Timmons, Jeffrey Scott, MS MAY 2021

Timmons, Jeffrey Scott, M.S. MAY 2021 GEOLOGY

Identifying the Isotopic Signature of Lake Effect Precipitation on the Northeast Ohio Isoscape (126 pp.)

Thesis Advisor: Anne J. Jefferson

Lake effect precipitation occurs when cold air moves across an open body of warm water and water vapor from the lake rises through the air column, causing instability, which leads to precipitation predominantly downwind. The isotopes of hydrogen in water are less sensitive than oxygen isotopes to the kinetic fractionation that occurs during lake evaporation, resulting in a greater than normal excess of deuterium in lake effect or recycled precipitation. A water isoscape shows the spatial distribution of stable water isotopes and, in this study, I studied the isoscape of northeast Ohio to discern where lake effect precipitation affects groundwater and lake hydrology.

I investigated a 10,000 km2 area in northeastern Ohio, where mean annual precipitation ranges from 900-1100 mm and winter snowfall varies from 800 to 2500 mm. Relief in the study area is <200 m.

Higher elevation areas near Lake Erie form the primary snowbelt, and the surrounding areas make up the secondary snowbelt. The study area is underlain by glacial deposits and sedimentary rocks.

From 13 December 2017 to 22 December 2018, precipitation was collected at 2 locations 50 km apart. One precipitation collector was in the primary snowbelt at Holden Arboretum in Kirtland, while the other precipitation collector was in the secondary snowbelt in Kent. Lake samples were collected from 30 lakes across the study area in May, July and September 2018. Groundwater samples were collected from 47 private wells during 2 sampling events in January and July 2018. River samples were collected from 7 rivers during May, July and September 2018. Twelve groundwater and surface water locations were sampled biweekly along a transect from Kent to Kirtland. All water samples were analyzed for δ18O and δ2H with a Picarro L2130-i.

Precipitation in the primary and secondary snowbelts are isotopically similar, but during the winter there is clear indication of storms reaching one area but not both. Precipitation has marked inter- storm isotopic variability, particularly in the winter. Two-week weighted averages reflect this variability, somewhat masking the typical sinusoidal seasonal signal. The average annual precipitation for Holden has δ18O of -9.3‰ and δ2H of -60.6‰. The Kent, average annual precipitation has δ18O of -9.3‰ and δ2H of -59.9‰. The 2-week isotopic values for δ18O ranged from -19.5‰ to -3.4‰ and the δ2H ranged from -

140.9‰ to -15.0‰. The local meteoric water line (LMWL) was calculated from the precipitation samples

δ2H =7.79 δ18O +11.42. The LMWL slope is similar to the global meteoric water line, but the d-excess is greater, indicating that precipitation is recycled.

Groundwater δ18O varies by more than 6‰ across the study area (-10.45 to -3.21‰), with the most depleted ground waters occurring in the high elevation, primary snowbelt. D-excess ranged from

-6.0‰ to 15.7‰, with 72% of wells (34) having a d-excess value greater than 10.0‰ and 26% of wells

(12) having an evaporative signature in January.

Lake water isotopes reflect an evaporative signature that does not provide clear evidence for precipitation recycling. The range of d-excess values for lakes 13.0‰ to -12.1‰, with 6 of 30 lakes showing a recycled isotopic signature in May and only 3 in September. Only four of the lakes showed a progressive evaporative enrichment over the summer. Evaporation to inflow ratios ranged from -0.206 to 0.083.

IDENTIFYING THE ISOTOPIC SIGNATURE OF LAKE EFFECT PRECIPITATION

ON THE NORTHEAST OHIO ISOSCAPE

A thesis submitted to the faculty of

Kent State University in partial fulfillment

of requirements for the degree of

Master of Science in Geology

May 2021

Jeffrey S. Timmons

Except for previously published materials

Thesis written by

Jeffrey S. Timmons

B.S., Kent State University, 2017

M.S., Kent State University, 2021

Approved by

______, Advisor Anne Jefferson

______, Chair, Department of Geology Daniel Holm

______, Interim Dean, College of Arts and Sciences Mandy Munro-Stasiuk Table of Contents

TABLE OF CONTENTS ------v

LIST OF FIGURES ------vii

LIST OF TABLES ------x

ACKNOWLEDGMENTS ------xi

CHAPTERS

Introduction ------1

Methods ------10

Sample collection ------10

Precipitation ------10

Groundwater ------12

Lakes ------12

Transect water samples ------13

Rivers ------14

Stable Isotope analyses ------14

Evaporation to inflow ratios for lakes ------15

Results ------18

Distribution of sampling locations and northeast Ohio sub-regions ------18

Precipitation ------18

Precipitation and snowfall ------18

Precipitation Isotopes ------22

Groundwater ------28

Lithology, surface elevation and well depths ------28

Groundwater Isotopes ------30

Groundwater d-excess ------37

Lake ------43

Seasonal variability ------43

Lake Characteristics ------46

Lake Isotopes ------47

Lake d-excess and relationship with groundwater ------54

Trends over time within regions ------58

Evaporation to inflow ratios ------67

Discussion ------73

Identifying the lake effect signature on the precipitation isoscape ------73

Identifying the lake effect signature on the groundwater isoscape ------74

Identifying the lake effect signature in the lake samples ------77

Testing the hypotheses ------79

Conclusion ------81

Directions for future research ------82

REFERENCES ------83

APPENDICES

A. [River data, graphs and maps] ------86

B. [Transect data]------96

C. [All isotope data with sampling location]------105

LIST OF FIGURES

Figure 1. shows the locations of precipitation, groundwater, and lake sampling locations, with respect to county boundaries and identified sub-regions. ------18

Figure 2. Daily precipitation amount (mm) from the closest NOAA observer stations to each collection location: the Chardon NOAA observer station for Holden and Twin Lake Kent NOAA observer station for Kent comparison.------20

Figure 3. Two-week precipitation total amounts collected at each location, corresponding to the 2-week sampling interval at Holden, the daily amounts were added together for the Kent location. ---- 21

Figure 4. Daily amount of snowfall that occurred at each location based on cooperative observer data -22

Figure 5. Kent daily and two-week weighted average δ18O. ------23

Figure 6. Two-week weighted average precipitation δ18O for Kent and Holden. We see an increase in the variability in the summer between the two locations. ------25

Figure 7. Figure 7. Precipitation δ18O and δ2H for Holden and Kent, color coded by each approx. three- month season, with winter as Dec 13th to April 1st, spring from April 1st to June 23rd, summer from June 23rd to September 16th, and fall from September 16th to December 22nd. These seasonal start and end dates were chosen to align with the dates of precipitation collection at Holden. ------25

Figure 8. Amount-weighted average precipitation isotopes per season for both locations; each approx. three-month season with winter as Dec 13th to April 1st, spring from April 1st to June 23rd, summer from June 23rd to September 16th, and fall from September 16th to December 22nd. These seasonal start and end dates were chosen to align with the dates of precipitation collection at Holden. - 27

Figure 9. The LMWL (green Line) from two-week precipitation data collected at Holden and Kent. The GMWL (black Line) has an intercept (d-excess) of 10‰ and the LMWL has an intercept 11‰.-- 27

Figure 10. Shows the relationship between the δ2H and δ18O for the January and July groundwater sampling events. The black line is the LMWL and the red line shows the linear trend for the entire groundwater data set, with the equation shown in the red box. ------31

Figure 11. δ18O (‰) for the groundwater sampling in January. ------33

vii

Figure 12. δ18O (‰) for the groundwater sampling in July. ------34

Figure 13. Difference in the δ18O (‰) between the two sampling events. Positive differences represent wells that were more negative in July than January. Negative differences are wells that were less negative in July than January. ------35

Figure 14. Relationship between the δ18O and d-excess of well water samples in January. ------38

Figure 15. Relationship between d-excess in the January GW sampling and well depth. ------39

Figure 16. Groundwater wells showing the January d-excess (‰). High d-excess represents recycled

precipitation. ------39

Figure 17. January d-excess relative to the elevation of the wells in each region. ------40

Figure 18. Relationship between the δ18O and d-excess of well water samples in July. ------41

Figure 19. shows the d-excess difference between January and July sampling events. The red and light blue dots are the major changes that shifted either to the negative or the positive respectively.

------42

Figure 20. Wells with the biggest d-excess changes between January and July also experienced the largest δ18O changes, because you can’t change the d-excess without changing the δ18O or the δ2H. ------43

Figure 21. δ18O and δ2H relationship for the three lakes from the transect collections. The red line is the Local Meteoric Water Line (LMWL), and the best fit lines show the samples variability across the study area. The range of the precipitation at Kent and Holden from both collection locations was δ18O of -17.4‰ to -3.4‰ and δ2H of -125.7‰ to -15.7‰. ------44

Figure 22. Variability of the δ18O over the year of sampling the transect locations. The triangular points are the dates I collected the survey lakes. The sampling began in January, but several locations were frozen at times, resulting in missing data points. The range of the precipitation δ18O was - 17.4‰ to -3.4‰ over the same period. ------46

Figure 23. The δ18O and δ2H of all the lake samples coded by date. The LMWL is the red line. ------48

Figure 24. δ18O and δ2H of all three rounds of samples coded by region. ------49

viii

Figure 25. September samples color coded by region show that, by September, most of the lakes are evaporative. ------50

Figure 26. δ18O (‰) for each of the May lake samples. These are the starting values that are used later to calculate E:I ratios. ------51

Figure 27. δ18O (‰) for the July lake samples. ------52

Figure 28. September δ18O (‰) values for surveyed lakes. ------53

Figure 29. May d-excess for surveyed lakes.------55

Figure 30. September d-excess. We see more of the lakes are showing a low d-excess value caused by the evaporation over the summer months.------56

Figure 31. July lake and groundwater d-excess color coded by region. Region 2 clusters to the far right and Region 5 has a small range for the lake values. The lines divide the lakes by d-excess values and whether the isotopic signature is recycled, normal, evaporative and very evaporative. ------58

Figure 32. Region 1 lakes (A) δ18O values and (B) d-excess over time. ------60

Figure 33. Region 2 lakes (A) δ18O values and (B) d-excess over time. ------62

Figure 34. Region 4 lakes (A) δ18O values and (B) d-excess over time. ------64

Figure 35. Region 5 lakes (A) δ18O values and (B) d-excess over time. ------66

Figure 36. E:I ratios for May-July (July), July-September (Sept) and May-September (total) compared to d- excess values at the end of each interval. We can see that most of the September samples are positively evaporative and approx. half the July lakes are not yet evaporative. ------68

Figure 37. E:I from the two summer periods, color coded by region. ------69

Figure 38. compares the lake depth vs. E:I ratios. Only lakes with actual depths were used. ------70

Figure 39. July-September E:I ratios for each lake. All negative ratios are red to show they are not evaporative. 258 is Pawpaw Lake and 11 is Mantua Bog. ------71

Figure 40. July to September E:I versus the lake area (km2).------71

Figure 41. July to September E:I vs. the lake area to drainage area ratio. ------72

LIST OF TABLES

Table 1. precipitation amounts collected and observed at both collection locations, compared to the closest NOAA cooperative observer stations. Snow depth and number of events is derived from the cooperative observer data. The total amounts are broken down for each three-month astronomical season, with winter as Jan 1st to April 1st, spring from April 1st to June 23rd, summer from June 23rd to September 16th, and fall from September 16th to December 22nd. ------19

Table 2. δ18O ‰ and the δ2H ‰ for Kent daily and two-week weighted precipitation values ------22

Table 3. δ18O and δ2H Weighted average minimum, maximum and mean at both precipitation locations.

------24

Table 4. number of wells, elevation range, average elevation, depth range and average depth for each of the five regions in the study. ------29

Table 5. shows the isotopic range and average for each region for the January and July sampling. ------32

Table 6. the breakdown of the number of lakes, range of lake areas, mean lake area, lake depths, drainage area and lake area to drainage area inverse ratios. ------47

Table 7. δ18O mean, median, minimum, maximum, and range for each of the lake surveys. ------48

Table 8 shows the correlation results for the lakes isotopes and d-excess. ------57

Table 9. mean, median, min, max and range for the δ18O and the d-excess for Region 1. ------61

Table 10. has the mean, median, min, max and range for the δ18O and the d-excess for Region 2. ------61

Table 11 δ18O and d-excess for Lake Roaming Rock (241) in Region 3. ------63

Table 12. has the mean, median, min, max and range for the δ18O and the d-excess for Region 4. ------63

Table 13. has the mean, median, min, max and range for the δ18O and the d-excess for Region 5.------64

Acknowledgements

I want to say thank you to my advisor, Anne J. Jefferson, without whom this would not have been possible. Thanks to my committee members for taking the time to be a part of the biggest accomplishment of my life. To Catherin Lyons, my VA vocational rehabilitation counselor, thank you for believing in me when the system said not to. This work was supported by a Geological Society of

America student research grant and the Katherine Moulton Award from the Department of Geology at

Kent State. Thanks to Holden Arboretum for allowing sample collection in the Snowbelt. Thank you to my family for all the love and support.

Introduction

Water isotopes are the ideal tracers of the hydrologic cycle because they are the water itself

(Bruckner, 2017), but fractionate during phase changes, allowing hydrologists to infer the history and provenance of the water (Kendall and Doctor, 2004). The isotopic composition of precipitation in an area is closely linked to the origin of the moisture, season, altitude, latitude, lake evaporation, and continentality (Bowen and Revenaugh, 2003). The precipitation in turn affects surface water and groundwater isotopes, leading to the spatial and temporal variability that enables them to be used as tracers (Clark and Fritz, 1997).

Hydrologist have used isotopes since the 1960’s for various purposes, including separating hydrographs into pre-event vs. event water, quantifying evaporation from water bodies, and constraining watershed transit time (Clark and Fritz, 1997). Water isotopes can also be used for dating groundwater and indicating potential recharge locations of groundwater. For example, Bohlke and

Denver (1995), used radioactive tritium (3H) isotopes in their study to help determine the age of groundwater with respect to nitrate contamination in agricultural watersheds. As another example,

Cowie (2014) showed that water isotopes can give information about precipitation inputs into subsurface mine workings, affecting the choice of remediation approach.

The isotopes of an individual element differ in the number of neutrons, but not the number of protons that the nucleus contains. The difference in mass affects the rates at which different isotopes

1 are affected by physical and chemical processes. Most of the elements in the periodic table have at least two or more naturally occurring isotopes, except for 21 elements that are monoisotopic (only one isotope). The proton is the part of the atom that defines the element, and the number of neutrons determines the isotope that forms. For example, 99.76% of oxygen (O) atoms have an atomic mass of 16

(16O), made up of 8 protons with 8 neutrons, and 0.2% of oxygen atoms have 8 protons with 10 neutrons with an atomic mass of 18 (18O), while an even smaller fraction of O atoms have a mass of 17 (Clark and

Fritz, 1997) . The isotopes that form as unstable or radioactive nuclides have a specific probability of decay over time, known as a half-life. In contrast, stable isotopes do not decay over time. Hydrogen forms three isotopes protium (1H), deuterium (2H), and tritium (3H). All three are naturally occurring, but two are stable and the third one tritium, is unstable (radioactive). Protium has one proton, one electron, and zero neutrons, giving it a mass of 1. Deuterium has one proton, one electron, and one neutron giving it a mass of 2. Tritium has one proton and 2 neutrons giving it a mass of 3. When a nuclide of a low mass element exceeds a ratio of ~ 1.5:1 (neutron: proton), it is more likely to be unstable. Tritium is the unstable hydrogen isotope, with a 2:1 neutron to proton ratio.

Stable isotopic composition of light elements like oxygen and hydrogen are typically reported as delta (δ) values. “δ” values are reported in units of parts per thousand (‰ or per mil) relative to a standard of known composition (Kendall and Caldwell, 1998). To calculate δ values, the formula δ (in ‰)

18 16 = (RX / RS-1)*1000 where R is the ratio of the heavy to light isotope (e.g., O/ O) and RX and RS are ratios of the samples and standards respectively. Vienna Standard Mean Ocean Water (VSMOW) is the reference standard that is used to compare the isotopic ratios for both oxygen and hydrogen. A positive

δ value indicates the isotopic ratio of the sample is higher than the standard and a negative δ value means the ratio of the sample is lower than that of the standard. The average terrestrial abundance ratio of heavy to light isotopes for oxygen is 1:500, and the ratio for hydrogen is much lower at 1:6410

(Kendall and McDonnell, 1998).

Mass differences of isotopes affect bond strength, causing them to move through phase changes differently, in a process called fractionation. As an isotope begins to change from one phase to another, the weakest bonds are broken first, and the stronger bonds hold together. This allows for the exchange between heavy and light isotopes to take place. This process alters the proportions of the stable isotopes in the compound and is known as the mass-dependent isotope fractionation effect

(Kendall and McDonnell, 1998). As the fractionation process occurs, a unique isotopic signature is created by altering the ratio of the heavy and light isotopes contained within the compound or water source. For water, fractionation occurs naturally during evaporation and condensation. The lighter isotopes evaporate in a preferential manner while heavier isotopes condense into precipitation advantageously to light isotopes (Bruckner, 2017). Similarly, melting and freezing of water causes fractionation.

In 1880, Lord Rayleigh derived the Rayleigh equation for the fractional distillation of mixed liquids. He described the exponential relationship of the partitioning isotopes between two reservoirs as one decreases in size. This equation is used to describe the isotope fractionation process if three conditions are met. First, material is continuously removed from a mixed system containing molecules of two or more isotopic species (e.g., water with 18O and 16O). Second, the fractionation accompanying the removal process at any instance is described by the fractionation factor (α), and third α does not change

α-1 during the process. The Rayleigh equation is written as: (R / Ro) = (Xi / Xio) where R = ratio of the

18 16 isotopes (e.g., O/ O) in the reactant, Ro = initial ratio, Xi = the concentration or amount of the more

16 abundant (lighter) isotope (e.g., O), Xio = initial concentration of the more abundant isotope. Because the concentration of Xi >> Xh, Xi is approximately equal to the amount of original material in phase, if Xh is the less abundant (heavy) isotope. The equilibrium fractionation factors (αl-v) for the water from liquid to vapor phase transition are 1.0098 and 1.084 at 20°C and 1.0117 and 1.111 at 0°C for 18O and 2H, respectively (Majoube, 1971). In both instances, αl-v > 1, which means that the liquid phase is heavier

18 18 than the vapor phase (e.g., for αl-v = 1.0098, the δ O of water is +9.8‰ higher than the δ O value of vapor at equilibrium). For solid ice to liquid water transition (0°C), the values are 1.0035l and 1.0208v, for

18O and 2H, respectively (Arnason, 1969). Hai-ying et al. (2009), showed that the δ18O and δ2H are proportional to temperature, but when temperature is constant the δ2H is larger than the δ18O. This indicates that δ2H is more sensitive to temperature differences than δ18O. This relationship underpins the observations of precipitation that Craig (1961) used to define global meteoric water line (GMWL).

The GMWL is defined as δ2H = 8 * δ18O + 10. The slope of 8 is the approximate value produced by

Rayleigh’s equilibrium condensation of rain at 100% humidity and the y intercept of 10 is the deuterium excess (d-excess) value.

There are two main ways that isotopic fractionation occurs: equilibrium fractionation and kinetic processes. Both are important in the water cycle. During isotopic equilibrium, the forward and backward reaction rate of a given isotope is the same. This means that the isotopic composition of two compounds have ratios that are constant at a given temperature but not identical to one another. As phase changes occur, the ratio of heavy to light isotopes in the molecule change in the given phases. For example, as water evaporates the light isotopes become enriched in the vapor phase (16O and 1H), while the heavier isotopes enrich the remaining water (18O and 2H) in the liquid phase. This equilibrium exchange reaction between two given substances (liquid and vapor) uses the fractionation factor (α) from the Rayleigh equation: α l-v = Rl /Rv where R = the ratio of the heavy isotope to the light isotope

(2H/H, 18O/16O) in the compound’s liquid and vapor (Kendal and McDonnell, 1998).

Another way that isotopes fractionate is through kinetic processes. Kinetic fractionation occurs as stable isotopes are separated from each other by their mass during unidirectional processes that are fast and incomplete. Kinetic fractionation occurs when liquid water evaporates. Isotopically lighter water molecules (16O) will evaporate slightly more easily than will the isotopically heavier water molecules with 18O, and this difference will be greater than it would be if the evaporation was taking

4 place under equilibrium conditions with bidirectional processes. The atmosphere becomes enriched in

16O, and the liquid water is enriched in 18O. Equilibrium fractionation causes the vapor to become about

10‰ (1%) depleted in 18O relative to the liquid water, kinetic fractionation increases the fractionation effect and often makes the vapor 15‰ depleted. Condensation happens almost entirely by equilibrium processes; it enriches cloud droplets slightly less than evaporation depletes the vapor (Kendall, 2004).

Because of this, rainwater is isotopically lighter than its source liquid water.

The isotopes of hydrogen in water are far less sensitive to kinetic fractionation than oxygen isotopes, compared to the equilibrium fractionation factor of 2H/1H. Kinetic fractionation does not deplete 2H as much as 18O. This causes an excess of deuterium in vapor and rainfall, in relationship to seawater. The deuterium excess value is about +10‰ in meteoric waters and the non-zero value is directly related to kinetic isotope fractionation. Deuterium excess (d) is defined as d= δ2H-8* δ18O, deriving from the Global Meteoric Water Line equation (Craig, 1961).

Stable isotopes of precipitation (δ2H and δ18O) are informative, but the deuterium excess (d- excess = δ2H − 8 × δ18O) can be utilized to further constrain temporal and spatial variations of the hydrological process and hydroclimatic conditions (Dansgaard, 1964). The d-excess is less variable because co-variation of δ2H and δ18O is eliminated and it is more sensitive to the kinetic fractionation processes (Guan et. al., 2013).

The deuterium excess is used to identify source regions of water vapor (Dansgaard, 1964).

Winter precipitation originating from the Gulf of Mexico is characterized by distinctly higher deuterium excess values than precipitation that originated in the Arctic, reflecting the specific source conditions during water vapor formation (Tian et al., 2018).

Increased deuterium excess in precipitation can also come from significant re-evaporation of moisture from continental basins (e.g., the Great Lakes) (Bowen, et.al., 2012). If moisture from

1 16 precipitation with an average excess of 10‰ is re-evaporated, the lighter H2 O molecule may re- contribute preferentially to the isotopic composition of the water vapor, which ultimately leads to deuterium (2H) enriched precipitation (Bowen, et.al., 2012). Winter precipitation that forms over the

Great Lakes region is categorized by distinctly higher d-excess values, reminiscent of the source conditions during formation of the water vapor (Tian. et al., 2018).

Variation in the isotopes in precipitation occurs because of several factors, including the source of the moisture. Seasonality also affects precipitation isotopes (Li et.al., 2017). We expect to see an isotopically lighter, more depleted, signature for snow and winter precipitation and an isotopically heavier, more enriched, signature for rain and summer precipitation (Rozanski, et al., 1993). The latitude of the area where precipitation occurs also controls the isotopic composition of the water, and this is known as latitude effect (Clark and Fritz, 1997). Continentality effect influences isotopic composition because the greater the distance the air mass travels from source to inland storm events, the more likely that rain will be lighter due to the rain out of heavier isotopes from multiple storm events (Gat, 2000). Within a single storm, the amount effect indicates that the lighter isotope ratios occur later in the storm (Clark and Fritz, 1997).

In the Great Lakes region, an interesting hydrologic phenomenon is lake effect precipitation.

Lake effect precipitation occurs when cold air moves across an open body of warm water and mixes, causing instability which leads to lake effect precipitation predominantly downwind (Cipullo et al, 2011).

This type of weather occurs in certain areas where a long fetch over an open warm water body provides the moisture that increases convection coupled with uniform wind direction and minimal shear (Cipullo, et al, 2011). The south and east side of Lake Erie can be affected by lake effect precipitation (Schmidlin,

1989). Another factor to consider is lake ice and how it affects the amount of recycled water that is expected from lake effect precipitation. Lake effect precipitation is heavily dependent on the temperature difference between the air and water surface. When ice covers the lake, the temperature

6 difference is reduced and the amount of lake effect precipitation is reduced (Burnett et al., 2003). Lake effect precipitation can have strong impacts on soil development, nutrient cycling, and groundwater recharge that affects regional ecosystems (Schaetzl, 2005; Stottlemyer & Toczydlowski, 1995). A secondary moisture flux from lake evaporation changes d-excess values in downwind precipitation

(Bowen, et.al., 2012), as described above.

For lentic water bodies, evaporation to inflow (E:I) ratios integrate many important climate drivers, like precipitation, evaporation and hydrological processes such as groundwater inflow, lake discharge and catchment runoff. All of these processes can influence the biological and geochemical processes that occur within lakes to alter the concentrations of solutes like carbon, nitrogen and phosphorus (Fraterrigo and Downing 2008). Changes in the hydrological cycling of lakes that drive E: I can also have intense effects on carbon and nitrogen budgets (Cardille et al. 2009, Jeppesen et al. 2011).

A change in the quantity of lake inflow that leaves as evaporation shows the evaporative effects of concentrating solutes and reflects the lake energy balance that influences the internal biological nutrient process. E:I ratios will also affect the water isotopes in the lake (Brooks, et. al., 2014).

Interest in spatial variation of water isotopes has led scientists to view the landscape through isotopes, which has led to the creation of water isoscapes. A water isoscape is a spatially explicit prediction about the stable isotopic composition of water used to create a map of the landscape.

Isoscapes are often established at state, continental, or global scales. Such isoscapes are helpful to document and visualize large-scale hydrologic patterns (Hurley et al, 2010). However, a small-scale

(<10,000 km2) isoscape will allow for significantly more data points in a confined area to establish greater precision when identifying variation in hydrologic processes or applying isotopic data to other disciplines. For example, stable isotope ratios are used by a variety of different fields including ecology and law enforcement, and isoscapes can help with such applications. Kennedy et al. (2011) showed that stable isotopes can be used to identify where humans grew up on a continental scale and Hurley et al.

(2010) used stable isotopes to track illegal packages of marijuana and where they were grown. Both studies were done on a continental scale but lacked the ability to pinpoint exact locations. Small-scale isoscapes may also be useful to identify variation that cannot be associated with continental scale processes.

In the Great Lakes region, several studies have used isoscapes and identified the isotopic effects of lake effect precipitation. Gat et. al. (1994) compared the d-excess of the lake water from across the

Great Lakes region to the d-excess of precipitation in the same region to determine that up to 15% of the precipitation was recycled moisture from the Great Lakes. Bowen et. al. (2012) examined groundwater isotopes in western Michigan to determine the d-excess of precipitation that occurred downwind from Lake Michigan. They were able to estimate that up to 32% of recharge in individual aquifers is derived from recycled Lake Michigan water, and 10% to 18% of the evaporated water vapor is reprecipitated into the downwind Lake Michigan drainage basin (Bowen et al., 2012).

In the wintertime, northeast Ohio (NEO) receives lake effect precipitation in a primary snowbelt, surrounded by a secondary snowbelt. The primary snowbelt stretches from east of Cleveland towards

Erie, Pennsylvania and includes all of Geauga and most of Ashtabula Counties, as well as the northern parts of Portage and Trumbull Counties and small portions of Cuyahoga and Summit Counties. The secondary snowbelt includes the rest of Cuyahoga, Summit, Portage, and Trumbull Counties, as well as

Lake, Medina, and Mahoning Counties (Team, 2016).

Kirtland, Ohio is the heart of primary snowbelt, receiving an average of 1680 mm of snow and

1250 mm of total precipitation per year (National Centers for Environmental Information (NCEI), 2018).

South of the primary snowbelt, in the secondary zone, Kent, Ohio receives 1250 mm of snow and 1140 mm (NCEI, 2018) of total precipitation per year (Figure 1).

The overall goal of my research is to identify the isotopic signature of lake effect precipitation across a nine-county region in northeast Ohio, in precipitation, surface water, and groundwater. Both inside and outside the Snow Belt, I expect to see a more isotopically depleted signature for snow and a heavier, more enriched signature for rain, because of the temperature-dependent fractionation discussed earlier. I hypothesize that this will lead to an overall more isotopically depleted signature of precipitation in Kirtland. I further hypothesize that the isotopic signature from the lake effect precipitation is enough to identify areas where groundwater recharge and discharge to surface water is affected by the lake effect. However, I also hypothesize that there will be regional variability in surface water and groundwater isotopes that cannot be explained by lake effect processes.

