3.3.2 Predicted Fe and Mn Concentrations
Reservoir turnover had substantial impacts on Fe and Mn concentrations.
At the beginning of the deployment (16 October 2020), 17 days prior to
turnover, both Fe and Mn displayed large differences in concentration
between the epilimnion and hypolimnion (Figures 4D-E). The average total
Fe and total Mn concentrations across all hypolimnetic depths (6.2, 8.0,
and 9.0 m) were 3.73 mg/L and 1.48 mg/L; across all epilimnetic depths
(0.1, 1.6, and 3.8 m) they were 0.41 mg/L and 0.14 mg/L, respectively
(Figures 4D-E). Substantial changes in epilimnetic concentrations were
not observed until 24 hours prior to turnover. Within that 24 hour
period, average epilimnetic total Fe and total Mn increased by 70%
(0.61 to 1.04 mg/L) and 66% (0.29 to 0.48 mg/L), respectively.
In contrast to the epilimnion, we observed declining total Fe and Mn
concentrations in the hypolimnion prior to turnover (Figures 4D-E).
Between 16 October and 02 November 2020, hypolimnetic total Fe and total
Mn concentrations declined at a rate of 0.13 and 0.11 mg/L/d,
respectively. However, there were also periods of fluctuations in total
Fe and total Mn concentrations by as much as 1 mg/L/d (Figure 4D-E). In
the 24 hours prior to turnover, average hypolimnetic total Fe and total
Mn decreased by 45% (2.09 to 1.14 mg/L) and 32% (0.82 to 0.55 mg/L),
respectively.
A strong concentration gradient between the epilimnion and hypolimnion
remained for total Fe and total Mn until full reservoir turnover on 02
November 2020. After turnover, water temperature and DO rapidly
equalized across the full water column, coinciding with the rapid
equalization of total Fe and Mn concentrations across the water column
(Figures 4D-E). Total Fe and Mn concentrations were lower and less
variable than during the pre-turnover period (Figures 4D-E). The
reservoir remained well-mixed for 2 days, but then shifting thermal
gradients led to a temporary re-stratification that began on 02 November
2020 and lasted until the end of the deployment on 09 November 2020
(Figures 4A-B). The re-stratification of the reservoir was also evident
in total Fe and total Mn concentrations (Figures 4D-E).
3.4 Oxygen On Deployment
3.4.1 Water Temperature, Stratification, and DO
DO concentrations, water temperature, and Schmidt stability differed
considerably between the two deployments (Figures 5A-C). At the start of
the Oxygen On deployment (26 May 2021), 16 days prior to HOx activation,
epilimnetic DO concentrations were high (5-15 mg/L) and exhibited a
consistent decline throughout the deployment due to warm air
temperatures (Figure S14). Metalimnetic and hypolimnetic DO
concentrations were both approximately 0 mg/L throughout the deployment.
The water temperature profile shows distinctly stratified layers in the
reservoir prior to HOx operation, with a sharp temperature gradient
throughout the epilimnion for the entire deployment and a slight
temperature gradient in the hypolimnion (Figure 5B). Immediately
following HOx activation on 11 June 2021, the water temperature profile
equalized across layers below 6m depth, indicating mixing within the
hypolimnion due to HOx activation (Figure 5B). The water temperature
profile in the epilimnion was unaffected by HOx operation. Metalimnetic
and hypolimnetic DO concentrations did not increase above 0 mg/L in the
few days after activation of the HOx system. This is attributed to
chemical oxygen demand in the hypolimnion resulting from high
concentrations of reduced solutes (e.g., Fe(II) and Mn(II)).
3.4.2 Predicted Fe and Mn Concentrations
At the beginning of the deployment, the highest concentrations of total
Fe and Mn were at the lowest depth (9m) and concentrations decreased
upwards in the water column, with a sharp decrease between the
hypolimnion and epilimnion (Figures 5D-E). In the first 24 hours of the
deployment, total Fe and Mn concentrations averaged across all
epilimnetic depths were 0.43 and 0.03 mg/L, respectively, while across
the hypolimnetic depths they were 2.71 and 0.54 mg/L, respectively.
