Submarine groundwater discharge (SGD) occurs along the coastline and the continental shelf in every ocean basin and is a major source of nutrients to the coastal ocean [1
]. Best estimates suggest that SGD water input to the ocean is equivalent to 60–400% of riverine water flux [1
]. Nutrients transported to the ocean through SGD have been shown to affect marine biota, specifically the abundance and productivity of phytoplankton, macro-algae, and seagrasses, which have implications for organisms in higher trophic levels [5
]. SGD is comprised of fresh groundwater, seawater that has circulated through the coastal aquifer, or a mixture of both water types [10
]. When fresh groundwater and circulating sea water mix in the coastal aquifer, several processes can occur that increase or decrease the concentration of nutrients in the groundwater [13
]. Therefore, nutrient fluxes to the coastal ocean including nitrate (NO3
), ammonium (NH4
), phosphate (PO4
), and silicate (SiO4
), can be modulated by these processes. Quantifying the relative contribution of each of the governing processes within the coastal aquifer is required to ensure accurate extrapolation of SGD-related solute fluxes regionally and globally [13
]. Recent attempts to upscale SGD fluxes have excluded the associated solute (nutrients, gases, carbon, etc.) fluxes, due to the difficulty of constraining their concentrations in the coastal aquifer [1
]. As the scientific community moves toward regional and global SGD flux estimates and SGD-associated solute fluxes to the ocean, quantitative methods are needed to constrain processes that regulate solute concentrations in the coastal aquifer across regional scales [13
Nutrient concentrations in coastal aquifers are modulated by conservative mixing, oxidation of ammonium, nitrification/denitrification of nitrate, adsorption, desorption, precipitation and other processes (Table 1
]. These processes have been qualitatively described at small spatial scales [14
]. However, quantification of these processes within a coastal aquifer has not previously been achieved, especially at the regional scales where it is most needed for assessing solute fluxes to the coastal ocean and predicting how such fluxes might change with climate change and other environmental perturbations. SGD water volume fluxes have been calculated at the basin scale in the North Atlantic [4
], Northwestern Pacific [18
], Mediterranean Sea [19
], and globally [1
] but associated solute fluxes cannot be determined at the basin scale until a better understanding and more quantitative description of the processes that govern solute concentrations at larger scales is achieved.
Principal component analysis (PCA) has been previously used to quantify processes that govern groundwater quality, including at the regional scale [21
]. PCA is an exploratory statistical technique that can be used to identify and rank factors contributing to the variance in datasets [28
]. Previous PCA-based groundwater studies have been largely confined to systems where flow rates are low and processes other than conservative mixing regulate concentrations of groundwater solutes. Coastal aquifers often have high flow rates and nutrient concentrations can be heavily modulated by mixing with seawater [10
]. Here, conservative mixing and other processes in the coastal aquifer of Monterey Bay, CA, an area where SGD was identified as an important nutrient source to the coastal ocean [6
], are quantified. Data collected at four different locations along the coast of Monterey Bay were analyzed via PCA to provide an overall view of the relative importance of processes in the coastal aquifer that may affect the nutrient loads associated with SGD in the region.
Boxplots of salinity (A), nitrate (B), ammonium (C), silicate (D), phosphate (E), δ15
(F), and δ18
(G) for each sample type: well groundwater (right box in each panel), coastal groundwater (middle box in each panel), and ocean water (left box in each panel) are shown in Figure 2
. Parameters that decreased in concentration from well groundwater to ocean water included nitrate (from 200 ± 70 μM to 10 ± 1 μM) and silicate (390 ± 30 μM to 13 ± 2 μM). Only silicate concentrations when considering all water types were statistically different from each other. Both groundwater types were statically higher in nitrate concentration than ocean water but were not different from each other. Salinity, δ15
, and δ18
increased from well water to ocean water (from 13 ± 4 to 33.0 ± 0.1, from 5.6 ± 0.2 ‰ to 10.2 ± 0.4 ‰, and from 0.0 ± 0.4 ‰ to 10.7 ± 0.8 ‰, respectively). Each water type was statistically different from the others with respect to δ18
. However, the only statistical difference with respect to δ15
was that well groundwater had lower δ15
than the other two water types. Ocean water salinity was statistically higher than both groundwater types. Phosphate and ammonium were highest in the coastal groundwater (6.8 ± 1.7 μM and 4.4 ± 0.9 μM), and lower in the well groundwater (2.0 ± 0.4 μM and 0.6 ± 0.3 μM) and ocean water (0.9 ± 0.1 μM and 3.6 ± 0.7 μM). For phosphate concentrations, coastal groundwater was statistically different from ocean water, and neither ocean water nor coastal groundwater was different from the well groundwater. No sample types were statistically different for ammonium.
