Reactive Transport of Nutrients and Bioclogging During Dynamic Disconnection Process of Stream and Groundwater Academic Article uri icon

abstract

  • ©2019. American Geophysical Union. All Rights Reserved. Biofilm-induced dynamic evolution of streambed permeability commonly concurs with the transition from connection to disconnection between surface water and groundwater in arid regions. However, in most previous studies, static streambeds were assumed to examine the evolution of disconnection, or despite dynamic streambeds being considered, the feedbacks between nutrients transport and microbial growth were ignored. In this study, we developed an innovative coupled variably saturated flow, microbial growth, biogeochemical reactions, and bioclogging model. We applied this model to investigate the feedbacks between nutrients transport and microbial growth and their controls on infiltration evolution. Our results showed that a new clogging layer can naturally develop due to these feedbacks and does not require prior clogging. The development of the new clogging layer promotes the occurrence of disconnection. These results illustrate that as bioclogging is a dominant process, previous static disconnection conditions cannot be used as criteria to predict whether disconnection can occur in a stream-aquifer system. Furthermore, different from the previous assumption of constant specific microbial growth rates, biomass growth, and streambed permeability evolution are self-limiting. Accordingly, due to initial low growth rate, infiltration increases when the water table declines, and it then decreases and reaches a minimum while a stable biofilm is developed. These trends coincide with the infiltration variations reported in previous field investigations. After reaching the minimum, infiltration increases again with decline of the water table until achieving a constant at the moment of disconnection. This stage was missing in previous studies because constant specific growth rates were assumed.

author list (cited authors)

  • Xian, Y., Jin, M., Zhan, H., & Liu, Y.

citation count

  • 14

publication date

  • May 2019