Determination of dominant biogeochemical processes in a contaminated aquifer-wetland system using multivariate statistical analysis.
Determining the processes governing aqueous biogeochemistry in a wetland hydrologically linked to an underlying contaminated aquifer is challenging due to the complex exchange between the systems and their distinct responses to changes in precipitation, recharge, and biological activities. To evaluate temporal and spatial processes in the wetland-aquifer system, water samples were collected using cm-scale multi-chambered passive diffusion samplers (peepers) to span the wetland-aquifer interface over a period of 3 yr. Samples were analyzed for major cations and anions, methane, and a suite of organic acids resulting in a large dataset of over 8000 points, which was evaluated using multivariate statistics. Principal component analysis (PCA) was chosen with the purpose of exploring the sources of variation in the dataset to expose related variables and provide insight into the biogeochemical processes that control the water chemistry of the system. Factor scores computed from PCA were mapped by date and depth. Patterns observed suggest that (i) fermentation is the process controlling the greatest variability in the dataset and it peaks in May; (ii) iron and sulfate reduction were the dominant terminal electron-accepting processes in the system and were associated with fermentation but had more complex seasonal variability than fermentation; (iii) methanogenesis was also important and associated with bacterial utilization of minerals as a source of electron acceptors (e.g., barite BaSO(4)); and (iv) seasonal hydrological patterns (wet and dry periods) control the availability of electron acceptors through the reoxidation of reduced iron-sulfur species enhancing iron and sulfate reduction.
Báez-Cazull
Susan E
SE
Texas A&M University, 3115 TAMU College Station, Texas 77843, USA.
McGuire
Jennifer T
JT
Cozzarelli
Isabelle M
IM
Voytek
Mary A
MA
D004784:Environmental Monitoring / Q000706:statistics & numerical data*; D015999:Multivariate Analysis; D009825:Oklahoma; D025341:Principal Component Analysis; D012037:Refuse Disposal; D014874:Water Pollutants, Chemical / Q000032:analysis*; D014881:Water Supply; D053833:Wetlands
D014874:Water Pollutants, Chemical