Surface water quality in Otsego County, NY, prior to potential natural gas exploration

Sarah Crosier1

Abstract –Baseline water quality data was established for Otsego County, NY prior to potential natural gas exploration. Hydraulic fracturing may contaminate surface water with chemicals, salts and sediments. Averages for pH, total dissolved solids, and conductivity were calculated for 50 Otsego County streams from data collected using a YSI® multi-parameter probe from August 2010 – April 2012. Limestone bedrock sub-watersheds had significantly higher conductivity, TDS and pH than shale bedrock sub-watersheds. Winter and summer peaks and fall and spring lows occurred in conductivity and TDS. Road salt use, precipitation and evaporation likely caused seasonal variation. Sub-watershed size had no significant effect on parameters. These data will serve as a control for future water quality testing if hydraulic fracturing occurs in Otsego County, NY.

INTRODUCTION

This study was conducted to identify baseline water quality conditions at base flow for streams in Otsego County. Water quality varies between streams due to different physical, chemical, and microbiological characteristics (Rajeshwari and Saraswathi 2009). These factors are dependent upon topography, geology, vegetative cover (Dosskey et al. 2010), land use in a watershed (Ou and Wang 2011) and watershed size (Landers et al. 2007).

Stream chemistry varies naturally throughout the seasons due to changes in precipitation, evaporation, nutrient input, and biotic activity within the streams. Anthropogenic pollutants such as road salt (Jackson and Jobbágy 2005, Kaushal et al. 2005), urban storm water runoff and agricultural pesticides, nutrients, and sediments (Madden et al. 2007) also affect stream quality variably. Stream quality may differ between years, particularly due to changes in flow conditions due to higher or lower-than-average rainfall.

The goal was to ascertain the range of water quality parameters common in pre-drilling Otsego County so that we may detect changes in water quality should natural gas exploration occur. Hydrofracturing for natural gas may cause water degradation due to chemical, salt, or sediment contamination (Balyszak 2011). Conductivity, pH, and total dissolved solids (TDS) are basic water quality parameters used to identify contamination of water due to natural gas drilling (EPA 2011). We monitored these water quality variables monthly in 50 streams in Otsego County. If pollution occurs from potential natural gas activities, we expect conductivity and TDS to rise (due to more ions present) and for pH to decrease due to increased acidity from chemicals used for hydrofracturing. Various combinations of chemicals are used to facilitate the fracturing process. For example, pH may increase because acid, such as hydrochloric acid, is used to dissolve minerals and initiate cracks in rock from which gas may be extracted (EPA 2011).

1 Otsego County SWCD intern. Environmental Sciences, State University of New York College at Oneonta, Oneonta, New York 13820.

By monitoring at base flow conditions, we identified the natural variation of stream water quality in Otsego County. We were able to observe when, how often, and how much water quality parameters vary throughout the year. Knowing these ranges can allow us to detect surface water quality issues in the future. Our focus was to establish baseline conditions prior to potential natural gas exploration, but the information gained can allow us to document other pollutions that may occur within the County.

FIELD SITE DESCRIPTION

We conducted this study in Central New York in Otsego County, which is located west of Albany, southeast of Utica, and northeast of Binghamton. Otsego County is part of the Upper Susquehanna River Watershed. Following protocols established by the Susquehanna River Basin Commission used in their Remote Monitoring Network, we selected 50 sites on low-order streams (Table 1) throughout Otsego County, NY. We chose low order streams that drain 170 square kilometers or less to account for the sensitivity of our field instruments. Figure 1 is a map showing monitoring site locations. Sites are located at the terminus of each sub-watershed and are easily accessible from or next to bridges. A sub-watershed in this paper refers to the area of land draining to a monitoring site. The watersheds in which the monitoring sites are located are defined by the New York State Department of Environmental Conservation (NYS DEC) 12-digit Hydrologic Unit Code (HUC) and are listed in Table 1.

METHODS

Equipment A YSI Professional Plus® multi-parameter meter was used to collect pH, conductivity, temperature, and TDS data as well as time and date information. Monitoring SUNY Oneonta students and Otsego County Soil and Water District employees conducted water monitoring from August 13, 2010 - April 21, 2012. We visited each of the 50 sites monthly. Some sites were not monitored as frequently due to inaccessibility from ice formation, hazardous access, or time constraints.

