Publication Date

5-2016

Date of Final Oral Examination (Defense)

2-12-2016

Type of Culminating Activity

Thesis

Degree Title

Master of Science in Hydrologic Sciences

Department

Geosciences

Major Advisor

Kevin P. Feris, Ph.D.

Advisor

Shawn G. Benner, Ph.D.

Advisor

Daniele Tonina, Ph.D.

Abstract

The hyporheic zone (HZ) of streams can be a significant source of nitrous oxide (N2O). However, the biogeochemical processes controlling N2O emissions remain poorly constrained due to difficulties in obtaining high-resolution chemical, physical, and biological data from streams. We performed a large-scale flume experiment to unravel the complexities of a natural system by constraining streambed morphology, flow rate, organic carbon loading, grain size distribution, and exogenous nitrate loading while enabling regular monitoring of dissolved oxygen, pH, alkalinity, and concentrations of NO3-, NO2-, NH4+, and N2O in the HZ. We employed real-time PCR (qPCR) to quantify the distribution of denitrifying functional genes (nirS and nosZ, genes that encode nitrite reductase and nitrous oxide reductases, respectively) in HZ sediment cores as a measure of denitrifying microorganism abundance. Linear and nonlinear mixed-effects models were used to elucidate specific controls on N2O production within the HZ by coupling the distribution of denitrifying microbial communities to flow dynamics (i.e. hyporheic hydraulics and streambed morphology) and biogeochemical processes. We found that hot spots for denitrification (N2O generation) were significantly influenced by the availability of total nitrogen only when dissolved oxygen concentrations were below 31 μmol/L. The addition of denitrifying gene abundance, nirS, and the interaction term between nirS and total nitrogen as modeling parameters significantly improved the quality of our model and predicted an increase in N2O when nirS abundance was greater than 5.01x106 copy #/gram dry sediment. We were also able to establish a significant negative relationship between the relative abundance of nosZ to nirS (nosZ/nirS) and N2O generation. Our statistical model also emphasized the role of streambed morphology on N2O generation, which is attributed to its control over the delivery and distribution of dissolved oxygen, oxidized nitrogen species, and denitrifying genes within the HZ. These results may be useful in predicting N2O production in HZ systems and can inform mitigation strategies targeting reduction of N2O production in HZ systems with elevated levels of reactive nitrogen.

Download

Share

COinS