Methods

Sample collection

Precipitation

Precipitation samples were collected for isotopic analysis at two locations: within the primary snowbelt, at The Holden Arboretum in Kirkland, Ohio; and in Kent, Ohio, in the secondary snowbelt. The precipitation collector for the Holden location was installed 12/13/2017 and was collected bi-weekly, starting 12/29/2017 while, in Kent, precipitation was collected daily from 12/13/2017 to 12/22/2018.

The Palmex Rain Sampler (RS1) precipitation collector was used at The Holden Arboretum to collect bi-weekly samples for one year, totaling 26 samples. The RS1 was designed to be oil free and evaporation free and to require minimal maintenance. The precipitation enters the collector through a funnel (with bird guard), passes through the stainless-steel mesh (to prevent dirt and debris from clogging the intake tube) into the intake tube and a 3-liter plastic jug. As the jug fills with water, the bottom of the intake tube is under water (allowing water to enter and not allowing evaporation). The

RS1 was mounted to a 1.2 m tall post in an open field inside the Holden Arboretum. The distance from the collector to the tree line was a minimum of 300 m in all directions. During the winter months, a stove pipe extension was added to the top of the collector to facilitate the additional volume of snow that could be collected before melting into the collector. Precipitation volume was measured at the time of collection using a graduated cylinder. If snow was present at time of collection or if the precipitation

10 sample was frozen in the jug, it was taken back to the Watershed Hydrology lab at Kent State University and allowed to completely melt in the refrigerator before it was measured, filtered and collected.

In Kent, daily precipitation was collected in a standard 4-inch (10 cm) rain gauge in a clearing between a house and wooded area. Precipitation was collected each morning at 8:00 am from the previous 24-hour period, when rainfall depths exceeded 0.1 inch (0.254 cm).

At both locations, a 20 ml sample of precipitation was syringe-filtered at the time of collection with a 0.7 μm GFF filter. A 20 ml borosilicate glass vial was filled to the top and sealed with a poly-seal lined cap with conical insert. Each sample was labeled with a unique code that identified where and when the sample was collected. The samples were then transported to the Watershed Hydrology lab and refrigerated until analyzed.

Precipitation depths from the collection locations were compared to the closest NOAA cooperative observer stations. The Twin Lakes, Franklin Township, OH, USA (GHCND:US1OHPT0010)

NOAA cooperative observer location was 6 km north and the closest NOAA cooperative observer station to the Kent collection location. Daily amounts from the NOAA observer at Twin Lakes were compared to the amount collected at the Kent collection location to determine the amount of under- or over-catch that was occurring. The Holden precipitation collector only measures bulk precipitation over the two- week interval. The closest NOAA Cooperative Observer with daily precipitation amounts was 12 km east in Chardon (Station ID GHCND: USC00331458), which allowed me to get daily precipitation data for the

Holden location. Use of the cooperative observer data allowed me to compare individual storm data for

Kent and Holden to determine if each location received the same amount of precipitation from each storm. To calculate the weighted average, I determined the depth of each daily precipitation during a 2- week period, calculated the sum of each isotopic value multiplied by its depth, and divided that result by

11 the sum of all the depth. The seasonal weighted averages were calculated using the same process as the 2-week weighted averages.

Groundwater

Private and community wells providing water to convenience stores and gas stations were used to collect groundwater samples. On January 1st-4th, 2018 water samples from 76 locations were collected in approximately 8 km by 8 km grids across the study area. Following the initial round of sampling, the Ohio Department of Natural Resources (ODNR) well database

(https://apps.ohiodnr.gov/water/maptechs/wellogs/app/) was consulted to determine the water source for each of the sampling locations. The database provided the elevation of the well, the lithology of the well, and the depth of the well. If the convenience store or gas station did not have a well listed, I then contacted the location directly to determine the source of the water. After reviewing the data, 29 of the

76 initial locations were found to be sourcing surface water from Lake Erie or surface reservoirs and were excluded from subsequent sampling. A second round of sampling was conducted on July 28th-31st,

2018, and included the 47 groundwater locations. During both sampling rounds, cold water was run from the faucet for 30 seconds before the collection vial was filled. The tap water samples were not filtered, but were otherwise labeled, stored, and processed identically to other samples.

Lakes

During the summer of 2018, 93 lentic water samples were collected from 30 lakes and ponds from across the Northeast Ohio study area. Each lake was sampled during three separate campaigns

(May 30th-June 1st, July 28th-31st, September 28th-30th). The lakes were chosen from those shown in the

Delorme Atlas and Gazetteer of Ohio (2015), excluding reservoirs when possible. Reservoirs were excluded because of concerns about the effects of rivers flowing into them on evaporation calculations.

Initially I planned to collect 3 to 4 samples per county but due to access issues I was able to collect a total of 30 samples across the study area.

The sampled lakes are likely well mixed (Horne and Goldman, 1994). The spring turnover helps to mix the lakes early in the season, because of the density difference as the lakes thaw, although thermal stratification can develop in the summer. The small size and shallow depths for some of the sampled lakes suggest that the epilimnion may be the entire depth of the lake, depending on the season and the wind interaction (Horne and Goldman, 1994).

The lakes were sampled from the same dock or shore location each time. Samples were collected using a one-gallon bucket attached to a 20 ft cable. The bucket was field rinsed before being thrown into the water and allowed to sink through the water column before retrieval. A 60 ml syringe was used to draw water from the bucket. The syringe was field rinsed three times, by rinsing it with the water in the bucket and discarding the water away from the bucket. This was done to ensure that the syringe contained only the current sample and not a previous sample. The syringe was filled a fourth time and a 0.7 μm GFF filter was attached. With the filter attached, 10-20 ml of water was pushed through the filter to ensure the filter contained the current sample, before filling the 20 ml borosilicate vials as described above. Samples were labeled, transported, and processed as previously described.

Transect water samples

Once every two weeks, I would drive from Ravenna, Ohio on a 100-mile round trip to The

Holden Arboretum to collect 12 water samples on a north-south transect through the study area. The timing of transect sample collection coincided with the collection of precipitation samples at Holden.

The transect samples included 3 groundwater collection sites, 2 lentic water bodies, and 6 rivers. For groundwater samples cold water from a faucet would run for 30 seconds before sample collection.

Surface water samples were collected as described for lakes and rivers. In all cases, samples were

13 stored in 20 ml borosilicate glass vials, filled to the top and sealed with a poly-seal lined cap with conical insert. Each sample was labeled with a unique code that identified where and when the sample was collected. The samples were then transported to the Watershed Hydrology lab at Kent State and refrigerated until analyzed.

Results of the lentic transect water samples are described in the lakes section of Chapter 3.

Other transect sample data are presented in the appendices.

Rivers

During three rounds of sampling, river water samples were collected from the five major rivers

(Mahoning River, Conneaut Creek, Grand River, Cuyahoga River, Chagrin River) within the study area.

Two tributaries of the Chagrin River (Pierson Creek, East Branch Chagrin River) were also sampled. All rivers were sampled in two locations: near the head waters and near the mouth. The first round of samples was collected May 30th – June 1st, 2018, the second round was collected from July 28th- July 31st,

2018, and the third round was collected from September 28th-30th, 2018. The river samples were collected from the riverbank or from a bridge using a bucket. The same procedure was used to collect and filter the samples as was used for the lake samples. Data from the river sampling are presented in the appendices.

Stable Isotope analyses

All the water samples were analyzed for δ2H and δ18O in Dr. Jefferson’s Watershed Hydrology lab at Kent State University using a Picarro L2130-i analyzer. The Picarro’s design allows it to measure stable water isotopes using a cavity ring down spectroscopy technique (Busch and Busch, 1997). Raw data from the Picarro is processed using an Excel spreadsheet based on van Geldern and Barth (2012), which accounts for memory and drift correction within each run and it normalizes data to the

International Atomic Energy Agency (IAEA) VSMOW standards. When the samples were being analyzed

14 by the Picarro they were bracketed with in-house working standards, calibrated to IAEA VSMOW and

SLAP standards, repeated standards for drift correction, and check standards used to ensure inter-run consistency of results. Within-run replicate samples were placed at the beginning and end of each run to check the drift correction, and between run sample replicates were also used to ensure comparable results across runs. If a check standard or replicate sample was outside the tolerances (0.16‰ for δ18O,

1.0‰ for δ2H), the entire run was repeated. If replicate samples were within the tolerances of one another, the average value was taken.

Evaporation to inflow ratios for lakes

To calculate the evaporation to inflow ratios (E:I) for the lake samples, I used the Hydro- calculator designed by Skrzypek et.al. (2015). This calculator uses an algorithm based off the model from

Craig and Gordon (1965) revised by Horita et. al. (2008). This calculator allowed me to calculate the E:I ratios without having the depths for each of the lakes. There were several data input fields required for the calculator: (1) mean temperature (T) between the initial sample and the second sample; (2) mean relative humidity as a fraction (h) between initial sample and second sample; (3) mean precipitation

(δRain) between initial sample and second sample; and (4) the slope of Local Evaporation Line (LEL). The values for the mean temperature (23°C) and the mean relative humidity (0.69) were obtained from the cooperative observer station locations and the LEL (4.39) was calculated from the lake data obtained during the study.

The hydro-calculator produces results in two different models: (1) steady state and (2) a field model. The steady-state model is where inflow I equals evaporation E plus outflow. The field model is a non-steady state model, where there is no inflow or outflow to the pool and the decrease in water level is due to evaporation only. I chose to present the results for the field model, because steady state is not accurate for field observations and the differences between the two models was very small.

The lakes data consists of three visits to each lake, and the May sample serves as the starting point for each lake. The July sample is compared to the May sample to calculate the amount of evaporation that has occurred between visits. The amount calculated is the May-July E:I ratio. The

September values are compared to the July samples to calculate the July-September E:I ratio and the total E:I is calculated from May to September. The hydro calculator returns both δ18O and δ 2H values for each sampling event and I reported the δ18O values to stay consistent with the rest of my reporting values.

Results

Distribution of sampling locations and northeast Ohio sub-regions

The study area is defined geographically as 9 counties in northeast Ohio. Within this study area,

I identified five sub-regions, based on their geography and topography (Figure 1). Two subregions are in the primary snowbelt, while the other three subregions are in the secondary snowbelt. The “West of the

Primary Snowbelt” (Region 1) consists of three counties; Cuyahoga, Summit, and Medina County, within this region I sampled 11 groundwater wells and 11 lakes. The “Primary Snowbelt High Elevation” (Region

2) consists of Lake and Geauga counties, this region has 12 groundwater wells and 7 lakes used for sampling, as well as the precipitation collector at Holden Arboretum. The “Primary Snowbelt Low

Elevation” (Region 3) includes Ashtabula county and has 6 sampled groundwater wells and 1 sampled lake. The “South of Primary Snowbelt High Elevation” (Region 4) is contained within Portage County, and it has 8 sampled groundwater wells, 5 sampled lakes, and the Kent precipitation collector. The “South of the Primary Snowbelt Low Elevation” (Region 5) includes Mahoning and Trumbull County, this region contains 10 sampled groundwater wells, 7 in Trumbull County and 3 in Mahoning County, and 7 sampled lakes. Region 5 mostly drains to the south toward the Ohio River, while the other four regions drain to the north into Lake Erie.

Figure 1. shows the locations of precipitation, groundwater, and lake sampling locations, with respect to county boundaries and identified sub-regions.

Precipitation

Precipitation and snowfall amounts

Between December 13th, 2017 and December 22nd , 2018, total precipitation for the Holden precipitation collection location was 1466 mm, with a total snowfall of 3492 mm, based on the NOAA

Cooperative Observer station located in Chardon, Ohio (Table 1).

During the same period, the Kent location received a total of 1241.5 mm of precipitation and

1,544 mm of snowfall based on the observations of the NOAA Cooperative Observer location at Twin

Lakes, Ohio. During the study, the snowbelt experienced 5 more snowfall events (58) than the area south of the snowbelt (53) but had more than twice as much snowfall. The NOAA cooperative observer’s data show that Kent received 85% of the precipitation that Holden received over the course of the study, with the biggest difference occurring in the winter.

Table 1. Precipitation amounts collected and observed at both collection locations, compared to the closest NOAA cooperative observer stations. Snow depth and number of events is derived from the cooperative observer data. The total amounts are broken down for each approx. three-month season, with winter as Dec 13th to April 1st, spring from April 1st to June 23rd, summer from June 23rd to September 16th, and fall from September 16th to December 22nd. These seasonal start and end dates were chosen to align with the dates of precipitation collection at Holden.

Location and Collected NOAA Snow (mm) Snow events Collected vs. NOAA season Precipitation (mm) Precipitation Precipitation (%) (mm) Holden Winter not recorded 390 3042 42 n/a Holden Spring 357 327 99 4 1.09 Holden Summer 421 382 0 0 1.10 Holden Fall 297 374 353 12 0.79 Holden Overall 1074 1466 3492 58 0.73 Kent Winter 289 258 1300 39 1.12 Kent Spring 263 359 77 5 0.73 Kent Summer 323 359 0 0 0.90 Kent Fall 227 267 167 9 0.85 Kent Overall 1103 1242 1544 53 0.89

Table 1 shows the amount of precipitation that was measured at the precipitation collection locations relative to the amount recorded at the cooperative observer locations. The difference between the Holden collected and the NOAA observed amounts are due to the lack of collection amounts during the winter (Table 1). In other seasons, there is good agreement between the collected and recorded amounts. The difference between the Kent collected and NOAA observed amounts could be due to the protocol of not collecting a sample if the precipitation amount was less than 3 mm at the

Kent location. The difference between the NOAA observer and our Kent site was 11.2%, so despite the small size of individual events, spread over the year the Kent collector missed 138.6 mm of precipitation.

On almost every day that precipitation occurred at Holden there was also precipitation at Kent

(Figure 2), but more precipitation fell at Holden than in Kent on most days. The two week precipitation amounts reduce the variability between the two collection locations (Figure 3), but Holden does receive more precipitation than the Kent location during most of the two week collection times.

60.0

50.0

40.0

30.0

20.0

10.0 Precipitation(mm)

0.0 12/12/2017 3/12/2018 6/12/2018 9/12/2018 12/12/2018

Date

Holden Kent

120.0

100.0

80.0

60.0

40.0 Precipitation(mm) 20.0

0.0 12/20/2017 3/21/2018 6/20/2018 9/19/2018 12/19/2018 Date

Holden Kent

Figure 3. Two-week precipitation total amounts collected at each location, corresponding to the 2-week sampling interval at Holden, the daily amounts were added together for the Kent location.

Holden received 1742 mm more snow than the Kent location just in the winter season (Figure

3). On the date of the first precipitation collection at Holden (12/29/2017), there was 229 mm of snow on the ground at the Holden site and 64 mm at the Kent location. The snow on the ground was not the first measurable snow of the season; both locations had received snow prior to the beginning of this study. Holden had snow on the ground for 76 days out of the year and had 13 more days with snow on the ground then Kent did (63 days). The Kent precipitation collector caught 112% of the winter precipitation volume that was recorded at the Twin Lakes site, whereas in other seasons the non- collection of small events led to an overall under-catch in Kent. Local snow accumulations can vary based on precipitation collector location (under- or over- catching), so it is possible to have highly variable snow depths, explaining why the Kent collector was able to collect more snow precipitation than was observed at the cooperative observer location at Twin Lakes.

400 350 300 250 200

150 Snowfall Snowfall (mm) 100 50 0 12/11/2017 3/15/2018 6/17/2018 9/19/2018 12/22/2018 Date

Holden Kent

Figure 4. Daily amount of snowfall that occurred at each location based on cooperative observer data.

Precipitation Isotopes

The Holden precipitation collector produced 26 samples that were collected bi-weekly. On each of the 26 visits to Holden there was precipitation in the collector. The Kent location produced 83 daily rain samples >3 mm. Kent precipitation was collected daily for the days when precipitation >3 mm occurred, and two-week amount-weighted averages were calculated from the isotopic compositions of the daily samples. There is a larger range of the δ18O and δ2H for the daily precipitation versus the two- week average precipitation, but the mean values are similar (Table 2). Seasonal differences in precipitation isotopes are observed with both the daily and two-week data (Figure 5). During the winter months, there is a far greater amount of variability in the daily precipitation isotopes than seen in the summer months (Figure 5). The most negative precipitation event (December 31, 2017, δ18O = -25.3‰) does not have a big effect on the two-week average, because two events in the same two-week period were rain events that were less negative (δ18O = -6.6‰ and -6.5‰), resulting in an average δ18O of -

12.8‰. The daily precipitation events where the δ18O ≤ -15.0‰ are all snowfall events. During the summer months, there is less variability in the daily data, and we see fewer extreme negative values.

Table 2. δ18O ‰ and the δ2H ‰ minimum, maximum, and amount-weighted mean for Kent daily and two-week weighted precipitation values

Kent Daily δ18O (‰) 2 Week δ18O (‰) Daily δ2H (‰) 2 Week δ2H (‰) Minimum -25.3 -19.5 -181.1 -140.9 Maximum -1.5 -3.8 + 0.8 -15.0 Mean -9.5 -9.8 -62.5 -65.5

-5

-10

-15

O O (‰)

18 δ

-20

-25

-30 12/11/2017 3/15/2018 6/17/2018 9/19/2018 12/22/2018

Date Kent 2 Week Weighted Average Kent Daily

Figure 5. Kent daily and two-week weighted average δ18O.

Precipitation values showed little difference between the two collection locations. The δ18O and

δ2H were similar in Holden and Kent over the study period (Figure 6, Table 3). The annual average precipitation δ18O and δ2H at Holden is -9.3‰ and at Kent it is -9.1‰, while for δ2H, it was -60.6‰ and -

59.9‰ at Holden and Kent, respectively (Table 3). Kent minimum δ18O occurred on 3/18/18 (-19.5‰) and Holden’s minimum δ18O occurred during the two-week period ending on 11/24/18 (-17.6‰).

Maximum δ18O at Holden occurs during the two-week period ending on 7/21/18 (-3.4‰), and at Kent, it occurs during the two-week period ending on 6/23/18 (-3.6‰). At Kent, the lowest d-excess (8.1‰)

23 occurs during the two-week period ending on 12/22/18 but is much higher than the lowest d-excess at

Holden. The d-excess minimum (1.6‰) for Holden occurred during the period ending on 2/4/18. It is possible that this d-excess could be due to sublimation occurring after the snow fell, while it was trapped in the stove-pipe winter collector, before melting into the secure non-evaporative container.

The sample collected on 2/4/18 at Holden is far less negative than the Kent sample collected at that time. Excluding the 2/4/18 two-week period, the d-excess minimum at Holden was 10.7‰ on 3/3/18.

The d-excess maximum (18.3‰) happens in Holden during the period ending on 10/13/18, and the Kent d-excess maximum (17.9‰) is during the period ending on 12/8/18.

Table 3. δ18O and δ2H weighted average minimum, maximum and mean at both precipitation locations.

δ18O Average (‰) δ2H Average (‰) d-excess (‰) Holden Winter -11.5 -79.8 12.5 Holden Spring -7.1 -43.5 13.6 Holden Summer -7.0 -42.7 13.0 Holden Fall -12.6 -85.7 15.4 Holden Annual -9.8 -64.5 13.6

Kent Winter -13.3 -93.5 12.7 Kent Spring -6.1 -36.2 12.4 Kent Summer -6.8 -42.1 11.9 Kent Fall -11.9 -79.7 15.2 Kent Annual -9.7 -64.7 13.1

Some of the smaller differences between Holden and Kent may be attributed to some storms not reaching both collection locations, differing amount of snowfall or rain at each location, or small storms not sampled at the Kent location. Despite differences in climate, location, and sampling technique, the two precipitation locations are very similar to each other in terms of the isotopic composition.

0.0

-5.0

-10.0

O O (‰) 18 δ -15.0

-20.0

-25.0 12/11/2017 3/15/2018 6/17/2018 9/19/2018 12/22/2018 Date

Holden 2 week Kent 2 Week

Figure 6. Two-week weighted average precipitation δ18O for Kent and Holden.

-20

-40

-60 H H (‰)

2 -80 δ

-100

-120

-140 -18 -16 -14 -12 -10 -8 -6 -4 -2 0 δ18O (‰) Kent Winter Kent Spring Kent Summer Kent Fall Holden Winter Holden Spring Holden Summer Holden Fall Figure 7. Precipitation δ18O and δ2H for Holden and Kent, color coded by each approx. three-month season, with winter as Dec 13th to April 1st, spring from April 1st to June 23rd, summer from June 23rd to September 16th, and fall from September 16th to December 22nd. These seasonal start and end dates were chosen to align with the dates of precipitation collection at Holden.

When the samples from each season are color coded to better visualize where each season falls along the LMWL, winter and fall are seen to be more isotopically variable than spring and summer precipitation (Figure 7). The winter samples were expected to plot near the bottom left of the data set.

According to Craig (1961), isotopically depleted values are associated with colder regions and enriched values are associated with warmer regions that plot at the top right of the GMWL. The fall samples are scattered across most of the graph, and this is expected due to the variability of the precipitation during this transitional period. The spring and the summer points plot more to the top and right where they are expected to be (Craig, 1961), with a smaller range across the dates.

Amount-weighted averages were calculated for each season (Figure 8, Table 3). Seasonal averages for the winter at both locations are more negative than the rest of the seasons. The most negative δ18O was during the winter (-19.5‰) at Kent and least negative δ18O was during the summer at

Holden (-3.4‰). The seasonal averages at both collection locations are very similar to one another

(Table 3).

0.0

-20.0

-40.0

-60.0

H H (‰)

2 δ -80.0

-100.0

-120.0 -12.0 -10.0 -8.0 -6.0 -4.0 -2.0 0.0 δ18O (‰)

Kent Winter Kent Spring Kent Summer Kent Fall Holden Winter Holden Spring Holden Summer Holden Fall

0.0

-20.0

-40.0

-60.0

H H (‰) GMWL

2 LMWL

δ -80.0 y = 7.7984x + 11.421 y = 8x + 10

-100.0

-120.0

-140.0 -20.0 -18.0 -16.0 -14.0 -12.0 -10.0 -8.0 -6.0 -4.0 -2.0 0.0 δ18O (‰)

Holden Kent

Figure 9. The LMWL (green Line) from two-week precipitation data collected at Holden and Kent. The GMWL (black Line) has an intercept (d-excess) of 10‰ and the LMWL has an intercept 11‰.

The Kent daily precipitation samples were combined to get a two-week, amount-weighted average before being used to construct the local meteoric water line (LMWL) (Figure 9). Separate

LMWLs for the precipitation collected in Holden and Kent had similar slopes and intercepts so they were combined to create one regional LMWL. However, the LMWL has an intercept of 11.42, as compared to

GMWL that has an intercept of 10 (Craig, 1961). The higher intercept may indicate that the water has been recycled from local sources (Bowen et, al. 2012). The slopes of the LMWL and the GMWL appear similar but have not been statistically tested for significant differences.

Groundwater

Lithology, surface elevation, and well depths

Lithology of the screened intervals of the 47 sampled wells is variable and contains several aquifer types. The groundwater wells were separated into five lithological categories based on the information retrieved from the Ohio Department of Natural Resources Water Wells database

(https://gis.ohiodnr.gov/MapViewer/?config=waterwells). The most common lithology across the study area is sandstone with 25 (53%) of the 47 wells sampled. Shale was the second most common lithology reported by the well logs, with 14 (30%) of the 47 wells sampled. Gravel, conglomerate and till make up the remaining 8 (17%) wells sampled. Of these, there were 5 wells drawing from gravel, 2 wells in conglomerate, and 1 well in till. Well log information from the Ohio Department of Natural Resources for the depth, elevation and lithology for each well did not specify the sandstone or shale aquifers or formations. Wells drawing from conglomerate, gravel and till are spread across the study area in different watersheds, so it is expected that the wells are drawing from multiple aquifers.

Sampled wells range from surface elevations of 254 to 400 meters above sea level (masl), with an average elevation of 324 m. Region 1 has the lowest elevation well and the largest range of well

28 elevations of any region (Table 4). The highest and lowest elevation wells are ~10 km apart with a difference of 107 meters in elevation. Region 2 has the highest elevation well, and the highest average elevation of sampled wells. Most of the sampled wells in that region are within a 30 m elevation range, with the wells to the far northwest and southeast at lower elevations. In Region 3, well elevations increase as you move from the west to the east and from north to south, but the average well elevation is the lowest of any region. The 47 m elevation change over Region 4 is the smallest among the regions.

Table 4. Number of wells, elevation range, average elevation, depth range and average depth for each of the five regions in the study.

Region Sampled Elevation of Average Depth (m) Average wells (#) wells (masl) elevation of wells depth (m) (masl)

1 (west) 11 254-361 319 23-76 42 2 (high primary snowbelt) 12 315-400 363 15-88 32 3 (low primary snowbelt) 7 266-345 286 15-30 23 4 (south of high snowbelt) 8 319-366 343 14-49 28 5 (south of low snowbelt) 9 275-352 308 19-59 30

There is considerable variability in sampled well depths across the study area (Table 4). Sampled well depths range from 14-88 m, with an average depth of 31 m (Table 4). Three of the 47 sampled wells are deeper than 75 m, and seven wells draw water from less than 20 m deep. Region 1 has two of the deepest wells in the study (76 m); these belong to a municipality and are 24 m deeper than any other wells in this region. The wells in Region 1 draw water from either shale (4 wells) or sandstone (7 wells).

The lowest elevation well in Region 1 is the fourth deepest well, whereas the second highest elevation well is the shallowest. The wells in Region 2 are drawing from three types of lithology; the two shallowest wells are drawing water from conglomerate at a depth of only 15 m. Two of the wells are drawing from shale at depths between 27 and 30 m. The eight wells in sandstone are drawing water

29 from between 16 and 88 m below the land surface. Many of the wells in Region 2 are within a 30 m range of elevation, but the wells show a trend of deeper well depths from the northwest corner of the region to shallower wells as you move east. Region 3 has the lowest average well depth (23 m) and a spread of only 15 m from the shallowest to deepest sampled well. The wells in this region are dominantly drawing water out of shale (5 of 7 wells), and despite the change in land surface elevation from west to east, the depths of the wells remain relatively shallow. Sampled wells in Region 4 are divided evenly; four wells are in gravel and four wells are in sandstone, with the shallower wells in gravel and the deeper wells in sandstone. The wells Region 5 are drawing from three lithologies. Five wells are in sandstone, three are drawing from shale, and one is set in glacial till. Overall, there is no obvious correlation between elevation and depth of wells within the study area.

Groundwater isotopes

There is a smaller isotopic range for groundwater than there is for precipitation. Two rounds of sampling of the 47 wells resulted in a δ18O range from -3.21 to -10.45‰, with mean values of -8.33‰ in

January and -8.46‰ in July (Tables 5). These mean values are slightly less negative than the annual average δ18O values for precipitation(-9.3‰ Holden and -9.1‰ Kent). The δ18O- δ2H relationship for groundwater samples in January and July is visually the same (Figure 10). Therefore, a single regression line was fit to the data. The best-fit line equation for the groundwater data set is: δ2H = 4.91 δ18O - 15.2, with an R2 of 0.9591. As shown in the graph, the groundwater slope is lower than the LMWL, which is an indication that the groundwater experienced evaporation after falling to the ground as precipitation.

This evaporation likely occurred in the unsaturated zone, before the precipitation recharges the aquifer.

-10 y = 4.9137x - 15.188 R² = 0.9591 -20 -30 -40 -50

-60 H(‰)

2 -70 δ -80 -90 -100 -110 -120 -130 -18 -16 -14 -12 -10 -8 -6 -4 -2 0 δ18O(‰) January GW July GW

When looking at the map of the January δ18O groundwater samples (Figure 11), the high elevation primary snowbelt (Region 2) has low variability and depleted isotopic values, but other regions have greater variability and there are no obvious patterns that can be seen. The groundwater in Region

2 has the most negative average δ18O (-9.38‰) (Table 5). In this region, 10 of the 12 wells fall within 1‰

(-10.44‰ to -9.55‰) of each other, while the two remaining wells, which are at lower elevations, have isotopic signatures that are different (-6.23‰ and -6.41‰) from the rest of the wells in the region.

These two outlier wells (sample locations 122 and 199) are approximately 30 m lower in elevation than the rest of the wells in Region 2 and may be drawing water from different sources than the rest of the wells. Well 122 is the lowest elevation Region 2 well at 315 m and draws water from sandy shale at a depth of 30 m, whereas the closest well at a higher elevation (229) draws water from a conglomerate at

15 m deep. Well 199 is at an elevation of 325 m and draws water from sandstone at a depth of 64 m.