Analysis Sub-watershed area- ArcGIS® was used to display average conductivity and pH values for data collected from August 2010-August 2011 for each of the sub-watersheds. Relationships between the means of TDS, pH, conductivity and sub-watershed area were tested using Spearman’s Rank Correlation using SYSTAT®.

Geology- Sites were divided into two categories: limestone, and shale (Figure 1), based on the geology of the area according to the Otsego County Soil Survey (Figure 2). Some sites were not included because their respective sub-watersheds were both shale and limestone based. A Mann-Whitney Test was run using Minitab® on data from 45 sub-watersheds to determine if bedrock was significantly correlated with conductivity.

Stream monitoring location

Primarily Limestone with some shale

Shale, siltstone, and sandstone

Figure 1. Sites sampled for water quality in Otsego County, NY from 13Aug10 – 21Apr12 with bedrock geology. See Table 1 for a list of stream names and the corresponding identification numbers.

Table 1. Sites monitored for water quality in Otsego County, NY from 13Aug10 – 21Apr12. Sites listed by sub-watershed name. HUC codes are used by the NYSDEC, NRCS, and USGS for delineating watershed boundaries. The 12 digit code used here is the smallest unit of watershed depicted. Site ID refers to site number in Figure 1. Bridge location is where the site was accessed from. Area (km2) is the area of the sub-watershed.

