Citation
Poster Sessions: Atmospheric and Geological Sciences

Material Information

Title:
Poster Sessions: Atmospheric and Geological Sciences
Creator:
Becker, Aidan
Carr, Katelyn
Chapman, Charles
Coble, James
Frieman, Richard
Geary, Kathleen
Insolia, Nicole
Krawiec, Jennifer
Lee, Rachel
Moro, Gabrielle
Mosher, Hayley
Ploss, Kathryn
Rampersad, Joshua
Stroup, Justin
Sumell, Karissa
Vanalstine, Landon
Publication Date:
Copyright Date:
2021

Subjects

Subjects / Keywords:
Quest 2021
Atmospheric Science
Geological Science

Notes

Abstract:
Impact of changes in flow rate on stream morphology: A Physical Modeling Approach by Jennifer Krawiec. The EMRiver stream table is a metal “box” that is 94 cm wide, 275 cm long, and about 13 cm deep. The box is filled with a well sorted, ground up plastic that resembles the size of medium sand. This plastic modeling media acts as “sediment” in our model. Before each run is conducted, the sediment is smoothed, packed down, and a starting channel is made. The starting channel is 2.5cm wide and approximately 4cm deep. The table is tilted to a constant slope of 3.3 degrees. A total of 21 runs were conducted at different flow rates. The flow rate was varied between a range of 40-80 ml/s. We allow the stream model to run for about 60 min, while a Raspberry Pi camera takes still photos which are then stitched into a time-lapse video. We then measured the meander sinuosity (channel length / straight line distance) and stream width (bank to bank) from still photos. Channel width measurements were taken at 3 different points along the length of the table. From this information, we can see how flow rate impacts the morphology of the stream channel. Our preliminary results suggest that as the flow rate increases, the width of the stream channel increases and sinuosity decreases. This study has application to agriculture, civil engineering, and land usage planning. It also shows the impact of climate change (periods of increased precipitation or droughts) on the behavior of river systems. ( ,,,,,,,,,,,,,,,,,,,,,,,,,,, )
Abstract:
Sonar Imagery of Shoreline Tufa Deposits and Bathometric Mapping at Green Lakes State Park, NY by Aidan Becker, Justin Stroup, Rachel Lee, Nicole Insolia. Green Lakes State Park, located in Fayetteville, New York, holds two deep and narrow meromictic lakes which are hypothesized to be plunge pools associated with the retreat of the Laurentide Ice Sheet (~13,000 years ago). Today, the catchment area for Green and Round Lake is small and the lakes are mainly groundwater fed. This groundwater flows through the Syracuse formation and the gypsum-bearing Vernon Shale and discharges into the lakes rich in calcium, magnesium and sulfate. Tufa deposits are located at sites of groundwater discharge. Tufa deposits are thrombolitic microbialite structures, mainly composed of calcite accreted during cyanobacterial photosynthesis. The tufa deposits vary in size from meters to tens of meters and are found in various locations along the lakeshores. Here, we update the bathometric mapping using sonar techniques and provide the first sonar imagery of the nearshore environment to identify the locations of tufa deposits. Sonar data was collected with a Humminbird SOLIX 12 CHIRP MEGA SI + G2 with frequencies of 50/83/200/455/800 kHz & 1.2 MHHz during the summer and fall of 2019 and 2020. The sonar data was analyzed using Reefmaster, Sonar TRX, ArcGIS and Google Earth. Results indicate, both lakes exhibit steep slopes about 30° and the maximum depths detected at Green and Round Lake were ~175 feet and ~159 feet below the lakes’ surfaces. Sonar imagery reveals numerous locations of woody debris and clearly shows tufa deposits. In Green Lake, we identify 14 locations of tufa deposition, those being previously discovered and newly discovered, most concentrated on the East and West shores. Tufa deposition was limited in Round Lake with 4 localities of tufa found each consisting of multiple distinct tufa heads all concentrated on the eastern and southern shore. Our work provides data needed to refine prior bathometric mapping and provides a new viewpoint for understanding tufa geometry and the locations of tufa formation. These data will aid in understanding the link between groundwater discharge and tufa formation. It will also help with ongoing and future conservation efforts of this unique site.
Abstract:
Mapping of Submerged Shorelines at Junius Ponds, NY by Nicole Insolia, Justin Stroup, Karissa Sumell and Aidan Becker. Wetland hydrology can be complex with changes in water budgets and routing, which can influence sensitive ecosystems containing rare plant and animal species that rely on stable or slowly changing water levels. Junius Ponds, Unique Area, NY consists of four interconnected ponds which were formed in kame deposits associated with the last glaciation. Water flows from south to north from Phillips Pond to Lowery Pond and into East and West Newton Ponds. In some locations along the margins of the ponds, there are fens containing rare endemic species. Water levels in these ponds are pivotal because they control the amount of rare fen habitat available. Rising water