Lindsey Dahms

Becka Anton

Tabatha Lee

 

Nitrate levels in Wisconsin rivers and lakes

Abstract

            We tested the nitrate levels of eight lakes and eight rivers in Wisconsin. We hypothesized that rivers would have a higher concentration of nitrate compared to lakes, based upon their input sources. Our p-value of 0.301 shows that our hypothesis is not supported, and that there is not a significant difference in the nitrate levels of the two different types of water.

Key words: Nitrate, rivers, lakes, input sources

Introduction

Nitrate levels in rivers and lakes have increased overtime due to the activities of humans. Most of the nitrate that enters various river networks degrade river water quality and increase in nutrients (Seitzinger et al. 2002). The sources of nitrates found in water are from nitrogen fertilizer, animal wastes, wastewater, landfill, tanks, urban runoff, and soil organic matter (Zhang et al. 1998).  Nitrate levels found in lakes correspond to local land usage in the area (Vennie 2009). Nitrate may enter a lake from non-point sources such as surface runoff and diffusion of nitrate from watersheds, while rivers obtain their inputs directly from point sources such as fertilizers, sewage, and chemical runoff (Caraco et al. 1999). We hypothesized that rivers would have a higher concentration of nitrate compared to lakes, based upon their input sources.

Methods and Materials

On November 7th, 2010 between the approximate time interval of 1100 to 1600, eight rivers and eight lakes were sampled haphazardly and evaluated for nitrate concentration.  The samples were tested with Nitrate/Nitrite water quality test strips, model number: 481109-E, manufactured by WaterWorks.

The rivers tested were: Fox River, Pewaukee River, Honey Creek, Root River, Bark River, Rock River, Kinnickkinnic River, and Milwaukee River. Lakes tested were: Upper Blue Spring Lake, Lake Monona, Lauderdale Lake, Pleasant Lake, Tripp Lake, Whitewater Lake, Cravath Lake, and Lake Wandawega. Results were obtained by placing the testing strip into the water source for two seconds, then removing the strip and waiting one minute for color to develop. By matching the color shown on the strip with the guide provided in the test kit, we were able to approximate the nitrate concentration, in parts per million.  Our data was analyzed using Microsoft Excel 2007, and a type two, one tailed t-test was done.

Results

There was no significant difference between the bodies of water tested (Fig. 1, p = 0.301). The average amount of nitrate in rivers was 6 parts per million (Fig. 1, std. dev. +/- 6.164). The average amount of nitrate in lakes was 8.25 parts per million (Fig. 1, std. dev. +/- 5.377).  A p-value of 0.301 was found using a type two, one tailed t-test. A type two test was used because we were doing a comparison between lakes and rivers, and one tailed due to the prediction made of rivers having higher nitrate levels.

 

Fig 1.  Average level of Nitrate in Rivers and Lakes with standard deviation error bars, p=0.301

Discussion

The rivers and lakes of Wisconsin that we tested did not have a significant difference in their nitrate levels. We predicted that the rivers would have more nitrate content because of their  sources of input, mainly point sources. These include: fertilizer use, sewage, and chemical runoff  (Caraco et al. 1999). Our p-value of 0.301 was not small enough to be significant, therefore our hypothesis was not supported. The nitrate level in rivers averaged to 6 parts per million, and the level in lakes was 8.25 parts per million in Wisconsin.

Differences in nitrogen retention are correlated with the differences in precipitation (Saunders et al. 2001).  Based on differences in weather patterns, some rivers or lakes could have received more rainfall, leading to increased NO3 runoff.  If we repeated this experiment, we would research the known sources of pollution and patterns of runoff before testing the water.  This would allow us to better correlate the differences in nitrate levels based on the structure of a lake vs. a river instead of the environmental surroundings. Using a larger sample size could also reveal data which could be significant in supporting our hypothesis.

Literature Cited:

 

Caraco, N. F., & Cole, J. J. (1999). Human impact on nitrate export: An Analysis Using Major World Rivers. Ambio, 28(2) 167-170. Retrieved from JSTOR.

Saunders, D.L., Kalff, J. (2001). Nitrogen retention in wetland, lake and rivers. Hydrobiologia, 443(1-3), 205-212. Accessed on SpringerLink database.

Seitzinger, S. P., Styles, R. V.  Boyer, E. B., Alexander, R. B., Billen, G., Howarth, R. W., Mayer, B., Breemen, N. V. (2002). Nitrogen retention in rivers: Model development and application to watersheds in the northeastern U.S.A. Biogeochemistry, 57/58 199-237. Retrieved from JSTOR.

Vennie, James. 2009. Nitrogen: Understanding Lake Data. Wisconsin Department of Natural Resources. Accessed at: http://dnr.wi.gov/lakes/publications/under/nitrogen.htm

Zhang, M., Geng, S., Smallwood, K. (1998). Assessing groundwater nitrate contamination for resource and landscape. Ambio, 27(3) 170-174. Retrieved from JSTOR.