TY - JOUR
T1 - Elucidating the relationship between gaseous O2 and redox potential in a soil aquifer treatment system using data driven approaches and an oxygen diffusion model
AU - Turkeltaub, Tuvia
AU - Mannheim, Ron
AU - Furman, Alex
AU - Weisbrod, Noam
N1 - Funding Information: Financial support. This work has been supported within the frame-work of the Goldinger Trust, Jewish Federation of Delaware and by the German–Israeli Water Technology Cooperation Pro-gram (Grant No. WT1601/2689), by the German Federal Ministry of Education and Research (BMBF), by the Israel Ministry of Science, Technology and Space (MOST). Publisher Copyright: © 2023 Elsevier B.V.
PY - 2023/3/1
Y1 - 2023/3/1
N2 - Knowledge concerning the redox potential (Eh) conditions in the vadose zone of a soil aquifer treatment (SAT) system constitutes valuable information for assessing water quality and operational efficiency. The complex nature of Eh conditions in SAT limits the ability to predict and quantify them using detailed models. Alternatively, data-driven models can be used for predictions and relationship analysis. Hourly measurements of Eh, volumetric water content (θ), soil temperature (T), and gaseous oxygen (O2) were obtained at multiple depths of a SAT vadose zone. A correlation analysis showed that O2 correlated with Eh for most temporal components. Only the monthly component of T and the daily component of θ were correlated with Eh. A detailed multiple linear regression (MLR) analysis illustrated that the gaseous O2, at shallow depths, can explain the majority (above 80%) of the Eh variability. The MLR curve demonstrated breakpoints in the Eh response to O2 at shallow depths, which were identified using a piecewise regression. These breakpoints explain, in part, the different stages of microbial activity throughout the SAT wetting and drying cycles. Combining an oxygen transport analytical model with the piecewise regression enabled the Eh prediction through easy-to-acquire T and θ measurements. At deeper depths, the Eh–O2 relationship demonstrates a step-function characteristic, which indicates that the changes in Eh occur due to the arrival of a low-Eh solution. Thus, the Eh dynamic in the SAT vadose zone is mostly controlled by aerobic conditions.
AB - Knowledge concerning the redox potential (Eh) conditions in the vadose zone of a soil aquifer treatment (SAT) system constitutes valuable information for assessing water quality and operational efficiency. The complex nature of Eh conditions in SAT limits the ability to predict and quantify them using detailed models. Alternatively, data-driven models can be used for predictions and relationship analysis. Hourly measurements of Eh, volumetric water content (θ), soil temperature (T), and gaseous oxygen (O2) were obtained at multiple depths of a SAT vadose zone. A correlation analysis showed that O2 correlated with Eh for most temporal components. Only the monthly component of T and the daily component of θ were correlated with Eh. A detailed multiple linear regression (MLR) analysis illustrated that the gaseous O2, at shallow depths, can explain the majority (above 80%) of the Eh variability. The MLR curve demonstrated breakpoints in the Eh response to O2 at shallow depths, which were identified using a piecewise regression. These breakpoints explain, in part, the different stages of microbial activity throughout the SAT wetting and drying cycles. Combining an oxygen transport analytical model with the piecewise regression enabled the Eh prediction through easy-to-acquire T and θ measurements. At deeper depths, the Eh–O2 relationship demonstrates a step-function characteristic, which indicates that the changes in Eh occur due to the arrival of a low-Eh solution. Thus, the Eh dynamic in the SAT vadose zone is mostly controlled by aerobic conditions.
UR - http://www.scopus.com/inward/record.url?scp=85147541264&partnerID=8YFLogxK
U2 - https://doi.org/10.1016/j.jhydrol.2023.129168
DO - https://doi.org/10.1016/j.jhydrol.2023.129168
M3 - Article
SN - 0022-1694
VL - 618
JO - Journal of Hydrology
JF - Journal of Hydrology
M1 - 129168
ER -