Prior to HOx operation, both total Fe and Mn in the hypolimnion
exhibited large, sub-daily fluctuations which resulted in concentration
changes of up to 1.62 mg/L/hr and 0.19 mg/L/hr, respectively (Figures
5D-E). These sub-daily fluctuations were most pronounced at the lowest
depth.
The spatial and temporal cycling dynamics of Fe and Mn were
significantly affected by hypolimnetic oxygenation. Prior to activation
of the HOx system on 11 June 2021, epilimnetic total Fe and Mn
concentrations remained constant (sd = 0.07 mg/L and 0.004 mg/L,
respectively) and low (maximum concentrations = 0.63 mg/L and 0.05 mg/L,
respectively). Hypolimnetic total Fe and Mn concentrations during this
period were much more variable (sd = 1.85 mg/L and 0.19 mg/L,
respectively) and higher (maximum concentrations = 7.90 mg/L and 1.08
mg/L, respectively). Shortly after HOx activation, total Fe and Mn
concentrations equalized contemporaneously with the equalization of
water temperature across the hypolimnetic depths, indicating that this
layer of the reservoir was well-mixed with respect to Fe and Mn (Figures
5B, 5D-E). In contrast, differences in total Fe and Mn concentrations
across the epilimnetic depths increased slightly after activation of the
HOx system.
Approximately 6 hours after turning on the HOx system, total Fe and Mn
at 9m depth declined by approximately 2.5 mg/L and 0.25 mg/L,
respectively (Figures 5D-E). Concentrations of total Fe and Mn at all
hypolimnetic depths subsequently increased over the next 24 hours,
before eventually stabilizing over the following 24 hours at
concentrations of 1.5-3.5 mg/L and 0.5-0.75 mg/L, respectively. For the
remainder of the deployment, total Fe and Mn concentrations remained
equal across all hypolimnetic depths and exhibited less variability
(Figures 5D-E).
3.5 Predicted Fe and Mn Soluble-to-Total Ratios
The ratio of predicted soluble to total Fe (SFe:TFe) and Mn (SMn:TMn)
was calculated to assess redox transformations. We observed distinct
changes in these ratios over the course of both deployments, most
notably in the hypolimnion (Figure 6). During the Turnover Deployment,
the hypolimnion was maintained at oxic conditions pre-turnover (due to
HOx) and post-turnover (due to mixing). As expected, hypolimnetic
SFe:TFe was approximately 0 during this entire deployment, indicating
that all Fe in the hypolimnion was in the particulate fraction (soluble
Fe + particulate Fe = total Fe). In contrast, hypolimnetic SMn:TMn was
approximately 1 at the beginning of the deployment, indicating that all
Mn was in the soluble fraction. However, in the week prior to turnover,
hypolimnetic SMn:TMn oscillated between 0.5 and 1. Following turnover,
SMn:TMn was greater than 0.75 and remained high until the end of the
deployment.
At the beginning of the Oxygen On deployment, SFe:TFe differed greatly
with depth in the hypolimnion, with ratios greater than 0.8 at 9m depth
and ratios close to 0 at 6.2m and 8m depths (Figures 6C-D). Between the
beginning of the deployment and HOx activation on 11 June 2021, the
SFe:TFe at 6.2m and 8m increased continuously to approximately the same
level as 9m (Figures 6C-D). Just before the initiation of HOx operation,
the SFe:TFe at all hypolimnion depths was > 0.75,
indicating that most of the Fe in the hypolimnion was in the soluble
fraction. However, immediately after turning the HOx system on, the
SFe:TFe in the hypolimnion decreased steadily. In the 48-hour period
after HOx activation, the SFe:TFe in the hypolimnion declined to less
than 0.25 and remained low until the end of the experimental period
(Figure 6C-D), indicating oxidation processes. In contrast to Fe,
SMn:TMn in the hypolimnion was > 0.90 for the entire
deployment. We did not observe a significant effect of HOx operation on
SMn:TMn (0.99 pre-HOx, 0.97 post-HOx).
