**

**> 6,000**

## TN Major Sources

- TN Major Sources

- TP
-  Major Sources

- Atmospheric Deposition

- Diffuse

- Fertilizer

- Waste

- Population

**Total Nitrogen by Source and Basin**

## Total Nitrogen Delivered to Estuary (39 Mkg)

**Notes:**
These numbers do not include any waste-water discharges to the estuaries below the tide line of the streams

Because the DRBC would like the total land contribution to the estuary they are helping us to re-evaluate the location and estimates of waste-water discharges.

Henry Walker whose speaking next is going to mention briefly the nutrient model of the DE Estuary and the benefit this SPARROW output, deliverd loads, would be to updating this work.

## Nitrogen Incremental Yieldby Source and AMNET Basin

**Nitrogen Incremental Yield****by Source and AMNET Basin**

**NONE**

**SEVERE**

**MODERATE**

**IMPAIRMENT**

## SPARROW and Water-Quality Monitoring

## SPARROW TN Errors

**SPARROW TN Errors**

- Lowest
- Highest

**Error Evaluation**

-  Model explains ~90 to 95% of spatial variability in loads
-  Prediction errors for stream reaches are typically +/-  5 to 60% of load
-  Generally half of the independent variables are non-significant

## Slide 22

## Delaware River Basin SPARROW Model Points of Contact

- Mary Chepiga        609-771-3955    mchepiga@usgs.govSusan Colarullo     609-771-3922     colarull@usgs.govJeff Fischer           609-771-3953     fischer@usgs.gov

- US Geological Survey
- Delaware NAWQA

## SPARROW Budget Equation

- Load

- Sources

- Land-to-water
- delivery

- Instream
- decay

- Error

-   Spatial non-linear regression
-   Adjusts land and stream delivery factors on
-     the basis of basin-wide statistical relationships
-   Minimizes errors at monitoring sites

**Notes:**
n = # sources, i= # reaches, J(I)=sum of all reaches above i, but below upstream monitor stations, 
Z=land surface characteristic of reach catchment, T=channel transport char.

## Total Phosphorus Load, 
in kilograms per year

- in kilograms per year

- Total Phosphorus2000 Total Loads

**< 1,000**

**1,000  - 10,000**

**10,001 – 20,000**

**20,001 – 400,000**

**> 400,000**

## Total Phosphorus Incremental Load, 
in kilograms per year

- in kilograms per year

- Total Phosphorus2000 Incremental  Loads

**< 50**

**51  - 500**

**501 – 1,000**

**1,001 – 10,000**

**> 10,000**

## TP 
Incremental
Loads

- TP Total Loads

- TP
- Incremental
- Loads

## Total Phosphorus Incremental Yield, 
in kg per km2 per year

- in kg per km**2** per year

- Total Phosphorus2000 Incremental Yields

**< 0.5**

**0.6  - 2.0**

**2.1 – 4.0**

**4.1 – 10**

**> 10**

## Data Sources

## Data Sources (cont’d)