Beyond the snowbelt, Region 5 had the isotopically heaviest average groundwater in January, while

Region 3 had the greatest variability (Table 5). Wells across the entire study are variable in their depth, lithology, and elevation with no distinguishable pattern that correlates to isotopic values.

Table 5. shows the isotopic range and average for each region for the January and July sampling.

January GW Isotopic Range (δ18O) Average (δ18O) Region 1 -9.13 to -6.30 ‰ -7.60 ‰ Region 2 -10.45 to -6.23 ‰ -9.38 ‰ Region 3 -9.83 to -3.21 ‰ -8.02 ‰ Region 4 -9.68 to -8.30 ‰ -9.00 ‰ Region 5 -9.73 to -4.82 ‰ -7.45 ‰ Combined -10.45 to -3.21 ‰ -8.33 ‰

July GW Isotopic Range (δ18O) Average (δ18O) Region 1 -9.00 to -6.82 ‰ -7.70 ‰ Region 2 -10.32 to -6.74 ‰ -9.38 ‰ Region 3 -9.69 to -3.32 ‰ -7.96 ‰ Region 4 -9.69 to -3.32 ‰ -8.98 ‰ Region 5 -9.64 to -5.62 ‰ -8.10 ‰ Combined -10.32 to -3.32 ‰ -8.46 ‰

Figure 11. δ18O (‰) for the groundwater sampling in January.

Figure 12. δ18O (‰) for the groundwater sampling in July.

The July groundwater sampling revealed a similar pattern (Figure 12). For 4 out of the 5 regions, the difference between January and July average δ18O is ≤0.1 ‰ (Table 5). Region 5 shows the difference from January to July average δ18O is 0.65‰. In that region, three of the nine wells show

>1.0‰ changes in the δ18O (Figure 13).

When comparing the well-by-well differences between the two sampling events (Figure 13), if a location had <0.20‰ δ18O difference between January and July it was considered to be the same, because the difference was within two times the analytical error. If the δ18O difference was between

0.21‰ and 1.0‰ it is considered to be different, with all δ18O differences >1‰ is considered to be very different. When applying these standards to the groundwater data, 28 of the 47 wells (60%) had no difference, 13 of the 47 wells (28%) were ±0.21 to ±1.00‰, (+9,-4) were different, and 6 of the 47 wells

(12%) were very different, with a difference >1.00‰, (+4,-2).

In Region 1, only 18% of the wells stayed the same, while 82% of the wells experienced a change from January to July. One well (#127) in this region had a very different isotopic composition between the two sampling events (-1.43‰ δ18O difference). In Region 2, 8 of 12 wells (67%) experienced no change between the two sampling events, while the remaining 4 wells (33%) experienced a change in their isotopic composition. These differences are discussed further below. In Region 3, 4 of 6 (67%) wells did not experience any change from January to July. The remaining 2 wells (33%) experienced a slight change; one well went to the positive and the other went to the negative. Either of these measurements could be seasonal variation. In Region 4, 7 of 8 (88%) wells saw no difference between the two sampling events. The only well to experience a change in this region was location 126, and it was a δ18O difference of -0.28‰. Region 4 experienced the least well-by-well change overall, with 7 of 8 wells showing no difference. In Region 5, 5 of 10 (50%) wells experienced no difference. One well was considered to be different between the two sampling events, this well is at the far east and southern part of the study area. Three wells are considered to be very different shown in light blue through the middle of Region 5.

The biggest seasonal differences across all of the regions were seen in Region 2. Location 122 was -6.23‰ in January and -9.96‰ in July, a difference of 3.73‰. This location was previously discussed as a low-elevation outlier in the Region 2 January dataset. The other low elevation Region 2 well (199) also had isotopically lighter water in July, though the difference was much smaller (0.3‰ δ18O). Location

197 had a less negative δ18O isotopic composition in July (-7.14‰) than January (-10.23‰), for a difference of -3.08‰. This well is sourcing water from conglomerate matrix at a depth of 15 m, at the second highest elevation across the study area (387 m). In the southernmost part of Region 2, well 199 also experienced a smaller negative isotopic shift (0.3‰ δ18O).

Groundwater d-excess

D-excess is used as an indicator of whether water has been recycled via processes like lake evaporation and lake effect precipitation. Generally, precipitation that is not recycled or evaporative has a d-excess value between 8.0‰ and 10.0‰, and recycled precipitation has higher d-excess values (Gat et al., 1994). Hereafter, normal waters (i.e., not recycled or evaporative) are defined as having d-excess values of 8.0‰ to 10.0‰, recycled waters have d-excess values > 10.0‰, and evaporative waters have d-excess < 8.0‰. The LMWL for northeast Ohio, determined above, has a d-excess of 11.42, indicating some effect of recycling.

The January groundwater samples have a d-excess range from -6.0 to 15.7‰ (average = 10.7‰), and only one of the 47 wells (2%) were within the range for normal waters (Figure 14). With d-excess values <8.0‰, an evaporative signal characterized 12 wells (26%). These wells had d-excess from 4.7‰ down to -6.0‰ suggesting the water underwent evaporation following precipitation. A recycled water signal, with d-excess values >10.0‰, was found in 34 wells (72%), with a range from 10.91‰ up to

15.74‰.

There are clearly defined breaks between the evaporative and the recycled waters, as indicated by examination of d-excess versus δ18O values (Figure 14). There is one very low outlier (-6‰ d-excess), and then a group around -6.0‰ δ18O and below 5.0‰ d-excess. The recycled water group has δ18O values of -8.0‰ to -11‰ and above 10‰ d-excess.

5 ‰)

0 D excess excess D ( -5

-10 -12 -10 -8 -6 -4 -2 0 δ18O (‰)

Normal Precip Recycled Precip Evaporative Precip

Figure 14. Relationship between the δ18O and d-excess for groundwater samples in January.

There does not appear to be a relationship between well depth and d-excess (Figure 15).

However, the biggest outlier and lowest d-excess for January (well 177, -6.0‰) draws groundwater from

21 m deep, but has a static water level that is only 6 m deep, which is unusually shallow for groundwater wells. The July sampling of this well produced a similarly low d-excess (-7.7‰).

10 ‰) 5

0 D Excess Excess D (

-5

-10 0 10 20 30 40 50 60 70 80 90 100 Depth (m)

Figure 15. Relationship between d-excess in the January GW sampling and well depth.

Figure 16. Groundwater wells showing the January d-excess (‰). High d-excess represents recycled precipitation.

There are geographical and elevation patterns to d-excess (Figures 16-17). D-excess in Region 1 shows that the wells in the south are receiving recycled waters and the wells in the north are receiving evaporative waters. Region 2 shows a weak correlation with the elevation and the recycled precipitation isotopic signature, with one of the low elevation wells having evaporative rather than recycled water.

Region 4 shows a pretty consistent recycled signature across the region regardless of the elevation.

However, Regions 3 and 5 have more varied elevations than Regions 2 and 4, and they do not show the same correlation between elevation and recycled precipitation.

20.00

15.00

10.00 ‰) 5.00

D excess excess D ( 0.00

-5.00

-10.00 250 270 290 310 330 350 370 390 410

Elevation (m) Region 1 Region 2 Region 3 Region 4 Region 5

Figure 17. January d-excess relative to the elevation of the wells in each region.

The separation between the evaporative and recycled groups was not as distinct in July as it was in January. There was still a clear grouping for the recycled signature, but with more normal waters, there is no large gap between the recycled and evaporative groups (Figure 18). Overall, most of the groundwater d-excess values in July were very similar to the January values, with only slight changes occurring in a few locations. In July, the average d-excess was 10.7‰, with a range from -7.7‰ to

15.2‰. In July, 2 of the 47 wells (4%) were in the range of normal precipitation, which was an increase

40 of 1 well from the January sampling. The evaporative signature for July showed up in 11 wells (23%) and the recycled signature showed up in 34 wells (72%). A single well went from evaporative in January to normal in July. The outlier with the lowest d-excess was the same well (#177) as was the outlier for

January.

5 D excess excess D (‰) 0

-5

-10 -12 -10 -8 -6 -4 -2 0 δ18O (‰)

Normal Precip Reycyled Precip Evaporative Precip

Figure 18. Relationship between the δ18O and d-excess of well water samples in July.

From January to July, d-excess values in 6 of the 47 wells (13%) were <0.2‰, and these wells were distributed across all 5 regions (Figure 19). Across the five regions, there were 30 wells (64%) that experienced a d-excess difference of 0.2‰ to 1.0‰ between the two collection events. The 11 wells

(23%) that had the biggest differences in d-excess (>1.0‰) between January and July are scattered across the study area, but not found in Region 4. The wells with the biggest d-excess changes between

January and July also experienced the biggest δ18O changes (Figure 20) because you can’t have one change without the other.

Figure 19. shows the d-excess difference between January and July sampling events. The red and light blue dots are the major changes that shifted either to the negative or the positive respectively.

-2

excess excess Difference (‰)

- d -4

-6 -6 -4 -2 0 2 4 6 δ18O Difference (‰)

Figure 20. Wells with the biggest d-excess changes between January and July also experienced the largest δ18O changes, because you can’t change the d-excess without changing the δ18O or the δ2H.

Lakes

Seasonal Variability

Three lentic water bodies were sampled throughout the year, allowing seasonal isotopic variability and δ18O-δ2H relationships to be examined in greater detail than is possible for the broader summer sampling. For the three lentic water bodies sampled along the transect, the δ18O-δ2H best-fit lines diverge substantially from the LMWL (Figure 21). The Mantua Bog plots close to or above the

LMWL for part of the year, except for a few samples in the spring. The Science Center Pond plots slightly below Mantua Bog but exhibits a greater range of isotope values. Corning Lake does not plot on the

LMWL; instead, all points plot below the line. The lack of points on the LMWL could be due to the lack of winter sampling, because Corning Lake was frozen over until early March.

-5.00 Mantua Bog y = 6.715x + 0.3156

Science Ctr Pond y = 6.6122x - 2.1906 -25.00 Corning Lake y = 5.6084x - 12.687

LMWL y = 7.7984x + 11.421

-45.00

‰)

H ( H

2 δ -65.00

-85.00

-105.00 -14.00 -12.00 -10.00 -8.00 -6.00 -4.00 -2.00 0.00 δ18O (‰)

Mantua Bog Science Ctr Pond Corning Lake

Figure 21. δ18O and δ2H relationship for the three lakes from the transect collections. The red line is the Local Meteoric Water Line (LMWL), and the best fit lines show the samples variability across the study area. The range of the precipitation at Kent and Holden from both collection locations was δ18O of - 17.4‰ to -3.4‰ and δ2H of -125.7‰ to -15.7‰.

The seasonal variability of the lentic water bodies (Figure 22) shows a similar sinusoidal pattern to that of the precipitation (Figure 6). From March to early September, the waters become more enriched in δ18O and δ2H, but by the end of September we can see a downward δ18O trend leading into fall and winter. The Science Center Pond and Corning Lake have well defined sinusoidal curves, while the

Mantua Bog shows a dampened pattern. Mantua Bog doesn’t show much variability over the course of the year but does show a few points that are evaporative in spring and late summer. This tells me that the Mantua Bog is fed more by groundwater with low seasonal variability than by the highly variable precipitation and that the water has experienced some evaporation between entering the ground and reaching the bog. This contradicts the convention that bogs are fed by precipitation rather than groundwater (EPA, 2018).

The size of the lakes seems to play a major role in how the water body responds to precipitation events. The Science Center Pond is the smallest body of water in the study at 0.004 km2, and the pond has the most well-defined, largest amplitude sinusoidal pattern, except for the δ18O point (-11.7‰) collected on 7/7/2018 (Figure 22). On the previous day, the Holden area received over 50 mm of rain and this rain event produced ten times the amount of rain that had fallen in the two weeks prior, explaining why we see this extreme drop from a single rain event. The isotopic δ18O value from the precipitation collected during that same two-week period was -5.8‰, this included a total of 6 rain events that produced 96mm of rain. The isotopic drop that we see at the Science Center Pond (0.004 km2) is not reflected in Corning Lake (0.06 km2) because its larger size may homogenize a single event more easily than the smallest lake in the study. The January 12th sampling of the Science Center Pond showed a δ18O of -6.21‰ which was unexpected for January. The enriched isotopic signature didn’t show up in the Holden two-week collection for that period (-12.5‰), but it did show up in the Kent daily precipitation for 1/12/2018 (δ18O -6.5‰). That rain event produced 9.4 mm in Holden and 3.8 mm in

Kent. The enriched isotopic signature did not show up in any of the river samples from that day because the rain in January caused a lot of snowpack to melt, likely causing the rain’s isotopic signature to get lost in the more depleted isotopic signature of snowmelt. The other two water bodies were not sampled.

-2

-4 )

‰ -6 O O (

18 -8 δ -10

-12

-14 1/10/2018 3/20/2018 5/28/2018 8/5/2018 10/13/2018 12/21/2018 Date

Mantua Bog Science Ctr Pond Corning Lake

Lake Characteristics

The lakes survey consisted of collecting 30 lentic locations three times between May and

September. The lake areas range from 0.004 km2 to 1.8 km2, with an average area of 0.33 km2. The drainage areas range from 0.092 km2 to 172.0 km2, with an average area of 23.73 km2. The ratio of the drainage area to lake area ranges from 5000:1 to 2.5:1. The maximum depths of the lake range from an assumed 2m to a reported 17 m. However, many of the depths for the lakes were unknown, so I assumed a minimum of 2 m depth for the lakes without published depths. To overcome the problem of not having accurate lake depths for E:I calculation, I used the hydro-calculator’s built-in algorithms to compensate (Skrzypek et.al. 2015).

Table 6. The breakdown of the number of lakes, range of lake areas, mean lake area, lake depths, drainage area and lake area to drainage area inverse ratios.

Region 1 Region 2 Region 3 Region 4 Region 5 Lakes 11 7 1 5 6 Lake Area (km2) 0.02 to 1.4 0.004 to 0.6 1.8 0.06 to 1.2 0.08 to 0.71 Mean Area (km2) 0.46 0.16 N/A 0.39 0.34 Lake Depths (m) 3.65 to 12.5 2.74 to 16.8 4.6 4.6 to 11.9 N/A Drainage Area (km2) 0.09 to 56.7 0.09 to 35.0 172 1.8 to7.3 11.4 to 170.4 Mean Drain Area (km2) 17.8 10.6 N/A 4.6 61.9 LA : DA 250:1 to 2.5:1 5000:1 to 3:1 95:1 105:1 to 6:1 1000:1 to 23:1

Lake Isotopes

Samples collected during the three lake surveys differ substantially from the LMWL (Figure 23).

Many May lake samples are clustered towards more negative δ18O and δ2H values with several lake samples plotting above the LMWL. In contrast, by July, only one lake sample is above the LMWL and the lakes have become more enriched and evaporative, plotting to the right on the graph. Samples from

September that can be seen clustering farther to the right, between δ18O values of -6 to -5. The most enriched lake in the survey is Brady Lake (30), near Kent; in May, the lake’s δ18O value was -1.33‰.

Overall, the δ18O and δ2H values combined for the lakes, by date, suggests that there is slight progressive evaporation occurring between May and September, but this is less clear by examination of δ18O alone

(Table 7). A local evaporation line (LEL) based on all three lake surveys is δ2H = 4.39 δ18O – 16.71 (Figure

23).

0.00 May y = 4.4256x - 16.765 July y = 4.5168x - 16.293 -10.00 Sept y = 4.2511x - 17.357

LMWL y = 7.7984x + 11.421 -20.00

-30.00

H H (‰)

2 δ

-40.00

-50.00

-60.00 -10.00 -9.00 -8.00 -7.00 -6.00 -5.00 -4.00 -3.00 -2.00 -1.00 0.00 δ18O (‰)

May July Sept

Figure 23. The δ18O and δ2H of all the lake samples coded by date. The LMWL is the red line.

Table 7. δ18O mean, median, minimum, maximum, and range for each of the lake surveys.

δ18O (‰) May July Sept Mean -5.83 -6.14 -5.40 Median -6.42 -6.49 -5.66 Min -7.90 -8.19 -8.48 Max -1.33 -2.65 -1.78 Range 6.57 5.54 6.70

Some differences in the lake water isotopes can also be distinguished when the data are plotted by region (Figure 24). All regions show substantial spread in the samples, except Region 3, which has only one lake. Region 5 is the most tightly clustered region. By the end of the summer, all the lakes in

Region 5 that were on the LMWL in May have shifted to evaporative (Figure 25). Lakes in regions 1 and

4 plot furthest to the right in September. In September, Region 4 has both the isotopically most enriched

48 and most depleted lakes, highlighting the wide lake-to-lake variation possible within a small geographic area.

0.00

-10.00 y = 7.7984x + 11.421

-20.00 )

‰ -30.00

H H (

2 δ

-40.00

-50.00

-60.00 -9.00 -8.00 -7.00 -6.00 -5.00 -4.00 -3.00 -2.00 -1.00 0.00 δ18O (‰) Region 1 Region 2 Region 3 Region 4 Region 5

Figure 24. δ18O and δ2H of all three rounds of samples coded by region.

0.0

-10.0 y = 7.7984x + 11.421

-20.0 )

‰ -30.0

H H (

2 δ

-40.0

-50.0

-60.0 -9.0 -8.0 -7.0 -6.0 -5.0 -4.0 -3.0 -2.0 -1.0 0.0 δ18O (‰) Region1 Sept Region 2 Sept Region 3 Sept Region 4 Sept Region 5 Sept

Figure 25. September samples color coded by region show that, by September, most of the lakes are evaporative.

Isotopic variations by region are more clearly visible in maps (Figures 26-28). In May (Figure 26), the lakes in the east and north of the study area are isotopically lighter than the lakes in the south west section of the study area. In July (Figure 27) and September (Figure 28), isotopic values show more variability within regions than in May.

Figure 26. δ18O (‰) for each of the May lake samples. These are the starting values that are used later to calculate E:I ratios.

Figure 27. δ18O (‰) for the July lake samples.

When looking at the July data (Figure 27) there is more variability than observed on the other two sample dates. This could be due to regional variability in precipitation amounts or isotopes during

June and July and/or the isotopic response to precipitation as moderated by the size of the lake. Many lakes became isotopically lighter in July than they were in May, instead of becoming more enriched due to evaporation. The lakes that were highly enriched in May show less enrichment in July, contrary to expectations that they would become more enriched over the summer.

By the end of September (Figure 28), there is less variability then the previous samplings in regions 1 and 4, while Region 5 showed the least amount of variability overall. In September, the lakes in

52 region 5 are fairly homogenous isotopically. This could be because the all the lakes in region 5 are artificial reservoirs, which were not sampled in other regions.

Region 2 shows the most variability of any of the regions in September, with Corning Lake (228) appearing as an outlier. Corning Lake was part of the bi-weekly transect, so its September isotopic value can be set in context (Figure 22). From June until September 1st, 2018, Corning Lake became increasingly enriched (max: -3.32‰) and then steadily became more depleted until the end of the study. Clearly,

Corning Lake is not representative of lakes in this area, emphasizing the importance of sampling multiple water bodies to understand processes affecting water isotopes at a regional scale.

Figure 28. September δ18O (‰) values for surveyed lakes.

Lake d-excess and relationship with groundwater

Over the course of the summer, an increasing number of sampled lakes became evaporative or extremely evaporative, based on d-excess. In Figure 29, color coding for the d-excess was chosen based on Gat et al. (1994) to easily identify the various types of waters in the lakes: normal meteoric water that has not been recycled or evaporated (yellow, 8 to 10‰); recycled waters (orange, 10 to 12‰); extremely recycled waters (red, >12‰); evaporative waters (green, 8 to 0.01‰); and extremely evaporative waters (light blue, < 0.0). In May, 5 of 30 lakes were normal, 2 were recycled, 4 extremely recycled, 12 evaporative, and 8 extremely evaporative. In July, 10 of 30 lakes were normal, 1 recycled, 1 extremely recycled, 14 evaporative, and 5 extremely evaporative. In September, 1 of 30 lakes were normal, 2 recycled, 1 extremely recycled, 17 evaporative, and 10 extremely evaporative.

In May, the highest d-excess values are found in region 5 and the northern portion of region 1

(Figure 29). Region 5 is also more variable than the four other regions, which is contradictory to the δ18O results (Figure 5). Region 2, the high elevation primary snowbelt, does not show as much variability as

Region 5 in May.

Figure 29. May lake samples d-excess (‰)

By September, the eastern third of the study area is more homogenous than the rest of northeastern Ohio. Over the summer, Region 5 showed a gradual shift from recycled to normal to evaporative, while the rest of the regions did not exhibit consistent progressive change during the study.

The only lakes that remain recycled or normal are found in Regions 2 and 4, the high elevation, primary snowbelt and south of the high elevation, primary snowbelt.

Figure 30. September d-excess. We see more of the lakes are showing a low d-excess value caused by evaporation over the summer months.

Relationships between isotopic values within and across months can also be explored using correlation analysis (Table 8). There is a strong correlation between the δ18O and the δ2H for each month sampled and a strong inverse correlation between the δ18O and the d-excess (Table 8). The d- excess from September lakes correlates very well to the d-excess from the July lake samples (r = 0.90) which is slightly higher than the correlation between the δ18O and the δ2H from the same months. This correlation is also higher than the correlation between May d-excess and July or September d-excess.

Table 8 shows the correlation results for the lakes isotopes and d-excess.

May July Sept July May July Sept July May Lake July Lake Sept Lake July GW Lake Lake Lake GW Lake Lake Lake GW D-excess D-excess D-excess D-excess δ18O δ18O δ18O δ18O δ2H δ2H δ2H δ2H May Lake 1.000 δ18O July Lake 0.490 1.000 δ18O Sept Lake 0.637 0.776 1.000 δ18O July GW 0.098 0.027 0.215 1.000 δ18O May Lake 0.962 0.455 0.684 0.255 1.000 δ2H July Lake 0.405 0.963 0.657 0.058 0.387 1.000 δ2H Sept Lake 0.594 0.725 0.976 0.263 0.664 0.643 1.000 δ2H July GW 0.160 0.028 0.209 0.980 0.302 0.063 0.254 1.000 δ2H May Lake -0.944 -0.483 -0.516 0.102 -0.820 -0.387 -0.450 0.030 1.000 D-excess July Lake -0.545 -0.941 -0.845 0.016 -0.494 -0.815 -0.752 0.019 0.552 1.000 D-excess Sept Lake -0.648 -0.789 -0.969 -0.147 -0.666 -0.635 -0.891 -0.145 0.559 0.900 1.000 D-excess July GW D- 0.008 -0.023 -0.207 -0.950 -0.159 -0.046 -0.256 -0.869 -0.208 -0.010 0.140 1.000 excess

All correlations between lake isotopic values and those of the nearest sampled groundwater well were weak (<0.31) (Table 8). There are several factors that could explain why there is only weak correlation between groundwater and lake isotopic values. The groundwater wells draw water from various depths and aquifers across the study area, and the closest groundwater well might not be drawing from the same aquifer as the lake interacts with. Also, if lakes are recharging groundwater, the lake isotopic signature probably gets lost as it mixes with groundwater recharged away from lakes.

A bivariate plot illustrates the lack of strong relationship between the lakes and nearby groundwater (Figure 31). Region 2 has the tightest groundwater cluster of the five regions, with all wells indicating recycled water sources, but the lakes are quite variable. Conversely, Region 5 lakes show very little variability in the July lake d-excess despite having a wide range for the groundwater d-excess.

Regions 1 and 4 are scattered in both groundwater and lakes, and Region 3 only has one lake. The correlation illustrated in Figure 31 has r = -0.01 (Table 8).

Recycled

10 Normal

‰) 5 Evaporative

D excess excess D Lakes July( Very -5 Evaporative

-10 0 2 4 6 8 10 12 14 16 D excess July Nearest GW Well (‰)

Region 1 Region 2 Region 3 Region 4 Region 5

Trends over time within regions

The lakes have been compared region by region across the study area, but here I am looking at the individual lakes in each region to assess differences in patterns over the course of the summer and investigate potential explanations for these patterns. I compared the δ18O and d-excess of each lake in each region to the other lakes in that region.

Region 1 experiences a decrease in the average δ18O from May to July, and then it increases from July to September (Table 9, Figure 32). However, the range of δ18O decreases in each survey, suggesting that the lakes become more isotopically homogeneous throughout the summer. Similarly, the d-excess increases from May to July and then decreases from July to September. This shows the relationship between the δ18O and the d-excess: as one increases the other decreases. Two lakes in

Region 1 (249 and 252) experienced progressive evaporative enrichment, based on a continuous increase in δ18O and decrease in d-excess. The two lakes are not similar in lake or drainage area, but neither of the lakes have tributaries that feed into them. The remaining lakes in Region 1 that did not show a progressive evaporation have considerable variability in lake and drainage area, and some of the lakes have small tributaries. Lakes with tributaries could be receiving more run off from early summer precipitation, causing the lake isotopic signature to show a more depleted value than an enriched value as expected. During the early part of July, the study area did not receive a lot of rain, but that changed the day before the sampling was to begin. At Holden on July 27th, it rained 39.4 mm, while the Kent area received 20.8 mm. This is a likely explanation for why the lakes showed a less evaporative signature in

July before rebounding to evaporative in September.

0 A

-3

O O (‰)

18 δ -6

-9 5/28/2018 7/28/2018 9/27/2018 Date

15 B

D excess D excess (‰) -5

-10

-15 5/25/2018 7/28/2018 9/30/2018 Date 63 243 244 246 247 248 249 250 251 252 253

Figure 32. Region 1 lakes (A) δ18O values and (B) d-excess over time.

There is less variability over time in Region 2 (Table 10, Figure 33) than Region 1. Examining the

δ18O and d-excess patterns of individual lakes over the summer (Figure 33), two lakes (228, 254) experienced progressive evaporative enrichment, 2 lakes became isotopically lighter from May to July and then became enriched from July to September, and 3 lakes became enriched from May to July and then more depleted by September. The lakes that became more depleted from July to September are

60 among the smallest lakes in the entire study and very responsive to precipitation fluctuations. The two lakes that show progressive evaporative enrichment are Corning Lake (228) and Kelso Lake (254).

Corning Lake is almost the size of the watershed itself. Corning lake has an area of 0.06 km2 and a watershed of 0.07 km2. Kelso Lake is only slightly larger at 0.11 km2 with a watershed of 0.23 km2. The depth of Corning lake is 2.7 m and the depth for Kelso Lake is unknown.

Table 9. Mean, median, minimum, maximum, and range for the δ18O and the d-excess for Region 1.

δ18O (‰) May July September Mean -5.04 -6.21 -4.94 Median -5.12 -6.66 -5.04 Minimum -7.36 -7.88 -6.06 Maximum -2.71 -3.53 -2.93 Range 4.65 4.35 3.13 d-excess (‰) May July September Mean 2.30 4.89 1.21 Median 3.94 6.24 2.23 Minimum -7.35 -5.84 -7.17 Maximum 12.43 9.94 7.99 Range 19.78 15.78 15.16

Table 10. Mean, median, minimum, maximum, and range for the δ18O and the d-excess for Region 2.

δ18O (‰) Region 2 May July September Mean -6.45 -5.75 -5.90 Median -6.82 -6.07 -5.86 Minimum -7.46 -7.43 -7.50 Maximum -4.41 -3.93 -3.77 Range 3.05 3.50 3.73 d-excess (‰) Region 2 May July September Mean 4.95 3.95 4.24 Median 6.19 4.85 6.04 Minimum -3.13 -4.54 -3.63 Maximum 9.63 8.11 10.96 Range 12.76 12.65 14.59

0 A

-3

O O (‰)

18 δ -6

-9 5/25/2018 7/28/2018 9/30/2018 Date

15 B 10

5 ‰)

D excess excess D ( -5

-10

-15 5/25/2018 7/28/2018 9/30/2018 Date

121 228 254 255 256 257 258

Figure 33. Region 2 lakes (A) δ18O values and (B) d-excess over time.

In Region 3, only Lake Roaming Rock (241) was sampled (Table 11). It is one of the largest lakes in the survey at 1.81 km2 and has a drainage area at 172 km2. In May, there were two lakes that were isotopically similar to 241, but they are on the far western edge of the study area and are far smaller than Lake Roaming Rock. In July, the lake is among the lightest in the study, and in September, it is dissimilar to lakes in adjacent regions. The dissimilarity of Lake Roaming Rock to lakes in surrounding

62 regions highlights the variability found within the study area. Due to lack of access resulting in only having one lake in Region 3, it is unclear whether size or geography has the strongest effect on the isotopic variation.

