Analyzing and Optimizing Denitrification in Agricultural Surface Waters - Spatial and Temporal Analysis of Denitrification Hot Spots

The goal of this project was to identify the environmental drivers of microbial denitrification hot spots and hot moments in Minnesota's agricultural landscape, specifically in channels and floodzones (areas that are intermittently flooded with nitrate-laden water). We conducted a combination of laboratory experiments, outdoor experiments, and field monitoring to gain a mechanistic understanding of denitrification across a range of spatial scales, from microbial processes to field-scale processes. From this research, several drivers were found that increased denitrification and could be applied towards nitrate removal management strategies. These strategies include targeting areas with low-organic sediment and amending the sediment with a carbon source, modifying ditch or channel geometry to enhance connectivity with a floodplain, and manipulating water flow in ditches or channels. Results from this study indicated that periodic inundation increased denitrification rates, and that the timing and duration of flooding affects the microbial communities (abundance and diversity) in floodplain areas. Therefore, remediation strategies that create sites that periodically flood, and especially strategies that include constructed floodplains, have the potential to increase nitrate removal in agricultural ditches. To evaluate potential management strategies for nitrate removal, predictive equations were developed and tested to predict relative denitrification rates in channels and floodplains. The in-channel equation was tested across two years of field data collection and compared well to previous research. The effect of inundation history on floodplain denitrification, however, limits the use of the floodplain equation, as the equation did not perform well across a dry and wet year. The temporal variability of denitrification rates and microbial communities in intermittently flooded areas needs to be better understood to accurately predict relative denitrification rates in floodplains across space and time.