4. Discussion
4.1 PLSR modeling of high frequency absorbance spectra can predict
Fe and Mn concentrations
Using UV-visible absorbance spectra and PLSR modeling, we made hourly
predictions of Fe and Mn concentrations at 6 depths in our study
reservoir. Our results indicate that this method can successfully
predict Fe and Mn concentrations based on their covariability with
UV-vis absorbance spectra, despite the paucity of clearly-defined
absorbance peaks for these elements. PLSR models were able to explain a
high proportion of the variability in the sampling data (Table 1) and
predictions agreed with expected Fe and Mn cycling dynamics. For
example, the rapid decline in SFe:TFe following the onset of HOx
operation (Figure 6C) matches expectations based on the rapid oxidation
kinetics of Fe(II) in the presence of oxygen (Davison & Seed 1983);
previous studies have also demonstrated substantial decreases in soluble
Fe following short periods of HOx (Dent et al. 2014, Munger et al. 2016,
Krueger et al. 2020). Based on model skill metrics (i.e.,
R2 and RMSEP) and visual inspection of the predicted
time series, accurate predictions of Fe and Mn concentrations using this
method are influenced by numerous factors, including: the range and
variance of concentrations in the calibration dataset, the sample size
used for calibration, the number of outliers in the calibration dataset,
the number of components in the PLSR model, and the inherent
predictability of each variable at a particular site (i.e., the strength
of correlation with the UV-vis absorbance spectra).
Our results suggest that our methodology may be most appropriate for
measuring elevated concentrations of Fe and Mn (> 0.1
mg/L). This result agrees with Vaughan et al. (2018), who suggested that
the application of this method to predict riverine total phosphorus (TP)
concentrations was best for sites with elevated TP (>0.1
mg/L) concentrations. In our study, PLSR models fit to data with lower
concentrations of Fe and Mn (< 0.1 mg/L) generally did not
perform well. For example, soluble Fe during the Turnover Deployment had
median concentrations of 0.06 mg/L and 0.02 mg/L in the epilimnion and
hypolimnion, respectively (Figure 3 and Table S1). Accordingly, the PLSR
models for soluble Fe had the lowest R2 (epilimnion:
0.74; hypolimnion: 0.06) and highest RMSEP relative to median
calibration concentration out of any model for the Turnover Deployment
(Tables 1, S1).
Our PLSR models were also sensitive to the range and variance of
sampling data used for calibration. Preliminary model testing revealed
that PLSR models were hindered by the distinct water chemistry between
epilimnetic and hypolimnetic depths (Fe and Mn mean differences
>1.3 mg/L and 0.8 mg/L, respectively; see Figure 3) and
therefore models were generated separately for each reservoir layer.
This conforms with findings of previous studies using in situUV-vis spectrophotometers and PLSR in waterbodies, which all achieved
higher accuracy with site-specific models (Avagyan, Runkle, & Kutzbach
2014, Vaughan et al. 2018, Etheridge et al. 2014). However, when
comparing pairs of PLSR models (i.e., the same variable + depth
combination) between the two deployments, the models fit to data with a
higher standard deviation had higher R2 values, with
the sole exception of hypolimnetic total Fe (Tables 1 and S1). These
results suggest that there is a tradeoff between capturing the maximum
variability in observed concentrations and the limitations imposed by
the degree of covariability between the UV-vis absorbance spectra and
the variable of interest (also observed by Avagyan, Runkle, & Kutzbach
2014 and Allen 2021). To achieve an accurate predictive model, grouping
data based on the spatial and temporal context of measurement achieved a
better fitting model while still maximizing the variability captured in
the calibration data.