levels submerge and remove habitat. Over the last ~100 years, pond water levels have generally risen and today are near their highest in historical time. Water levels and water routing are governed by culverts associated with I-90 and SR 318, changes in land use, and are also influenced by factors like beavers and climate. Here, we use a combination of historical aerial imagery, bathymetric mapping, and side scan sonar to investigate the modern high stand shoreline and prior submerged shorelines. This information provides constraints on past wetland extents and associated water level changes. The sonar data was collected with a Humminbird SOLIX 12 CHIRP MEGA SI + G2 with frequencies of 50/83/200/455/800 kHz & 1.2 MHHz in the summer of 2018. Reefmaster, SonarTRX, ArcGIS, and Google Earth were utilized in the analysis of sonar data and generating detailed bathymetry. Comparing depth and speed corrected side scan sonar data with aerial imagery indicates that, past shoreline features in Lowery Pond are approximately 1-1.5 meters below the pond surface level. There are also several generations of shoreline features indicating multiple lake level stages. These data are foundational for examining the evolution of wetland systems through time and for site management.
Abstract:
A Grain Size Transect of Badwater Basin, Death Valley, CA by James S. Coble, Hayley M. Mosher, Justin S. Stroup and Richard A. Frieman. Death Valley, CA is a well-known closed basin with a xeric environment. The Death Valley Fault Zone is a right lateral-moving fault in California. It runs from a connection with the Furnace Creek Fault Zone south to a junction with the Garlock Fault. Materials eroded from the bounding mountain chains are focused in the center of the basin. These sediments are transported by gravity, wind, and water with sporadic times of alluviation. On occasion, portions of the valley floor flood dissolving evaporite minerals which are later concentrated by evaporation. Other than these and rare episodes, the floor of Death Valley is covered in sediment and in some locations desiccation polygons. Analysis of the stratigraphy in Death Valley provides a wealth of information on paleoclimate in the region and shows both arid and wet conditions through time. Here, we characterize the modern grain size distributions of clastic materials at 10 sites using 40 samples within the Badwater Basin. The data set forms an east west transect across the center portion of the valley floor. Since evaporite minerals are abundant but their grain size results from crystallization conditions, we focus on the grain size of clastic minerals in the basin. We measured grain size of the clastic fraction after precipitates and organic matter was removed using a pretreatment procedure. Samples were disaggregated with sonication and a hexametaphosphate solution and grain size was measured using a Coulter LS 13 320. We focus on the grains sizes contained within desiccation polygons but also present additional samples for context. We examine multiple samples from different locations within individual desiccation polygons, from the edges and centers and compare these with samples along an 8-kilometer transect. The most abundant grain size range was between 0.4 to 150µm. The grain size distributions from multiple samples taken at each of the 10 sites were mostly consistent, suggesting that the grain sizes detected are representative of a given site location. In the transect, the average grain size across the playa is finest in the middle furthest from the alluvial fans. This research provides a snapshot of the grain sizes, environment, and spatial distribution of grain sizes on the modern playa floor which may help future interpretation of sedimentary records in the basin.
Abstract:
Impact of changes in slope on stream morphology: A Physical Modeling Approach by Katelynn Carr. Physical models in a laboratory setting can be used to observe and replicate the morphology of streams in nature. Throughout this research project, the Emriver Em3 Geomodel Stream Table was used to produce stream channels under different initial slope conditions. An imitation laboratory sediment is used in the table that is made of plastic and set to comparable scales as a well-sorted medium sized sand. Before each trial, the table is set to a uniform sediment thickness of 5 cm. The initial channel is always set to a width of 2.5 cm, and an initial depth of 4 cm. The flow rate of water into the table was always set to a constant 60 mL/sec. A total of 21 trials were done at 7 different slopes ranging from 2.0° to 3.50°. We used a Raspberry Pi camera to take still photos, from which we measured the sinuosity and width of the channel from these photos and compared to those of other slopes. Comparing the sinuosities and widths of the trials at different slopes can show how the change in slope affects the sinuosity and width of the channel. Our preliminary results suggest that as the slope of the stream increases the width will increase, and the sinuosity of the channel will decrease. These results could model what would be expected to happen in a real-world situation where the slope can change from processes like uplift, erosion, or baselevel change through a change in sea-level.