Sub-Watershed Site ID HUC Town Coordinates Bridge Area (km2) Geologya Area sq mi N W Aldrich Brook 17 020501010802 Morris 42.55701 75.22853 State Hwy 51, south Cty Hwy 49 18.1 S 7.0 Brier Creek 23 020501011102 Otego 42.37381 75.21772 State Rt 7, west of Cty Hwy 5 23.1 S 8.9 Cahoon Creek 14 020501010803 Butternuts 42.47196 75.31449 Bloom Street, east of Butternut Creek 27.4 S 10.6 Campbell Brook 24 020501010905 Plainfield 42.82387 75.23535 Cty Hwy 18, south of Cty Hwy 21, X Pritchard 12.5 L 4.8 Chase Creek 36 020501010604 Middlefield 42.6579 74.96046 State Hwy 28, across from SPCA 19.5 L 7.5 Cripple Creek 39 020501010603 Springfield 42.81396 74.9005 State Hwy 80, across from Bartlet Rd 40.6 L 15.7 Decatur Creek 42 020501010303 Worcester 42.5914 74.75387 State Hwy 7, east of Cty Hwy 39 34.9 L 13.5 Dunderberg Creek 15 020501010803 Butternuts 42.47233 75.31643 Bloom Street, west of Butternut Creek 16.2 S 6.2 Elk Creek 39 020501010302 Maryland 42.54499 74.84201 State Hwy 7, east of Valder Road 85.3 L 33.0 Flax Island Creek 10 020501011101 Otego 42.38968 75.18527 State Rt 7, west of Flax Island Road 13.1 S 5.1 Fly Creek 1 020501010103 Otsego 42.71806 74.98177 State Hwy 28/80 east of Village 36.6 L 14.1 Harrison/Cooper Creeks 6 020501010504 Laurens 42.48724 75.11815 Cty Hwy 11, North of State Hwy 23 22.6 S 8.7 Hayden Creek 8 020501010603 Springfield 42.82129 74.88303 Cty Hwy 53, East of State 80 24.1 L 9.3 Herkimer Creek 33 020501010102 Richfield 42.78866 75.0247 State Hwy 28, south of Taylor Road 22.8 L 8.8 Hinman Hollow Brook 37 020501010604 Milford 42.59509 74.0457 State Hwy 28, south of Oxbow Road 20.8 L 8.0 Hyder Creek 32 020501010102 Richfield 42.81657 75.01965 State Hwy 28, north of Wing Hill Road 24.2 L 9.4 Indian/Sand Hill Creeks 11 020501011103 Unadilla 42.37147 75.26382 State Hwy 7, east of Cty Hwy 3a 37.3 S 14.4 Lake Brook 3 020501010503 Laurens 42.53328 75.08913 Brook Street, south of Town Hall 16.8 S 6.5 Lidell Creek 26 020501010103 Exeter 42.75981 75.02778 State Hwy 28 south of Cty Hwy 16 * L * Middle Wharton Creek 35 020501010702 Edmeston 42.70475 75.24465 State Hwy 80, South of Burdick Ave 167.8 L 64.8 Mill Creek 23 020501010703 Edmeston 42.70471 75.24458 Cty Hwy 20, across from Bert White Road 24.8 L 9.6 Moorehouse Brook 21 020501010304 Maryland 42.53473 74.89551 State Rt 7, east of Cty Hwy 42 18.6 7.2 Morris Brook 16 020501010803 Morris 42.5088 75.28967 St Hwy 51, across from Dimmock Hollow Rd 20.2 S 7.8 O'Connel Brook 48 020501010203 Middlefield 42.6908 74.84377 Moore Road, South off State Hwy 166 8.5 L 3.3 Oneonta Creek 7 020501010606 Oneonta 42.45571 75.05533 Fair Street, under J. Lettis Hwy 21.5 S 8.3 Oquiniuos Creek 31 020501010102 Richfield 42.85014 74.99079 Elm Street, south of Town 52.7 L 20.3 Otsdawa Creek 9 020501011101 Otego 42.39995 75.17185 State Hwy 7, East of Cty Hwy 7 51.9 S 20.1 Palmer Creek 41 020501010303 Maryland 42.5652 74.78461 State Hwy 7, west of Gohan road 4.8 1.9 Pleasant Brook 45 020501010201 Roseboom 42.71973 74.76939 State Hwy 165, North of Pleasant Brook 56.5 L 21.8 Pool Brook 4 020501010503 Laurens 42.54105 75.08086 Cty Hwy 11, South of Pool Brook road 14.9 S 5.8 Potato Creek 38 020501010304 Maryland 42.50283 74.92709 State Rt 7, east of Peterson Road 8.5 S 3.3 Red Creek 25 020501010604 Middlefield 42.6862 74.9184 Intersection of Cty Hwy 33 and 52 33.1 L 12.8 Rogers Hollow Brook 13 020501010910 Unadilla 42.34176 75.39375 Cty Hwy 1 & 1B 33.2 S 12.8 Shadow Brook 27 020501010602 Springfield 42.79071 74.85894 Mill Road, West of Cty Hwy 31 43.0 L 16.6 Shellrock Brook 46 020501010203 Middlefield 42.70922 74.81886 Hubble Hollow Road & State Hwy 166 14.8 L 5.7 Sparrowhawk Brook 40 020501010303 Maryland 42.5473 74.8251 Race Street, south of State Hwy 7 6.6 L 2.6 Spring Brook 49 020501010605 Milford 42.53008 74.97894 State Hwy 28, east of Cty Hwy 44 29.8 S 11.5 Stony/Mill Creeks 19 020501010801 New Lisbon 42.59245 75.18867 Meyers Mill Rd, North of Cty Hwy 12 23.1 S 8.9 Trout Brook 29 020501010603 Springfield 42.80672 74.90287 State Hwy 80, North of Cty Hwy 27 13.3 L 5.1 Unamed Blue line 12 020501011105 Unadilla 42.32403 75.31158 Watson Street, west of cemetary 8.0 S 3.1 Unamed Blue line Lower CV 47 020501010204 Middlefield 42.68145 74.86813 State Hwy 166, north of Cty Hwy 52 5.2 L 2.0 Upper Butternut Creek 18 020501010801 New Lisbon 42.58939 75.19321 Cty Hwy 12, East of State Hwy 51 111.4 L 43.0 Upper Cherry Valley Creek 44 020501010202 Roseboom 42.74007 74.77361 State Hwy 165, East of Town 61.1 L 23.6 Upper Otego Creek 50 020501010502 Hartwick 42.61636 75.05741 Cty Hwy 11D, West of State Hwy 205 59.8 L 23.1 Upper Schenevus Creek 43 020501010301 Worcester 42.58863 74.7499 Cty Hwy 39, South of State Hwy 7 66.6 25.7 Upper Unadilla River 34 020501010905 Plainfield 42.84246 75.24294 Cty Hwy 18, north of Unadilla Forks 149.7 L 57.8 Upper Wharton Creek 23 020501010701 Burlington 42.68868 75.24188 Cty Hwy 19, East of State Hwy 51 83.7 L 32.3 West Branch Otego Creek 2 020501010501 Laurens 42.59083 75.06508 Cty Hwy 11, East of Cty Hwy 15 50.8 S 19.6 Wharton creek 5 020501010504 Laurens 42.51121 75.10594 Cty Hwy 11 and New Road 169.5 S 65.4 Whitney Creek 20 020501010303 Maryland 42.53648 74.88545 State Hwy 7, east of Dog Hill/Kenyon Road 6.0 2.3 * Lidell creek sub-watershed area data unavailable a L = Limestone, S = Shale Some geology data omitted because the sub-watershed contained both types of bedrock.

