Jayasinghe, Sampath

Miller, David A.

English

Research Papers in Economics

 
 
 
 
Assessing Factor Contribution to Nitrogen Concentration Levels in the Raccoon River Watershed in Iowa 
 
 
 
Sampath Jayasinghe  
Decision Innovation Solutions Inc.  
3315 109th St., Suite B 
Urbandale, IA 50322 
& 
PhD Candidate 
Department of Economics 
Iowa State University 
Ames, IA 5011 
Phone: (515)-460 0002 
e-mail: sampathj@iastate.edu 
 
David Miller 
Director, Research & Commodity Services 
Iowa Farm Bureau Federation 
5400 University Ave 
West Des Moines, IA 50266 
Phone: (515)-225 5430 
e-mail: dmiller@ifbf.org  
 
Poster prepared for presentation at the Agricultural & Applied Economics Association’s 2011 
AAEA & NAREA Joint Annual Meeting, Pittsburgh, Pennsylvania, July 24-26, 2011 
 
 
Copyright 2011 by Sampath Jayasinghe and Dave Miller. All rights reserved. Readers may make verbatim copies of this 
document for non-commercial purposes by any means, provided that this copyright notice appears on 
all such copies. 
 
 
  
 
 
The Raccoon River Watershed (RRW) in 
Iowa has received considerable attention in 
recent years due to concerns regarding ex-
cessive nitrate-nitrogen (N) concentrations 
in the Raccoon River (RR).  
 
Source: Jha, Gassman,  and Arnold, (2007). 
Frequent detections of N concentrations 
above the federal drinking water standard of 
10 mg L-1 have raised questions about the 
sources of N in the RR.   
Intensive agricultural production is a pre-
dominant use of a significant portion of the 
land in the RRW and is a primary driver of 
the local economy within the watershed. 
The increase in livestock production is also a 
concern within the watershed.  
The purpose of this study is to assess the 
factors affecting the monthly N concentra-
tions in the RRW. What determines the vari-
ation of N concentrations among a list of 
presumed relevant factors (fertilizer applica-
tion rate, rainfall, temperature, livestock, 
crop-N-removal, and population), and what 
are their relative importance? 
 
This study employs the GARCH(1,1) pro-
cess to model the distribution of nitrate 
concentrations in the Raccoon River. The 
GARCH model is an extension of the Au-
toregressive Conditional Heteroscedastic 
(ARCH) model originally developed by 
Eagle (1982).  
GARCH is a time series technique used to 
model the serial dependence of volatility. 
The GARCH model allows current and 
lagged conditional variances, as well as past 
realization of the disturbance term, to af-
fect the sample data generating process. 
1) Mean Equation:  
 
 
 
Yt = Average N Concentration; 
FLOWt = Average water flow rate; 
RFt =  Average rainfall; 
TEMt = Average Temperature; 
FERt= Total Nitrogen fertilizer application; 
NREt = Total N update  
POPt = Total population; 
Tt = months; 
εt = error term. 
2) Variance Equation: 
 
 
 
Study period: 1992-2008 
Monthly N concentration data: Des- 
Moines Water Works at Van Meter 
Water flow rate:  Des Moines Water Works 
Rainfall and Temperature: National Cli-
mate Data Center 
Corn planted acreage and yield: NASS/
USDA 
Livestock numbers: NASS/USDA 
Commercial fertilizer sales: Commercial 
Feed and Fertilizer Bureau  
Plant N uptake: calculated by assuming 
that corn grain contains, on average,7% 
crude protein and that the protein is com-
prised of 16% nitrogen (Morrison,1961). 
 
Estimated mean equation is explicitly con-
structed by lags of N concentration and 
current and lagged values of a number of 
independent variables. Hence, the model 
estimated has an interesting separation of 
short- and long-run effects. 
 
There is no statistically significant, observed 
increasing trend in N concentrations. There 
are very significant intra-annual variations in 
N concentrations and the existence of a very 
strong seasonal pattern. 
 
Variations in rainfall and temperature con-
tribute more to the monthly variation in N 
concentration than do the changes in nitro-
gen application rates. Practices such as stra-
tegically-placed wetlands designed for nitro-
gen removal could prove very beneficial in 
mitigating the effects of seasonal climatic 
variables such as rainfall and temperature on 
in-stream nitrogen levels.   
 
Estimated parameters in the variance equa-
tion are not statistically significant except the 
intercept term.  
Introduction 
Objective 
Method 
Data Description 
Results 
Variable  Lag  Parameter 
Estimate 
Short Run 
Implied 
Elasticities
1 
Long Run 
Implied 
Elasticities
1 
Mean Equation 
Constant    3.2270 
(32.8058) 
   
N-Concentration   -1  0.7370** 
(0.0129) 
   
  -2  -0.0729 
(0.0838) 
   
Water Flow Rate (t)    -0.0031 
(0.0035) 
   
Precipitation (t)    0.0124* 
(0.0051) 
0.1333  0.1333 
  -1  0.0163** 
(0.0038) 
0.1727  0.2695 
  -2  -0.0045 
(0.0032) 
   
Temperature (t)    0.0058 
(0.0453) 
   
  -1  0.0706* 
(0.0249) 
0.6110  0.6484 
  -2  -0.0498 
(0.0259) 
   
Total N Fertilizer 
Application (t) 
  1.75e-08 
(1.39e-08) 
   
  -1  3.05e-08 
(2.09e-0.8) 
   
  -2  4.49e-08* 
(2.15e-08) 
0.0863  0.1454 
  -3  5.38e-08* 
(2.02-e08) 
0.0997  0.1841 
  -4  4.40e-08* 
(2.61e-08) 
0.0815  0.2070 
  -5  3.72e-08* 
(1.23e-08) 
0.0688  0.2079 
  -6  2.38e-08 
(1.27e-08) 
   
Plant N Uptake (t)    -1.28e-08 
(4e-08) 
   
Population (t)    -6.19e-05 
(2.98e-04) 
   
Time (t)    0.0021 
(0.0255) 
   
R
2    0.5091     
Log-likelihood    -426.9810     
  Note:  *, ** denotes statistical significance level at 0.05 and 0.01 respectively; and standard errors are 
in parentheses (Heteroskedasticity consistent standard errors according to Bollerslev and 
Wooldridge,1992); 1 calculated at their mean values. 
Assessing Factor Contribution to Nitrogen Concentration Levels in the Raccoon River Watershed in Iowa 
Agricultural & Applied Economics Association 2011 Annual Meeting in Pittsburgh, PA (Selected Poster) 
Sampath Jayasinghe, Decision Innovation Solutions Inc., West Des Moines, Iowa 
Dave Miller, Iowa Farm Bureau Federation, West Des Moines, Iowa  

Assessing Factor Contribution to Nitrogen Concentration Levels in the Raccoon River Watershed in Iowa

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