DOI: 10.5061/dryad.8pk0p2nn1
title: Chemical effects of snowmelt on an alpine lake in the Wind River Range, WY

description: Nitrogen deposition from air pollution is increasingly reaching alpine
 lakes where the addition of nitrate and ammonium to sensitive surface
 waters can cause acidification and or eutrophication. Thirty years of
 sampling in the Wind River Range, WY have shown some lakes increasing in
 nitrogen. We sought to determine (1) if nutrient concentrations in Deep
 Lake increase during snowmelt when atmospheric deposition is released from
 the snowpack and (2) assess if the sampling season, location,
 meteorological factors, and time of day samples are collected influence
 lake chemistry metrics, to inform monitoring. We analyzed water samples
 from the outlet of Deep Lake in peak snowmelt (June) and from the inlet,
 outlet, and middle of Deep Lake when the basin was snow free (August). In
 June, outlet samples were more acidic, and nitrogen content was three
 times August levels. Acid neutralizing capacity (ANC) declined with
 snowmelt. August inlet samples were higher in nutrients than outlet and
 mid-lake samples. Our results indicate that atmospheric pollution in the
 snowpack enters the lake with snowmelt. Although Deep Lake has not
 acidified, ANC levels indicate a risk of episodic acidification if
 nitrogen deposition continues to increase. When monitoring lakes at risk
 for episodic acidification, sampling during the late snowmelt pulse should
 be prioritized. Simplified sampling protocols may be used in some lakes,
 as epilimnion and outlet samples were nearly identical. The time of day
 and cloud cover did not affect lake chemistry, while wind speed and
 precipitation weakly increased August ANC and June pH, respectively.
description: The Wind River Range extends roughly 250 kilometers, forming the
 continental divide through west-central Wyoming as part of the Rocky
 Mountains and the southeastern arm of the Greater Yellowstone Ecosystem
 (GYE). Rugged, glacially sculpted terrain, a high density of alpine lakes
 (over 1,500 lakes across 173,374 ha; Grenon et al. 2010; McMurray et al.
 2013), cold temperatures, thin or absent soils, and a short growing season
 (less than 40 consecutive nights above freezing per year) characterize the
 Wind River Range (https://wrcc.dri.edu/narratives/WYOMING.htm). Archean
 granitic rock, granitic gneiss, and migmatites are predominant across the
 range (Frost et al. 1998). Precipitation comes primarily in the form of
 snow and averages 100-130 cm total annual water equivalent at the
 lower-to-mid elevations and reaches up to 150 cm or more along the
 continental divide (Hall et al. 2012). An estimated two-thirds of the
 annual precipitation runs off as stream flow, with the rest attributed to
 evapotranspiration (Foster and Hall 1981; Hall et al. 2012). While the
 exact proportion of annual water derived from snow in the Wind River Range
 is undocumented, snowfall, snow cover, and the timing of snowmelt have
 been identified as the primary drivers of stream discharge for the region,
 emphasizing the dominance of snow in these hydrologic systems (Hall et al.
 2012, 2015). Snowmelt from the western slopes of the Wind River Range
 drains to the Green River, providing water to the largest tributary of the
 Colorado River. Two oil and gas extraction sites, the
 Pinedale Anticline and Jonah Project Area (Fig. 1), are located 40 km west
 and upwind of the southwestern Wind River Range in nearby Boulder, WY, and
 have been identified as a source of reactive nitrogen to the Southern Wind
 River Range, contributing the highest volume of nitrogen pollution in
 winter months (Zhang et al. 2018). The Jim Bridger coal plant 110 km to
 the south may provide an additional local source of reactive nitrogen to
 the mountain range. These extraction sites are sources of nitrogen in the
 form of nitrate, but they may also be a source of ammonia to the Wind
 River Range (Brahney et al. 2015; McMurray et al. 2013). Additional
 sources of nitrogen to the GYE also come from regional and long-distance
 transport from agriculture, fire and other sources (Zhang et al.