Abstract:
A Lake Ontario Watershed Study by Landon Vanalstine. A water budget study over the Lake Ontario basin examined the influence of precipitation, snow melt, evaporation, and river inflow/outflow on lake water levels over the period from 2000 to 2019.
Abstract:
Geologic Mapping of Glacial Debris at Rice Creek Field Station by Charles Chapman, Kathryn Ploss, Gabrielle Moro, Joshua Rampersad. The geologic study of the Rice Creek drumlin educational outreach was done with the community. Using the data provided by the geochemical and mineralogical analyses of rock samples taken from multiple sites across the drumlin, as well as previously collected geospatial and lithologic data on erratics on the drumlin, an interactive map will be developed for those hiking the trail so they can learn the geology through the trails. This project will be used, potentially, in local school systems to create field trips for students to better understand their local environments, and to provide a deeper understanding of geology. Educational outreach and gaining the interest of the general public and students with diverse backgrounds, which is important for the continued growth in science, as well as in the field of geology.
Abstract:
Petrographic Analysis of Glacial Debris at Rice Creek Field Station by Kathryn Ploss, Charles Chapman, Gabrielle Moro, Joshua Rampersad. This study of the Rice Creek Drumlin performs a statistical analysis of the glacial sediment at Rice Creek based on rock lithology and geochemistry. Rock samples were collected in different size fractions along the west side of the drumlin. These samples were then separated by lithology into clastics and crystalline rocks. The clastic were then further sorted into fossiliferous and non-fossiliferous, and the crystalline rocks were separated into igneous and metamorphic, and further sorted based on composition. A statistical analysis was conducted based on the breakdown of the groups, and compared to a previous analysis on the East side of the Drumlin to find if the drumlin was consistent in rock distribution. In order to better understand the composition of the igneous and metamorphic rocks, petrography was completed as well as EMP analysis to further understand the specific breakdown in the chemical components of the minerals. The compositional data will also be compared to the previous study of the East side of the Drumlin, and be used to correlate the crystalline rocks to the source rocks in the Canadian Shield.
Abstract:
QUANTIFYING THE GRAINSIZE OF CLASTICS IN LOWER SALT UNIT FROM SEARLES LAKE, CA: STEPS TOWARDS UNDERSTANDING PALEOCLIMATIC CHANGES by Hayley M. Mosher, Justin S. Stroup, James S. Coble, Richard A. Frieman, Kathleen M. Geary. Today, drought conditions are common in the Southwestern United States. However, this has not always been the case. Paleoclimate archives indicate many fluctuations from wet to dry conditions on time scales from centuries to millennia. The causes are well hypothesized, but distinguishing them and characterizing the spatial and temporal patterns of moisture balances in the larger region is best done with a network of continuous and high resolution paleoclimate records. One such location is Searles Lake, CA which is well known for containing a long and near complete record of deposition spanning the last ~3 Ma. In 2017, a new sediment core was collected from the surface of the dry lakebed to a depth of 76 meters. The core contains alternating layers of salt (evaporite minerals) and mud which generally indicate dry and wet conditions over the last ~150 ka. Prior work from Smith et al., 1979 and 2009 established the general stratigraphy of the basin. Here, we present grainsize data from six mud layers contained within the Lower Salt (~25-38 m depth). Samples were pretreated to disaggregate and isolate clastic grains and grain size was measured using a Beckman Coulter LS 13 320 particle size analyzer. Of the more than 100 samples analyzed, the dominant grain sizes range from 0.04 to 200µm. Within this range, we observe several characteristic grain size distributions within the units. From bottom to top the distributions are left skewed become more right skewed and then shift back to a left skew distribution. This implies coarsening and fining patterns. Interpreting these data with other pilot data that suggest finer grain sizes occur during wetter conditions and coarser grainsizes are found during dryer conditions. Our measurements, suggest fluctuations in lake levels occurred within the muds, indicating more variability then just the dominant alternations of salt and mud (dry and wet). Future work will include expansion of the grainsize record to the salt units and deeper in the stratigraphy. These data will be combined with other proxy data to provide a detailed depositional and climate history of the basin.
Summary:
Session Chair: Justin Stroup
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Collected for SUNY Oswego Institutional Repository by the online self-submittal tool. Submitted by Zach Vickery.

