An Evaluation of Water Quality Parameters and Flow Dynamics In

An Evaluation of Water Quality Parameters and Flow Dynamics in High Rock Lake, North Carolina to Assist in the Development of Nutrient Criteria for Lakes and Reservoirs in the State

Morgan Rudd

Dr. Michael O’Driscoll, Advisor Dr. Grant Murray, Advisor

April 26th, 2018

Master of Environmental Management Degree Candidate | May 2018

Masters project submitted in partial fulfillment of the requirements for the Master of Environmental Management degree in the Nicholas School of the Environment of Duke University

EXECUTIVE SUMMARY North Carolina reservoirs have a history of eutrophication problems, and studies addressing NC lake water quality were conducted as early as the 1960s. Most of North Carolina’s lakes are manmade reservoirs, and reservoir waters may respond differently to nutrient inputs based on differences in watershed area, residence time, depth, and other variables. A better understanding of riverine discharge and water quality parameter dynamics in North Carolina reservoirs will help guide nutrient development for the state. Due to impairments associated with designated uses for water supply, recreation, and aquatic life, High Rock Lake (HRL) has been listed on North Carolina’s 303d list of impaired waters since 2004. The lake and its tributaries are impaired due to elevated turbidity, chlorophyll-a, and pH. High Rock Dam, located in Rowan and Davidson Counties in North Carolina, was constructed on the Yadkin River in 1927. HRL is primarily fed by the Yadkin River and several smaller tributaries, draining a total area of 3974 square miles. North Carolina currently has surface water standards for chlorophyll-a (40 µg/L), turbidity (25 NTU- lakes), and pH (<6 or >9), but not for nutrients. The North Carolina Department of Environmental Quality (NC DEQ) chose HRL as a pilot study to help develop nutrient criteria for lakes throughout the state. Three distinct datasets were provided by NC DEQ for analyses: a long- term dataset of chemical and physical water quality measurements collected from 7/21/1981 to 9/13/2011, a high-frequency dataset consisting of hourly water quality measurements collected from 7/13/2016 to 10/5/2016, and a phytoplankton dataset of phytoplankton taxonomic assemblages collected from 7/21/2004 to 9/13/2011. Corresponding discharge data was used as a proxy for lake residence time, and was retrieved from the USGS Yadkin River-Yadkin College gage station upstream of High Rock Lake. Sampling stations were separated into “upper”, “mid”, and “lower” lake sections based on distance from the dam. Analysis of the long-term dataset indicated a high degree of spatial variability in water quality in HRL. Turbidity, total nitrogen, and total phosphorus decrease with increasing proximity to the dam, whereas chlorophyll-a is most elevated within the mid-section of the lake. Exceedances in the state’s turbidity and chlorophyll-a standards occurred at each lake section. The increase in chlorophyll-a concentrations seen in the mid-lake section is attributed to decreasing turbidity and increasing light availability for photosynthesis. Future analyses should identify a turbidity threshold at which light becomes a limiting resource. Analysis of data below this turbidity threshold will help clarify specific nutrient-chlorophyll relationships.

The high-frequency dataset elucidated how discharge, total dissolved solids, temperature, and dissolved oxygen co-vary with chlorophyll-a. Dissolved oxygen had the largest cross- correlation value, indicating that chlorophyll-a and DO experience simultaneous increases. This is attributed to DO being a byproduct of photosynthesis, and indicates the potential to monitor DO in the future and use its concentration to determine when algal blooms will occur. Phytoplankton taxonomic assemblage varies according to lake section, with the lower- section of the lake experiencing the most elevated levels of cyanobacteria. This is of particular concern as toxic microcystins can be produced during cyanobacteria blooms, posing a threat to human health. Denton residents utilize the Tuckertown Reservoir, located downstream of HRL, as their primary water supply. Cyanobacteria should be regularly monitored for toxins. Riverine discharge appears to influence chlorophyll-a and biovolume, and future studies should aim to identify the impact of discharge, lake location, and seasonality on phytoplankton assemblage. An improved understanding of discharge-water quality relationships can help guide nutrient criteria development for the state’s reservoirs.

