Statistical analysis for biogeochemical processes in a sandy column with dynamic hydrologic regimes using spectral induced polarization (SIP) and self-potential (SP)

Abstract

SUMMARYThe capillary fringe (CF) is characterized by transient and steep redox gradients and is thought to be a hot spot for biogeochemical processes. Understanding chemical fate and transport in the CF is significant, however, biogeochemical dynamics at the CF are poorly understood because of the difficulty to measure representatively with high spatio-temporal resolution at depths under dynamic hydrologic regimes. Hydrogeophysics is a developing field that uses minimally intrusive and quick response methods to monitor hydrological properties. Two geoelectrical methods [spectral induced polarization (SIP) and self-potential (SP)], which are sensitive to the solid–liquid interfaces (SIP) and biogeochemical processes (SP) can address the above difficulty. The challenge lies on linking the geoelectrical responses with biogeochemical processes, where many different processes contribute to the signals. We conducted a soil column experiment under five hydrologic regimes focusing on nitrogen transformations with SIP and SP measurements: (1) a static regime with a stable water level; (2) an infiltration regime with periodic pulse infiltration events with a constant water level and (3) fluctuating regimes with water level fluctuations under three drying-wetting frequencies (6/12/18-day-cycle). This is the first large lab-scale work in a well-controlled and highly instrumented soil column. The dynamic hydrologic conditions stimulated complex biogeochemical processes at the CF, and therefore the SIP and SP signals result from many physical and biogeochemical processes. Therefore, we relied on statistical analysis in this study for a novel interpretation. Spearman correlation analysis supported water content played the most important role in real conductivity (σ′) dynamics in the vadose zone, whereas fluid conductivity dominated σ′ in the saturated zone. Both correlation analysis and spatial moment analysis implicated that water content was the driving factor for both σ′ and imaginary conductivity (σ″). A multiple linear regression model indicated the gradient of redox potential, the gradient of soil matric potential and water content were the three main influencing factors for the SP signals. We proposed that the water level fluctuation can efficiently facilitate microbial electron transfer through ions transport between the different redox zones, and aggregate redox processes to create SP signal gradients. Depth zonation analysis, using six environmental indexes (Eh and nitrogen species; water content; real conductivity; imaginary conductivity; SP signal; microbial community composition), suggested that water content induced by soil hydrology was the most dominant factor, captured by all the indexes. In turn, it led to indirect inference on biogeochemical processes and resultant geoelectrical signals. Applying geoelectrical methods to such biogeochemical processes will not only lead to a better understanding of the mechanistic meanings of the geoelectrical signals, but also build relationships between geoelectrical signals and biogeochemical parameters to facilitate a novel way to monitor biogeochemical processes.