 2018). Deep Lake (elevation 3,218 m; 42.719084°N,
 109.172130°W; Fig. 1) basin has a 190 ha watershed that lies in the
 southwestern Wind River Range within the Bridger Wilderness and is
 estimated to be 90% barren 7% grass, and 3% forest (Brahney 2012). Parent
 material in the basin is predominantly granitic, which breaks down slowly
 and thus has limited contribution of base cations to the total ANC
 (Brahney 2012; Mast et al. 1990, 2001; Turk and Spahr 1991). Like many
 high alpine lakes in the Wind River Range, the inlet and lake surface
 remain frozen through June, and water enters the lake diffusely from all
 sides as snow melts. In August, water primarily enters the lake through
 one main inlet, though groundwater contribution is possible but unknown
 (Fig. 1). Deep Lake is 24.5 ha in area and 27.0 m deep (Grenon et al.
 2010). Deep Lake is not fed by any glaciers or permanent snowfields and
 all inputs thus reflect annual snowmelt, current precipitation, or
 possibly ground water which we were unable to examine. Given the watershed
 area, rates of evapotranspiration, and assuming 110 cm total annual water
 equivalence, mean annual runoff is estimated to be 1.4 × 10<sup>6
 </sup>m<sup>3 </sup>(Foster and Hall 1981; Hall et al.
 2012). Outflow from the lake can reflect the chemistry
 of the epilimnion when the lake is stratified, or a mix of layers
 following lake turnover (Hutchinson 1975). Thus, water chemistry at the
 outlet can be a function of input occurring over multiple years. Assuming
 the average depth is half the maximum depth of the lake, lake volume is
 calculated to be 3.3 × 10<sup>6 </sup>m<sup>3
 </sup>and mean residence time in Deep Lake is estimated to be 2.3
 years, by equation (1) (Winchester 1968; Hutchinson 1975).
                         Water residence time (yrs) = Lake Volume
 (m<sup>3</sup>) / Mean Annual Runoff
 (m<sup>3</sup>/yr)    (1) Detailed
 bathymetry of the lake is not available to form a more accurate estimate.
 We selected a value of one half because of the steepness of the
 surrounding terrain (Fig. 1). Our approximation is probably an upper limit
 to the volume of the lake, and consequently, the water residence time. It
 is important to note that traditional thinking about water residence time
 can be somewhat misleading for a water body like Deep Lake. In this
 system, almost all of the flow occurs during the short period of snowmelt.
 If this discharge continued throughout the year, water residence time
 would be much shorter. Instead, for most of the year, discharge is close
 to zero and the water in the lake through the colder months has a much
 longer effective residence time. Though it was not observed in the course
 of our study, in many years the outlet of Deep Lake dries up from late
 summer through autumn. Taken together, this means that all of the lake
 water that we measured (outlet and mid-lake) had an effective water
 residence time that was much shorter than the average residence time of
 all water in the lake. It is possible to estimate the magnitude of these
 effects. When the lake is stratified, we measured the epilimnion to be 9 m
 thick, and water residence time for this layer alone is 1.4 years.
 Furthermore, if most of the flow through the lake occurs in three of the
 twelve months, then this number reduces to an effective water residence
 time during the time we sampled of about four months.