TABLE OF CONTENTS 1.! INTRODUCTION ...... 1 2.! STUDY SITE ...... 5 3.! METHODS ...... 8 3.1.!Long-term chemical and physical dataset ...... 11 3.2.!High-frequency dataset ...... 11 3.3.!Phytoplankton dataset ...... 12 4.! RESULTS ...... 13 4.1.!Long-term chemical and physical dataset ...... 13 4.2.!High-frequency dataset ...... 18 4.3.!Phytoplankton dataset ...... 23 5.! DISCUSSION & CONCLUSIONS ...... 27 6.! FUTURE WORK ...... 30 7.! REFERENCES ...... 32 8.! APPENDIX ...... 35

1. INTRODUCTION Eutrophic conditions result from the enrichment of plant nutrients and can occur in fresh water, brackish, or marine systems. In the past half century, nutrient additions to lakes and rivers have increased significantly as a result of anthropogenic activity (Mainstone & Parr 2002). Point sources and non-point sources of pollution contribute to the eutrophication of aquatic systems (Yang et al. 2008). The nutrient enrichment of aquatic systems can lead to a variety of deleterious effects, such as: algal blooms, changes in food web dynamics, shifts in phytoplankton assemblage, impairment of human water supply and recreational usage, and hypoxic or anoxic conditions. While total nitrogen and total phosphorus have been identified as the primary eutrophic inducing factors, other environmental factors such as solar radiation, temperature, water velocity, and residence time can inhibit or promote eutrophication (Yang et al. 2008). Chlorophyll is the pigment found in chloroplasts that facilitates the process of photosynthesis to produce carbohydrates for the organism (Smith & Smith 2012). There are several types of chlorophyll, but chlorophyll-a is dominant in green plants and algae, and can be used as an indicator of algal abundance in aquatic systems (US EPA 2016). Measurements of chlorophyll- a are often taken to assess algal growth, with higher concentrations of the pigment corresponding to the concentration of phytoplankton in the water sample (Hambrook Berkman & Canova 2007). Excess algal growth, and thus higher chlorophyll-a concentrations, can have negative implications for the aquatic system itself and communities that utilize the waterbody (US EPA 2016). Bodies of water can be naturally oligotrophic, with minimal algal growth, or eutrophic, characterized by higher concentrations of chlorophyll-a. Levels of chlorophyll-a can become problematic when they deviate from a natural baseline and begin to negatively influence aquatic organisms or human uses of the waterbody. Several parameters influence the abundance of chlorophyll-a in aquatic systems, such as: nutrient availability, light availability and/or limitations, flow, and residence time. Studies addressing the water quality of North Carolina lakes were conducted as early as the 1960s (Weiss & Kuenzler 1976). A comprehensive analysis and determination of the trophic states of North Carolina lakes was conducted in the 1970s. Weiss and Kuenzler acknowledged that nutrient enrichment of aquatic systems is a natural process, but that accelerated nutrient enrichment is what prompted the development of the trophic state classification system in order to characterize the degree of eutrophication in lakes and reservoirs (1976). Their study demonstrated that smaller

lake size was typically associated with higher trophic states than larger lakes, and that lakes located in the Coastal Plain and Piedmont regions were characterized by higher trophic states than those located in the Mountain province (Weiss & Kuenzler 1976). This report generated by Weiss and Kuenzler along with input from the Water Quality Standards Advisory Group resulted in North Carolina’s adoption of a 40 µg/L standard for chlorophyll-a. Unfortunately, many of the state’s water resources are still experiencing eutrophication problems as documented by exceedances of the chlorophyll-a standards. To address these problems, North Carolina is in the process of generating nutrient criteria for waterbodies throughout the state. Reservoirs are the only lakes present in North Carolina’s Piedmont region and tend to have eutrophication problems. Large reservoirs are characterized by greater watershed area, volume, surface area, water column depth, and shorter residence times than natural lakes (Kennedy 2001). The increased size in drainage basin results in higher loading rates of nutrients and sediment to the reservoir, which influence water quality (Kennedy 2001). A more recent study demonstrated the importance of drought conditions and reservoir age on chlorophyll-a production in North Carolina reservoirs. Drought conditions in lakes are characterized by decreased flushing, longer residence times, and decreased turbidity. Under these conditions, there is a positive relationship between chlorophyll-a production and both total nitrogen and total phosphorus (Touchette et al. 2007). Old age reservoirs experienced significantly - lower TN:TP ratios, but significantly higher NOx concentrations (Touchette et al. 2007). Old age reservoirs also exhibited a two-fold increase in cyanobacteria mean abundance in comparison to moderately aged reservoirs (Touchette et al. 2007). These results indicate the importance of climatic conditions and reservoir age on phytoplankton relationships with predictor variables, such as TN and TP, as well as phytoplankton assemblage. As nutrient-related water quality impairment of North Carolina’s Piedmont reservoirs has been a common occurrence since the 1970s (Weiss & Kuenzler 1976, Touchette et al. 2007), the North Carolina Department of Environmental Quality has led efforts to understand and manage nutrient inputs. To be in compliance with the Clean Water Act, North Carolina must conduct periodic water quality assessments of aquatic systems throughout the state. Lakes and reservoirs are generally monitored by NC DEQ on a rotating 5-year basis, monthly from May-September (NC DEQ 2018a). The Division of Water Resources (DWR) and other monitoring programs collect surface water quality data from various aquatic systems throughout the state (NC DEQ 2017a). These data