Table 11. δ18O and d-excess for Lake Roaming Rock (241) in Region 3.

Region 3 May July September δ18O (‰) -5.42 -7.47 -6.70 d-excess (‰) 2.27 9.32 7.47

In Region 4, the five sampled lakes separate into two clusters (Figure 34). The two lakes (11 and

231) that are isotopically lighter than the other three lakes have smaller lake areas (0.18 and 0.058 km2) and considerably larger drainage areas (4.37 and 6.03 km2) than the others. The two lighter lakes are showing progressive depletion of δ18O and relatively high d-excess values, which might suggest predominantly groundwater-fed lakes with low evaporation. The three isotopically heavier lakes show a similar pattern to many lakes in other regions, with an isotopic decrease in July, potentially due to the variability of the precipitation received. These three lakes have an evaporative d-excess throughout the summer.

Table 12. Mean, median, minimum, maximum, and range for the δ18O and the d-excess for Region 4.

δ18O (‰) Region 4 May July September Mean -4.85 -5.64 -5.12 Median -4.52 -4.93 -3.70 Minimum -7.90 -8.19 -8.48 Maximum -1.33 -2.65 -1.78 Range 6.57 5.54 6.70 d-excess (‰) Region 4 May July September Mean -0.85 2.58 0.89 Median -0.74 0.27 -4.33 Minimum -12.10 -7.97 -11.03 Maximum 9.33 12.07 12.88 Range 21.43 20.04 23.90

0 A

-3

O O (‰)

18 δ -6

-9 5/25/2018 7/28/2018 9/30/2018 Date

15 B

5 ‰)

D excess excess D ( -5

-10

-15 5/25/2018 7/28/2018 9/30/2018 Date

11 27 30 231 245

Figure 34. Region 4 lakes (A) δ18O values and (B) d-excess over time.

Region 5 has the tightest isotopic clustering among all regions (Figure 35, Table 13). The δ18O isotopic range for May was only 1.26‰, the smallest for any region during the study. Region 5 lakes exhibited progressive evaporative enrichment, as I hypothesized all the regions would. All the lakes in

Region 5 are manmade reservoirs, which might help to explain why region 5 has the tightest range and

64 why all the lakes responded similarly over the duration of the study. Manmade reservoirs are designed to hold water that would normally pass through a given area increasing the residence time and opportunity for evaporation and mixing of isotopically variable precipitation inputs. It is also possible that this Region received a more isotopically uniform rainfall and failed to see the strange mid-summer isotopically light precipitation that Chardon and Kent received.

Table 13. Mean, median, minimum, maximum, and range for the δ18O and the d-excess for Region 5.

δ18O (‰) Region 5 May July September Mean -7.19 -6.59 -5.64 Median -7.15 -6.63 -5.68 Minimum -7.68 -7.27 -6.24 Maximum -6.42 -5.91 -4.55 Range 1.26 1.36 1.69 d-excess (‰) Region 5 May July September Mean 10.14 7.77 4.95 Median 11.50 8.35 5.25 Minimum 4.50 3.64 2.27 Maximum 13.00 9.20 6.94 Range 8.50 5.56 4.66

0 A

-3

O O (‰)

18 δ -6

-9 5/25/2018 7/28/2018 9/30/2018 Date

15 B 10

5 ‰)

D excess excess D ( -5

-10

-15 5/25/2018 7/28/2018 9/30/2018 Date

233 234 235 237 238 239

Figure 35. Region 5 lakes (A) δ18O values and (B) d-excess over time.

Evaporation : inflow ratios

The E:I ratio shows the importance of evaporation (E) to inflows (I) in the lake’s water balance.

The higher the E:I ratio the more important evaporation is. Negative E:I ratios occur when a lake becomes less evaporative between consecutive samples, and they can’t be further analyzed. In 2018, negative E:I ratios are common in July (comparing May to July isotopes), but E:I ratios shift to more positive values by September (comparing July to September isotopes) (Figure 36). This may reflect isotopically depleted mid-summer precipitation influencing lake isotope values in the July sampling, or greater evaporation during later summer months, which are often warmer. The total E:I ratios

(comparing May to September isotopes) are more like the May-July E:I ratios than the July-September

E:I ratios (Figure 36), which indicates that the May isotope values have a large effect on the total E:I ratios. Over the whole summer, 16 of 30 lakes had positive E:I ratios, with a maximum E:I ratio of 0.13.

The other 14 lakes had negative E:I ratios, indicating that evaporation did not significantly affect the lake water balance.

As lake d-excess (at the time of the second sampling) increases, there is a decrease in the E:I ratios (Figure 36). When d-excess values are greater than approximately 8.0, E:I values drop to zero or below. Overall, evaporation as part of the lake water balance can be relatively important in this region, with up to more than 10% of inflows evaporating in summer months, but its importance varies widely among lakes.

0.15

0.1

0.05

-0.05 E:I

-0.1

-0.15

-0.2

-0.25 -15 -10 -5 0 5 10 15 D excess (‰) July Sept Total

Figure 36. E:I ratios for May-July (July), July-September (Sept) and May-September (Total) compared to d- excess values at the end of each interval. We can see that most of the September samples are positively evaporative and approx. half the July lakes are not yet evaporative.

Comparison of E:I ratios in the early and late summer periods reveals distinct regional clustering

(Figure 37). Quadrants in Figure 37 indicate whether a lake was positively or negatively evaporative in

May-July and July-September. Quadrant I (top right) is lakes were evaporative throughout the summer.

Most Region 5 lakes plot here, but no Region 3 or 4 lakes do. Quadrant II (top left) shows the lakes that had negative E:I ratios in early summer but were evaporative later in the summer. Most Region 1 lakes fall in this quadrant, but lakes from all regions are present. Quadrant III (bottom left) is lakes that never made it to an evaporative signature. Only two Region 4 lakes plot here. Quadrant IV (bottom right) lakes had a positive E:I ratio in early summer but had a negative E:I in the second half of the summer. Three out of seven Region 2 lakes plot there. We can clearly see that the second half of the summer produced more evaporative lakes then the first half (Figure 37). For July-September, no obvious spatial pattern is

68 observed for lakes with positive E:I ratios but the five lakes with negative E:I ratios form a north-south line in the middle of the study area (Figure 38).

0.2

0.15

0.1

0.05

0 September September E:I

- -0.05 July

-0.1

-0.15

-0.2 -0.2 -0.15 -0.1 -0.05 0 0.05 0.1 0.15 0.2 May-July E:I

Region 1 Region 2 Region 3 Region 4 Region 5

Figure 37. E:I from the two summer periods, color coded by region.

To examine what lake characteristics might explain E:I ratios, I chose the July-September E:I period, because more lakes had positive ratios than during other periods. Lake area does not appear to be correlated with July-September E:I ratios (Figure 39). Only the smallest lakes are negative after the second visit, but the small lakes also have a wide range of E:I ratios. There is also not a clear relationship between lake depth and E:I ratio (Figure 40). Similarly, there is no simple correlation between the lake

69 area to drainage area ratio and E:I ratio (Figure 41). However, all of the lakes with negative E:I ratios also had small lake area to drainage area ratios, but some lakes with small lake area to drainage area ratios also had positive E:I. There was no trend in positive E:I values with lake area : drainage area.

Figure 38. July-September E:I ratios for each lake. All negative ratios are red to show they are not evaporative. 258 is Pawpaw Lake and 11 is Mantua Bog.

0.1

0.05

-0.05

-0.1

September September E:Iratio

- July -0.15 0.000 0.500 1.000 1.500 2.000

Lake Area (km2) Region 1 Region 2 Region 3 Region 4 Region5

Figure 39. July to September E:I versus lake area).

0.09

0.08

0.07

0.06

0.05

0.04 September September E:Iratio

- 0.03

July 0.02

0.01

0 0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 18.0 Lake Depth (m)

September

Figure 40. compares the lake depth vs. E:I ratios. Only lakes with measured (not assumed) depths were used.

0.1

0.05

-0.05

September September E:Iratio -

July -0.1

-0.15 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 Lake area : Drainage area

Region 1 Region 2 Region 3 Region 4 Region 5

Figure 41. July to September E:I vs. the lake area to drainage area ratio.

Discussion

Identifying the lake effect signature on the precipitation isoscape

The primary versus secondary areas of lake effect precipitation are clearly visible in the differences in annual and seasonal precipitation between Holden Arboretum and Kent, Ohio. The total snowfall within the primary snowbelt for the Holden area is more than twice as much as the area in the secondary snowbelt in Kent (Table 1). In three out of four seasons, Holden received more precipitation than the Kent location (Table 1), and Holden had more precipitation on 21 of the 26 bi-weekly collections than the Kent location (Figure 4).

In terms of precipitation isotopes, the distinction between the primary and secondary snowbelt is less clear. When the LMWL is broken down into the separate components of the Holden and Kent precipitation, there is a slight difference between the two. However, both data sets plot above the

GMWL, with a d-excess >10, which is an indication that the precipitation has been recycled from local sources. Examining the average precipitation isotopes values and d-excess on a seasonal basis reveals more variability. The amount-weighted average precipitation isotopes in the spring and summer are less negative then the fall and winter for both locations, while the d-excess is highest in the fall and lowest in the winter (Table 3). In all seasons, the d-excess is slightly higher at Holden than at Kent. As Lake Erie begins to freeze over, the impact of the lake effect precipitation starts to diminished, until the lake

73 completely freezes over severely diminishing the lake effect, which may be why the winter precipitation for Holden in 2018 has a less recycled d-excess (11.7‰) than in spring and summer. In biweekly samples, the d-excess for the precipitation in my study ranged from a low of 1.6‰ occurring at Holden to a maximum of 18.3‰, also at Holden. The Kent d-excess ranged from 8.1‰ to 17.9‰ (Figure 7).

Variability in storm-to-storm precipitation could be a major contributor to the differences seen in the isotopic signature across the study area. The amount of snowfall that affects the primary snowbelt but does not reach the secondary snowbelt appears to be important to the differences we see in the isotopic signatures at each location. Precipitation collection in Regions 1, 3, and 5 might help further reveal these differences, but was beyond the scope of this study.

Identifying the lake effect signature on the groundwater isoscape

Clear evidence for the effects of lake effect in the groundwater isotopic signature is found in the d-excess (Figure 16). When the data set is broken down into regions, there is one area that shows striking isotopic homogeneity. The high elevation primary snowbelt, Region 2, has a d-excess between

12.01‰ and 15.74‰ which is a clear indicator that the region has received recycled water (Figure 16).

Region 2 also has 10 of 12 groundwater wells with δ18O between -9.5‰ and -10.44‰ for the January sampling, while the rest of the study area is considerably more variable and somewhat less negative than Region 2 (Figure 11).

The two Region 2 wells closest to Lake Erie show a less strong lake effect isotopic signature

(Figure 16). These two wells (122, 199) at the northwestern edge of Region 2 are 9-75 meters lower than the rest of the wells in the region, and they show a different isotopic signature. In January, the two wells had δ18O that looked evaporative instead of recycled. Six months later, one well shifted to showing a recycled signature, while the other stayed the same with an evaporative signature. A third well (197), in

74 the northeastern corner of Region 3, also had an evaporative signature in the summer, even though it is one of the highest elevation wells, possibly due to its shallow depth (21m). Lake effect precipitation does not always affect the areas right next to the lake because the rising warm moist air mass must reach high enough to cool the water vapor to cause it to snow. (US Department of Commerce, 2018).

The wells right along the lake shore could be missing the bulk of the precipitation required to show the lake effect signature expected and also not receiving groundwater flow from areas with a stronger lake effect signature.

Region 3, the low snowbelt, doesn’t seem to be very similar to Region 2 when examining δ18O signatures only (Figure 11). There are six wells in this region with a broad range of δ18O signatures.

However, the d-excess shows that most of the wells in Region 3 have a recycled signature (Figure 16).

We can see in this region how it is not as important to have steep topography to produce lake effect precipitation. Instead, the key requirements are warm lake water and cold enough air to cause the moist water vapor to lift and produce precipitation. A greater number of groundwater samples in Region 3 could also clarify the prevalence of recycled water in this region, but, for this project, sampling was limited by lack of publicly accessible wells.

Groundwater results for the secondary snowbelt were less consistent than for the primary snowbelt regions. In Region 4, south of the primary snowbelt, 7 of the 8 wells were showing similar δ18O signatures in January, although slightly less negative than the wells in Region 2 (Figure 11). The January d-excess for Region 4 shows that 5 of the 8 wells had strong recycled signatures (12.01-15.74‰), and the remaining 3 wells were in the range of 10.01 to 12.00‰, also indicating some recycled water (Figure

16). This is consistent with the recycled precipitation sampled in Kent, within region 4. Region 1 and

Region 5 were more variable, with about half of wells indicating some recycled water based on January d-excess (Figure 16). The wells in Region 1 and 5 could be experiencing some amount of evaporation

75 between the time the precipitation falls and when it reaches the aquifer, causing some of the wells to show an evaporative signature.

Overall, lake effect precipitation is more important than evaporation to the groundwater isotopic values. This shows that the water was recycled from local sources and that the primary snowbelt does have an effect on the local groundwater isoscape. The lithology, depth and elevation for groundwater wells are also important to the isotopic values, as shown by the two wells in Region 2 that are out of sync with the isotopic values of the surrounding wells. Shallow wells could allow evaporation to affect the isotopic values of the water, while deeper wells might be drawing from confined aquifers. The elevation of the well could also influence the amount of lake effect precipitation a given area receives in the study area. To assess the effects of lake effect on the groundwater, the timing of the sample collection is less important than when collecting lake samples. The groundwater samples were collected in January and again in July and the results were very similar to each other, which suggests that most of the study area’s groundwater has a consistent isotopic signature.

The groundwater results from this study are similar to those of Bowen et al. (2012), which looked at the lake effect expressed in Michigan groundwater. The Michigan study had a range of δ18O from -13.4‰ to -5.2‰, and this study had a similar range (-10.5‰ to -3.2‰). The d-excess in the

Michigan study ranged from a low of -7.5‰ to a maximum of 20.8‰, with an average of -10.3‰. In this study, the January groundwater samples have a d-excess range from -6.0 to 15.7‰, with an average of

10.7‰. In July, the average d-excess was also 10.7‰. Both studies support the widespread influence of lake effect precipitation on groundwater in the region downwind of the lake.

Identifying the lake effect signature in the lake samples

For lentic water bodies, variability in isotopes depends on type and size more than position in the primary versus secondary snowbelt. The two lakes within the primary snowbelt (Corning Lake and

Science Center Pond) have more evaporative signatures than the Mantua Bog in the secondary snowbelt

(Figure 22), even though the primary snowbelt location receives greater precipitation. The Science

Center Pond was the smallest lentic body of water in the study. This pond had a large amplitude seasonal variability and more response to precipitation than the larger Corning Lake.

Lake water isotopes in both the primary and secondary snowbelts are affected in a similar manner by evaporation during the warm months of the year. When considering the lake isotope data, the δ18O for May lakes is less variable than July and September (Figure 26-28). However, the lake May samples showed only 6 of 30 lakes having d-excess values of recycled water, and those lakes were all in the secondary snowbelt (Figure 29).

In May, the high elevation primary snowbelt (Region 2) lakes have low variability and depleted isotopic values, similar to the data from the groundwater for Region 2. However, when we look at the d- excess for May in Region 2 we see a different picture than we did with the groundwater d-excess. Based on the d-excess, 5 of the 7 lakes in Region 2 have evaporative to extreme evaporative signature and 2 lakes are considered to have normal water, without signs of evaporation or recycling. In contrast, the d- excess for the groundwater suggests that it is highly recycled (Figure 16). The isotopic signature in the one lake of the low elevation primary snowbelt (Region 3) is similar to the high elevation primary snowbelt (Region 2); both regions start out in May showing evaporative values for the lake d-excess and continue the same pattern through September. The effect of lake effect precipitation can also be seen clearly in the d-excess of the groundwater for Region 4 in the secondary snowbelt (Figure 16), but the

77 lakes in that region did not show the same pattern in May, with variable isotopes and mostly evaporative d-excess values (Figure 29).

In northeast Ohio lakes, evaporation contributes more to the isotopic signature than does the recycling from lake effect precipitation. The relative importance of evaporation depends on the characteristics of the lake and watershed and the timing of sample collection. Small lakes, with small watersheds, can receive large amounts of lake effect precipitation which can alter the isotopic value that evaporation has imparted on a lake over a given season. The amount of evaporation occurring in a lake can be erased by the amount of precipitation that falls in the watershed. Also, if a river runs into or out of the lake, it can alter the evaporative signature expected from an area. In order to assess the effects of lake effect precipitation on lake water isotopes, the timing of lake sampling matters. Sampling lakes earlier in the spring might have shown more of a lake effect signature as a starting value and made the transition into an evaporative signature clearer.

Brooks et al. (2014) sampled four lakes in northeast Ohio during the summer of 2007 as part of a national lake survey. The isotopic range for the δ18O from their study was -3.6 to -8.9‰, d-excess ranged from -5 to 5‰, and the E:I ratio ranged from 0.3 to 0.0. These results were consistent with my findings in 2018. The δ18O ranged from -1.8 to -8.5‰, d-excess ranged -12.1 to 13.0‰ and the E:I ratios ranged from -0.15 to 0.1. Brooks et al. (2014) did not show any negative E:I ratios for the Ohio samples. The ranges for the data varied slightly, but the Brooks et, al (2014) study only collected one sample from the lakes which could account for the variance in the data, and three out of the four sampled lakes were reservoirs, which were excluded from this study.

Testing the hypotheses

My first hypothesis that precipitation in Holden will be isotopically more depleted and have higher d-excess, because it is more northerly and receives more lake influenced precipitation, is not supported by the data from this study. Both the precipitation collectors were located in either the primary snowbelt (Holden) or the secondary snowbelt (Kent), and both received very similar precipitation, with the exception of an occasional storm that didn’t reach both locations (Figure 6, Table 3). The LMWL slope and intercept were also very similar in both locations, and when combined they show that the

LMWL sits slightly above the GMWL (Figure 9), suggesting the precipitation recycled from Lake Erie affects the isotopes at both locations. If I had another precipitation collector farther south in Stark or

Carroll County, I think there would be a different isotopic signature than the recycled lake effect we see across the study area.

The second hypothesis that the isotopic lake effect signature is detectable in groundwater is supported by the data in this study. The d-excess for the January sampling (Figure 16) shows that the recycled precipitation reaches every part of the study area in sufficient amounts to affect groundwater throughout the primary and secondary snowbelts. The primary snowbelt has a depleted isotopic signature that is clearly defined when looking at the January sampling of the groundwater wells (Figure

11) and likely reflects greater recharge from winter precipitation. The largest effects of recycled precipitation on groundwater are seen in the high primary snowbelt (Region 2) and the area immediately to its south (Region 4).

The final hypothesis that the isotopic lake effect signature is detectable in surface water in some parts of the region is weakly supported by the data from this study. There were several lakes that started with a recycled signature but moved to and evaporative signature by the second sampling. The lake sampling started in May; this might have been too late of a start. The lakes had at least a month

79 and a half where they were not covered by ice allowing for a potential recycled signature to be lost to evaporation or early spring storms.

Conclusion

This research has shown that it is possible to identify the signature of lake effect precipitation on the northeast Ohio water isoscape. Precipitation and groundwater isotopes were more clearly affected by recycled precipitation than lake water isotopes.

Comparing the volumes of the precipitation and snow that falls within the primary and secondary snowbelt is an initial indication that the effects of lake effect precipitation should be identifiable across the northeast Ohio water isoscape. However, precipitation δ18O and δ2H did not reveal differences between the lake effect isotopic signature of the primary or secondary snowbelt. Both locations appeared to receive the same precipitation sources in most cases, but different volumes. The d-excess shows that lake effect precipitation that occurs in all four seasons at both locations.

Groundwater isotopes clearly identify where the bulk of the recycled precipitation occurs. The groundwater d-excess shows that recycled precipitation reaches all parts of the study area in sufficient amounts to have a noticeable signature >10‰ in most wells in both the primary and secondary snowbelts. A depleted isotopic signature is clearly defined when looking at the high elevation, primary snowbelt (Region 2) during both the January and July sampling of the groundwater and reflects a higher proportion of recharge from winter precipitation in the primary snowbelt.

The isotopic lake effect precipitation signature does not show up very well in the lake samples, with only 19% of the surveyed lakes having a starting, May isotopic signature of recycled water. By the end of the summer, almost all lakes in the region have an evaporative isotopic signature. Starting the lake sampling earlier in the year and having multiple samplings might show a transition from recycled to evaporative.

Directions for future research

Despite the small scale (<10,000 km2) and relatively low relief in the study area, groundwater and lake isotopes were heterogeneous. The geographic location of northeast Ohio is special in the fact that it can receive precipitation from at least five different source locations on any given day depending on which way the wind blows (Stein et al., 2015). The geologic foundation on which northeast Ohio sits is complex due to its history of glaciation. Groundwater wells can draw from many different lithologies and at many different depths and depending on the configuration water sources can range from ancient aquifers to small perched aquifers. This project has shown that water isotopes are useful tools for understanding the hydrology of northeast Ohio.

Future research could investigate any one aspect of the current research and tease apart the nuances to get a better understanding of the northeast Ohio isoscape. For example, work could focus on understanding which lakes in the study area are groundwater fed and how that affects the effects of evaporation on lake isotopes. The region’s rivers could also be a singular focus for the next graduate student, using the data collected in this project (and presented in the Appendix) as a starting point for understanding their isotopic dynamics.

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Stottlemyer, R., et al. “Nitrogen Mineralization in Boreal Forest Stands of Isle Royale, Northern Michigan.” Boreal Forests and Global Change, 1995, pp. 191–202., doi:10.1007/978-94-017-0942-2_21.

Team, C. 1. (2016, December 08). Where is the Lake Erie snow belt in Ohio? Retrieved from https://www.cleveland19.com/story/33996575/where-is-the-lake-erie-snow-belt-in-ohio/

Tian C, Wang L, Kaseke KF, Bird BW. Stable isotope compositions (δ2H, δ18O and δ17O) of rainfall and snowfall in the central United States. Sci Rep. 2018;8(1):6712. Published 2018 Apr 30. doi:10.1038/s41598-018-25102-7 van Geldern, R., & Barth, J. A. (2012). Optimization of instrument setup and post‐run corrections for oxygen and hydrogen stable isotope measurements of water by isotope ratio infrared spectroscopy (IRIS). Limnology and Oceanography: Methods, 10(12), 1024-1036.

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Appendix A

River Data, Graphs and Maps

-10

-20 LMWL -30 y = 7.7984x + 11.421

-40 H H (‰)

2 -50 δ -60

-70

-80

-90 -14 -12 -10 -8 -6 -4 -2 0 δ18O (‰) Cuyahoga River East Branch Chagrin River Pierson Creek Chagrin River EB Head Chagrin River

Figure A1. Transect river water isotopes compared to the LMWL.

-2

-4

) -6

‰

O O ( 18

δ -8

-10

-12

-14 2/4/18 4/7/18 6/8/18 8/9/18 10/10/18 12/11/18 Date

Cuyahoga River EB Chagrin Mouth Pierson Creek EB Chagrin Head Chagrin River

Figure A2. δ18O (‰) for the transect rivers over time.

-35.0

-40.0

-45.0 y = 7.7984x + 11.421

-50.0 H H (‰)

2 -55.0 δ -60.0

-65.0

-70.0 -10.0 -9.5 -9.0 -8.5 -8.0 -7.5 -7.0 -6.5 -6.0 -5.5 -5.0 δ18O (‰) May River July Rivers Sept Rivers Figure A3. is showing how all the rivers compared to the LMWL for each of the three collection events.

‰) 10

9 D Excess Excess D ( 8

5 5/25/2018 7/28/2018 9/30/2018 Date

Cuyahoga Head Cuyahoga Mouth EB Chagrin Head EB Chagrin Mouth Chagrin Head Chagrin Mouth Mahoning Head Mahoning Mouth Grand Head Grand Mouth Conneaut Head Conneaut Mouth Pierson Ashtabula Big Creek

Figure A4. D-excess is used to determine if the water is recycled, normal or evaporative. May shows that 40% of the samples are recycled, 47% are normal and 13% are evaporative. July has 33% of the samples showing a recycled signature, 40% are normal and 27% are considered evaporative. September has 86% of the samples showing a recycled isotopic signature and the normal and evaporative are 7% each.

13.00

12.00

11.00

10.00 ‰)

9.00

8.00 D Excess Excess D ( avg.

7.00 -10 -9 -8 -7 -6 δ18O avg. (‰)

Cuyahoga H Cuyahoga M Conneaut H Conneaut M Chagrin H Chagrin M EBC H EBC M Grand H Grand M Mahoning H Mahoning M Pierson creek Ashtabula River Big Creek

Figure A5. is showing the variability between the headwaters and the mouth of each river as compared to the δ18O and the D excess (‰).

1.500

1.000

0.500

0.000 O O (‰)

18 -0.500 Δ

-1.000

-1.500

-2.000 1.0 10.0 100.0

DA Ratio Mouth/ Headwaters Conneaut Creek EB Chagrin Grand River Cuyahoga River Chagrin River Mahoning River

Figure A 6 The Δ18O (‰), which is the difference between the mouth and headwaters δ18O (‰) for each of the three collection events versus the drainage area ratio between the mouth and the headwaters displayed on a log scale. The square is the May event, the circle is the July event and the triangle is the September event.

Figure A4. shows the nested watersheds as well as the collection locations marked with a dot in each watershed.

Table A1 River data showing the δ18O, δ2H and d-excess.