 Snow depth, snow-water equivalent and precipitation data
 referenced in this analysis were from the National Resources Conservation
 Service Big Sandy Opening snow-telemetry (SNOTEL) site (elevation 2770 m;
 42.64580°N, 109.25965°W) located 10.6 km southwest of Deep Lake (National
 Water and Climate Center 2016). Annual precipitation at this site was
 reported to be 107% of average by the June sampling period and 97% of
 average by the August sampling period (National Water and Climate Center
 2016). <i>Study Design</i>
 Sampling of Deep Lake occurred during two time intervals in the
 summer of 2016: (1) peak snowmelt (June 1-18) and, (2) peak primary
 production (August 7-13). In June, we collected grab samples of water at
 the outlet twice per day, in the morning (7:00-9:00) and evening (17:00 –
 19:00) for 19 days along with one cycle of samples collected at the outlet
 every hour for 24 hours (8:00 June 9, 2016 to 8:00 June 10, 2016). We were
 unable to collect water samples from the mid-lake surface and lake inlet
 in June because those sites were frozen. In August, water samples were
 collected at the outlet, mid-lake, and inlet twice per day for 7 days, in
 the morning (7:00-10:00) and in the evening (17:00-19:00) as weather
 conditions allowed. A 24-hour sampling cycle was not conducted in
 August. All samples were collected from the epilimnion
 at 10 cm depth and filtered with 0.45 μm nominal pore size
 Polyethersulfone Sterile Syringe Filters (N.A. PN 28145-505)
 VWR<b>®</b> attached to BD 60 ml
 Luer-Lok<sup>TM</sup> syringes (REF 309653)
 VWR<b>®</b>. We collected 100 ml of filtered water via two
 syringe pulls, and stored the water in 125 ml polyethylene bottles,
 allowing 25 ml of headspace in the bottle to prevent rupture when they
 were frozen for long term storage. Neither acid nor other preservatives
 were added to the bottles. Bottles and syringes were rinsed with lake
 water (collected about 3m downstream of the sampling location) and
 syringes were not reused after sample collection. Samples were kept at
 approximately 1-3 ºC while in the field by submersing them in meltwater
 downstream of the sampling site. The bottles were immediately frozen
 following transport from the field until they were thawed for analysis.
 Water temperature and pH were measured at each sample collection using an
 Oakton<b>®</b> pH 150 Waterproof Portable pH/mV/Temperature
 Meter (EW-35614-90). For every sampling event we
 observed meteorologic conditions, recording wind speed, and proportion of
 cloud cover following the Bridger-Teton National Forest Wind River
 Mountains Air Quality Monitoring Program Methods Manual (U.S. Department
 of Agriculture, Forest Service 2002). We also qualitatively recorded any
 precipitation since the last sampling period noting no precipitation as 0,
 precipitation since the last sampling event as 1, and precipitation during
 the sampling event as 2. A Solinst<b>®</b>
 Levelogger<b>®</b> Jr. Edge M5 (110241) was submerged 0.4 km
 downstream of the lake outlet and recorded pressure every 5 minutes for
 the duration of the sampling periods. An adjacent, terrestrial
 Solinst<b>®</b> Levelogger<b>®</b> Edge M5
 (110023) simultaneously recorded changes in atmospheric pressure. Using
 the difference between the two devices, we calculated downstream water
 depth at 5 minute intervals, corrected for variation in barometric
 pressure. In August we recorded temperature and pH
 every meter to 19-m (the maximum reach of our measuring equipment) at
 mid-lake to evaluate depth profiles and identify a thermocline with a
 YSI<b>®</b> 556 Handheld Multi Parameter Instrument (556-01).
 The thermocline is a boundary between the epilimnion and hypolimnion,
 which limits mixing between the layers and allows flow to occur within the
 epilimnion (Lerman et al. 1995). An inflection point in the temperature
 gradient is used to identify the epilimnion, and a lake is considered
 strongly stratified when there is a temperature gradient of &gt;
 4°C between the surface and 60% of its depth (16.0 m for Deep Lake)
 (Landers et al. 1987; Lerman et al. 1995).