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A water budget study over the Lake Ontario basin examining the influence of precipitation, snow melt, evaporation, and river inflow/outflow on lake water levels over the period from 2000 to 2019. Yellow stars denote stream flow stations USGS 04216000 & 04264331 used in study. Ontario Watershed Perimeter https://www.sciencebase.gov/catalog/ item/530f8a0ee4b0e7e46bd300dd

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Daymet : Daily Surface Weather Data on a 1km Grid for North America, Version 3 https ://daac.ornl.gov /cgibin/dataset_lister.pl?p=32 Precipitation and snow meltSources of data: North American Regional Reanalysis Daily evaporation https://www.psl.noaa.gov/data/gridded/data.narr.html USGS St. Lawrence outflow https://waterdata.usgs.gov/nwis/dv?referred_module=sw&site_no=04264331 USGS Niagara River inflow https://waterdata.usgs.gov/nwis/dv?referred_module=sw&site_no=04216000 NOAA Daily Water Levels https://tidesandcurrents.noaa.gov/waterlevels.html?id=9052030

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The average Lake Ontario profile shown in yellow excludes the record breaking water level period from 2017 to 2019.Daily water levels at OSGN6 from 2000 to 20192019 2017

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National Data Buoy Center’s OSGN6 site at the mouth of the Oswego River.2018 2019 2017 2016 2015 2014 2012 2013 2011 2010 2009 2008 2006 2007 2004 2005 2001 2002 2003 2000 Top five peaks in the Lake Ontario water level are 2019, 2017, 2011, 2002, and 2008. 249.07, 248.93, 247.38, 247.19, and 247.18 feet Average peak day is day 150. Top five greatest rises of water levels are 2017, 2019, 2008, 2011, and 2013 4.83, 4.52, 3.63, 3.40, and 3.22 feetOSGN6 Water Levels from 2000 to 2019 IJC regulation of water levels began on 2014.

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f swe : snow water melt over land evap : evaporation over lake Lake Ontario Water Basin Budget Equation used in study. rivers : river inflow from another basin (Niagara River) and river outflow (St. Lawrence River) precip : precipitation over basin (includes precip over lake) Sources:Sinks:Units: kgfis the fractional amount of precip+swe reaching the lake. Determined from the residual. actual change in the water level over period of interest

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precip: precipitation over basin swe : snow water melt over land Niag: Niagara River inflow StL: St. Lawrence River outflow All: precip+swe+Niag+StL+evap evap: evaporation over lake No apparent evidence for record breaking years of 2017 & 2019.

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Yellow highlight indicates the top five greatest rises of water levels. Precip. + SWE correlates positively to water level change. No apparent evidence for record breaking years of 2017 & 2019. On a yearly average, 60% of Precip & SWE reaches the lake.

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precip: precipitation over basin swe : snow water melt over land Niag: Niagara River inflow StL: St. Lawrence River outflow All: precip+swe+Niag+StL+evap evap: evaporation over lake Clear evidence for record breaking years of 2017 & 2019. Higher than normal precip+swe along with lower than normal Niag+StL (inflow/outflow) High water levels also occurred in 2011 & 2008.