DRNAREA Sample 18O 2H Date D excess Location Description Lat Long (km2) 77.00 -6.85 -48.28 5/30/2018 6.48 77 Cuyahoga Mouth 41.24283 -81.5502 1339 77.01 -7.00 -48.41 7/31/2018 7.58 77 Cuyahoga Mouth 41.24283 -81.5502 1339 77.02 -7.42 -49.13 9/28/2018 10.22 77 Cuyahoga Mouth 41.24283 -81.5502 1339 90.00 -7.12 -50.56 10/20/2017 6.39 90 Cuyahoga Head 41.28377 -81.2169 409 90.01 -4.63 -26.76 2/4/2018 10.32 90 Cuyahoga Head 41.28377 -81.2169 409 90.02 -1.97 -22.27 2/17/2018 -6.51 90 Cuyahoga Head 41.28377 -81.2169 409 90.03 -10.14 -69.25 3/3/2018 11.88 90 Cuyahoga Head 41.28377 -81.2169 409 90.04 -10.14 -68.53 3/18/2018 12.57 90 Cuyahoga Head 41.28377 -81.2169 409 90.05 -10.21 -68.48 3/31/2018 13.21 90 Cuyahoga Head 41.28377 -81.2169 409 90.06 -9.47 -64.00 4/14/2018 11.75 90 Cuyahoga Head 41.28377 -81.2169 409 90.07 -9.16 -62.11 4/27/2018 11.16 90 Cuyahoga Head 41.28377 -81.2169 409 90.08 -8.62 -58.52 5/12/2018 10.47 90 Cuyahoga Head 41.28377 -81.2169 409 90.09 -8.02 -54.55 5/27/2018 9.62 90 Cuyahoga Head 41.28377 -81.2169 409 90.10 -8.14 -55.24 6/9/2018 9.90 90 Cuyahoga Head 41.28377 -81.2169 409 90.11 -7.78 -52.55 6/23/2018 9.72 90 Cuyahoga Head 41.28377 -81.2169 409 90.12 -7.01 -46.55 7/7/2018 9.50 90 Cuyahoga Head 41.28377 -81.2169 409

90.13 -6.44 -42.27 7/21/2018 9.25 90 Cuyahoga Head 41.28377 -81.2169 409 90.14 -7.36 -50.24 8/4/2018 8.60 90 Cuyahoga Head 41.28377 -81.2169 409 90.15 -7.29 -50.72 8/18/2018 7.58 90 Cuyahoga Head 41.28377 -81.2169 409 90.16 -6.92 -47.41 9/1/2018 7.96 90 Cuyahoga Head 41.28377 -81.2169 409 90.17 -8.52 -58.14 9/15/2018 10.05 90 Cuyahoga Head 41.28377 -81.2169 409 90.18 -7.82 -49.91 9/30/2018 12.64 90 Cuyahoga Head 41.28377 -81.2169 409 90.19 -7.70 -51.45 10/13/2018 10.13 90 Cuyahoga Head 41.28377 -81.2169 409 90.20 -7.82 -53.93 10/27/2018 8.62 90 Cuyahoga Head 41.28377 -81.2169 409 90.21 -9.13 -61.21 11/10/2018 11.85 90 Cuyahoga Head 41.28377 -81.2169 409 90.22 -9.61 -65.11 11/24/2018 11.76 90 Cuyahoga Head 41.28377 -81.2169 409 90.23 -9.92 -67.22 12/8/2018 12.12 90 Cuyahoga Head 41.28377 -81.2169 409 90.24 -10.68 -72.99 12/22/2018 12.42 90 Cuyahoga Head 41.28377 -81.2169 409 Chagrin River East 123.00 -9.67 -63.55 12/13/2017 13.83 123 branch Mouth 41.62788 -81.3114 88 Chagrin River East 123.01 -6.31 -40.73 1/12/2018 9.72 123 branch Mouth 41.62788 -81.3114 88 Chagrin River East 123.02 -5.28 -39.15 2/4/2018 3.13 123 branch Mouth 41.62788 -81.3114 88 Chagrin River East 123.03 -11.13 -73.85 2/17/2018 15.17 123 branch Mouth 41.62788 -81.3114 88 Chagrin River East 123.04 -11.19 -76.16 3/3/2018 13.37 123 branch Mouth 41.62788 -81.3114 88 Chagrin River East 123.05 -10.76 -71.96 3/18/2018 14.12 123 branch Mouth 41.62788 -81.3114 88 Chagrin River East 123.06 -10.73 -71.87 3/31/2018 13.97 123 branch Mouth 41.62788 -81.3114 88 Chagrin River East 123.07 -10.06 -66.78 4/14/2018 13.68 123 branch Mouth 41.62788 -81.3114 88 Chagrin River East 123.08 -9.86 -65.71 4/27/2018 13.21 123 branch Mouth 41.62788 -81.3114 88 Chagrin River East 123.09 -9.26 -61.47 5/12/2018 12.63 123 branch Mouth 41.62788 -81.3114 88 Chagrin River East 123.10 -9.29 -61.28 5/27/2018 13.06 123 branch Mouth 41.62788 -81.3114 88 Chagrin River East 123.11 -9.36 -61.78 6/9/2018 13.12 123 branch Mouth 41.62788 -81.3114 88 Chagrin River East 123.12 -9.23 -60.88 6/23/2018 12.96 123 branch Mouth 41.62788 -81.3114 88 Chagrin River East 123.13 -7.34 -47.47 7/7/2018 11.24 123 branch Mouth 41.62788 -81.3114 88 Chagrin River East 123.14 -8.56 -56.24 7/21/2018 12.21 123 branch Mouth 41.62788 -81.3114 88 Chagrin River East 123.15 -9.04 -59.88 8/4/2018 12.47 123 branch Mouth 41.62788 -81.3114 88 Chagrin River East 123.16 -9.23 -61.02 8/18/2018 12.85 123 branch Mouth 41.62788 -81.3114 88 Chagrin River East 123.17 -8.07 -52.13 9/1/2018 12.43 123 branch Mouth 41.62788 -81.3114 88 Chagrin River East 123.18 -8.96 -59.28 9/15/2018 12.40 123 branch Mouth 41.62788 -81.3114 88

Chagrin River East 123.19 -8.65 -56.65 9/29/2018 12.57 123 branch Mouth 41.62788 -81.3114 88 Chagrin River East 123.20 -10.62 -68.26 10/13/2018 16.67 123 branch Mouth 41.62788 -81.3114 88 Chagrin River East 123.21 -9.61 -62.92 10/27/2018 13.98 123 branch Mouth 41.62788 -81.3114 88 Chagrin River East 123.22 -10.05 -66.15 11/10/2018 14.26 123 branch Mouth 41.62788 -81.3114 88 Chagrin River East 123.23 -10.00 -66.13 11/24/2018 13.84 123 branch Mouth 41.62788 -81.3114 88 Chagrin River East 123.24 -10.22 -67.95 12/8/2018 13.81 123 branch Mouth 41.62788 -81.3114 88 Chagrin River East 123.25 -11.52 -78.27 12/22/2018 13.93 123 branch Mouth 41.62788 -81.3114 88 141.00 -7.78 -56.17 1/1/2018 6.04 141 Big Creek 41.44261 -81.7549 54 141.01 -7.48 -52.48 5/31/2018 7.39 141 Big Creek 41.44261 -81.7549 54 141.02 -6.73 -47.99 7/31/2018 5.88 141 Big Creek 41.44261 -81.7549 54 141.03 -7.59 -50.17 9/28/2018 10.57 141 Big Creek 41.44261 -81.7549 54 Conneaut Creek 214.00 -14.82 -96.60 1/12/2018 21.92 214 Mouth 41.9376 -80.5635 469 Conneaut Creek 214.01 -11.99 -80.69 2/17/2018 15.21 214 Mouth 41.9376 -80.5635 469 Conneaut Creek 214.02 -8.82 -58.84 5/30/2018 11.72 214 Mouth 41.9376 -80.5635 469 Conneaut Creek 214.03 -7.84 -52.85 7/30/2018 9.88 214 Mouth 41.9376 -80.5635 469 Conneaut Creek 214.04 -8.53 -55.14 9/29/2018 13.12 214 Mouth 41.9376 -80.5635 469 Conneaut Creek 215.00 -14.97 -97.48 1/12/2018 22.27 215 Head 41.89432 -80.5746 407 Conneaut Creek 215.01 -11.96 -80.51 2/17/2018 15.20 215 Head 41.89432 -80.5746 407 Conneaut Creek 215.02 -8.82 -58.46 5/30/2018 12.09 215 Head 41.89432 -80.5746 407 Conneaut Creek 215.03 -7.75 -51.60 7/30/2018 10.37 215 Head 41.89432 -80.5746 407 Conneaut Creek 215.04 -8.53 -55.03 9/29/2018 13.23 215 Head 41.89432 -80.5746 407 217.00 -14.36 -93.66 1/12/2018 21.21 217 Ashtabula 41.83603 -80.684 14 217.01 -11.89 -79.86 2/17/2018 15.24 217 Ashtabula 41.83603 -80.684 14 217.02 -7.86 -53.47 5/30/2018 9.45 217 Ashtabula 41.83603 -80.684 14 217.03 -7.89 -52.58 7/30/2018 10.55 217 Ashtabula 41.83603 -80.684 14 217.04 -7.89 -51.70 9/29/2018 11.46 217 Ashtabula 41.83603 -80.684 14 221.00 -11.04 -72.84 1/12/2018 15.52 221 Pierson Creek 41.628 -81.3149 6 221.01 -10.83 -76.30 2/4/2018 10.34 221 Pierson Creek 41.628 -81.3149 6 221.02 -10.72 -74.16 2/17/2018 11.60 221 Pierson Creek 41.628 -81.3149 6 221.03 -10.65 -72.01 3/3/2018 13.16 221 Pierson Creek 41.628 -81.3149 6 221.04 -10.62 -71.14 3/18/2018 13.84 221 Pierson Creek 41.628 -81.3149 6 221.05 -10.33 -69.10 3/31/2018 13.57 221 Pierson Creek 41.628 -81.3149 6

221.06 -9.81 -65.12 4/14/2018 13.35 221 Pierson Creek 41.628 -81.3149 6 221.07 -9.62 -64.09 4/27/2018 12.86 221 Pierson Creek 41.628 -81.3149 6 221.08 -9.20 -61.03 5/12/2018 12.58 221 Pierson Creek 41.628 -81.3149 6 221.09 -9.14 -60.34 5/27/2018 12.74 221 Pierson Creek 41.628 -81.3149 6 221.10 -9.33 -61.54 6/9/2018 13.14 221 Pierson Creek 41.628 -81.3149 6 221.11 -10.04 -66.67 6/23/2018 13.64 221 Pierson Creek 41.628 -81.3149 6 221.12 -7.36 -48.98 7/7/2018 9.91 221 Pierson Creek 41.628 -81.3149 6 221.13 -9.34 -61.34 7/21/2018 13.41 221 Pierson Creek 41.628 -81.3149 6 221.14 -9.33 -61.65 8/4/2018 13.02 221 Pierson Creek 41.628 -81.3149 6 221.15 -9.43 -62.11 8/18/2018 13.30 221 Pierson Creek 41.628 -81.3149 6 221.16 -8.10 -53.37 9/1/2018 11.44 221 Pierson Creek 41.628 -81.3149 6 221.17 -8.41 -56.36 9/15/2018 10.89 221 Pierson Creek 41.628 -81.3149 6 221.18 -7.91 -53.04 9/29/2018 10.25 221 Pierson Creek 41.628 -81.3149 6 221.19 -10.46 -66.81 10/13/2018 16.91 221 Pierson Creek 41.628 -81.3149 6 221.20 -9.13 -59.87 10/27/2018 13.16 221 Pierson Creek 41.628 -81.3149 6 221.21 -9.67 -63.88 11/10/2018 13.48 221 Pierson Creek 41.628 -81.3149 6 221.22 -9.78 -64.82 11/24/2018 13.41 221 Pierson Creek 41.628 -81.3149 6 221.23 -9.80 -65.43 12/8/2018 12.96 221 Pierson Creek 41.628 -81.3149 6 221.24 -10.64 -72.62 12/22/2018 12.54 221 Pierson Creek 41.628 -81.3149 6 Chagrin River East 222.00 -10.27 -67.19 2/4/2018 14.94 222 branch Head 41.5947 -81.2966 58 Chagrin River East 222.01 -11.01 -73.23 2/17/2018 14.88 222 branch Head 41.5947 -81.2966 58 Chagrin River East 222.02 -11.16 -75.57 3/3/2018 13.68 222 branch Head 41.5947 -81.2966 58 Chagrin River East 222.03 -10.71 -71.33 3/18/2018 14.37 222 branch Head 41.5947 -81.2966 58 Chagrin River East 222.04 -10.71 -71.33 3/31/2018 14.38 222 branch Head 41.5947 -81.2966 58 Chagrin River East 222.04 -10.71 -71.33 3/31/2018 14.38 222 branch Head 41.5947 -81.2966 58 Chagrin River East 222.05 -10.03 -66.48 4/14/2018 13.79 222 branch Head 41.5947 -81.2966 58 Chagrin River East 222.06 -9.85 -65.64 4/27/2018 13.18 222 branch Head 41.5947 -81.2966 58 Chagrin River East 222.07 -9.32 -61.85 5/12/2018 12.71 222 branch Head 41.5947 -81.2966 58 Chagrin River East 222.08 -9.36 -61.72 5/27/2018 13.18 222 branch Head 41.5947 -81.2966 58 Chagrin River East 222.09 -9.47 -62.42 6/9/2018 13.34 222 branch Head 41.5947 -81.2966 58 Chagrin River East 222.10 -9.39 -61.61 6/23/2018 13.50 222 branch Head 41.5947 -81.2966 58 Chagrin River East 222.11 -7.53 -48.73 7/7/2018 11.51 222 branch Head 41.5947 -81.2966 58 Chagrin River East 222.12 -8.74 -57.09 7/21/2018 12.82 222 branch Head 41.5947 -81.2966 58

Chagrin River East 222.13 -9.20 -60.61 8/4/2018 12.97 222 branch Head 41.5947 -81.2966 58 Chagrin River East 222.14 -9.38 -61.75 8/18/2018 13.32 222 branch Head 41.5947 -81.2966 58 Chagrin River East 222.15 -8.39 -54.05 9/1/2018 13.05 222 branch Head 41.5947 -81.2966 58 Chagrin River East 222.16 -9.07 -59.99 9/15/2018 12.56 222 branch Head 41.5947 -81.2966 58 Chagrin River East 222.17 -8.44 -55.92 9/29/2018 11.60 222 branch Head 41.5947 -81.2966 58 Chagrin River East 222.18 -11.89 -77.15 10/13/2018 17.94 222 branch Head 41.5947 -81.2966 58 Chagrin River East 222.19 -9.61 -63.41 10/27/2018 13.44 222 branch Head 41.5947 -81.2966 58 Chagrin River East 222.20 -10.11 -66.69 11/10/2018 14.16 222 branch Head 41.5947 -81.2966 58 Chagrin River East 222.21 -10.28 -68.00 11/24/2018 14.27 222 branch Head 41.5947 -81.2966 58 Chagrin River East 222.22 -10.39 -68.54 12/8/2018 14.62 222 branch Head 41.5947 -81.2966 58 Chagrin River East 222.23 -11.49 -77.94 12/22/2018 13.98 222 branch Head 41.5947 -81.2966 58 Chagrin River 223.00 -10.68 -70.25 2/4/2018 15.17 223 Head 41.53664 -81.2436 30 Chagrin River 223.01 -11.59 -77.67 2/17/2018 15.08 223 Head 41.53664 -81.2436 30 Chagrin River 223.02 -10.68 -71.88 3/3/2018 13.59 223 Head 41.53664 -81.2436 30 Chagrin River 223.03 -10.88 -74.25 3/18/2018 12.77 223 Head 41.53664 -81.2436 30 Chagrin River 223.04 -10.79 -72.58 3/31/2018 13.76 223 Head 41.53664 -81.2436 30 Chagrin River 223.05 -9.96 -67.27 4/14/2018 12.44 223 Head 41.53664 -81.2436 30 Chagrin River 223.06 -9.31 -62.62 4/27/2018 11.85 223 Head 41.53664 -81.2436 30 Chagrin River 223.07 -8.47 -58.11 5/12/2018 9.67 223 Head 41.53664 -81.2436 30 Chagrin River 223.08 -7.77 -52.97 5/27/2018 9.16 223 Head 41.53664 -81.2436 30 Chagrin River 223.09 -7.40 -51.51 6/9/2018 7.67 223 Head 41.53664 -81.2436 30 Chagrin River 223.10 -7.08 -49.77 6/23/2018 6.89 223 Head 41.53664 -81.2436 30 Chagrin River 223.11 -6.52 -45.29 7/7/2018 6.85 223 Head 41.53664 -81.2436 30 Chagrin River 223.12 -5.58 -38.47 7/21/2018 6.21 223 Head 41.53664 -81.2436 30 Chagrin River 223.13 -5.89 -40.95 7/30/2018 6.15 223 Head 41.53664 -81.2436 30 Chagrin River 223.14 -5.74 -40.72 8/18/2018 5.20 223 Head 41.53664 -81.2436 30

Chagrin River 223.15 -5.48 -38.94 9/1/2018 4.86 223 Head 41.53664 -81.2436 30 Chagrin River 223.16 -6.31 -44.19 9/15/2018 6.28 223 Head 41.53664 -81.2436 30 Chagrin River 223.17 -7.04 -47.17 9/29/2018 9.15 223 Head 41.53664 -81.2436 30 Chagrin River 223.18 -7.63 -51.28 10/13/2018 9.77 223 Head 41.53664 -81.2436 30 Chagrin River 223.19 -7.39 -50.21 10/27/2018 8.88 223 Head 41.53664 -81.2436 30 Chagrin River 223.20 -9.53 -63.80 11/10/2018 12.42 223 Head 41.53664 -81.2436 30 Chagrin River 223.21 -9.89 -66.63 11/24/2018 12.52 223 Head 41.53664 -81.2436 30 Chagrin River 223.22 -10.70 -71.80 12/8/2018 13.82 223 Head 41.53664 -81.2436 30 Chagrin River 223.23 -10.77 -73.11 12/22/2018 13.04 223 Head 41.53664 -81.2436 30 Grand River 225.00 -11.56 -77.52 2/17/2018 14.93 225 Mouth 41.72581 -81.1846 1629 Grand River 225.01 -7.27 -49.76 5/30/2018 8.37 225 Mouth 41.72581 -81.1846 1629 Grand River 225.02 -7.15 -48.52 7/30/2018 8.71 225 Mouth 41.72581 -81.1846 1629 Grand River 225.03 -7.64 -48.66 9/29/2018 12.45 225 Mouth 41.72581 -81.1846 1629 227.00 -11.09 -74.70 2/17/2018 14.01 227 Grand River Head 41.64984 -80.8695 754 227.01 -7.42 -50.55 5/30/2018 8.81 227 Grand River Head 41.64984 -80.8695 754 227.02 -7.15 -47.82 8/4/2018 9.40 227 Grand River Head 41.64984 -80.8695 754 227.03 -7.35 -46.51 9/29/2018 12.31 227 Grand River Head 41.64984 -80.8695 754 Mahoning River 232.00 -7.09 -48.32 5/30/2018 8.43 232 Head 41.0052 -81.0711 51 Mahoning River 232.01 -5.44 -38.37 7/29/2018 5.14 232 Head 41.0052 -81.0711 51 Mahoning River 232.02 -6.92 -44.00 9/28/2018 11.40 232 Head 41.0052 -81.0711 51 Mahoning River 236.00 -7.96 -53.99 5/30/2018 9.66 236 Mouth 41.05973 -80.5852 2642 Mahoning River 236.01 -7.19 -48.75 7/29/2018 8.75 236 Mouth 41.05973 -80.5852 2642 Mahoning River 236.02 -6.67 -45.80 9/29/2018 7.54 236 Mouth 41.05973 -80.5852 2642 Chagrin River 242.00 -8.10 -54.60 5/30/2018 10.19 242 Mouth 41.62852 -81.3998 508 Chagrin River 242.01 -7.15 -48.28 7/30/2018 8.90 242 Mouth 41.62852 -81.3998 508 Chagrin River 242.02 -7.36 -48.77 9/29/2018 10.11 242 Mouth 41.62852 -81.3998 508

Appendix B

Transect Data

Table B1 lists transect sites data

Identifier d18O d2H Date Location 11.00 -7.6102 -51.7867 8/26/2017 Mantua Bog on Peck RD. 11.02 -8.02424 -54.9761 10/20/2017 Mantua Bog on Peck RD. 11.03 -9.55251 -62.544 2/4/2018 Mantua Bog on Peck RD. 11.04 -9.56718 -64.7647 2/17/2018 Mantua Bog on Peck RD. 11.05 -10.2438 -70.0228 3/3/2018 Mantua Bog on Peck RD. 11.06 -9.65514 -64.4634 3/18/2018 Mantua Bog on Peck RD. 11.07 -9.44744 -63.0799 3/31/2018 Mantua Bog on Peck RD. 11.08 -8.98853 -59.8615 4/14/2018 Mantua Bog on Peck RD. 11.09 -8.89037 -59.574 4/27/2018 Mantua Bog on Peck RD. 11.10 -7.90412 -54.3553 5/12/2018 Mantua Bog on Peck RD. 11.11 -7.89659 -53.8441 5/27/2018 Mantua Bog on Peck RD. 11.12 -8.19114 -55.1188 6/9/2018 Mantua Bog on Peck RD. 11.13 -8.06821 -53.5443 6/23/2018 Mantua Bog on Peck RD. 11.14 -7.01291 -46.1941 7/7/2018 Mantua Bog on Peck RD. 11.15 -7.62723 -51.2179 7/21/2018 Mantua Bog on Peck RD. 11.16 -8.18549 -55.0054 8/4/2018 Mantua Bog on Peck RD. 11.17 -8.22273 -55.2416 8/18/2018 Mantua Bog on Peck RD. 11.18 -7.55075 -49.5271 9/1/2018 Mantua Bog on Peck RD. 11.19 -8.9492 -59.7823 9/15/2018 Mantua Bog on Peck RD. 11.20 -8.24764 -54.4464 9/30/2018 Mantua Bog on Peck RD. 11.21 -8.38526 -55.3514 10/13/2018 Mantua Bog on Peck RD. 11.22 -8.93011 -59.1239 10/27/2018 Mantua Bog on Peck RD. 11.23 -9.70219 -63.6651 11/10/2018 Mantua Bog on Peck RD. 11.24 -9.89534 -65.3524 11/24/2018 Mantua Bog on Peck RD. 11.25 -9.74681 -64.9553 12/8/2018 Mantua Bog on Peck RD. 11.26 -10.5979 -71.3333 12/22/2018 Mantua Bog on Peck RD. 90.00 -7.11939 -50.5647 10/20/2017 Cuyahoga Head 90.01 -4.63423 -26.758 2/4/2018 Cuyahoga Head 90.02 -1.9689 -22.2652 2/17/2018 Cuyahoga Head 90.03 -10.1409 -69.2481 3/3/2018 Cuyahoga Head 90.04 -10.137 -68.5306 3/18/2018 Cuyahoga Head 90.05 -10.2113 -68.4767 3/31/2018 Cuyahoga Head 90.06 -9.46898 -64.0002 4/14/2018 Cuyahoga Head 90.07 -9.15762 -62.1054 4/27/2018 Cuyahoga Head 90.08 -8.62433 -58.5246 5/12/2018 Cuyahoga Head 90.09 -8.02108 -54.5489 5/27/2018 Cuyahoga Head 90.10 -8.14256 -55.2442 6/9/2018 Cuyahoga Head

90.11 -7.78311 -52.5489 6/23/2018 Cuyahoga Head 90.12 -7.00667 -46.5496 7/7/2018 Cuyahoga Head 90.13 -6.43909 -42.2676 7/21/2018 Cuyahoga Head 90.14 -7.35515 -50.2405 8/4/2018 Cuyahoga Head 90.15 -7.28766 -50.7185 8/18/2018 Cuyahoga Head 90.16 -6.92108 -47.4096 9/1/2018 Cuyahoga Head 90.17 -8.52313 -58.1374 9/15/2018 Cuyahoga Head 90.18 -7.76193 -49.9347 9/30/2018 Cuyahoga Head 90.18 -7.69719 -51.4515 9/30/2018 Cuyahoga Head 90.19 -7.81892 -53.9285 10/13/2018 Cuyahoga Head 90.20 -9.13252 -61.2063 10/27/2018 Cuyahoga Head 90.21 -9.60918 -65.112 11/10/2018 Cuyahoga Head 90.23 -9.91686 -67.2165 12/8/2018 Cuyahoga Head 90.24 -10.6768 -72.9905 12/22/2018 Cuyahoga Head 120.00 -17.7535 -118.892 12/13/2017 Holden Precipitation 120.01 -16.7246 -115.997 12/29/2017 Holden Precipitation 120.02 -12.4934 -81.9049 1/12/2018 Holden Precipitation 120.03 -5.05204 -38.8053 2/4/2018 Holden Precipitation 120.04 -12.6853 -90.7057 2/17/2018 Holden Precipitation 120.05 -10.8518 -76.113 3/3/2018 Holden Precipitation 120.06 -14.2677 -100.457 3/18/2018 Holden Precipitation 120.07 -8.68984 -54.5516 3/31/2018 Holden Precipitation 120.08 -7.63552 -48.0381 4/14/2018 Holden Precipitation 120.09 -8.88374 -57.9906 4/27/2018 Holden Precipitation 120.10 -4.44818 -21.8969 5/12/2018 Holden Precipitation 120.11 -5.93674 -35.7805 5/27/2018 Holden Precipitation 120.12 -9.19361 -57.5115 6/9/2018 Holden Precipitation 120.13 -6.77951 -40.1892 6/23/2018 Holden Precipitation 120.14 -5.76486 -34.2166 7/7/2018 Holden Precipitation 120.15 -3.42619 -15.7046 7/21/2018 Holden Precipitation 120.16 -9.51083 -62.7663 8/4/2018 Holden Precipitation 120.17 -4.82053 -25.4763 8/18/2018 Holden Precipitation 120.18 -6.77032 -38.4891 9/1/2018 Holden Precipitation 120.19 -11.5059 -79.9749 9/15/2018 Holden Precipitation 120.20 -7.34937 -45.5023 9/29/2018 Holden Precipitation 120.21 -7.75677 -43.72 10/13/2018 Holden Precipitation 120.22 -13.9931 -94.5637 10/27/2018 Holden Precipitation 120.23 -12.7544 -85.2979 11/10/2018 Holden Precipitation 120.25 -17.4556 -125.854 12/8/2018 Holden Precipitation 120.25 -13.4079 -91.35 12/8/2018 Holden Precipitation 120.26 -15.8268 -114.365 12/22/2018 Holden Precipitation

121.00 -9.71036 -64.3442 12/13/2017 Long Science Ctr Pond 121.01 -6.21297 -40.7846 12/29/2017 Long Science Ctr Pond 121.02 -10.7941 -73.2957 1/12/2018 Long Science Ctr Pond 121.03 -11.4735 -82.9566 2/17/2018 Long Science Ctr Pond 121.04 -11.3311 -77.4325 3/3/2018 Long Science Ctr Pond 121.05 -10.5181 -69.6488 3/31/2018 Long Science Ctr Pond 121.06 -9.43835 -64.6031 4/14/2018 Long Science Ctr Pond 121.07 -8.90311 -61.4961 4/27/2018 Long Science Ctr Pond 121.08 -7.19161 -49.9513 5/12/2018 Long Science Ctr Pond 121.09 -6.06287 -43.2368 5/27/2018 Long Science Ctr Pond 121.10 -6.20117 -45.1169 6/9/2018 Long Science Ctr Pond 121.11 -11.7467 -80.3453 6/23/2018 Long Science Ctr Pond 121.12 -5.13459 -33.2216 7/7/2018 Long Science Ctr Pond 121.13 -4.29201 -30.7295 7/21/2018 Long Science Ctr Pond 121.14 -4.89675 -35.9661 8/4/2018 Long Science Ctr Pond 121.15 -4.74913 -34.0861 8/18/2018 Long Science Ctr Pond 121.16 -5.08985 -32.8992 9/1/2018 Long Science Ctr Pond 121.17 -6.92968 -47.4558 9/15/2018 Long Science Ctr Pond 121.18 -7.27002 -48.0786 9/29/2018 Long Science Ctr Pond 121.19 -7.03432 -43.539 10/13/2018 Long Science Ctr Pond 121.20 -8.11197 -52.9286 10/27/2018 Long Science Ctr Pond 121.21 -9.74539 -64.4299 11/10/2018 Long Science Ctr Pond 121.22 -10.65 -72.089 11/24/2018 Long Science Ctr Pond 121.24 -13.4062 -94.3702 12/22/2018 Long Science Ctr Pond 122.00 -10.07 -65.3621 12/13/2017 Long Science Ctr GW 122.02 -6.23449 -40.2958 1/12/2018 Long Science Ctr GW 122.03 -8.93931 -77.0069 2/4/2018 Long Science Ctr GW 122.04 -10.851 -78.1347 2/17/2018 Long Science Ctr GW 122.05 -10.2042 -66.2377 3/3/2018 Long Science Ctr GW 122.06 -10.1418 -65.7321 3/18/2018 Long Science Ctr GW 122.07 -10.1117 -65.3362 3/31/2018 Long Science Ctr GW 122.08 -10.0306 -64.9834 4/14/2018 Long Science Ctr GW 122.09 -9.97139 -64.6124 4/27/2018 Long Science Ctr GW 122.10 -9.93708 -64.3967 5/12/2018 Long Science Ctr GW 122.11 -9.98662 -64.6702 5/27/2018 Long Science Ctr GW 122.12 -9.96329 -64.5148 6/9/2018 Long Science Ctr GW 122.13 -9.93523 -64.5079 6/23/2018 Long Science Ctr GW 122.14 -9.94232 -64.4408 7/7/2018 Long Science Ctr GW 122.15 -9.96213 -64.7008 7/21/2018 Long Science Ctr GW 122.16 -9.96403 -64.9739 8/4/2018 Long Science Ctr GW 122.17 -9.96093 -64.6352 8/18/2018 Long Science Ctr GW