Silicate concentrations were considered to be conservative in these analyses because of the distinct differences between the terrestrial (silicate = 390 ± 30 μM) and oceanic (silicate = 13 ± 2 μM) end members and the limited reactivity of silicate in groundwater. Conservative mixing behavior of silicate in similar settings has been observed previously [34
]. At this location, silicate displays a more conservative behavior than salinity because seawater intrusion resulted in well groundwater with high salinity. To determine if the other parameters were mixed conservatively, each parameter was plotted against silicate in Figure 3
, and linear correlations were fitted. There were no strong linear correlations (R2
< 0.25) with silicate concentration for any of the parameters examined here. While not exhibiting simple mixing between the end members (e.g., a linear trend), nitrate concentrations increased with increasing silicate concentrations, and δ18
decreased with increasing silicate concentrations. Ammonium and phosphate concentrations and δ15
were highest in the mid-range (20–200 μM) of silicate concentrations.
, and δ15
plotted against nitrate concentration are shown in Figure 4
A–C. Ammonium concentrations, δ18
, and δ15
increased as nitrate concentration decreased. Ocean water data clustered in the low nitrate and high ammonium/δ18
portion of the graph, and well groundwater data clustered in the high nitrate and low ammonium/δ18
area. Coastal groundwater data displayed the most variation, encompassing both these end-members and the area in between. Also shown in Figure 4
D is δ15
plotted against δ18
. In Figure 4
D, well groundwater and ocean water data are distinct, particularly with respect to δ18
. Coastal groundwater exhibited more variation with much of the data plotting either between ocean water and well groundwater data or along a near 2 δ15
trend (~0.5 slope), a trend typical of denitrification in groundwater.
shows the results of the PCA. Components 1, 2, 3, and 4 accounted for 39%, 19%, 14%, and 12%, of the variability respectively. The length of the vectors with respect to each component represent the relative contribution of that parameter (nutrient concentrations, salinity, δ15
, or δ18
) to that component. That is, the longer the vector with respect to a given component, the more that parameter (nitrate concentrations, salinity, etc.) correlated with or contributed to that component. Vectors that extend similarly (e.g., the same direction and length) indicate those parameters correlated with each other. Nitrate and silicate concentrations correlated with component 1 and with each other, indicating that as one of these parameters increased so did the other. Conversely, δ15
, and salinity negatively correlated with component 1. This indicates as nitrate and silicate increased δ15
, and salinity decreased. Ocean water samples clustered at the most negative portion of component 1, while well groundwater clustered in the most positive portion of component 1. Coastal groundwater fell between well groundwater and ocean water.
δ15NNO3 correlated most strongly with component 2. Well groundwater clustered at the negative end of component 2, and coastal groundwater had the most variance, reaching from the most negative to most positive data along this component. Ocean water data clustered around 0, indicating there was less variation in ocean water with respect to this component compared to well and coastal groundwater. Ammonium strongly correlated with component 3 while phosphate correlated to a lesser degree. Component 3 was most influenced by coastal groundwater as these data extend the full length of component 3. Ocean water and well groundwater cluster near 0, indicating those data had little influence on component 3. Phosphate correlated most strongly with component 4.