Dissertations and Theses @ UNI

Availability

Thesis (UNI Access Only)

Keywords

Nutrient pollution of water--Iowa; Cedar River Watershed (Minn. and Iowa); Agricultural pollution--Iowa;

Abstract

In an agriculturally dominant watershed, it is very important to geovisualize and understand the nutrient dynamics in terms of its distribution and transportation for better watershed management. Previous studies have indicated the Cedar River Watershed shares the largest percentage of nutrients delivered into the Mississippi River, thereby contributing to the dead zone in the Gulf of Mexico. This study was conducted on 18 different sites in the Upper Cedar River Watershed from April 4 through October 31, 2014 to determine spatiotemporal dynamics and find the best predictors for high nutrients by integrating GIS and statistical analysis. Over seven month periods, samples were taken once a week. The lab analysis was done mainly for Nitrate-nitrogen (NO3-N), Total Phosphorus (TP), and Total Suspended Solids (TSS).

In this study, 29% and 82% of samples analyzed (n = 540) showed NO3-N and TP concentrations above the EPA recommended level of 10 mg/L and 100 µg/L respectively. The study showed that there was a high flux of NO3-N and TP concentrations in the early and mid-season as compared to the late season, indicating spring snowmelt and rainfall events played significant roles in carrying nutrients from the agricultural fields to the streams. Spatially, the sites in tributaries showed slightly higher NO3-N concentrations than the main channel, Cedar River. For TP, on the other hand, most of the sites in the main channel showed high concentrations compared to the tributaries. In terms of loads, the main channel showed high loads as compared to the tributaries throughout the study period. The study found the total estimated NO3-N and TP loads in the watershed over seven month were 9369 and 221 tons respectively. The estimation of nutrient yield showed that the tributaries had high yield compared to the main channel.

The correlation analysis and the stepwise backward multiple regression model showed that there was a moderate to strong relationship among precipitation, TSS and nutrients, which concluded precipitation and TSS to be the best predictors in explaining nutrient variability. The model predicted that a unit increase of precipitation and TSS respectively increased the stream NO3-N concentrations by 0.239 mg/L and 0.018 mg/L, and the stream TP concentrations by 7.98 µg/L and 0.283 µg/L. Similarly, a unit increase of precipitation and TSS loads respectively increased stream NO3-N loads by 4.430 tons/day and 0.080 tons/day, and the stream TP loads by 0.035 tons/day and 0.003 tons/day. Cropland, on the other hand, did not show any significant association. The relationship of proportion of cropland with NO3-N (r = 0.156) and NO3-N load (r = - 0.204), and with TP (r = -0.111) and TP load (r = -0.185) indicated that the nutrient change did not have consistent response with the cropland. In addition to cropland, the study also did not show any significant association of developed land and animal confinements with nutrients.

In the future, a year long study considering other factors such as best management practices, stream order or stream size, and fertilizer usage would be beneficial to get a complete picture of the nutrient problem in the watershed.

Year of Submission

2018

Degree Name

Master of Arts

Department

Department of Geography

First Advisor

Andrey Petrov, Chair, Thesis Committee

Second Advisor

Mohammad Z. Iqbal, Co-chair, Thesis Committee

Date Original

12-2018

Object Description

1 PDF file (x, 132 pages)

Language

en

File Format

application/pdf

Download
Off-Campus Download

Comments?

Share

COinS