122.18 -10.0233 -65.0349 9/1/2018 Long Science Ctr GW 122.19 -9.95317 -64.846 9/15/2018 Long Science Ctr GW 122.20 -9.91666 -64.2675 9/29/2018 Long Science Ctr GW 122.21 -9.96753 -64.3237 10/13/2018 Long Science Ctr GW 122.22 -9.93383 -64.4781 10/27/2018 Long Science Ctr GW 122.23 -9.91774 -64.3191 11/10/2018 Long Science Ctr GW 122.24 -9.91931 -64.4259 11/24/2018 Long Science Ctr GW 122.26 -9.98896 -64.7855 12/22/2018 Long Science Ctr GW 123.00 -9.67269 -63.5517 12/13/2017 East Branch Chagrin River Mouth 123.01 -6.30598 -40.7275 1/12/2018 East Branch Chagrin River Mouth 123.02 -5.28466 -39.1456 2/4/2018 East Branch Chagrin River Mouth 123.03 -11.1278 -73.849 2/17/2018 East Branch Chagrin River Mouth 123.04 -11.1915 -76.1609 3/3/2018 East Branch Chagrin River Mouth 123.05 -10.7591 -71.9568 3/18/2018 East Branch Chagrin River Mouth 123.06 -10.7303 -71.8738 3/31/2018 East Branch Chagrin River Mouth 123.07 -10.0586 -66.785 4/14/2018 East Branch Chagrin River Mouth 123.08 -9.86483 -65.708 4/27/2018 East Branch Chagrin River Mouth 123.09 -9.2622 -61.4674 5/12/2018 East Branch Chagrin River Mouth 123.10 -9.293 -61.2846 5/27/2018 East Branch Chagrin River Mouth 123.11 -9.3619 -61.7787 6/9/2018 East Branch Chagrin River Mouth 123.12 -9.23019 -60.8845 6/23/2018 East Branch Chagrin River Mouth 123.13 -7.33914 -47.4715 7/7/2018 East Branch Chagrin River Mouth 123.14 -8.5565 -56.241 7/21/2018 East Branch Chagrin River Mouth 123.15 -9.04329 -59.8753 8/4/2018 East Branch Chagrin River Mouth 123.16 -9.23304 -61.0176 8/18/2018 East Branch Chagrin River Mouth 123.17 -8.0708 -52.1322 9/1/2018 East Branch Chagrin River Mouth 123.18 -8.96009 -59.2771 9/15/2018 East Branch Chagrin River Mouth 123.19 -8.65206 -56.6456 9/29/2018 East Branch Chagrin River Mouth 123.20 -10.6168 -68.2627 10/13/2018 East Branch Chagrin River Mouth 123.21 -9.61272 -62.9241 10/27/2018 East Branch Chagrin River Mouth 123.22 -10.0503 -66.1456 11/10/2018 East Branch Chagrin River Mouth 123.23 -9.99626 -66.1335 11/24/2018 East Branch Chagrin River Mouth 123.24 -10.2203 -67.9503 12/8/2018 East Branch Chagrin River Mouth 123.25 -11.524 -78.2656 12/22/2018 East Branch Chagrin River Mouth 221.00 -11.0449 -72.8367 1/12/2018 Pierson Creek 221.01 -10.83 -76.3047 2/4/2018 Pierson Creek 221.03 -10.6464 -72.0111 3/3/2018 Pierson Creek 221.04 -10.6216 -71.1364 3/18/2018 Pierson Creek 221.05 -10.3334 -69.0962 3/31/2018 Pierson Creek 221.06 -9.80853 -65.1163 4/14/2018 Pierson Creek 221.07 -9.61855 -64.0931 4/27/2018 Pierson Creek

100

221.08 -9.20133 -61.0266 5/12/2018 Pierson Creek 221.09 -9.13551 -60.3417 5/27/2018 Pierson Creek 221.10 -9.33409 -61.5357 6/9/2018 Pierson Creek 221.11 -10.0388 -66.6695 6/23/2018 Pierson Creek 221.12 -7.36056 -48.9754 7/7/2018 Pierson Creek 221.13 -9.34353 -61.3406 7/21/2018 Pierson Creek 221.14 -9.33428 -61.6549 8/4/2018 Pierson Creek 221.15 -9.42594 -62.1053 8/18/2018 Pierson Creek 221.16 -8.10115 -53.3705 9/1/2018 Pierson Creek 221.17 -8.40595 -56.3557 9/15/2018 Pierson Creek 221.18 -7.9109 -53.0396 9/29/2018 Pierson Creek 221.19 -10.4647 -66.8124 10/13/2018 Pierson Creek 221.20 -9.12911 -59.8729 10/27/2018 Pierson Creek 221.21 -9.67047 -63.8847 11/10/2018 Pierson Creek 221.22 -9.77875 -64.8166 11/24/2018 Pierson Creek 221.23 -9.79968 -65.4333 12/8/2018 Pierson Creek 221.24 -10.6447 -72.6192 12/22/2018 Pierson Creek 222.00 -10.2664 -67.1925 2/4/2018 East Branch Chagrin River Head 222.01 -11.0142 -73.2303 2/17/2018 East Branch Chagrin River Head 222.02 -11.1564 -75.5672 3/3/2018 East Branch Chagrin River Head 222.03 -10.713 -71.334 3/18/2018 East Branch Chagrin River Head 222.04 -10.7144 -71.3327 3/31/2018 East Branch Chagrin River Head 222.05 -10.0342 -66.4842 4/14/2018 East Branch Chagrin River Head 222.06 -9.85339 -65.6448 4/27/2018 East Branch Chagrin River Head 222.07 -9.3205 -61.8549 5/12/2018 East Branch Chagrin River Head 222.08 -9.36296 -61.7225 5/27/2018 East Branch Chagrin River Head 222.09 -9.4699 -62.4165 6/9/2018 East Branch Chagrin River Head 222.10 -9.38926 -61.6138 6/23/2018 East Branch Chagrin River Head 222.11 -7.52998 -48.7324 7/7/2018 East Branch Chagrin River Head 222.12 -8.73891 -57.09 7/21/2018 East Branch Chagrin River Head 222.13 -9.19721 -60.6106 8/4/2018 East Branch Chagrin River Head 222.14 -9.38392 -61.7468 8/18/2018 East Branch Chagrin River Head 222.15 -8.3865 -54.0463 9/1/2018 East Branch Chagrin River Head 222.16 -9.06778 -59.9872 9/15/2018 East Branch Chagrin River Head 222.17 -8.44033 -55.9204 9/29/2018 East Branch Chagrin River Head 222.18 -11.8871 -77.155 10/13/2018 East Branch Chagrin River Head 222.19 -9.6063 -63.4123 10/27/2018 East Branch Chagrin River Head 222.20 -10.1062 -66.6873 11/10/2018 East Branch Chagrin River Head 222.21 -10.2828 -67.9961 11/24/2018 East Branch Chagrin River Head 222.22 -10.3939 -68.5352 12/8/2018 East Branch Chagrin River Head 222.23 -11.4896 -77.939 12/22/2018 East Branch Chagrin River Head

101

223.00 -10.6774 -70.2474 2/4/2018 Chagrin River Head 223.01 -11.5939 -77.6681 2/17/2018 Chagrin River Head 223.02 -10.6836 -71.8762 3/3/2018 Chagrin River Head 223.03 -10.8768 -74.2451 3/18/2018 Chagrin River Head 223.04 -10.7933 -72.5846 3/31/2018 Chagrin River Head 223.05 -9.96373 -67.2677 4/14/2018 Chagrin River Head 223.06 -9.30954 -62.6218 4/27/2018 Chagrin River Head 223.07 -8.47326 -58.1126 5/12/2018 Chagrin River Head 223.08 -7.76688 -52.9739 5/27/2018 Chagrin River Head 223.09 -7.39728 -51.507 6/9/2018 Chagrin River Head 223.10 -7.08248 -49.7705 6/23/2018 Chagrin River Head 223.11 -6.51867 -45.2949 7/7/2018 Chagrin River Head 223.12 -5.58447 -38.4672 7/21/2018 Chagrin River Head 223.13 -5.8876 -40.9472 7/30/2018 Chagrin River Head 223.14 -5.74008 -40.7245 8/18/2018 Chagrin River Head 223.15 -5.47532 -38.9381 9/1/2018 Chagrin River Head 223.16 -6.3093 -44.1937 9/15/2018 Chagrin River Head 223.17 -7.03963 -47.1656 9/29/2018 Chagrin River Head 223.18 -7.63156 -51.279 10/13/2018 Chagrin River Head 223.19 -7.38587 -50.2066 10/27/2018 Chagrin River Head 223.20 -9.52791 -63.7989 11/10/2018 Chagrin River Head 223.21 -9.89377 -66.63 11/24/2018 Chagrin River Head 223.22 -10.7025 -71.802 12/8/2018 Chagrin River Head 223.23 -10.7689 -73.1138 12/22/2018 Chagrin River Head 224.00 -9.68932 -63.0883 2/4/2018 Shell Gas Station GW 224.01 -9.74878 -63.3468 2/17/2018 Shell Gas Station GW 224.02 -9.77542 -63.3241 3/3/2018 Shell Gas Station GW 224.03 -9.68785 -62.9707 3/18/2018 Shell Gas Station GW 224.04 -9.73394 -63.0115 3/31/2018 Shell Gas Station GW 224.05 -9.7016 -63.1218 4/14/2018 Shell Gas Station GW 224.06 -9.66018 -62.9097 4/27/2018 Shell Gas Station GW 224.07 -9.66597 -63.1301 5/12/2018 Shell Gas Station GW 224.08 -9.71119 -63.2482 5/27/2018 Shell Gas Station GW 224.09 -9.63934 -62.8719 6/9/2018 Shell Gas Station GW 224.10 -9.72041 -63.0825 6/23/2018 Shell Gas Station GW 224.11 -9.71774 -63.3265 7/7/2018 Shell Gas Station GW 224.12 -9.65811 -63.1218 7/21/2018 Shell Gas Station GW 224.13 -9.64657 -63.0254 8/4/2018 Shell Gas Station GW 224.14 -9.69008 -63.2255 8/18/2018 Shell Gas Station GW 224.15 -9.68362 -63.2851 9/1/2018 Shell Gas Station GW 224.16 -9.58736 -62.9937 9/15/2018 Shell Gas Station GW

102

224.17 -9.65339 -63.1179 9/30/2018 Shell Gas Station GW 224.18 -9.73456 -63.3363 10/13/2018 Shell Gas Station GW 224.19 -9.64898 -62.9475 10/27/2018 Shell Gas Station GW 224.20 -9.68801 -63.1761 11/10/2018 Shell Gas Station GW 224.21 -9.66254 -62.8705 11/24/2018 Shell Gas Station GW 224.22 -9.69951 -63.0061 12/8/2018 Shell Gas Station GW 224.23 -9.68712 -63.2781 12/22/2018 Shell Gas Station GW 228.00 -7.78561 -56.7825 3/3/2018 Corning Lake 228.01 -7.91555 -57.8849 3/18/2018 Corning Lake 228.02 -8.01065 -58.0392 3/31/2018 Corning Lake 228.03 -7.75384 -56.5481 4/14/2018 Corning Lake 228.04 -7.64825 -55.5087 4/27/2018 Corning Lake 228.05 -6.83526 -50.977 5/12/2018 Corning Lake 228.06 -6.28661 -47.649 5/27/2018 Corning Lake 228.07 -6.0002 -46.3979 6/1/2018 Corning Lake 228.08 -5.80965 -45.5681 6/9/2018 Corning Lake 228.09 -5.54881 -44.4414 6/23/2018 Corning Lake 228.10 -4.82635 -39.6803 7/7/2018 Corning Lake 228.11 -4.012 -36.0004 7/21/2018 Corning Lake 228.12 -3.9324 -35.9966 8/4/2018 Corning Lake 228.13 -3.57454 -33.8096 8/18/2018 Corning Lake 228.14 -3.31934 -31.726 9/1/2018 Corning Lake 228.15 -3.44855 -33.1676 9/15/2018 Corning Lake 228.16 -3.76866 -33.7746 9/29/2018 Corning Lake 228.17 -4.18667 -33.7124 10/13/2018 Corning Lake 228.18 -4.09661 -33.8709 10/27/2018 Corning Lake 228.19 -5.92136 -44.3754 11/10/2018 Corning Lake 228.20 -6.21879 -46.5583 11/24/2018 Corning Lake 228.21 -6.81783 -50.4027 12/8/2018 Corning Lake 228.22 -7.02001 -52.1509 12/22/2018 Corning Lake 229.00 -10.4449 -67.8206 3/18/2018 Deep Spring Mineral water 229.01 -10.437 -67.7137 3/31/2018 Deep Spring Mineral water 229.02 -10.4069 -67.8324 4/14/2018 Deep Spring Mineral water 229.03 -10.3591 -67.5199 4/27/2018 Deep Spring Mineral water 229.04 -10.3449 -67.7054 5/12/2018 Deep Spring Mineral water 229.05 -10.3837 -67.7503 5/27/2018 Deep Spring Mineral water 229.06 -10.3444 -67.4851 6/9/2018 Deep Spring Mineral water 229.07 -10.3904 -67.7865 6/23/2018 Deep Spring Mineral water 229.08 -10.3879 -67.8155 7/7/2018 Deep Spring Mineral water 229.09 -10.3563 -67.7459 7/21/2018 Deep Spring Mineral water 229.10 -10.3192 -67.377 8/4/2018 Deep Spring Mineral water

103

229.11 -10.4059 -67.7494 8/18/2018 Deep Spring Mineral water 229.12 -10.3506 -67.4437 9/1/2018 Deep Spring Mineral water 229.13 -10.1724 -67.294 9/15/2018 Deep Spring Mineral water 229.14 -10.3177 -67.3057 9/29/2018 Deep Spring Mineral water 229.15 -10.3372 -67.42 10/13/2018 Deep Spring Mineral water 229.16 -10.3885 -67.703 10/27/2018 Deep Spring Mineral water 229.17 -10.3415 -67.3016 11/10/2018 Deep Spring Mineral water 229.19 -10.3621 -67.6975 12/21/2018 Deep Spring Mineral water 229.20 -10.397 -67.5667 12/22/2018 Deep Spring Mineral water

104

Appendix C

All isotope data with sampling location

105

Table C2 initial sample locations with corresponding data.

Sample Date Lat Long Region Place name Type δ18O (‰) δ2H (‰) D excess (‰) ID 11.00 8/26/2017 41.28269 -81.2101 4 Mantua Bog on Peck Lentic -7.61 -51.79 9.09 RD. 11.02 10/20/2017 41.28269 -81.2101 4 Mantua Bog on Peck Lentic -8.02 -54.98 9.22 RD. 11.03 2/4/2018 41.28269 -81.2101 4 Mantua Bog on Peck Lentic -9.55 -62.54 13.88 RD. 11.04 2/17/2018 41.28269 -81.2101 4 Mantua Bog on Peck Lentic -9.57 -64.76 11.77 RD. 11.05 3/3/2018 41.28269 -81.2101 4 Mantua Bog on Peck Lentic -10.24 -70.02 11.93 RD. 11.06 3/18/2018 41.28269 -81.2101 4 Mantua Bog on Peck Lentic -9.66 -64.46 12.78 RD. 11.07 3/31/2018 41.28269 -81.2101 4 Mantua Bog on Peck Lentic -9.45 -63.08 12.50 RD. 11.08 4/14/2018 41.28269 -81.2101 4 Mantua Bog on Peck Lentic -8.99 -59.86 12.05 RD. 11.09 4/27/2018 41.28269 -81.2101 4 Mantua Bog on Peck Lentic -8.89 -59.57 11.55 RD. 11.10 5/12/2018 41.28269 -81.2101 4 Mantua Bog on Peck Lentic -7.90 -54.36 8.88 RD. 11.11 5/27/2018 41.28269 -81.2101 4 Mantua Bog on Peck Lentic -7.90 -53.84 9.33 RD. 11.12 6/9/2018 41.28269 -81.2101 4 Mantua Bog on Peck Lentic -8.19 -55.12 10.41 RD. 11.13 6/23/2018 41.28269 -81.2101 4 Mantua Bog on Peck Lentic -8.07 -53.54 11.00 RD. 11.14 7/7/2018 41.28269 -81.2101 4 Mantua Bog on Peck Lentic -7.01 -46.19 9.91 RD. 11.15 7/21/2018 41.28269 -81.2101 4 Mantua Bog on Peck Lentic -7.63 -51.22 9.80 RD. 11.16 8/4/2018 41.28269 -81.2101 4 Mantua Bog on Peck Lentic -8.19 -55.01 10.48 RD. 11.17 8/18/2018 41.28269 -81.2101 4 Mantua Bog on Peck Lentic -8.22 -55.24 10.54 RD. 11.18 9/1/2018 41.28269 -81.2101 4 Mantua Bog on Peck Lentic -7.55 -49.53 10.88 RD. 11.19 9/15/2018 41.28269 -81.2101 4 Mantua Bog on Peck Lentic -8.95 -59.78 11.81 RD. 11.20 9/30/2018 41.28269 -81.2101 4 Mantua Bog on Peck Lentic -8.25 -54.45 11.53 RD. 11.21 10/13/2018 41.28269 -81.2101 4 Mantua Bog on Peck Lentic -8.39 -55.35 11.73 RD. 11.22 10/27/2018 41.28269 -81.2101 4 Mantua Bog on Peck Lentic -8.93 -59.12 12.32 RD. 11.23 11/10/2018 41.28269 -81.2101 4 Mantua Bog on Peck Lentic -9.70 -63.67 13.95 RD. 11.25 12/8/2018 41.28269 -81.2101 4 Mantua Bog on Peck Lentic -9.90 -65.35 13.81 RD. 11.26 12/22/2018 41.28269 -81.2101 4 Mantua Bog on Peck Lentic -9.75 -64.96 13.02 RD. 27.00 8/26/2017 41.19039 -81.3389 4 East Lake of the twin Lentic -10.60 -71.33 13.45 lakes on 43 Kent.

106

Dock out back of tavern on the lake. 27.02 10/21/2017 41.19039 -81.3389 4 East Lake of the twin Lentic -3.33 -31.58 -4.90 lakes on 43 Kent. Dock out back of tavern on the lake. 27.03 5/30/2018 41.19039 -81.3389 4 East Lake of the twin Lentic -3.46 -32.43 -4.75 lakes on 43 Kent. Dock out back of tavern on the lake. 27.04 7/31/2018 41.19039 -81.3389 4 East Lake of the twin Lentic -4.35 -36.75 -1.97 lakes on 43 Kent. Dock out back of tavern on the lake. 27.05 9/28/2018 41.19039 -81.3389 4 East Lake of the twin Lentic -3.70 -33.93 -4.33 lakes on 43 Kent. Dock out back of tavern on the lake. 30.00 8/26/2017 41.1711 -81.3194 4 Brady Lake at the Lentic -3.78 -34.12 -3.88 end of Ohio st. 30.02 10/21/2017 41.1711 -81.3194 4 Brady Lake at the Lentic -1.55 -23.36 -10.97 end of Ohio st. 30.03 5/30/2018 41.1711 -81.3194 4 Brady Lake at the Lentic -1.33 -22.73 -12.10 end of Ohio st. 30.04 7/31/2018 41.1711 -81.3194 4 Brady Lake at the Lentic -2.65 -29.14 -7.97 end of Ohio st. 30.05 9/28/2018 41.1711 -81.3194 4 Brady Lake at the Lentic -1.78 -25.27 -11.03 end of Ohio st. 63.01 5/31/2018 41.19596 -81.5767 1 Indigo Lake Lentic -3.15 -32.55 -7.35 Cuyahoga valley 63.02 7/31/2018 41.19596 -81.5767 1 Indigo Lake Lentic -3.66 -35.13 -5.84 Cuyahoga valley 63.03 9/28/2018 41.19596 -81.5767 1 Indigo Lake Lentic -3.29 -33.50 -7.17 Cuyahoga valley 121.00 12/13/2017 41.61729 -81.2986 2 Long Science Center Lentic -3.29 -33.36 -7.05 pond out front 121.01 12/29/2017 41.61729 -81.2986 2 Long Science Center Lentic -9.71 -64.34 13.34 pond out front 121.02 1/12/2018 41.61729 -81.2986 2 Long Science Center Lentic -6.21 -40.78 8.92 pond out front 121.03 2/17/2018 41.61729 -81.2986 2 Long Science Center Lentic -10.79 -73.30 13.06 pond out front 121.04 3/3/2018 41.61729 -81.2986 2 Long Science Center Lentic -11.47 -82.96 8.83 pond out front 121.05 3/31/2018 41.61729 -81.2986 2 Long Science Center Lentic -11.33 -77.43 13.22 pond out front 121.06 4/14/2018 41.61729 -81.2986 2 Long Science Center Lentic -10.52 -69.65 14.50 pond out front 121.07 4/27/2018 41.61729 -81.2986 2 Long Science Center Lentic -9.44 -64.60 10.90 pond out front 121.08 5/12/2018 41.61729 -81.2986 2 Long Science Center Lentic -8.90 -61.50 9.73 pond out front 121.09 5/27/2018 41.61729 -81.2986 2 Long Science Center Lentic -7.19 -49.95 7.58 pond out front 121.10 6/9/2018 41.61729 -81.2986 2 Long Science Center Lentic -6.06 -43.24 5.27 pond out front

107

121.11 6/23/2018 41.61729 -81.2986 2 Long Science Center Lentic -6.20 -45.12 4.49 pond out front 121.12 7/7/2018 41.61729 -81.2986 2 Long Science Center Lentic -11.75 -80.35 13.63 pond out front 121.13 7/21/2018 41.61729 -81.2986 2 Long Science Center Lentic -5.13 -33.22 7.86 pond out front 121.14 8/4/2018 41.61729 -81.2986 2 Long Science Center Lentic -4.29 -30.73 3.61 pond out front 121.15 8/18/2018 41.61729 -81.2986 2 Long Science Center Lentic -4.90 -35.97 3.21 pond out front 121.16 9/1/2018 41.61729 -81.2986 2 Long Science Center Lentic -4.75 -34.09 3.91 pond out front 121.17 9/15/2018 41.61729 -81.2986 2 Long Science Center Lentic -5.09 -32.90 7.82 pond out front 121.18 9/29/2018 41.61729 -81.2986 2 Long Science Center Lentic -6.93 -47.46 7.98 pond out front 121.19 10/13/2018 41.61729 -81.2986 2 Long Science Center Lentic -7.27 -48.08 10.08 pond out front 121.20 10/27/2018 41.61729 -81.2986 2 Long Science Center Lentic -7.03 -43.54 12.74 pond out front 121.21 11/10/2018 41.61729 -81.2986 2 Long Science Center Lentic -8.11 -52.93 11.97 pond out front 121.22 11/24/2018 41.61729 -81.2986 2 Long Science Center Lentic -9.75 -64.43 13.53 pond out front 121.23 12/8/2018 41.61729 -81.2986 2 Long Science Center Lentic -10.65 -72.09 13.11 pond out front 121.24 12/22/2018 41.61729 -81.2986 2 Long Science Center Lentic -13.41 -94.37 12.88 pond out front 228.00 3/3/2018 41.60839 -81.3007 2 Corning Lake Holden Lentic -7.79 -56.78 5.50 Arboretum 228.01 3/18/2018 41.60839 -81.3007 2 Corning Lake Holden Lentic -7.92 -57.88 5.44 Arboretum 228.02 3/31/2018 41.60839 -81.3007 2 Corning Lake Holden Lentic -8.01 -58.04 6.05 Arboretum 228.03 4/14/2018 41.60839 -81.3007 2 Corning Lake Holden Lentic -7.75 -56.55 5.48 Arboretum 228.04 4/27/2018 41.60839 -81.3007 2 Corning Lake Holden Lentic -7.65 -55.51 5.68 Arboretum 228.05 5/12/2018 41.60839 -81.3007 2 Corning Lake Holden Lentic -6.84 -50.98 3.71 Arboretum 228.06 5/27/2018 41.60839 -81.3007 2 Corning Lake Holden Lentic -6.29 -47.65 2.64 Arboretum 228.07 6/1/2018 41.60839 -81.3007 2 Corning Lake Holden Lentic -6.00 -46.40 1.60 Arboretum 228.08 6/9/2018 41.60839 -81.3007 2 Corning Lake Holden Lentic -5.81 -45.57 0.91 Arboretum 228.09 6/23/2018 41.60839 -81.3007 2 Corning Lake Holden Lentic -5.55 -44.44 -0.05 Arboretum 228.10 7/7/2018 41.60839 -81.3007 2 Corning Lake Holden Lentic -4.83 -39.68 -1.07 Arboretum 228.11 7/21/2018 41.60839 -81.3007 2 Corning Lake Holden Lentic -4.01 -36.00 -3.90 Arboretum 228.12 8/4/2018 41.60839 -81.3007 2 Corning Lake Holden Lentic -3.93 -36.00 -4.54 Arboretum 228.13 8/18/2018 41.60839 -81.3007 2 Corning Lake Holden Lentic -3.57 -33.81 -5.21 Arboretum

108

228.14 9/1/2018 41.60839 -81.3007 2 Corning Lake Holden Lentic -3.32 -31.73 -5.17 Arboretum 228.15 9/15/2018 41.60839 -81.3007 2 Corning Lake Holden Lentic -3.45 -33.17 -5.58 Arboretum 228.16 9/29/2018 41.60839 -81.3007 2 Corning Lake Holden Lentic -3.77 -33.77 -3.63 Arboretum 228.17 10/13/2018 41.60839 -81.3007 2 Corning Lake Holden Lentic -4.19 -33.71 -0.22 Arboretum 228.18 10/27/2018 41.60839 -81.3007 2 Corning Lake Holden Lentic -4.10 -33.87 -1.10 Arboretum 228.19 11/10/2018 41.60839 -81.3007 2 Corning Lake Holden Lentic -5.92 -44.38 3.00 Arboretum 228.20 11/24/2018 41.60839 -81.3007 2 Corning Lake Holden Lentic -6.22 -46.56 3.19 Arboretum 228.21 12/8/2018 41.60839 -81.3007 2 Corning Lake Holden Lentic -6.82 -50.40 4.14 Arboretum 228.22 12/22/2018 41.60839 -81.3007 2 Corning Lake Holden Lentic -7.02 -52.15 4.01 Arboretum 231.00 5/30/2018 41.01621 -81.1952 4 Schultz Lake out Lentic -7.02 -52.15 4.01 flow near Atwater 231.01 7/29/2018 41.01621 -81.1952 4 Schultz Lake out Lentic -8.10 -52.71 12.07 flow near Atwater 231.02 9/28/2018 41.01621 -81.1952 4 Schultz Lake out Lentic -8.48 -54.95 12.88 flow near Atwater 233.00 5/30/2018 41.01203 -80.8609 5 Upper Diehl Lake Lentic -7.41 -46.54 12.71 11152 S Lake Dr. 233.01 7/29/2018 41.01203 -80.8609 5 Upper Diehl Lake Lentic -6.24 -41.54 8.35 11152 S Lake Dr. 233.02 9/28/2018 41.01203 -80.8609 5 Upper Diehl Lake Lentic -4.55 -33.81 2.61 11152 S Lake Dr. 234.00 5/30/2018 41.06465 -80.6782 5 Newport Lake Lentic -6.98 -42.83 13.00 234.01 7/29/2018 41.06465 -80.6782 5 Newport Lake Lentic -6.63 -43.85 9.20 234.02 9/28/2018 41.06465 -80.6782 5 Newport Lake Lentic -6.24 -42.97 6.94 235.00 5/30/2018 41.03687 -80.5918 5 Lake Hamilton Lentic -7.15 -45.67 11.50 235.01 7/29/2018 41.03687 -80.5918 5 Lake Hamilton Lentic -6.19 -41.83 7.71 235.02 9/28/2018 41.03687 -80.5918 5 Lake Hamilton Lentic -5.68 -38.97 6.44 237.00 5/30/2018 41.09782 -80.5747 5 Mc Kelsey Lake Lentic -7.09 -47.47 9.27 237.01 7/29/2018 41.09782 -80.5747 5 Mc Kelsey Lake Lentic -7.06 -48.73 7.78 237.02 9/29/2018 41.09782 -80.5747 5 Mc Kelsey Lake Lentic -6.18 -45.19 4.27 238.00 5/30/2018 41.197 -80.5857 5 Coal burg Lake Lentic -6.42 -46.82 4.50 238.01 7/29/2018 41.197 -80.5857 5 Coal burg Lake Lentic -6.81 -45.59 8.86 238.02 9/29/2018 41.197 -80.5857 5 Coal burg Lake Lentic -5.78 -39.38 6.87 239.00 5/30/2018 41.19306 -80.6948 5 Girard Lake Lentic -7.65 -48.74 12.43 239.01 7/29/2018 41.19306 -80.6948 5 Girard Lake Lentic -7.27 -49.27 8.86 239.02 9/29/2018 41.19306 -80.6948 5 Girard Lake Lentic -5.66 -40.02 5.25 240.00 5/30/2018 41.29973 -80.7585 5 Mosquito Lake Lentic -7.68 -53.80 7.61 240.01 7/29/2018 41.29973 -80.7585 5 Mosquito Lake Lentic -5.91 -43.62 3.64 240.02 9/29/2018 41.29973 -80.7585 5 Mosquito Lake Lentic -5.42 -41.08 2.27 241.00 5/30/2018 41.65457 -80.8402 3 Lake Roaming Rocks Lentic -5.42 -41.08 2.27

