Skip to main content
U.S. flag

An official website of the United States government

Stratification of reactivity determines nitrate removal in groundwater

February 12, 2019

Biogeochemical reactions occur unevenly in space and time, but this heterogeneity is often simplified as a linear average due to sparse data, especially in subsurface environments where access is limited. For example, little is known about the spatial variability of groundwater denitrification, an important process in removing nitrate originating from agriculture and land use conversion. Information about the rate, arrangement, and extent of denitrification is needed to determine sustainable limits of human activity and to predict recovery time frames. Here, we developed and validated a method for inferring the spatial organization of sequential biogeochemical reactions in an aquifer in France. We applied it to five other aquifers in different geological settings located in the United States and compared results among 44 locations across the six aquifers to assess the generality of reactivity trends. Of the sampling locations, 79% showed pronounced increases of reactivity with depth. This suggests that previous estimates of denitrification have underestimated the capacity of deep aquifers to remove nitrate, while overestimating nitrate removal in shallow flow paths. Oxygen and nitrate reduction likely increases with depth because there is relatively little organic carbon in agricultural soils and because excess nitrate input has depleted solid phase electron donors near the surface. Our findings explain the long-standing conundrum of why apparent reaction rates of oxygen in aquifers are typically smaller than those of nitrate, which is energetically less favorable. This stratified reactivity framework is promising for mapping vertical reactivity trends in aquifers, generating new understanding of subsurface ecosystems and their capacity to remove contaminants.

Publication Year 2019
Title Stratification of reactivity determines nitrate removal in groundwater
DOI 10.1073/pnas.1816892116
Authors Tamara Kolbe, Jean-Raynald de Dreuzy, Benjamin Abbott, Luc Aquilina, Tristan Babey, Christopher Green, Jan Fleckenstein, Thierry Labasque, Anniet M Laverman, Jean Marçais, Stefan Peiffer, Zahra Thomas, Gilles Pinay
Publication Type Article
Publication Subtype Journal Article
Series Title Proceedings of the National Academy of Sciences
Index ID 70203224
Record Source USGS Publications Warehouse
USGS Organization WMA - Integrated Modeling and Prediction Division