Birgand et al. (2016) used a similar approach for making predictions of
soluble Fe concentrations in FCR after the activation of a HOx system.
They obtained a slightly better model fit, indicated by an
R2 value of 0.94, compared to our R2values of 0.79 and 0.75 (epilimnion and hypolimnion, respectively) for
the Oxygen On Deployment. We used calibration sample sizes of 48 and 45
(epilimnion and hypolimnion, respectively) while Birgand et al. (2016)
used 27. However, they used 5 components in their PLSR model, whereas we
used 4 components. Thus, the higher R2 value for their
model may be attributed to a higher ratio of components to sample size
(18%) compared to our study (8-9%).
4.2 Fe and Mn Concentrations Change Gradually in Response to
Weakening Stratification and Rapidly in Response to Full Turnover
Trends in predicted Fe and Mn concentrations shed light on the changes
that occurred in the reservoir before and after turnover. Hypolimnetic
concentrations of Fe and Mn began declining 17 and 9 days prior to
turnover, respectively, and shorter periods of more rapid concentration
fluctuations were superimposed upon these patterns of decline (Figures
4D-E). Combined, these results suggest that turnover, at least in our
study reservoir, is not a discrete event, but rather a process occurring
over an extended time period. McMahon (1969) measured a similar decrease
in soluble Fe using daily samples for nine days across spring mixing in
a dimictic lake; soluble Fe concentrations decreased by more than one
order of magnitude 5 days prior to full circulation. McMahon (1969) did
not offer any interpretation of this phenomenon, simply stating that the
changes in soluble Fe were concurrent with vernal circulation. Similar
trends have also been observed in other parameters of biogeochemical
relevance. For example, Kankaala et al. (2007) found that the majority
of CH4 in the hypolimnion of a lake was microbially
oxidized at the oxycline boundary during a month-long period of
weakening stratification before complete mixing occurred, resulting in
lower effluxes of CH4 to the atmosphere during turnover.
Predicted Fe and Mn concentration data can be compared to other time
series data to infer mechanisms behind the declining Fe and Mn
concentrations prior to turnover. Based on trends in Schmidt stability
and water temperature (Figures 4A-B), reservoir stratification was
weakening for a 9-day period prior to full turnover, in response to
daily and hourly shifts in meteorological conditions, including air
temperature and wind speed (Figure S13). Mixing between the hypolimnion
and metalimnion, as indicated by the homogenization of water temperature
between these layers, occurred periodically throughout the deployment,
with an increasing frequency as turnover approached (Figures 4A-B, S15).
These ephemeral periods of mixing between the hypolimnion and
metalimnion likely led to exchange of Fe and Mn between layers, which
suggests that hydrodynamic processes occurring on hourly to daily time
scales may have a substantial influence of Fe and Mn cycling. However,
without Fe and Mn concentration data at a high spatiotemporal
resolution, these patterns would not be observed.
The flexibility of using a multiplexor-spectrophotometer system with a
customized prediction algorithm (e.g., site-specific PLSR models) allows
for the quantification of high-resolution elemental stoichiometry by
making predictions of both the soluble and total fractions of Fe and Mn.
During the Turnover Deployment, Fe was predominantly composed of the
total fraction, whereas Mn was largely composed of the soluble fraction
until approximately one week before turnover, at which time the SMn:TMn
ratio began to decline (Figure 6B). This coincided with the onset of
declining total Mn concentrations that continued until turnover,
excluding a 2-day period from 28 October to 30 October 2020 when total
Mn concentrations temporarily increased (Figure 4E). The shift to
declining SMn:TMn and total Mn concentrations also coincided with
increased frequency of mixing between the metalimnion and hypolimnion
and declining stratification intensity (Figures 4A-B and 6B). These
trends suggest that declining total Mn concentrations in the
pre-turnover period were the result of increased oxidation of Mn(II),
perhaps due to the exposure of Mn(II) in the hypolimnion to Mn-oxidizing
microbes that inhabit the metalimnion, as demonstrated by a previous
study at FCR showing that the presence of Mn-oxidizing microorganisms
can substantially increase Mn oxidation rates (Munger et al. 2016).