Figure 2. Bedrock Geology of Otsego County, NY. Limestone is primarily present in the northern part of County, whereas shale, siltstone, and sandstone are present in southern part of County.

RESULTS

Sub-watershed size Sub-watershed size was weakly correlated with conductivity (Figure 3; r =0.35) and TDS (Figure 4; r = 0.32). No relationship was found between pH and sub-watershed area (Figure 5; r = -0.04). Sub-watersheds with shale bedrock appeared to be smaller than sub-watersheds with limestone bedrock (Figures 3 and 4) but no significant difference was found (T-test. T = 1.49, df = 42, p = 0.144).

Geology Geology had a strong influence on conductivity, TDS, and pH. Relationships exist between conductivity, pH, and geology (Figure 6). Significant differences exist in the conductivity (p=0.0001), TDS (p=0.0002), and pH (p=0.0019) measured in sub-watersheds with shale bedrock compared with sub-watersheds with limestone bedrock. Of the 45 sub-watersheds tested, 26 were limestone-based, and 19 were shale-based. 180 L

160 L

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120 L ) 2

m 100

k L ( S L

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A L L L 60 SS L L L S L S L L 40 S L S L L S S S L S L S S S L 20 S SL L L SL L S 0 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 Conductivity (mS/cm)

Figure 3. Relationship between sub-watershed area and conductivity (r = 0.35) for Otsego County, NY. Data points represent type of bedrock present in monitored sub-watershed where L = Limestone sub-watersheds and S = Shale sub-watersheds. Data collected from 13Aug10 – 21Apr12

180 L

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A L L L 60 S S L L L S L S L L 40 S L S L L SS S S L S L SS S L 20 SS L L L S L L S 0 0 100 200 300 400 TDS (mg/L)

Figure 4. Relationship between sub-watershed area and TDS (r = 0.32) for Otsego County, NY. Data points represent type of bedrock present in monitored sub-watershed where L = Limestone sub-watersheds and S = Shale sub-watersheds. Data collected from 13Aug10 – 21Apr12.

180 L

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A L L L 60 SS L L L S L S L L 40 S S L L S S S S S L L S S S L 20 S S L L L L L S L S 0 7.50 7.75 8.00 8.25 8.50 8.75 pH

Figure 5. Relationship between sub-watershed area and pH (r = -0.04) for Otsego County, NY. Data points represent type of bedrock present in monitored sub-watershed where L = Limestone sub-watersheds and S = Shale sub-watersheds. Data collected from 13Aug10 – 21Apr12.

Figure 6. Monitored sub-watersheds in Otsego County, NY, showing average conductivity and average pH. Averages represent data collected August 2010-August 2011.