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Clear evidence for record breaking years of 2017 & 2019. day 30 to day 150Accumulated water mass Units: kgBalance pslakeResidualBudgetModifiedLake waterRankYearprecipsweevapNiagSt. LawNiag+StLawp + sTotal%(p+s) f(p + s)kg change 20002.33E+138.02E+12-1.66E+115.38E+13-6.38E+13-1.00E+133.13E+132.12E+1371.82.25E+131.23E+1320011.78E+136.93E+12-2.21E+115.51E+13-6.75E+13-1.25E+132.47E+131.20E+1377.91.92E+136.57E+1220022.59E+135.28E+12-2.56E+116.04E+13-7.22E+13-1.19E+133.12E+131.91E+1367.92.12E+139.09E+1220032.12E+139.14E+12-3.41E+115.34E+13-6.16E+13-8.18E+123.04E+132.18E+1375.72.30E+131.45E+1320042.17E+137.61E+12-2.86E+115.74E+13-7.51E+13-1.78E+132.93E+131.12E+1388.62.59E+137.89E+1220051.64E+137.23E+12-3.19E+116.35E+13-8.10E+13-1.75E+132.36E+135.78E+1291.32.16E+133.74E+1220061.74E+133.69E+12-4.30E+115.93E+13-7.54E+13-1.60E+132.11E+134.58E+1283.91.77E+131.20E+1220071.69E+137.96E+12-5.41E+116.14E+13-8.19E+13-2.05E+132.49E+133.86E+12101.52.52E+134.23E+12420082.34E+139.52E+12-3.82E+116.14E+13-7.76E+13-1.62E+133.29E+131.63E+1371.72.36E+136.98E+1220092.21E+137.00E+12-3.08E+116.30E+13-8.09E+13-1.79E+132.91E+131.09E+1381.12.36E+135.42E+1220101.41E+133.25E+12-2.69E+115.75E+13-7.01E+13-1.26E+131.74E+134.55E+12102.81.79E+135.04E+12320113.01E+138.00E+12-3.43E+115.94E+13-7.44E+13-1.51E+133.81E+132.27E+1381.83.12E+131.58E+1320121.40E+134.25E+12-3.65E+116.41E+13-8.06E+13-1.65E+131.82E+131.33E+1284.31.54E+13-1.53E+12520132.03E+136.57E+12-4.88E+115.65E+13-6.66E+13-1.01E+132.68E+131.62E+1367.81.82E+137.60E+1220142.24E+138.03E+12-4.05E+115.91E+13-7.48E+13-1.57E+133.04E+131.43E+1392.72.82E+131.21E+1320151.57E+138.40E+12-4.39E+116.01E+13-6.86E+13-8.50E+122.41E+131.51E+1372.51.75E+138.52E+1220161.93E+137.30E+12-4.17E+116.84E+13-8.26E+13-1.42E+132.66E+131.20E+1362.41.66E+131.96E+12220173.04E+136.24E+12-4.22E+117.12E+13-7.97E+13-8.46E+123.66E+132.77E+1367.32.46E+131.57E+1320182.11E+136.88E+12-3.68E+117.34E+13-9.06E+13-1.71E+132.80E+131.05E+1381.62.28E+135.33E+12120192.50E+138.62E+12-4.37E+117.46E+13-8.33E+13-8.60E+123.36E+132.46E+1378.02.62E+131.71E+13average2.09E+137.00E+12-3.60E+116.16E+13-7.54E+13-1.38E+132.79E+131.38E+1380.12.21E+137.98E+12 std. dev 4.68E+121.72E+129.23E+106.13E+127.43E+123.81E+125.54E+127.51E+1211.24.18E+125.20E+12p + sp + s f (p + s)%(p + s)N + St Total WLWLWLWL correlation0.870.810.69-0.250.61 r20.760.660.480.060.37 Rivers Precip. + SWE correlates positively to water level change. The late winter spring average, 80% of Precip & SWE reaches the lake. Higher than normal precip+swe along with lower than normal outflow from Niag+StL (inflow/outflow)

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Higher than normal precip+swe along with higher than normal Niagara River inflow contributed to the record breaking years of 2017 and 2019. Lake Erie reached record water heights in 2019. As previous studies have shown, Precip+SWE or runoff correlates positively to water level change. High (low) Precip+SWE amounts show a relationship to high (low) water heights wl.Summary:On a yearly average, runoff is ~60% of Precip & SWE. Late winter and spring runoff is ~80% of Precip & SWE due to the realization of SWE and the dormancy of vegetation.

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Further research: Incorporate other data sets, e.g. SNODAS snow data, recently released Daymet data set version 4, and numerical model data, into study as a quality check on the robustness of the data analysis and statistical significance of the results.

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References: •Baijnath Rodino, J. A., Duquay C., 2018,:Historical Spatiotemporal Trends in Snowfall Extremes over Canadian Domain of the Great Lake Basins. Advances in Meteorology, 2018, 1 20.•Fortin, V and A.D. Gronewold , 2012, Encyclopedia of Lakes and Reservoirs Water Balance of the Laurentian Great Lakes, Springer, 864 869.•Quinn, F. H ., 2002: Secular Changes in Great Lakes Water Level Seasonal Cycles. J. Great Lakes Res ., 28, 451– 465•Suriana, Z. J., and Leathers, D., 2016: Twenty first century snowfall projections within the eastern Great Lakes region: detecting the presence of a lake induced snowfall signal in GCMs, Int. J. of Climatology, 36, 22002209. •https ://eos.org/articles/what caused the ongoing flooding on lake ontario•https://ijc.org/en/popular issues/water levels andflows•https://ijc.org/en/loslrb/watershed/causes2019high water event

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Supplement: Average monthly net basin supply (NBS) and NBS components for the North American Laurentian Great Lakes, averaged over the period 19482008. (ENCYCLOPEDIA of LAKES AND RESERVOIRS, Water Balance of the Laurentian Great Lakes) R: runoff, P: Over the lake precipitation, E: evaporation off lake.