are then analyzed and compared to established water quality standards to determine compliance with the Clean Water Act. The final step in this process is to categorize aquatic systems as compliant or noncompliant with the established standards (NC DEQ 2017a). Waters that fail to meet the established water quality criteria are listed as 303d “impaired waters” and require a TMDL (NC DEQ 2017a). North Carolina has surface water standards for chlorophyll-a (40 µg/L), turbidity (25 NTU- lakes), and pH (<6 or >9) (NC DEQ 2017b). Despite broad efforts to manage nutrient inputs to improve surface water quality, there are prevailing problems with eutrophication throughout the state. The 2014 finalized 303(d) list for North Carolina had 31 violations of the state’s chlorophyll- a standard of 40µg/L, an indicator of eutrophic conditions (NC DEQ 2014). These violations threaten the designated uses of the waterbodies in which they occur. To address the continued violation of water quality standards, DWR is responsible for generating nutrient criteria for three distinct water types: lakes/reservoirs, streams/rivers, and estuaries (NC DENR 2014). The Nutrient Criteria Implementation Plan was originally developed by DWR in 2004 as a response to the United States’ Environmental Protection Agency Federal Register Notice in 2001 which encouraged states to establish nutrient criteria management plans (NC DENR 2014). The Nutrient Criteria Development Plan (NCDP) of 2014 is the updated and agreed upon strategy for North Carolina to address nutrient concerns (NC DENR 2014). The NCDP called for the establishment of a Scientific Advisory Council, who will develop nutrient criteria based on the “linkage between nutrient concentrations and protection of designated uses”. The pilot studies for the NCDP are nutrient criteria development for High Rock Lake, Albemarle Sound, and the Central Portion of the Cape Fear River (NC DENR 2014). The associated criteria are expected to be implemented by 2021, with statewide adoption by 2025 (NC DENR 2014). Partial nutrient criteria development for lakes and reservoirs has occurred in several southeastern states such as Georgia and South Carolina, while Florida is the only state in Ecoregion IV to develop statewide standards for both nitrogen and phosphorus (Table 1) (US EPA 2017). For Florida lakes, water quality criteria were established on the basis of nutrient-phytoplankton dynamics (FL DEP 2013). Florida recognized the various naturally occurring lake types: oligotrophic, mesotrophic, and eutrophic, and developed criteria accordingly. Chlorophyll-a, total phosphorus, and total nitrogen standards are dependent on the long term mean lake color and alkalinity (FL DEP 2013). Florida’s maximum allowable chlorophyll-a concentration is lower than

North Carolina’s 40 µg/L chlorophyll-a standard (Table 2). Florida submitted its newly established criteria to the United States Environmental Protection Agency in 2012 for review. Upon review, the EPA found the water quality standards to be compliant with the goals of the Clean Water Act (US EPA 2012). These standards are now being implemented throughout the state, but there is little literature thus far to suggest whether they have been successful in improving the water quality for Florida’s designated uses. This information may contribute to the effort to establish nutrient criteria for lakes and reservoirs in North Carolina.

Table 1. States in Ecoregion IV with chlorophyll-a, nitrogen, and phosphorus standards for lakes/reservoirs. Numeric criteria in states with partial or statewide standards are dependent on location of lakes/reservoirs in the state (US EPA 2017).

State Chlorophyll-a Standard Nitrogen Standard Phosphorus Standard Alabama Partial None None Florida Statewide Statewide Statewide Georgia Partial Partial Partial Kentucky None None None Mississippi None None None North Carolina Statewide None None South Carolina Partial Partial Partial Tennessee Partial None None

Table 2. Florida’s chlorophyll-a, total phosphorus, and total nitrogen criteria for lakes (modified from FL DEP 2013).