Sub-watershed variability Conductivity and TDS were more variable than pH (Figures 7, 8 and 9). Pool Brook had the least variation in TDS (78.8 ± 14.6), while the Oneonta Creek experienced the most variation in TDS (200.3 ± 120.4). TDS and conductivity showed similar variation in the same streams. Five of the ten streams with the least variability for TDS were also listed in the ten least variable streams for conductivity, i.e., Lake Brook, Potato Creek, Brier Creek, Morris Brook, and Pool Brook (Table 2; Figures 7 and 8). Six of the ten streams with the most variability for TDS were also listed in the ten most variable streams for conductivity, i.e., Oquiniuos Creek, Cripple Creek, Shadow Brook, Hyder Creek, Upper Unadilla River, and Oneonta Creek. pH was relatively stable across sub-watersheds. Streams in which pH varied the most were the Unnamed Blue Line (8.74 ± 0.87) and Stony/Mill Creeks (7.63 ± 0.80). Trout Brook (8.58 ± 0.14) and Campbell Brook (8.33 ± 0.16) had the least variable pH.

Figure 7. Mean conductivity for streams monitored in Otsego County, NY ± 1 standard deviation. Means calculated from data collected monthly from 13Aug10 – 21Apr12.

Figure 8. Mean TDS for streams monitored in Otsego County, NY ± 1 standard deviation. Means calculated from data collected monthly from 13Aug10 – 21Apr12.

Figure 9. Mean pH for streams monitored in Otsego County, NY ± 1 standard deviation. Means calculated from data collected monthly from 13Aug10 – 21Apr12.

Table 2. Mean conductivity, TDS, and pH for streams monitored in Otsego County, NY ± 1 standard deviation. Means calculated from data collected monthly from 13Aug10 – 21Apr12.