109

241.01 7/29/2018 41.65457 -80.8402 3 Lake Roaming Rocks Lentic -7.47 -50.41 9.32 241.02 9/29/2018 41.65457 -80.8402 3 Lake Roaming Rocks Lentic -6.70 -46.13 7.47 243.00 5/30/2018 41.40047 -81.4413 1 Briar Hill Lake Lentic -7.36 -48.77 10.11 243.01 7/30/2018 41.40047 -81.4413 1 Briar Hill Lake Lentic -7.88 -53.81 9.23 243.02 9/29/2018 41.40047 -81.4413 1 Briar Hill Lake Lentic -6.03 -42.96 5.31 244.00 5/30/2018 41.32523 -81.3924 1 Aurora Pond Lentic -6.56 -44.04 8.47 244.01 7/31/2018 41.32523 -81.3924 1 Aurora Pond Lentic -6.96 -49.88 5.82 244.02 9/29/2018 41.32523 -81.3924 1 Aurora Pond Lentic -5.01 -40.17 -0.08 245.00 5/31/2018 41.0186 -81.3732 4 Wingfoot Lake Lentic -4.52 -36.93 -0.74 245.01 7/28/2018 41.0186 -81.3732 4 Wingfoot Lake Lentic -4.93 -39.19 0.27 245.02 9/28/2018 41.0186 -81.3732 4 Wingfoot Lake Lentic -3.37 -31.56 -4.60 246.00 5/31/2018 41.02993 -81.4311 1 Springfield Lake Lentic -2.97 -28.93 -5.19 246.01 7/28/2018 41.02993 -81.4311 1 Springfield Lake Lentic -4.82 -37.87 0.73 246.02 9/28/2018 41.02993 -81.4311 1 Springfield Lake Lentic -3.91 -33.47 -2.17 247.00 5/31/2018 40.99354 -81.6825 1 Silver Creek Lake Lentic -3.86 -32.56 -1.66 247.01 7/28/2018 40.99354 -81.6825 1 Silver Creek Lake Lentic -7.08 -47.28 9.38 247.02 9/28/2018 40.99354 -81.6825 1 Silver Creek Lake Lentic -5.71 -41.73 3.98 248.00 5/31/2018 41.05794 -81.9041 1 Chippewa Lake Lentic -6.08 -43.31 5.35 248.01 7/28/2018 41.05794 -81.9041 1 Chippewa Lake Lentic -7.39 -50.34 8.81 248.02 9/28/2018 41.05794 -81.9041 1 Chippewa Lake Lentic -6.03 -42.94 5.31 249.00 5/31/2018 41.14542 -81.8258 1 Lake Medina Lentic -5.62 -40.19 4.80 249.01 7/28/2018 41.14542 -81.8258 1 Lake Medina Lentic -3.53 -32.59 -4.32 249.02 9/28/2018 41.14542 -81.8258 1 Lake Medina Lentic -2.93 -29.82 -6.42 250.00 5/31/2018 41.15391 -81.6917 1 Granger Lake Lentic -2.71 -28.07 -6.39 250.01 7/28/2018 41.15391 -81.6917 1 Granger Lake Lentic -6.66 -47.03 6.24 250.02 9/28/2018 41.15391 -81.6917 1 Granger Lake Lentic -4.84 -38.83 -0.10 251.00 5/31/2018 41.22638 -81.7202 1 Hinkley Lake Lentic -4.88 -38.29 0.78 251.01 7/28/2018 41.22638 -81.7202 1 Hinkley Lake Lentic -7.28 -48.29 9.94 251.02 9/28/2018 41.22638 -81.7202 1 Hinkley Lake Lentic -6.06 -40.45 7.99 252.00 5/31/2018 41.36459 -81.8581 1 Wallace Lake Lentic -7.11 -44.46 12.43 252.01 7/28/2018 41.36459 -81.8581 1 Wallace Lake Lentic -6.58 -46.38 6.23 252.02 9/28/2018 41.36459 -81.8581 1 Wallace Lake Lentic -5.04 -38.05 2.23 253.00 5/31/2018 41.18644 -81.4886 1 Wyoga Lake Lentic -5.12 -37.05 3.94 253.01 7/31/2018 41.18644 -81.4886 1 Wyoga Lake Lentic -6.46 -44.16 7.54 253.02 9/28/2018 41.18644 -81.4886 1 Wyoga Lake Lentic -5.50 -39.59 4.41 254.00 6/1/2018 41.44129 -81.1755 2 Kelso Lake Lentic -6.82 -44.94 9.63 254.01 7/30/2018 41.44129 -81.1755 2 Kelso Lake Lentic -5.67 -44.84 0.50 254.02 9/30/2018 41.44129 -81.1755 2 Kelso Lake Lentic -4.58 -39.55 -2.92 255.00 6/1/2018 41.44845 -81.2063 2 Punderson Lake Lentic -4.41 -38.41 -3.13 255.01 7/30/2018 41.44845 -81.2063 2 Punderson Lake Lentic -6.49 -47.04 4.85 255.02 9/30/2018 41.44845 -81.2063 2 Punderson Lake Lentic -5.55 -42.44 1.97

110

256.00 6/1/2018 41.5444 -81.2308 2 Bass Lake Lentic -5.62 -41.94 3.05 256.01 7/30/2018 41.5444 -81.2308 2 Bass Lake Lentic -7.43 -51.36 8.11 256.02 9/28/2018 41.5444 -81.2308 2 Bass Lake Lentic -5.86 -40.82 6.04 257.00 6/1/2018 41.52659 -81.2594 2 Sycamore Lake Lentic -7.38 -52.86 6.19 257.01 8/4/2018 41.52659 -81.2594 2 Sycamore Lake Lentic -6.38 -43.97 7.10 257.02 9/29/2018 41.52659 -81.2594 2 Sycamore Lake Lentic -7.09 -47.43 9.26 258.00 6/1/2018 41.43184 -81.3158 2 Paw Paw Lake Lentic -7.46 -50.96 8.70 258.01 7/30/2018 41.43184 -81.3158 2 Paw Paw Lake Lentic -6.07 -40.55 8.00 258.02 9/30/2018 41.43184 -81.3158 2 Paw Paw Lake Lentic -7.50 -49.05 10.96 77.00 5/30/2018 41.24283 -81.5502 1 Cuyahoga River Lotic -6.85 -48.28 6.48 Mouth 77.01 7/31/2018 41.24283 -81.5502 1 Cuyahoga River Lotic -7.00 -48.41 7.58 Mouth 77.02 9/28/2018 41.24283 -81.5502 1 Cuyahoga River Lotic -7.42 -49.13 10.22 Mouth 90.00 10/20/2017 41.28377 -81.2169 4 Cuyahoga River Lotic -7.12 -50.56 6.39 Head 90.01 2/4/2018 41.28377 -81.2169 4 Cuyahoga River Lotic -4.63 -26.76 10.32 Head 90.02 2/17/2018 41.28377 -81.2169 4 Cuyahoga River Lotic -1.97 -22.27 -6.51 Head 90.03 3/3/2018 41.28377 -81.2169 4 Cuyahoga River Lotic -10.14 -69.25 11.88 Head 90.04 3/18/2018 41.28377 -81.2169 4 Cuyahoga River Lotic -10.14 -68.53 12.57 Head 90.05 3/31/2018 41.28377 -81.2169 4 Cuyahoga River Lotic -10.21 -68.48 13.21 Head 90.06 4/14/2018 41.28377 -81.2169 4 Cuyahoga River Lotic -9.47 -64.00 11.75 Head 90.07 4/27/2018 41.28377 -81.2169 4 Cuyahoga River Lotic -9.16 -62.11 11.16 Head 90.08 5/12/2018 41.28377 -81.2169 4 Cuyahoga River Lotic -8.62 -58.52 10.47 Head 90.09 5/27/2018 41.28377 -81.2169 4 Cuyahoga River Lotic -8.02 -54.55 9.62 Head 90.10 6/9/2018 41.28377 -81.2169 4 Cuyahoga River Lotic -8.14 -55.24 9.90 Head 90.11 6/23/2018 41.28377 -81.2169 4 Cuyahoga River Lotic -7.78 -52.55 9.72 Head 90.12 7/7/2018 41.28377 -81.2169 4 Cuyahoga River Lotic -7.01 -46.55 9.50 Head 90.13 7/21/2018 41.28377 -81.2169 4 Cuyahoga River Lotic -6.44 -42.27 9.25 Head 90.14 8/4/2018 41.28377 -81.2169 4 Cuyahoga River Lotic -7.36 -50.24 8.60 Head 90.15 8/18/2018 41.28377 -81.2169 4 Cuyahoga River Lotic -7.29 -50.72 7.58 Head 90.16 9/1/2018 41.28377 -81.2169 4 Cuyahoga River Lotic -6.92 -47.41 7.96 Head 90.17 9/15/2018 41.28377 -81.2169 4 Cuyahoga River Lotic -8.52 -58.14 10.05 Head 90.18 9/30/2018 41.28377 -81.2169 4 Cuyahoga River Lotic -7.82 -49.91 12.64 Head

111

90.19 10/13/2018 41.28377 -81.2169 4 Cuyahoga River Lotic -7.70 -51.45 10.13 Head 90.20 10/27/2018 41.28377 -81.2169 4 Cuyahoga River Lotic -7.82 -53.93 8.62 Head 90.21 11/10/2018 41.28377 -81.2169 4 Cuyahoga River Lotic -9.13 -61.21 11.85 Head 90.22 11/24/2018 41.28377 -81.2169 4 Cuyahoga River Lotic -9.61 -65.11 11.76 Head 90.23 12/8/2018 41.28377 -81.2169 4 Cuyahoga River Lotic -9.92 -67.22 12.12 Head 90.24 12/22/2018 41.28377 -81.2169 4 Cuyahoga River Lotic -10.68 -72.99 12.42 Head 123.00 12/13/2017 41.62788 -81.3114 2 Chagrin River East Lotic -9.67 -63.55 13.83 branch Mouth 123.01 1/12/2018 41.62788 -81.3114 2 Chagrin River East Lotic -6.31 -40.73 9.72 branch Mouth 123.02 2/4/2018 41.62788 -81.3114 2 Chagrin River East Lotic -5.28 -39.15 3.13 branch Mouth 123.03 2/17/2018 41.62788 -81.3114 2 Chagrin River East Lotic -11.13 -73.85 15.17 branch Mouth 123.04 3/3/2018 41.62788 -81.3114 2 Chagrin River East Lotic -11.19 -76.16 13.37 branch Mouth 123.05 3/18/2018 41.62788 -81.3114 2 Chagrin River East Lotic -10.76 -71.96 14.12 branch Mouth 123.06 3/31/2018 41.62788 -81.3114 2 Chagrin River East Lotic -10.73 -71.87 13.97 branch Mouth 123.07 4/14/2018 41.62788 -81.3114 2 Chagrin River East Lotic -10.06 -66.78 13.68 branch Mouth 123.08 4/27/2018 41.62788 -81.3114 2 Chagrin River East Lotic -9.86 -65.71 13.21 branch Mouth 123.09 5/12/2018 41.62788 -81.3114 2 Chagrin River East Lotic -9.26 -61.47 12.63 branch Mouth 123.10 5/27/2018 41.62788 -81.3114 2 Chagrin River East Lotic -9.29 -61.28 13.06 branch Mouth 123.11 6/9/2018 41.62788 -81.3114 2 Chagrin River East Lotic -9.36 -61.78 13.12 branch Mouth 123.12 6/23/2018 41.62788 -81.3114 2 Chagrin River East Lotic -9.23 -60.88 12.96 branch Mouth 123.13 7/7/2018 41.62788 -81.3114 2 Chagrin River East Lotic -7.34 -47.47 11.24 branch Mouth 123.14 7/21/2018 41.62788 -81.3114 2 Chagrin River East Lotic -8.56 -56.24 12.21 branch Mouth 123.15 8/4/2018 41.62788 -81.3114 2 Chagrin River East Lotic -9.04 -59.88 12.47 branch Mouth 123.16 8/18/2018 41.62788 -81.3114 2 Chagrin River East Lotic -9.23 -61.02 12.85 branch Mouth 123.17 9/1/2018 41.62788 -81.3114 2 Chagrin River East Lotic -8.07 -52.13 12.43 branch Mouth 123.18 9/15/2018 41.62788 -81.3114 2 Chagrin River East Lotic -8.96 -59.28 12.40 branch Mouth 123.19 9/29/2018 41.62788 -81.3114 2 Chagrin River East Lotic -8.65 -56.65 12.57 branch Mouth 123.20 10/13/2018 41.62788 -81.3114 2 Chagrin River East Lotic -10.62 -68.26 16.67 branch Mouth 123.21 10/27/2018 41.62788 -81.3114 2 Chagrin River East Lotic -9.61 -62.92 13.98 branch Mouth

112

123.22 11/10/2018 41.62788 -81.3114 2 Chagrin River East Lotic -10.05 -66.15 14.26 branch Mouth 123.23 11/24/2018 41.62788 -81.3114 2 Chagrin River East Lotic -10.00 -66.13 13.84 branch Mouth 123.24 12/8/2018 41.62788 -81.3114 2 Chagrin River East Lotic -10.22 -67.95 13.81 branch Mouth 123.25 12/22/2018 41.62788 -81.3114 2 Chagrin River East Lotic -11.52 -78.27 13.93 branch Mouth 141.00 1/1/2018 41.44261 -81.7549 1 Big Creek Lotic -7.78 -56.17 6.04 141.01 5/31/2018 41.44261 -81.7549 1 Big Creek Lotic -7.48 -52.48 7.39 141.02 7/31/2018 41.44261 -81.7549 1 Big Creek Lotic -6.73 -47.99 5.88 141.03 9/28/2018 41.44261 -81.7549 1 Big Creek Lotic -7.59 -50.17 10.57 214.00 1/12/2018 41.9376 -80.5635 3 Conneaut Creek Lotic -14.82 -96.60 21.92 Mouth 214.01 2/17/2018 41.9376 -80.5635 3 Conneaut Creek Lotic -11.99 -80.69 15.21 Mouth 214.02 5/30/2018 41.9376 -80.5635 3 Conneaut Creek Lotic -8.82 -58.84 11.72 Mouth 214.03 7/30/2018 41.9376 -80.5635 3 Conneaut Creek Lotic -7.84 -52.85 9.88 Mouth 214.04 9/29/2018 41.9376 -80.5635 3 Conneaut Creek Lotic -8.53 -55.14 13.12 Mouth 215.00 1/12/2018 41.89432 -80.5746 3 Conneaut Creek Lotic -14.97 -97.48 22.27 Head 215.01 2/17/2018 41.89432 -80.5746 3 Conneaut Creek Lotic -11.96 -80.51 15.20 Head 215.02 5/30/2018 41.89432 -80.5746 3 Conneaut Creek Lotic -8.82 -58.46 12.09 Head 215.03 7/30/2018 41.89432 -80.5746 3 Conneaut Creek Lotic -7.75 -51.60 10.37 Head 215.04 9/29/2018 41.89432 -80.5746 3 Conneaut Creek Lotic -8.53 -55.03 13.23 Head 217.00 1/12/2018 41.83603 -80.684 3 Ashtabula Lotic -14.36 -93.66 21.21 217.01 2/17/2018 41.83603 -80.684 3 Ashtabula Lotic -11.89 -79.86 15.24 217.02 5/30/2018 41.83603 -80.684 3 Ashtabula Lotic -7.86 -53.47 9.45 217.03 7/30/2018 41.83603 -80.684 3 Ashtabula Lotic -7.89 -52.58 10.55 217.04 9/29/2018 41.83603 -80.684 3 Ashtabula Lotic -7.89 -51.70 11.46 221.00 1/12/2018 41.628 -81.3149 2 Pierson Creek Lotic -11.04 -72.84 15.52 221.01 2/4/2018 41.628 -81.3149 2 Pierson Creek Lotic -10.83 -76.30 10.34 221.03 3/3/2018 41.628 -81.3149 2 Pierson Creek Lotic -10.65 -72.01 13.16 221.04 3/18/2018 41.628 -81.3149 2 Pierson Creek Lotic -10.62 -71.14 13.84 221.05 3/31/2018 41.628 -81.3149 2 Pierson Creek Lotic -10.33 -69.10 13.57 221.06 4/14/2018 41.628 -81.3149 2 Pierson Creek Lotic -9.81 -65.12 13.35 221.07 4/27/2018 41.628 -81.3149 2 Pierson Creek Lotic -9.62 -64.09 12.86 221.08 5/12/2018 41.628 -81.3149 2 Pierson Creek Lotic -9.20 -61.03 12.58 221.09 5/27/2018 41.628 -81.3149 2 Pierson Creek Lotic -9.14 -60.34 12.74 221.10 6/9/2018 41.628 -81.3149 2 Pierson Creek Lotic -9.33 -61.54 13.14 221.11 6/23/2018 41.628 -81.3149 2 Pierson Creek Lotic -10.04 -66.67 13.64 221.12 7/7/2018 41.628 -81.3149 2 Pierson Creek Lotic -7.36 -48.98 9.91

113

221.13 7/21/2018 41.628 -81.3149 2 Pierson Creek Lotic -9.34 -61.34 13.41 221.14 8/4/2018 41.628 -81.3149 2 Pierson Creek Lotic -9.33 -61.65 13.02 221.15 8/18/2018 41.628 -81.3149 2 Pierson Creek Lotic -9.43 -62.11 13.30 221.16 9/1/2018 41.628 -81.3149 2 Pierson Creek Lotic -8.10 -53.37 11.44 221.17 9/15/2018 41.628 -81.3149 2 Pierson Creek Lotic -8.41 -56.36 10.89 221.18 9/29/2018 41.628 -81.3149 2 Pierson Creek Lotic -7.91 -53.04 10.25 221.19 10/13/2018 41.628 -81.3149 2 Pierson Creek Lotic -10.46 -66.81 16.91 221.20 10/27/2018 41.628 -81.3149 2 Pierson Creek Lotic -9.13 -59.87 13.16 221.21 11/10/2018 41.628 -81.3149 2 Pierson Creek Lotic -9.67 -63.88 13.48 221.22 11/24/2018 41.628 -81.3149 2 Pierson Creek Lotic -9.78 -64.82 13.41 221.23 12/8/2018 41.628 -81.3149 2 Pierson Creek Lotic -9.80 -65.43 12.96 221.24 12/22/2018 41.628 -81.3149 2 Pierson Creek Lotic -10.64 -72.62 12.54 222.00 2/4/2018 41.5947 -81.2966 2 Chagrin River East Lotic -10.27 -67.19 14.94 branch Head 222.01 2/17/2018 41.5947 -81.2966 2 Chagrin River East Lotic -11.01 -73.23 14.88 branch Head 222.02 3/3/2018 41.5947 -81.2966 2 Chagrin River East Lotic -11.16 -75.57 13.68 branch Head 222.03 3/18/2018 41.5947 -81.2966 2 Chagrin River East Lotic -10.71 -71.33 14.37 branch Head 222.04 3/31/2018 41.5947 -81.2966 2 Chagrin River East Lotic -10.71 -71.33 14.38 branch Head 222.05 4/14/2018 41.5947 -81.2966 2 Chagrin River East Lotic -10.03 -66.48 13.79 branch Head 222.06 4/27/2018 41.5947 -81.2966 2 Chagrin River East Lotic -9.85 -65.64 13.18 branch Head 222.07 5/12/2018 41.5947 -81.2966 2 Chagrin River East Lotic -9.32 -61.85 12.71 branch Head 222.08 5/27/2018 41.5947 -81.2966 2 Chagrin River East Lotic -9.36 -61.72 13.18 branch Head 222.09 6/9/2018 41.5947 -81.2966 2 Chagrin River East Lotic -9.47 -62.42 13.34 branch Head 222.10 6/23/2018 41.5947 -81.2966 2 Chagrin River East Lotic -9.39 -61.61 13.50 branch Head 222.11 7/7/2018 41.5947 -81.2966 2 Chagrin River East Lotic -7.53 -48.73 11.51 branch Head 222.12 7/21/2018 41.5947 -81.2966 2 Chagrin River East Lotic -8.74 -57.09 12.82 branch Head 222.13 8/4/2018 41.5947 -81.2966 2 Chagrin River East Lotic -9.20 -60.61 12.97 branch Head 222.14 8/18/2018 41.5947 -81.2966 2 Chagrin River East Lotic -9.38 -61.75 13.32 branch Head 222.15 9/1/2018 41.5947 -81.2966 2 Chagrin River East Lotic -8.39 -54.05 13.05 branch Head 222.16 9/15/2018 41.5947 -81.2966 2 Chagrin River East Lotic -9.07 -59.99 12.56 branch Head 222.17 9/29/2018 41.5947 -81.2966 2 Chagrin River East Lotic -8.44 -55.92 11.60 branch Head 222.18 10/13/2018 41.5947 -81.2966 2 Chagrin River East Lotic -11.89 -77.15 17.94 branch Head 222.19 10/27/2018 41.5947 -81.2966 2 Chagrin River East Lotic -9.61 -63.41 13.44 branch Head

114

222.20 11/10/2018 41.5947 -81.2966 2 Chagrin River East Lotic -10.11 -66.69 14.16 branch Head 222.21 11/24/2018 41.5947 -81.2966 2 Chagrin River East Lotic -10.28 -68.00 14.27 branch Head 222.22 12/8/2018 41.5947 -81.2966 2 Chagrin River East Lotic -10.39 -68.54 14.62 branch Head 222.23 12/22/2018 41.5947 -81.2966 2 Chagrin River East Lotic -11.49 -77.94 13.98 branch Head 223.00 2/4/2018 41.53664 -81.2436 2 Chagrin River Head Lotic -10.68 -70.25 15.17 223.01 2/17/2018 41.53664 -81.2436 2 Chagrin River Head Lotic -11.59 -77.67 15.08 223.02 3/3/2018 41.53664 -81.2436 2 Chagrin River Head Lotic -10.68 -71.88 13.59 223.03 3/18/2018 41.53664 -81.2436 2 Chagrin River Head Lotic -10.88 -74.25 12.77 223.04 3/31/2018 41.53664 -81.2436 2 Chagrin River Head Lotic -10.79 -72.58 13.76 223.05 4/14/2018 41.53664 -81.2436 2 Chagrin River Head Lotic -9.96 -67.27 12.44 223.06 4/27/2018 41.53664 -81.2436 2 Chagrin River Head Lotic -9.31 -62.62 11.85 223.07 5/12/2018 41.53664 -81.2436 2 Chagrin River Head Lotic -8.47 -58.11 9.67 223.08 5/27/2018 41.53664 -81.2436 2 Chagrin River Head Lotic -7.77 -52.97 9.16 223.09 6/9/2018 41.53664 -81.2436 2 Chagrin River Head Lotic -7.40 -51.51 7.67 223.10 6/23/2018 41.53664 -81.2436 2 Chagrin River Head Lotic -7.08 -49.77 6.89 223.11 7/7/2018 41.53664 -81.2436 2 Chagrin River Head Lotic -6.52 -45.29 6.85 223.12 7/21/2018 41.53664 -81.2436 2 Chagrin River Head Lotic -5.58 -38.47 6.21 223.13 7/30/2018 41.53664 -81.2436 2 Chagrin River Head Lotic -5.89 -40.95 6.15 223.14 8/18/2018 41.53664 -81.2436 2 Chagrin River Head Lotic -5.74 -40.72 5.20 223.15 9/1/2018 41.53664 -81.2436 2 Chagrin River Head Lotic -5.48 -38.94 4.86 223.16 9/15/2018 41.53664 -81.2436 2 Chagrin River Head Lotic -6.31 -44.19 6.28 223.17 9/29/2018 41.53664 -81.2436 2 Chagrin River Head Lotic -7.04 -47.17 9.15 223.18 10/13/2018 41.53664 -81.2436 2 Chagrin River Head Lotic -7.63 -51.28 9.77 223.19 10/27/2018 41.53664 -81.2436 2 Chagrin River Head Lotic -7.39 -50.21 8.88 223.20 11/10/2018 41.53664 -81.2436 2 Chagrin River Head Lotic -9.53 -63.80 12.42 223.21 11/24/2018 41.53664 -81.2436 2 Chagrin River Head Lotic -9.89 -66.63 12.52 223.22 12/8/2018 41.53664 -81.2436 2 Chagrin River Head Lotic -10.70 -71.80 13.82 223.23 12/22/2018 41.53664 -81.2436 2 Chagrin River Head Lotic -10.77 -73.11 13.04 225.00 2/17/2018 41.72581 -81.1846 2 Grand River Mouth Lotic -11.56 -77.52 14.93 225.01 5/30/2018 41.72581 -81.1846 2 Grand River Mouth Lotic -7.27 -49.76 8.37 225.02 7/30/2018 41.72581 -81.1846 2 Grand River Mouth Lotic -7.15 -48.52 8.71 225.03 9/29/2018 41.72581 -81.1846 2 Grand River Mouth Lotic -7.64 -48.66 12.45 227.00 2/17/2018 41.64984 -80.8695 3 Grand River Head Lotic -11.09 -74.70 14.01 227.01 5/30/2018 41.64984 -80.8695 3 Grand River Head Lotic -7.42 -50.55 8.81 227.02 8/4/2018 41.64984 -80.8695 3 Grand River Head Lotic -7.15 -47.82 9.40 227.03 9/29/2018 41.64984 -80.8695 3 Grand River Head Lotic -7.35 -46.51 12.31 232.00 5/30/2018 41.0052 -81.0711 5 Mahoning River Lotic -7.09 -48.32 8.43 Head 232.01 7/29/2018 41.0052 -81.0711 5 Mahoning River Lotic -5.44 -38.37 5.14 Head

115

232.02 9/28/2018 41.0052 -81.0711 5 Mahoning River Lotic -6.92 -44.00 11.40 Head 236.00 5/30/2018 41.05973 -80.5852 5 Mahoning River Lotic -7.96 -53.99 9.66 Mouth 236.01 7/29/2018 41.05973 -80.5852 5 Mahoning River Lotic -7.19 -48.75 8.75 Mouth 236.02 9/29/2018 41.05973 -80.5852 5 Mahoning River Lotic -6.67 -45.80 7.54 Mouth 242.00 5/30/2018 41.62852 -81.3998 2 Chagrin River Mouth Lotic -8.10 -54.60 10.19 242.01 7/30/2018 41.62852 -81.3998 2 Chagrin River Mouth Lotic -7.15 -48.28 8.90 242.02 9/29/2018 41.62852 -81.3998 2 Chagrin River Mouth Lotic -7.36 -48.77 10.11 122.00 1/12/2018 41°36'52.02"N 81°17'38.02"W 2 Long Science Center GW -6.23 -40.30 9.58 Tap Water 125.00 1/1/2018 41° 6'39.05"N 4 Speedway gas GW -8.58 -57.60 11.04 81°14'36.40"W station corner Lynn and Prospect Rootstown, OH Tap 126.00 1/1/2018 41° 1'46.70"N 81°14'55.07"W 4 Marathon Gas GW -9.17 -59.35 14.03 station corner of 44 and 224 Randolph, OH, Tap 127.00 1/1/2018 41° 1'51.21"N 81°25'35.42"W 4 Speedway gas GW -8.40 -55.47 11.76 station corner of 224 and 91 (1275) tap Lakemore, OH 130.00 1/1/2018 40°59'21.05"N 81°39'51.82"W 1 Circle K gas station GW -8.06 -52.20 12.32 at 21 and eastern Rd Norton, OH Tap 131.00 1/1/2018 40°59'53.63"N 81°48'36.03"W 1 Circle K gas station GW -8.96 -58.34 13.37 at Broad and Silvercreek Rd Wadsworth, OH Tao 132.00 1/1/2018 41° 2'9.05"N 81°51'53.97"W 1 Circle K gas station GW -8.93 -58.62 12.78 at 76 and 3 seville Tap 133.00 1/1/2018 40°59'53.29"N 81°48'35.68"W 1 BP minimart Lake Rd GW -8.26 -55.18 10.91 and Reid Rd Chippew on the Lake, OH tap 135.00 1/1/2018 41°13'58.66"N 81°50'28.11"W 1 Speedway at 42 GW -6.30 -48.01 2.40 Pearl Rd and Oxford Dr Tap, Brunswick OH 136.00 1/1/2018 41°20'36.47"N 81°49'32.15"W 1 Sheetz at Whitney GW -6.51 -49.63 2.47 Rd and Pearl Rd/ 42 Middleburg Hts, OH tap 144.00 1/2/2018 41° 1'26.51"N 81° 8'51.12"W 4 Circle K gas stationa GW -8.74 -56.28 13.64 Atwater at 183 and 224 Tap 145.00 1/2/2018 41° 0'54.77"N 80°59'13.31"W 4 Army corps of eng. GW -8.98 -58.64 13.18 Berlin, OH Berlin Lake Bedell Rd South of 224 Tap