4.3 Hypolimnetic Oxygenation Causes Oxidation of Fe, but not Mn
The MUX-spectrophotometer system enabled us to observe Fe and Mn
concentration changes in response to hypolimnetic oxygenation at an
unprecedented spatiotemporal resolution. Fe and Mn concentrations in the
hypolimnion both spiked in the 48 hours following oxygenation, then
declined (Figures 5D-E). However, Fe concentrations decreased to levels
lower than they were prior to oxygenation, especially at the lowest
depth, whereas Mn concentrations declined to approximately the same
levels prior to oxygenation (Figures 5D-E). These results indicate that
the HOx system effectively physically mixed the hypolimnion with respect
to both metals, as total Fe and total Mn concentrations quickly
converged across hypolimnetic depths after turning on the HOx system
(Figures 5D-E) The physical mixing induced by the HOx system appeared to
affect Fe and Mn similarly, suggesting that the spike in total Fe and Mn
immediately following HOx activation was a result of increased mixing
and/or entrainment of particulates in the hypolimnion due to stirring of
the bottom sediments. The convergence of Fe and Mn concentrations across
hypolimnetic depths has previously been observed in response to HOx
activation (Gerling et al. 2014), but results from this study reveal
that this can occur in less than 24 hours, and may subsequently be
followed by an ephemeral spike in total Fe and Mn concentrations.
Concentrations of total Fe and Mn displayed much greater short-term
variability prior to HOx activation than they did post-activation. This
was especially pronounced at the lowest depth (9 m) where concentrations
fluctuated significantly over a period of less than 24 hours (Figures
5D-E). Given that the SFe:TFe ratio in the upper and middle hypolimnion
(6.2m and 8m) steadily increased during the pre-HOx period (Figure 6C),
likely due to diffusion of soluble Fe out of the lower hypolimnion, the
rapid fluctuations in total Fe in the lower hypolimnion may have been
attributed to shifting diffusion gradients. However, similar patterns in
short-term variability were observed in Fe and Mn, despite the fact that
Mn was predominantly in the soluble phase for the entire deployment,
suggesting that diffusion of soluble Mn out of the lower hypolimnion was
not responsible for the pre-HOx rapid fluctuations observed at 9 m.
The change in redox conditions caused by adding DO to the hypolimnion
had a much more pronounced effect on Fe than Mn, as has been observed in
other studies (e.g., Gantzer et al. 2009). The contrasting responses of
Fe and Mn to oxygenation can be seen most clearly in the resulting
changes in soluble:total ratios (Figure 6). The SFe:TFe ratio in the
hypolimnion exhibited a nearly constant linear decline in the 48 hours
post-oxygenation and remained below 0.25 for the remainder of the
deployment. This indicates that soluble Fe in the water column was
rapidly oxidized by the HOx system, even though there was no measurable
increase in hypolimnetic DO. This is further supported by the fact that
the mean hypolimnetic total Fe concentration was consistently lower
after HOx operation began than it was previously. The observed trends in
SFe:TFe ratios agree with previous research on the effects of HOx
systems on Fe in lakes and reservoirs. For example, Dent et al. (2014)
found that SFe:TFe declined to 0.58 after 8 hours of hypolimnetic
oxygenation. In our study, it took approximately twice as long (16
hours) for SFe:TFe to reach 0.58. However, the Fe concentrations in Dent
et al. (2014) were lower (0.17 - 2.88 mg/L) than those in our study
(0.31 - 7.42 mg/L).