Stream Name Conductivity (mS/cm) TDS (mg/L) pH Aldrich Brook 0.076 ± 0.04 83.0 ± 28.6 7.70 ± 0.28 Brier Creek 0.065 ± 0.02 79 ± 19.8 7.61 ± 0.40 Cahoon Creek 0.103 ± 0.04 138.6 ± 71.4 7.81 ± 0.38 Campbell Brook 0.127 ± 0.06 161.2 ± 53.0 8.33 ± 0.16 Chase Creek 0.116 ± 0.06 150.3 ± 67.1 8.37 ± 0.26 Cripple Creek 0.281 ± 0.08 360.0 ± 106.7 8.36 ± 0.20 Decatur Creek 0.077 ± 0.03 106.8 ± 35.1 8.07 ± 0.29 Dunderberg Creek 0.101 ± 0.05 135.4 ± 80.4 7.90 ± 0.38 Elk Creek 0.071 ± 0.03 85.3 ± 31.2 7.83 ± 0.32 Flax Island Creek 0.070 ± 0.03 77.5 ± 22.0 8.08 ± 0.48 Fly Creek 0.153 ± 0.07 195.5 ± 67.6 8.23 ± 0.41 Harrison/Cooper Creeks 0.096 ± 0.03 128.2 ± 37.8 7.79 ± 0.53 Hayden Creek 0.326 ± 0.07 418.6 ± 89.0 8.42 ± 0.22 Herkimer Creek 0.173 ± 0.07 220.2 ± 66.3 8.34 ± 0.25 Hinman Hollow Brook 0.107 ± 0.05 137.4 ± 49.2 8.26 ± 0.31 Hyder Creek 0.272 ± 0.09 358.4 ± 90.1 8.42 ± 0.27 Indian/Sand Hill Creeks 0.077 ± 0.05 106.5 ± 65.2 7.85 ± 0.44 Lake Brook 0.065 ± 0.02 86.5 ± 23.0 7.79 ± 0.32 Lidell Creek 0.140 ± 0.06 184.5 ± 60.9 8.42 ± 0.29 Middle Wharton Creek 0.159 ± 0.07 168.6 ± 49.9 8.09 ± 0.28 Mill Creek 0.087 ± 0.03 118.2 ± 26.1 8.18 ± 0.34 Moorehouse Brook 0.066 ± 0.03 83.2 ± 38.3 7.79 ± 0.30 Morris Brook 0.065 ± 0.02 90.0 ± 20.5 7.81 ± 0.35 O'Connel Brook 0.074 ± 0.04 99.7 ± 36.0 7.74 ± 0.46 Oneonta Creek 0.159 ± 0.09 200.3 ± 120.4 8.17 ± 0.27 Oquiniuos Creek 0.278 ± 0.07 382.9 ± 110.2 8.41 ± 0.22 Otsdawa Creek 0.073 ± 0.03 102.8 ± 34.9 7.91 ± 0.32 Palmer Creek 0.042 ± 0.03 56.3 ± 46.4 7.92 ± 0.20 Pleasant Brook 0.089 ± 0.06 104.5 ± 39.3 7.89 ± 0.41 Pool Brook 0.055 ± 0.01 78.8 ± 14.6 7.56 ± 0.40 Potato Creek 0.037 ± 0.01 47.4 ± 20.6 7.95 ± 0.51 Red Creek 0.121 ± 0.06 152.7 ± 62.8 8.36 ± 0.35 Rogers Hollow Brook 0.065 ± 0.02 91.7 ± 34.0 7.94 ± 0.28 Shadow Brook 0.301 ± 0.08 374.9 ± 90.8 8.27 ± 0.24 Shellrock Brook 0.071 ± 0.04 90.9 ± 41.1 8.11 ± 0.46 Sparrowhawk Brook 0.040 ± 0.02 54.7 ± 31.5 7.70 ± 0.28 Spring Brook 0.075 ± 0.02 88.5 ± 20.3 8.32 ± 0.35 Stony/Mill Creeks 0.054 ± 0.02 75.0 ± 30.1 7.63 ± 0.80 Trout Brook 0.198 ± 0.06 257.4 ± 78.7 8.58 ± 0.14 Unamed Blue line 0.096 ± 0.05 144.8 ± 91.3 8.74 ± 0.87 Unamed Blue line Lower CV 0.074 ± 0.02 98.8 ± 27.0 8.07 ± 0.56 Upper Butternut Creek 0.106 ± 0.04 123 ± 31.2 7.58 ± 0.37 Upper Cherry Valley Creek 0.230 ± 0.08 271.6 ± 69.7 8.08 ± 0.28 Upper Otego Creek 0.119 ± 0.04 144.5 ± 42.0 7.95 ± 0.39 Upper Schenevus Creek 0.116 ± 0.04 139.4 ± 36.4 7.72 ± 0.32 Upper Unadilla River 0.312 ± 0.08 428.6 ± 86.4 8.35 ± 0.25 Upper Wharton Creek 0.171 ± 0.07 191.5 ± 52.9 8.20 ± 0.27 West Branch Otego Creek 0.071 ± 0.04 83.4 ± 29.9 7.90 ± 0.39 Wharton creek 0.056 ± 0.02 74.0 ± 20.0 7.90 ± 0.38 Whitney Creek 0.040 ± 0.03 57.3 ± 47.2 7.89 ± 0.23

Seasonal variation Seasonal variation was observed in all of our monitored streams. For conductivity and TDS, two peaks are apparent in most of the data. A peak usually occurs in the winter months, as well as in the summer months. Spring and fall usually see a decline in TDS and conductivity. The Oneonta Creek has a noticeably large peak in the winter months and a moderate peak in the summer months (Figure 10). The fall and spring see relatively low levels of TDS and conductivity. A stream with lower variability, Pool Brook, shows a less dramatic peak of conductivity and TDS in the winter months, and a gentle swell throughout the summer and fall months (Figure 11). No significant seasonal pattern was observed for pH.

Figure 10. Seasonal variation of Oneonta Creek (Otsego County, NY), a stream with high conductivity and TDS variability. Data collected monthly from 13Aug10 – 21Apr12.

Figure 11. Seasonal variation of Pool Brook (Otsego County, NY), a stream with low TDS and conductivity variability. Data collected monthly from 13Aug10 – 21Apr12.

DISCUSSION

Sub-watershed size No a significant relationship between sub-watershed size and TDS, pH, or conductivity. Landers et al. (2007) listed watershed size as an important predictor of TDS, and conductivity. Larger watersheds tend to contain higher ionic concentrations. We monitored sub-watersheds ranging from 4.8 km2 to 167.8 km2. However, over 50% of our monitored sub-watersheds were under 25 km2, with only three sub-watersheds over 100 km2. Since the majority of the sub- watersheds were similar in size, differences between sub-watersheds were likely due to other factors, which was primarily geology.

