A novel high-frequency groundwater quality monitoring system.

High-frequency, long-term monitoring of water quality has revolutionized the study of surface waters in recent years. However, application of these techniques to groundwater has been limited by the ability to remotely pump and analyze groundwater. This paper describes a novel autonomous groundwater quality monitoring system which samples multiple wells to evaluate temporal changes and identify trends in groundwater chemistry. The system, deployed near Fresno, California, USA, collects and transmits high-frequency data, including water temperature, specific conductance, pH, dissolved oxygen, and nitrate, from supply and monitoring wells, in real-time. The system consists of a water quality sonde and optical nitrate sensor, manifold, submersible three-phase pump, variable frequency drive, data collection platform, solar panels, and rechargeable battery bank. The manifold directs water from three wells to a single set of sensors, thereby reducing setup and operation costs associated with multi-sensor networks. Sampling multiple wells at high frequency for several years provided a means of monitoring the vertical distribution and transport of solutes in the aquifer. Initial results show short period variability of nitrate, specific conductivity, and dissolved oxygen in the shallow aquifer, while the deeper portion of the aquifer remains unchanged-observations that may be missed with traditional discrete sampling approaches. In this aquifer system, nitrate and specific conductance are increasing in the shallow aquifer, while invariant changes in deep groundwater chemistry likely reflect relatively slow groundwater flow. In contrast, systems with high groundwater velocity, such as karst aquifers, have been shown to exhibit higher-frequency groundwater chemistry changes. The stability of the deeper aquifer over the monitoring period was leveraged to develop estimates of measurement system uncertainty, which were typically lower than the manufacturer's stated specifications, enabling the identification of subtle variability in water chemistry that may have otherwise been missed.

Mississippi River nitrate loads from high frequency sensor measurements and regression-based load estimation.

Accurately quantifying nitrate (NO3-) loading from the Mississippi River is important for predicting summer hypoxia in the Gulf of Mexico and targeting nutrient reduction within the basin. Loads have historically been modeled with regression-based techniques, but recent advances with high frequency NO3- sensors allowed us to evaluate model performance relative to measured loads in the lower Mississippi River. Patterns in NO3- concentrations and loads were observed at daily to annual time steps, with considerable variability in concentration-discharge relationships over the two year study. Differences were particularly accentuated during the 2012 drought and 2013 flood, which resulted in anomalously high NO3- concentrations consistent with a large flush of stored NO3- from soil. The comparison between measured loads and modeled loads (LOADEST, Composite Method, WRTDS) showed underestimates of only 3.5% across the entire study period, but much larger differences at shorter time steps. Absolute differences in loads were typically greatest in the spring and early summer critical to Gulf hypoxia formation, with the largest differences (underestimates) for all models during the flood period of 2013. In additional to improving the accuracy and precision of monthly loads, high frequency NO3- measurements offer additional benefits not available with regression-based or other load estimation techniques.

Microbial degradation of plant leachate alters lignin phenols and trihalomethane precursors.

Although the importance of vascular plant-derived dissolved organic carbon (DOC) in freshwater systems has been studied, the role of leached DOC as precursors of disinfection byproducts (DBPs) during drinking water treatment is not well known. Here we measured the propensity of leachates from four crops and four aquatic macrophytes to form trihalomethanes (THMs)-a regulated class of DBPs-before and after 21 d of microbial degradation. We also measured lignin phenol content and specific UV absorbance (SUVA(254)) to test the assumption that aromatic compounds from vascular plants are resistant to microbial degradation and readily form DBPs. Leaching solubilized 9 to 26% of total plant carbon, which formed 1.93 to 6.72 mmol THM mol C(-1). However, leachate DOC concentrations decreased by 85 to 92% over the 21-d incubation, with a concomitant decrease of 67 to 92% in total THM formation potential. Carbon-normalized THM yields in the residual DOC pool increased by 2.5 times on average, consistent with the preferential uptake of nonprecursor material. Lignin phenol concentrations decreased by 64 to 96% over 21 d, but a lack of correlation between lignin content and THM yields or SUVA(254) suggested that lignin-derived compounds are not the source of increased THM precursor yields in the residual DOC pool. Our results indicate that microbial carbon utilization alters THM precursors in ecosystems with direct plant leaching, but more work is needed to identify the specific dissolved organic matter components with a greater propensity to form DBPs and affect watershed management, drinking water quality, and human health.