 <i>Chemical Analysis</i> We used
 an ICP-OES Optima 3000 (Perkin Elmer, Waltham, MA) to measure
 concentrations of strong base cations (Ca<sup>2+</sup>,
 K<sup>+</sup>, Mg<sup>2+ </sup>and
 Na<sup>+</sup>), an Ion Chromatograph (IC) DX500 (Dionex,
 Sunnyvale, CA), to measure strong acid anions
 (NO<sub>3</sub><sup>-</sup>,
 SO<sub>4</sub><sup>-</sup> and
 Cl<sup>-</sup>), and an Astoria 2 Flow Analyzer (Astoria
 Pacific, Clackamas, OR) to measure ammonium, total nitrogen, and total
 phosphorus. ANC was determined by gran titration. Duplicates were
 collected in the field for one-tenth of all samples, and ten percent of
 collected water samples were split and run as lab replicates for QA/QC
 purposes. Blanks of deionized water were stored in sample collection
 bottles, frozen with field samples for storage, and also analyzed for
 QA/QC, but not transported into the field. Strong base cation
 concentrations were calculated as the sum of the normal (eq/L)
 concentrations of Ca<sup>2+</sup>, K<sup>+</sup>,
 Mg<sup>2+</sup> and Na<sup>+</sup>. The strong
 acid anion concentrations were taken to be the sum of the normal (eq/L)
 concentrations of NO<sub>3</sub><sup>-</sup>,
 Cl<sup>-</sup>, and
 SO<sub>4</sub><sup>2-</sup>.
 The ratio of nitrogen to phosphorus was calculated from the
 molarity of each sample as an indicator of nutrient limitation in the
 lake. In an analysis 2053 lakes and nearly 90 nitrogen and phosphorus lake
 enrichment experiments from Norway, Sweden and the Rocky Mountains, USA,
 Elser et al. (2009) found that lakes in low nitrogen-deposition areas had
 molar total nitrogen to total phosphorus ratio below 44.2 and were
 generally nitrogen-limited whereas lakes above a total nitrogen to total
 phosphorus ratio of 110 were consistently in high deposition areas and
 limited by phosphorus. Similarly, a synthesis of 221 lakes from 14
 countries found that nitrogen-limitation was consistent when the total
 nitrogen to total phosphorus ratio was below ~31 and total phosphorus was
 above 0.003mg P/L (Downing and McCauley 1992). Dissolved inorganic
 nitrogen to total phosphorus ratios have been suggested as a better
 indicator of nutrient limits on phytoplankton growth, and by this metric
 nitrogen-limitation transitions to phosphorus-limitation when molar
 dissolved inorganic nitrogen to total phosphorus ratios shift from 3.3 to
 7.5, with higher ratios typical of alpine lakes with moderate levels of
 nitrogen-deposition (Bergström 2010). We focused our
 analysis on testing for changes in concentrations of total nitrogen, total
 phosphorus, titrated ANC, and the sums of the strong base cations and
 strong acid anions. To assess differences in these lake chemistry metrics,
 we ran ANOVAs testing the effect of sampling season (outlet samples only),
 sampling location (August only), and time of day the sample was collected.
 We used simple linear regression to determine if ion concentrations became
 more dilute during June sampling interval at the lake outlet over time. In
 lake monitoring programs, researchers often wonder if meteorological
 factors influence the chemistry of epilimnion samples, and thus should be
 accounted for in sampling protocols. We used general linear regression to
 test the influence of cloud cover, precipitation, and wind speed on major
 lake chemistry parameters in both June and August. We took
 <i>p</i> &lt; 0.05 as our threshold for significance for
 all analyses. Reported uncertainties for summary values
 by location, season, and time of day are given as the standard deviation.
 Uncertainties for measurements of Ca<sup>2+</sup>,
 K<sup>+</sup>, Mg<sup>2+</sup>,
 Na<sup>+</sup>,
 NO<sub>3</sub><sup>-</sup>,
 SO<sub>4</sub><sup>-</sup>,
 Cl<sup>-</sup>,
 NH<sub>4</sub><sup>+</sup>, total nitrogen, total
 phosphorus, and titrated ANC were taken as the square root of the mean of
 the squares of the difference in replicates for each measure. Uncertainty
 values for the sum of the strong base cations and strong acid anions were
 taken to be the square root of the sum of the squared uncertainties of
 their components.
description: Units and notes on detection limits are included in the header of
 the master file.