Long-Term Annual Minimum calculated numeric Maximum calculated numeric Geometric Geometric interpretation interpretation Mean Lake Mean Color and Chlorophyll-a Annual Annual Annual Annual Alkalinity Geometric Geometric Geometric Geometric Mean Total Mean Total Mean Total Mean Total Phosphorus Nitrogen Phosphorus Nitrogen >40 Platinum 20 µg/L 0.05 mg/L 1.27 mg/L 0.16 mg/L 2.23 mg/L Cobalt Units ≤40 Platinum 20 µg/L 0.03 mg/L 1.05 mg/L 0.09 mg/L 1.91 mg/L Cobalt Units and >20 mg/L CaCO3 ≤40 Platinum 6 µg/L 0.01 mg/L 0.51 mg/L 0.03 mg/L 0.93 mg/L Cobalt Units and ≤20 mg/L CaCO3

Previous hydrodynamic and nutrient response models have indicated variability in chlorophyll-a concentrations throughout High Rock Lake. For example, light limitation is most severe at the upstream sampling station (HRL 051) than at lower-lake sampling stations, due to turbidity associated with Yadkin River inflow (Tetra Tech 2016). Nitrogen and phosphorus limitations appear to vary temporally and spatially (Tetra Tech 2016). A greater understanding of water quality dynamics throughout High Rock Lake and relationships with chlorophyll-a are vital to the development of appropriate nutrient criteria for North Carolina lakes and reservoirs. Understanding these relationships will guide the nutrient criteria development process. The purpose of this study is to examine temporal and spatial variations in chlorophyll-a in regards to associated measurements of turbidity, total nitrogen, total phosphorus, total dissolved solids, temperature, dissolved oxygen, and riverine discharge. The following sections will outline the study site and methodology used to assess the relationships between chlorophyll-a and various water quality parameters and Yadkin River discharge.

2. STUDY SITE High Rock Lake, located in Rowan and Davidson counties of North Carolina, was chosen as the pilot lake/reservoir for North Carolina’s nutrient criteria development (Figure 1). The High Rock dam was constructed in 1927 to provide hydroelectric power for aluminum production, and has a surface area of 15,190 acres and volume of 239,672 acre-feet (Tetra Tech 2016). Due to exceedances of pH, turbidity, and chlorophyll-a standards the reservoir is considered to be failing to meet its designated uses for water supply, recreation, and aquatic life. Therefore, High Rock Lake has been listed on North Carolina’s 303(d) list of impaired waters since 2004 (Figure 2) (Tetra Tech 2016, NC DEQ 2014). In North Carolina the pH, turbidity, and chlorophyll-a standards are 6.0-9.0, 50 NTU, and 40 µg/L, respectively, and portions of the lake have been incompliant with these standards (Tetra Tech 2016). Violations of pH and chlorophyll-a in the lake are associated with excessive algal growth, whereas turbidity violations are primarily attributed to sediment load (Tetra Tech 2016).

Figure 1. High Rock Lake watershed. The majority of the watershed is located in North Carolina, but the most northern portion is located in Virginia. The yellow star depicts the USGS Yadkin College gage station where discharge data was retrieved for analysis (modified from Tetra Tech 2012).

Figure 2. High Rock Lake impairments as of 2014. Impairments for turbidity, pH, and chlorophyll-a depicted (NC DEQ 2017c).

The High Rock Lake watershed drains an area of 3,974 square miles and is characterized by a variety of land uses and soil types. Developed land constitutes approximately 18.2 percent of the watershed, whereas agricultural land constitutes 32.6 percent of land use (Tetra Tech 2012). Impervious surface makes up, roughly, 2.75 percent of the High Rock Lake watershed, but varies accordingly with development (USGS 2017). Municipalities such as Winston-Salem, Lexington, and Salisbury have much higher estimated percentages of impervious cover than more rural parts of the watershed (Tetra Tech 2012).