In contrast to Fe, the SMn:TMn ratio in the hypolimnion displayed only a
very slight response (approximately 2% decrease) to HOx activation,
demonstrating that hypolimnetic oxygenation did not result in
significant oxidation of Mn. Our results agree with those from Dent et
al. (2014), who found that Mn was still 100% in the soluble phase 8
hours after oxygenation. Furthermore, previous studies at FCR have also
showed that soluble Mn does not respond significantly to oxygenation
alone and that other factors, such as microbially-mediated oxidation,
reservoir pH (range 6.4 - 7.1 observed in the hypolimnion during our
study) and dilution from physical mixing, are more important variables
impacting hypolimnetic soluble Mn than oxygenation (Munger et al. 2016,
Krueger et al. 2020).
4.4 Study Limitations
The MUX pumping system enabled us to monitor multiple depths
simultaneously, which is invaluable for investigating biogeochemical
processes in spatially heterogeneous systems such as
thermally-stratified reservoirs. However, there are several limitations
to be improved upon in future research. In our reservoir, the cuvette
fitted on the spectrophotometer experienced fouling, likely due to Fe
and Mn in the hypolimnion that oxidized and precipitated on the cuvette
walls upon exposure to oxygen. Despite our efforts to limit fouling (see
Methods), there was still a fouling signal detected in several periods
of our time series (Figures S4-5). PLSR models provided a remarkably
good numerical correction for this fouling signal, indicating that the
collection of additional calibration samples obtained at regular
intervals between servicing dates may yield lower uncertainties in
future deployments. We also found that truncating the UV-vis absorbance
spectra used for calibration to only include wavelengths greater than
250 nm substantially improved the model skill and diminished spikes in
the time series of predictions that corresponded to periods of heavy
fouling (Figures S6-7).
Our results captured sub-weekly patterns in Fe and Mn dynamics in FCR,
but the PLSR-predicted time series of Fe and Mn concentrations was not
able to adequately capture some of the high-magnitude, sub-daily
fluctuations that were observed in the sampling data (Figures 4 and 6).
This is likely due to varying PLSR model skill, which is related to the
sample size and distribution of data used for calibration, the number of
PLSR model components, and the inherent predictability of each variable.
Therefore, it follows that the strength of correlation between the
UV-vis absorbance spectra and Fe/Mn concentrations plays a strong role
in determining the limits to the temporal resolution. This relationship
can be refined through the methodological suggestions outlined above,
but ultimately depends upon the spectral properties of the study system.
5. Conclusions
Results from this study demonstrate that coupling a spectrophotometer
with a pumping system enabled unprecedented high-frequency monitoring of
Fe and Mn at multiple depths in our study reservoir, providing a unique
ability to observe hour-resolution biogeochemical dynamics in a
freshwater ecosystem. Our findings underscore the importance of
implementing robust and consistent methodologies for obtaining
calibration concentrations, choosing the number of components in PLSR
models, and quantifying the uncertainty around predictions.
The high-spatio-temporal resolution predictions provide novel insights
into Fe and Mn cycling dynamics that could improve aquatic monitoring
programs and reservoir management practices. First, we demonstrated that
Fe and Mn concentrations can fluctuate significantly on time scales much
shorter than those employed by most traditional monitoring programs. For
example, sub-daily fluctuations of total Fe and Mn during the Oxygen On
Deployment resulted in concentration changes of up to 1.62 mg/L/hr and
0.19 mg/L/hr, respectively. Considering that the secondary drinking
water standards for Fe and Mn are 0.3 and 0.05 mg/L, respectively,
sub-daily concentration changes of this magnitude are critical for water
quality management. Second, we observed an increase in total
hypolimnetic Fe and Mn in response to the re-stratification of our study
reservoir two days after turnover, which contradicts the common
assumption that metals concentrations equalize and remain consistently
low during the mixed period following turnover. Last, our results offer
new insights on the rapid response of Fe to hypolimnetic oxygenation;
within hours of activating the system, the soluble to total Fe ratio
indicated oxidation of Fe, even though there was no measurable increase
in DO. This study emphasizes the power of high spatiotemporal resolution
data for improving our understanding of biogeochemical cycles by
unveiling previously-unobserved processes altering Fe and Mn cycling.