116

146.00 1/2/2018 41° 1'26.24"N 80°51'28.05"W 5 Sunoco Gas station GW -9.73 -64.18 13.62 at 45 and 224 Ellsworth, OH tap 147.00 1/2/2018 41° 1'26.49"N 80°44'11.12"W 5 Sheetz Gas station GW -4.93 -36.71 2.77 at 11 and 224 in Canfield OH Tap 157.00 1/2/2018 41°14'0.38"N 80°33'50.64"W 5 Scotty's Brookfield GW -5.81 -41.74 4.73 express mark on Warren Sharon Rd and Bedford SE Brookfield OH 158.00 1/2/2018 41°14'16.13"N 80°44'24.46"W 5 Get Go gas station GW -5.81 -41.83 4.62 on Niles courtland road SE and East market, Howland Corners tap 159.00 1/2/2018 41°15'32.46"N 80°52'6.48"W 5 Circle K 4021 N GW -4.82 -35.97 2.63 Leavitt Rd and Parkman Rd NW warren OH 162.00 1/2/2018 41°18'30.38"N 80°44'39.29"W 5 Lakeside sport shop. GW -9.07 -59.23 13.34 Warren Meedville Rd and Wilson Sharpvill Rd 164.00 1/2/2018 41°23'18.54"N 80°39'55.57"W 5 Quinns Mini Mart at GW -8.68 -55.65 13.78 193 and 88 Johnson OH 165.00 1/2/2018 41°23'23.28"N 80°44'10.14"W 5 JAK's fine foods and GW -9.17 -59.60 13.79 gas station on 88 and 45 greenville Rd and Niles Courtland Rd NE Tap 166.00 1/3/2018 41°14'9.78"N 81° 8'39.48"W 4 Detour Drive thru on GW -9.32 -60.26 14.30 303/88 on Hadson Breeville Rd Freedom OH tap 168.00 1/3/2018 41°16'39.61"N 81° 5'24.16"W 4 Skylane Bowling GW -9.60 -62.88 13.95 Alley 82 and Liberty St tap Garrettsville OH 169.00 1/3/2018 41°22'14.30"N 81° 3'48.88"W 2 BP gas station at 88 GW -9.81 -63.74 14.77 and 422 Main market Rd and Madison Rd tap Elwood/Spike Weaver grand river access Parkman OH 171.00 1/3/2018 41°27'46.56"N 80°52'7.56"W 5 Quinns grocery store GW -9.62 -62.98 14.01 St rte 45 4of 87 North Bloomfield 173.00 1/3/2018 41°32'0.48"N 80°34'21.30"W 3 Post Office in GW -9.83 -64.08 14.59 williamsfield OH tap on 322 W of 7 174.00 1/3/2018 41°32'10.63"N 80°45'26.67"W 3 Colebrook Lounge on GW -8.51 -54.07 14.05 322 east of 46 Colebrook OH tap

117

175.00 1/3/2018 41°32'7.32"N 80°50'41.14"W 3 JD's pit stop 322/ GW -8.94 -57.87 13.63 main st and Satley rd Orwell OH tap 176.00 1/3/2018 41°36'20.27"N 80°51'53.71"W 3 Primary health GW -6.24 -47.26 2.65 network 5266 state rte 45 Rome OH tap 177.00 1/3/2018 41°36'18.29"N 80°46'50.73"W 3 BP gas station at 6 GW -3.21 -31.65 -6.01 and 46 New Lyme, OH grand army of the republic hay tap 179.00 1/3/2018 41°51'46.89"N 80°34'19.44"W 3 Bushnell store tap at GW -9.80 -63.44 14.98 7 and 84 center rd and bushnell 193.00 1/4/2018 41°23'13.42"N 81°12'59.71"W 2 Baitshop on corner GW -9.56 -62.14 14.33 og Washington ST & ravenna Rd/ 44 Auburn corner OH business for sale Tap 194.00 1/4/2018 41°28'14.38"N 81°11'35.79"W 2 87 New Berry OH GW -9.66 -62.32 14.95 tap 195.00 1/4/2018 41°27'44.49"N 81° 5'9.74"W 2 McDonalds at W GW -10.01 -65.53 14.57 high St & springdale ave in Middlefield OH tap 196.00 1/4/2018 41°36'26.84"N 81° 3'2.81"W 2 Montville country GW -10.07 -65.29 15.26 store at 528 & 6 / Madison rd & GAR hwy Mintville OH tap 197.00 1/4/2018 41°41'23.20"N 81° 3'2.53"W 2 Stockers on the park GW -10.24 -66.74 15.14 resturaunt on 527 in circle thompson OH 198.00 1/4/2018 41°36'24.94"N 81° 8'36.55"W 2 Hambden Corners GW -10.02 -64.61 15.54 gas station at 166 & GAR hwy tap Hambden Corners OH 199.00 1/4/2018 41°35'1.02"N 81°20'53.16"W 2 Circle K & 6 & 306 GW -6.41 -48.67 2.64 Chillcothe rd & Chardon Rd tap Pecks Corners OH 200.00 1/4/2018 41°31'23.04"N 81°20'18.90"W 2 Pizza Hut on GW -10.38 -67.46 15.61 Chillcothe rd & Mayfield OH tap 204.00 1/4/2018 41°23'23.37"N 81°20'24.85"W 2 McDonalds at GW -9.69 -63.54 14.02 Chillcothe Rd & Chagrin Rd Bain Bridge OH tap 206.00 1/4/2018 41°18'31.18"N 81°26'30.33"W 1 Panera Bread at 91 GW -6.51 -49.37 2.69 & 480/14 Twinsburg OH tap 207.00 1/4/2018 41°18'51.60"N 81°30'42.42"W 1 Speedway gas GW -6.49 -49.39 2.52 station at east aurora Rd & S Bedford Rd/ freeway

118

Dr Macedonia OH tap 208.00 1/4/2018 41°19'7.21"N 81°37'38.51"W 1 8952 Brecksville Rd GW -6.41 -48.73 2.53 & shell gas station Arlington St Brecksville OH tap 209.00 1/4/2018 41°14'23.76"N 81°39'13.77"W 1 Best Stop at 179 & GW -9.14 -58.68 14.42 303 Richfield OH tap 212.00 1/4/2018 41°14'17.03"N 81°20'50.92"W 4 Giant Eagle grocery GW -8.64 -57.62 11.53 store at 43 & 303/14 Streetsboro OH tap 213.00 1/4/2018 41° 9'1.55"N 81°21'3.10"W 4 McGilvery Hall Kent GW -8.31 -55.47 10.98 OH tap 224.00 2/4/2018 41°18'38.39"N 81°13'16.90"W 4 Shell Gas station at GW -9.69 -63.09 14.43 33 & 82 Tap grab 229.00 3/18/2018 41°34'43.06"N 81°14'40.34"W 2 Deep Spring Mineral GW -10.44 -67.82 15.74 water Chardon,Oh 122.01 7/21/2018 41°36'52.02"N 81°17'38.02"W 2 Long Science Center GW -9.96 -64.70 15.00 Tap Water 125.01 7/28/2018 41° 6'39.05"N 4 Speedway gas GW -8.73 -58.15 11.68 81°14'36.40"W station corner Lynn and Prospect Rootstown, OH Tap 126.01 7/28/2018 41° 1'46.70"N 81°14'55.07"W 4 Marathon Gas GW -8.89 -57.75 13.36 station corner of 44 and 224 Randolph, OH, Tap 127.01 7/28/2018 41° 1'51.21"N 81°25'35.42"W 4 Speedway gas GW -6.98 -48.14 7.67 station corner of 224 and 91 (1275) tap Lakemore, OH 130.01 7/28/2018 40°59'21.05"N 81°39'51.82"W 1 Circle K gas station GW -8.16 -53.59 11.66 at 21 and eastern Rd Norton, OH Tap 131.01 7/28/2018 40°59'53.63"N 81°48'36.03"W 1 Circle K gas station GW -8.99 -58.87 13.03 at Broad and Silvercreek Rd Wadsworth, OH Tao 132.01 7/28/2018 41° 2'9.05"N 81°51'53.97"W 1 Circle K gas station GW -8.90 -58.45 12.73 at 76 and 3 seville Tap 133.01 7/28/2018 40°59'53.29"N 81°48'35.68"W 1 BP minimart Lake Rd GW -8.64 -56.63 12.47 and Reid Rd Chippew on the Lake, OH tap 135.01 7/28/2018 41°13'58.66"N 81°50'28.11"W 1 Speedway at 42 GW -6.91 -51.71 3.54 Pearl Rd and Oxford Dr Tap, Brunswick OH 136.01 7/28/2018 41°20'36.47"N 81°49'32.15"W 1 Sheetz at Whitney GW -6.84 -51.50 3.21 Rd and Pearl Rd/ 42 Middleburg Hts, OH tap 144.01 7/29/2018 41° 1'26.51"N 81° 8'51.12"W 4 Circle K gas stationa GW -8.70 -56.17 13.43 Atwater at 183 and 224 Tap

119

145.01 7/29/2018 41° 0'54.77"N 80°59'13.31"W 4 Army corps of eng. GW -9.08 -59.62 13.04 Berlin, OH Berlin Lake Bedell Rd South of 224 Tap 146.01 7/29/2018 41° 1'26.24"N 80°51'28.05"W 5 Sunoco Gas station GW -9.65 -63.95 13.24 at 45 and 224 Ellsworth, OH tap 147.01 7/29/2018 41° 1'26.49"N 80°44'11.12"W 5 Sheetz Gas station GW -5.62 -41.74 3.21 at 11 and 224 in Canfield OH Tap 157.01 7/29/2018 41°14'0.38"N 80°33'50.64"W 5 Scotty's Brookfield GW -7.74 -53.37 8.58 express mark on Warren Sharon Rd and Bedford SE Brookfield OH 158.01 7/29/2018 41°14'16.13"N 80°44'24.46"W 5 Get Go gas station GW -7.72 -53.18 8.57 on Niles courtland road SE and East market, Howland Corners tap 159.01 7/29/2018 41°15'32.46"N 80°52'6.48"W 5 Circle K 4021 N GW -6.26 -45.78 4.31 Leavitt Rd and Parkman Rd NW warren OH 162.01 7/29/2018 41°18'30.38"N 80°44'39.29"W 5 Lakeside sport shop. GW -9.03 -58.87 13.40 Warren Meedville Rd and Wilson Sharpvill Rd 164.01 7/29/2018 41°23'18.54"N 80°39'55.57"W 5 Quinns Mini Mart at GW -8.53 -55.18 13.10 193 and 88 Johnson OH 165.01 7/29/2018 41°23'23.28"N 80°44'10.14"W 5 JAK's fine foods and GW -9.22 -59.61 14.16 gas station on 88 and 45 greenville Rd and Niles Courtland Rd NE Tap 166.01 7/30/2018 41°14'9.78"N 81° 8'39.48"W 4 Detour Drive thru on GW -9.22 -60.38 13.42 303/88 on Hadson Breeville Rd Freedom OH tap 168.01 7/30/2018 41°16'39.61"N 81° 5'24.16"W 4 Skylane Bowling GW -9.55 -62.85 13.56 Alley 82 and Liberty St tap Garrettsville OH 169.01 7/30/2018 41°22'14.30"N 81° 3'48.88"W 2 BP gas station at 88 GW -9.75 -63.76 14.25 and 422 Main market Rd and Madison Rd tap Elwood/Spike Weaver grand river access Parkman OH 171.01 7/29/2018 41°27'46.56"N 80°52'7.56"W 5 Quinns grocery store GW -9.59 -62.80 13.96 St rte 45 4of 87 North Bloomfield 173.01 7/29/2018 41°32'0.48"N 80°34'21.30"W 3 Post Office in GW -8.88 -57.29 13.76 williamsfield OH tap on 322 W of 7

120

174.01 7/29/2018 41°32'10.63"N 80°45'26.67"W 3 Colebrook Lounge on GW -8.41 -53.70 13.58 322 east of 46 Colebrook OH tap 175.01 7/29/2018 41°32'7.32"N 80°50'41.14"W 3 JD's pit stop 322/ GW -8.81 -57.50 12.95 main st and Satley rd Orwell OH tap 176.01 7/29/2018 41°36'20.27"N 80°51'53.71"W 3 Primary health GW -7.03 -52.48 3.76 network 5266 state rte 45 Rome OH tap 177.01 7/29/2018 41°36'18.29"N 80°46'50.73"W 3 BP gas station at 6 GW -3.33 -34.33 -7.70 and 46 New Lyme, OH grand army of the republic hay tap 179.01 7/30/2018 41°51'46.89"N 80°34'19.44"W 3 Bushnell store tap at GW -9.69 -62.95 14.55 7 and 84 center rd and bushnell 193.01 7/30/2018 41°23'13.42"N 81°12'59.71"W 2 Baitshop on corner GW -9.21 -60.21 13.47 og Washington ST & ravenna Rd/ 44 Auburn corner OH business for sale Tap 194.01 7/30/2018 41°28'14.38"N 81°11'35.79"W 2 87 New Berry OH GW -9.61 -62.29 14.58 tap 195.01 7/29/2018 41°27'44.49"N 81° 5'9.74"W 2 McDonalds at W GW -9.94 -65.39 14.15 high St & springdale ave in Middlefield OH tap 196.01 7/30/2018 41°36'26.84"N 81° 3'2.81"W 2 Montville country GW -10.03 -65.33 14.93 store at 528 & 6 / Madison rd & GAR hwy Mintville OH tap 197.01 7/30/2018 41°41'23.20"N 81° 3'2.53"W 2 Stockers on the park GW -7.15 -46.51 10.66 resturaunt on 527 in circle thompson OH 198.01 7/30/2018 41°36'24.94"N 81° 8'36.55"W 2 Hambden Corners GW -9.95 -64.77 14.83 gas station at 166 & GAR hwy tap Hambden Corners OH 199.01 7/30/2018 41°35'1.02"N 81°20'53.16"W 2 Circle K & 6 & 306 GW -6.73 -50.75 3.12 Chillcothe rd & Chardon Rd tap Pecks Corners OH 200.01 7/30/2018 41°31'23.04"N 81°20'18.90"W 2 Pizza Hut on GW -10.27 -67.53 14.65 Chillcothe rd & Mayfield OH tap 204.01 7/31/2018 41°23'23.37"N 81°20'24.85"W 2 McDonalds at GW -9.67 -63.42 13.93 Chillcothe Rd & Chagrin Rd Bain Bridge OH tap 206.01 7/31/2018 41°18'31.18"N 81°26'30.33"W 1 Panera Bread at 91 GW -6.82 -51.32 3.28 & 480/14 Twinsburg OH tap 207.01 7/31/2018 41°18'51.60"N 81°30'42.42"W 1 Speedway gas GW -6.84 -51.44 3.27 station at east

121

aurora Rd & S Bedford Rd/ freeway Dr Macedonia OH tap 208.01 7/31/2018 41°19'7.21"N 81°37'38.51"W 1 8952 Brecksville Rd GW -6.82 -51.35 3.22 & shell gas station Arlington St Brecksville OH tap 209.01 7/31/2018 41°14'23.76"N 81°39'13.77"W 1 Best Stop at 179 & GW -8.81 -57.18 13.31 303 Richfield OH tap 212.01 7/31/2018 41°14'17.03"N 81°20'50.92"W 4 Giant Eagle grocery GW -8.75 -58.49 11.47 store at 43 & 303/14 Streetsboro OH tap 213.01 7/31/2018 41° 9'1.55"N 81°21'3.10"W 4 McGilvery Hall Kent GW -8.37 -56.30 10.65 OH tap 224.01 8/4/2018 41°18'38.39"N 81°13'16.90"W 4 Shell Gas station at GW -9.65 -63.03 14.15 33 & 82 Tap grab 229.01 8/4/2018 41°34'43.06"N 81°14'40.34"W 2 Deep Spring Mineral GW -10.32 -67.38 15.18 water Chardon,Oh 120.00 12/13/2017 41°36'49.38"N 2 Holden Precipitation Precip -17.75 -118.89 23.14 81°17'40.02"W Collector 120.01 12/29/2017 41°36'49.38"N 2 Holden Precipitation Precip -16.72 -116.00 17.80 81°17'40.02"W Collector 120.02 1/12/2018 41°36'49.38"N 2 Holden Precipitation Precip -12.49 -81.90 18.04 81°17'40.02"W Collector 120.03 2/4/2018 41°36'49.38"N 2 Holden Precipitation Precip -5.05 -38.81 1.61 81°17'40.02"W Collector 120.04 2/17/2018 41°36'49.38"N 2 Holden Precipitation Precip -12.69 -90.71 10.78 81°17'40.02"W Collector 120.05 3/3/2018 41°36'49.38"N 2 Holden Precipitation Precip -10.85 -76.11 10.70 81°17'40.02"W Collector 120.06 3/18/2018 41°36'49.38"N 2 Holden Precipitation Precip -14.27 -100.46 13.68 81°17'40.02"W Collector 120.07 3/31/2018 41°36'49.38"N 2 Holden Precipitation Precip -8.69 -54.51 14.97 81°17'40.02"W Collector 120.08 4/14/2018 41°36'49.38"N 2 Holden Precipitation Precip -7.63 -48.00 13.05 81°17'40.02"W Collector 120.09 4/27/2018 41°36'49.38"N 2 Holden Precipitation Precip -8.88 -57.94 13.09 81°17'40.02"W Collector 120.10 5/12/2018 41°36'49.38"N 2 Holden Precipitation Precip -4.45 -21.89 13.69 81°17'40.02"W Collector 120.11 5/27/2018 41°36'49.38"N 2 Holden Precipitation Precip -5.93 -35.76 11.72 81°17'40.02"W Collector 120.12 6/9/2018 41°36'49.38"N 2 Holden Precipitation Precip -9.19 -57.47 16.04 81°17'40.02"W Collector 120.13 6/23/2018 41°36'49.38"N 2 Holden Precipitation Precip -6.78 -40.16 14.05 81°17'40.02"W Collector 120.14 7/7/2018 41°36'49.38"N 2 Holden Precipitation Precip -5.76 -34.20 11.91 81°17'40.02"W Collector 120.15 7/21/2018 41°36'49.38"N 2 Holden Precipitation Precip -3.43 -15.71 11.71 81°17'40.02"W Collector 120.16 8/4/2018 41°36'49.38"N 2 Holden Precipitation Precip -9.51 -62.71 13.33 81°17'40.02"W Collector 120.17 8/18/2018 41°36'49.38"N 2 Holden Precipitation Precip -4.82 -25.48 13.08 81°17'40.02"W Collector

122

120.18 9/1/2018 41°36'49.38"N 2 Holden Precipitation Precip -6.77 -38.46 15.68 81°17'40.02"W Collector 120.19 9/15/2018 41°36'49.38"N 2 Holden Precipitation Precip -11.50 -79.90 12.09 81°17'40.02"W Collector 120.20 9/29/2018 41°36'49.38"N 2 Holden Precipitation Precip -7.29 -45.32 12.96 81°17'40.02"W Collector 120.21 10/13/2018 41°36'49.38"N 2 Holden Precipitation Precip -7.75 -43.69 18.33 81°17'40.02"W Collector 120.22 10/27/2018 41°36'49.38"N 2 Holden Precipitation Precip -13.98 -94.48 17.39 81°17'40.02"W Collector 120.23 11/10/2018 41°36'49.38"N 2 Holden Precipitation Precip -12.78 -85.47 16.79 81°17'40.02"W Collector 120.24 11/24/2018 41°36'49.38"N 2 Holden Precipitation Precip -17.44 -125.73 13.81 81°17'40.02"W Collector 120.25 12/8/2018 41°36'49.38"N 2 Holden Precipitation Precip -13.40 -91.27 15.93 81°17'40.02"W Collector 120.26 12/22/2018 41°36'49.38"N 2 Holden Precipitation Precip -15.82 -114.26 12.27 81°17'40.02"W Collector 260.01 12/13/2017 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -17.46 -115.70 24.0 Gauge 260.02 12/15/2017 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -18.60 -132.46 16.3 Gauge 260.03 12/18/2017 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -8.27 -54.76 11.4 Gauge 260.04 12/24/2017 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -14.26 -104.26 9.8 Gauge 260.05 12/31/2017 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -25.31 -181.14 21.4 Gauge 260.06 1/1/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -6.68 -42.67 10.8 Gauge 260.07 1/12/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -6.50 -38.93 13.1 Gauge 260.08 1/13/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -12.79 -87.93 14.4 Gauge 260.09 1/17/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -10.38 -69.34 13.7 Gauge 260.10 1/23/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -5.71 -26.76 19.0 Gauge 260.11 1/28/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -8.50 -50.72 17.3 Gauge 260.12 1/31/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -18.00 -124.08 19.9 Gauge 260.13 2/5/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -17.83 -125.54 17.1 Gauge 260.14 2/8/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -17.60 -128.93 11.9 Gauge 260.15 2/11/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -9.05 -57.04 15.4 Gauge 260.16 2/15/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -6.08 -35.34 13.3 Gauge 260.17 2/16/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -8.51 -59.73 8.4 Gauge 260.18 2/18/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -9.85 -65.85 12.9 Gauge 260.19 2/20/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -5.21 -28.16 13.5 Gauge

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260.20 2/23/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -7.96 -61.91 1.8 Gauge 260.21 2/24/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -9.48 -66.38 9.5 Gauge 260.22 2/25/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -7.21 -45.97 11.7 Gauge 260.23 3/1/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -5.23 -32.56 9.3 Gauge 260.24 3/2/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -15.63 -114.86 10.1 Gauge 260.25 2/10/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -12.60 -92.37 8.4 Gauge 260.26 3/14/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -19.49 -140.89 15.0 Gauge 260.27 3/21/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -18.33 -135.38 11.3 Gauge 260.28 3/28/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -5.43 -29.15 14.3 Gauge 260.29 3/30/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -11.87 -85.78 9.2 Gauge 260.30 4/4/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -6.64 -41.50 11.7 Gauge 260.31 4/15/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -5.88 -31.38 15.7 Gauge 260.32 4/16/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -9.37 -64.24 10.7 Gauge 260.33 4/25/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -13.14 -96.72 8.4 Gauge 260.34 4/29/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -10.54 -73.12 11.2 Gauge 260.35 5/4/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -1.48 0.82 12.7 Gauge 260.36 5/13/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -4.86 -26.14 12.7 Gauge 260.37 5/14/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -3.83 -18.20 12.4 Gauge 260.38 5/20/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -6.37 -39.55 11.4 Gauge 260.39 5/22/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -8.07 -61.72 2.8 Gauge 260.40 5/23/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -4.54 -24.03 12.3 Gauge 260.41 6/3/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -6.95 -41.20 14.4 Gauge 260.42 6/10/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -3.68 -13.71 15.7 Gauge 260.43 6/11/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -3.66 -13.80 15.5 Gauge 260.44 6/19/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -4.11 -20.22 12.7 Gauge 260.45 6/24/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -12.68 -89.07 12.4 Gauge 260.46 6/28/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -7.46 -48.05 11.6 Gauge 260.47 7/5/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -4.57 -32.02 4.5 Gauge

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260.48 7/6/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -4.14 -23.13 10.0 Gauge 260.49 7/23/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -10.01 -66.71 13.3 Gauge 260.50 7/27/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -7.57 -48.72 11.9 Gauge 260.51 8/1/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -6.21 -42.79 6.9 Gauge 260.52 8/7/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -4.66 -21.67 15.6 Gauge 260.53 8/8/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -3.89 -21.49 9.6 Gauge 260.54 8/18/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -5.09 -30.44 10.3 Gauge 260.55 8/21/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -5.89 -32.25 14.9 Gauge 260.56 8/22/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -8.00 -48.46 15.6 Gauge 260.57 8/26/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -5.41 -26.06 17.2 Gauge 260.58 8/30/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -3.71 -12.94 16.8 Gauge 260.59 9/7/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -3.94 -17.08 14.5 Gauge 260.60 9/8/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -7.71 -51.64 10.0 Gauge 260.61 9/9/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -12.10 -88.02 8.8 Gauge 260.62 9/9/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -12.91 -88.75 14.6 Gauge 260.63 9/10/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -10.03 -63.76 16.5 Gauge 260.64 9/18/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -7.94 -54.95 8.6 Gauge 260.65 9/20/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -4.36 -26.37 8.5 Gauge 260.66 9/25/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -8.70 -54.85 14.8 Gauge 260.67 9/27/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -7.38 -43.33 15.7 Gauge 260.68 10/3/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -3.26 -11.60 14.5 Gauge 260.69 10/6/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -5.44 -30.75 12.8 Gauge 260.70 10/7/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -4.26 -17.29 16.8 Gauge 260.71 10/13/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -13.79 -89.89 20.4 Gauge 260.72 10/21/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -14.83 -102.88 15.7 Gauge 260.73 10/27/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -13.80 -91.27 19.1 Gauge 260.74 10/28/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -13.82 -87.74 22.8 Gauge 260.75 10/29/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -14.65 -100.64 16.6 Gauge

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260.76 11/2/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -8.87 -51.46 19.5 Gauge 260.77 11/3/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -16.17 -112.99 16.4 Gauge 260.78 11/6/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -10.25 -73.31 8.7 Gauge 260.79 11/9/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -13.79 -88.38 22.0 Gauge 260.80 11/17/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -17.90 -132.34 10.8 Gauge 260.81 11/20/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -16.34 -109.46 21.3 Gauge 260.82 11/25/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -14.53 -96.92 19.3 Gauge 260.83 11/26/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -8.02 -43.15 21.0 Gauge 260.84 11/28/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -13.45 -90.00 17.6 Gauge 260.85 12/2/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -12.57 -87.11 13.5 Gauge 260.86 12/16/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -12.78 -98.55 3.7 Gauge 260.87 12/21/2018 41° 9'27.95"N 81°21'5.03"W 4 Kent Precipitation Precip -15.78 -113.76 12.5 Gauge GNIR 12/18/2017 41° 9'0.23"N 4 GNIR Cuyahoga Lotic -8.27 -54.76 11.4 Kent 81°21'45.57"W River Kent GNIR 1/17/2018 41° 9'0.23"N 4 GNIR Cuyahoga Lotic -10.38 -69.34 13.7 Kent 81°21'45.57"W River Kent GNIR 2/16/2018 41° 9'0.23"N 4 GNIR Cuyahoga Lotic -9.85 -65.85 12.9 Kent 81°21'45.57"W River Kent GNIR 3/17/2018 41° 9'0.23"N 4 GNIR Cuyahoga Lotic -9.63 -65.83 11.2 Kent 81°21'45.57"W River Kent GNIR 4/15/2018 41° 9'0.23"N 4 GNIR Cuyahoga Lotic -8.46 -56.05 11.7 Kent 81°21'45.57"W River Kent GNIR 5/15/2018 41° 9'0.23"N 4 GNIR Cuyahoga Lotic -7.70 -50.94 10.7 Kent 81°21'45.57"W River Kent GNIR 6/17/2018 41° 9'0.23"N 4 GNIR Cuyahoga Lotic -7.77 -52.60 9.6 Kent 81°21'45.57"W River Kent GNIR 7/14/2018 41° 9'0.23"N 4 GNIR Cuyahoga Lotic -7.10 -48.97 7.8 Kent 81°21'45.57"W River Kent GNIR 8/16/2018 41° 9'0.23"N 4 GNIR Cuyahoga Lotic -7.05 -48.40 8.0 Kent 81°21'45.57"W River Kent GNIR 9/17/2018 41° 9'0.23"N 4 GNIR Cuyahoga Lotic -7.88 -53.91 9.2 Kent 81°21'45.57"W River Kent GNIR 10/16/2018 41° 9'0.23"N 4 GNIR Cuyahoga Lotic -7.45 -49.46 10.2 Kent 81°21'45.57"W River Kent GNIR 11/18/2018 41° 9'0.23"N 4 GNIR Cuyahoga Lotic -9.54 -64.82 11.5 Kent 81°21'45.57"W River Kent GNIR 12/12/2018 41° 9'0.23"N 4 GNIR Cuyahoga Lotic -9.31 -62.49 12.0 Kent 81°21'45.57"W River Kent

126