Geology Geology strongly influenced stream pH, conductivity, and TDS. Watersheds with limestone bedrock often have a high conductivity due to the relative softness of limestone, which allows dissolution of carbonate minerals into the water (Allan and Castillo 2007). Carbonates in the water neutralize acids and raise stream pH. My results support these patterns. Some of our limestone-based sub-watersheds had lower conductivities and TDS concentrations similar to the shale-based sub-watersheds. This can be explained by smaller area of these sub-watersheds (Figures 5 and 6). Lower conductivities and TDS concentrations may be observed because a smaller watershed area results in less interaction time between landscape and water. Some of these values might also be explained by the bedrock types used to represent limestone and shale areas. The area designated shale (Figure 1) included only shale, siltstone, and sandstone, but part of the limestone area represented, the Hamilton Group (Figure 2), included some shale as well. This can explain why a stronger distinction was not observed between shale and limestone in Figures 5-7.

Sub-watershed variability Sub-watersheds are highly variable due to their small size, relative to watersheds. Natural spatial variation is largely due to the rocks being weathered, how wet or dry the climate is and by the composition of the rain (Allan and Castillo 2007). Small streams are subject to flashy patterns of change in stream quality variables due to changes in stream discharge. Soil features such as permeability, can also change how much nutrients flow into a stream. Watersheds with highly permeable soil will have less runoff with more nutrients being absorbed into the soil (Calhoun et al. 2002).

Land use within a watershed could cause greater variation in some streams (Landers et al. 2007). For example, a watershed with agriculture may experience more variability over time due to seasonal use of fertilizers. Urban areas may also affect stream variability. Schoonover et al. (2005) studied the effects of urban land use on stream TDS concentration and found a 36% increase in TDS concentrations at base flow conditions and a 42% increase in storm flow conditions. Rose (2002) also found a 30% increase in base flow TDS concentration in an urban watershed compared to a lesser developed watershed. Land use affects water quality, even at base flow conditions. While I did not examine land use in Otsego County, it may be useful to study the relationship between variability and land use in the future.

Seasonal variation Conductivity and TDS - Stream chemistry varies seasonally due to changes in discharge, biological activity (Allan and Castillo 2007) and land use patterns (Landers et al. 2007). Conductivity and TDS were lowest in the spring and fall in the Oneonta Creek (Figure 13). Increased flow in the spring and fall likely diluted the conductivity and TDS, due to the inverse relationship between ionic concentrations and discharge (Allan and Castillo 2007). High TDS and conductivity values were observed in the Oneonta Creek from December 2011 through March 2011. These values can be explained by the use of road salt throughout the winter months. The less dramatic peak in conductivity and TDS in the summer months (June-October) can be explained by a decrease in precipitation and increase in evaporation, which led to a concentrating effect. Monitoring for several years may be required to establish accurate seasonal patterns. pH - Stream pH can vary according to sunlight due to biological activity within the stream. During photosynthesis, primary producers convert carbon dioxide (CO2) and water into carbohydrate. Hydroxyl ions (OH-) are produced in the process, raising stream pH. Additionally, plants take up CO2, decreasing levels of carbonic acid (H2CO3) in the stream, raising pH (Lampert and Sommer 1997). If primary production increases more than stream respiration, then stream CO2 will decrease, causing stream pH to rise. If they are in equilibrium, no change in pH will be observed. Since no significant seasonal variations in pH for our monitored streams were observed, primary production and respiration are likely in equilibrium.

ACKNOWLEDGEMENTS

I thank Paul Lord and Scott Fickbohm for assistance revising this paper; and Thomas Horvath for statistical assistance and additional revisions. I would also like to thank the SUNY Oneonta students and Soil and Water Conservation District employees for assistance in collecting water monitoring data. Additional thanks to the Otsego County Conservation Association (OCCA), Otsego County, Otsego County Soil and Water Conservation District, the SUNY Oneonta Biological Field Station and the Upper Susquehanna Coalition for supporting this project.

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