Skip to content
Spatial Potential for Enhanced In-field Denitrification from Perennial Vegetative Filter Strips
YEAR: 2018
INVESTIGATORS: Daniel Linton, Bradley Miller

Iowa’s waterways receive excessive nitrogen from agricultural lands. This project aims to identify the spatial specifics of a conservation practice that has demonstrated abilities to promote denitrification within agricultural fields, perennial vegetation filter strips. We have a strategy to identify the locations with the greatest potential for denitrification due to interactions between the filter strip and landscape processes resulting in changes in the soil environment. To do so, we will create and use a linear, fuzzy logic model to predict potential denitrification areas (PDA). The framework includes the spatial distribution of environmental factors which are conducive for denitrification following the following form: PDA= f (OC, T, pH, θv) where OC is a measure of accessible, oxidable carbon, T is a measure of favorable thermal conditions, pH is hydrogen ion activity, and θv is a measure of water holding capacity. In our current work, we have already observed the impact these filter strips are having on soil properties, affecting a greater area than generally assumed. Among those impacts, is a strong increase in θv within and surrounding the filter strips. This change in the soil environment suggests that if the other factors are present in the right combinations the capacity for denitrification in unsaturated hillslopes with perennial vegetation filter strips may also be increasing. Our research is unique in that it quantitatively accounts for the interaction between the hillslope morphology, hydrology, and the filter strips, which allows us to pinpoint the spatial interactions. Although impacts of perennial vegetation filter strips on water quality at the small catchment scale have been documented, the spatial distribution of the processes producing those impacts within the field has yet to be explored. By adding the soil sample analysis proposed here, our spatial modelling will create a map of PDA. The production and analysis of this map will assist in identify optimal filter strip design for increasing PDA.