Eighty-one percent of the watershed’s soil falls into hydrologic soil group B, which is characterized by moderate rates of infiltration due to its silt loam and loam texture (Tetra Tech 2012). However, 14% of the soil is within hydrologic soil group C, indicating that the soil has relatively low infiltration rates due to its sandy clay loam texture (Tetra Tech 2012). Areas that are characterized by impervious surface and soil group C are more likely to experience runoff, which can negatively influence the water quality of High Rock Lake. High Rock Lake has a history of eutrophication problems and has been documented as a eutrophic lake since the mid 1970s (US EPA 1975). Further assessments confirmed the lake’s eutrophic state over time (NC DEHNR 1992). Nutrient and sediment loading is likely associated with changes in land use and human activity. Nutrient sources include: urban and highway runoff, forested, pasture, and crop lands, point sources, and septic systems (Tetra Tech 2012). Based on the lake’s nitrogen to phosphorus ratio, the lake is expected to be in a transition between nitrogen and phosphorus limitation (Touchette et al. 2007, Tetra Tech 2016). Modeling efforts have shown that algal growth in High Rock Lake can be limited by light, nitrogen, or phosphorus depending on location, lake conditions, and time of year (Tetra Tech 2016).

3. METHODS Three datasets were provided by the North Carolina Department of Environmental Quality, Division of Water Resources. These datasets include physical, chemical, and biological data from High Rock Lake (Table 3). Water samples were collected at various sampling stations throughout the lake watershed, but only “main stem” stations were analyzed (Figure 3). The longer-term datasets were collected by grab sampling and analyzed through NC DWR’s certified lab. The high-frequency dataset was collected by a calibrated YSI multiparameter sonde. Main stem stations were those located along the Yadkin River, High Rock Lake’s primary tributary. These stations were then categorized as “upper”, “mid”, and “lower” stations based on proximity to the High Rock Lake Dam (Table 4). Yadkin River discharge data was retrieved from the United States Geological Survey’s National Water Information System (USGS 2018).

Figure 3. Main stem stations in HRL used in statistical analyses. Image captured 4/8/2017.

Table 3. Data used in statistical analyses of this study.

Dataset Source Collection Dates Sites of Interest Variables of Interest Number of Samples Long-Term DWR, 7/21/1981 – 9/13/2011 “Main Stem” •! Turbidity •! n = 24 – 52 per station NC DEQ stations (Figure 3) •! Total Nitrogen (298 total) •! Total Phosphorus •! n = 23 – 56 per station •! Chlorophyll-a (324 total) •! n = 24 – 57 per station (321 total) •! n = 19 – 42 per station (228 total) High-Frequency DWR, 7/13/2016 – 10/5/2016; YAD 152C •! Total Dissolved Solids •! n = 2013 NC DEQ Hourly measurements •! Temperature •! n = 2013 •! Dissolved Oxygen •! n = 2013 •! Chlorophyll-a •! n = 2013

Phytoplankton DWR, 7/21/2004 – 9/13/2011 “Main Stem” •! Cell Density •! n = 1113 NC DEQ stations; excluding •! Biovolume •! n = 1113 HRL 051

YAD 152C Discharge USGS Varies accordingly with Yadkin River- •! Discharge Varies accordingly with above above datasets Yadkin College datasets gage station

Table 4. High Rock Lake main stem sampling stations and distance to High Rock Lake Dam. Distance to dam was estimated with Google Earth Pro using the known longitudes and latitudes of the lake stations and the dam.

Station ID Distance to Dam (m) Lake Section YAD 1391A 16253.76 Upper HRL 051 12668.52 Upper YAD 152A 8759.19 Mid YAD 152C 7681.85 Mid YAD 169B 3447.3 Lower YAD 169E 1165.21 Lower YAD 169F 604.21 Lower

3.1 Long-term chemical and physical dataset Physical water quality data such as: specific conductivity, dissolved oxygen, temperature, and pH, were collected beginning in July 1981 and continued through September 2011 (NC DEQ 2016). Chemical data such as: alkalinity, dissolved metals, various nitrogen measurements, various phosphorus measurements, fecal coliform, and chlorophyll-a, were collected beginning in July 1981 and continued through September 2011. The frequency of data collection varied over the 30- year collection period, with the typical return period of five years and sampling more common in the summer months. More frequent collection was associated with special studies when funding was available. Total nitrogen was calculated by the summation of nitrogen oxides and total Kjeldahl nitrogen measurements. Turbidity, total nitrogen, total phosphorus, and chlorophyll-a were analyzed using R statistics software. Turbidity, total nitrogen, total phosphorus, or chlorophyll-a data did not typically meet assumptions of normality which is required to conduct an Analysis of Variance (ANOVA) regardless of outlier removal and transformations. Since the data did not come from a normal parent distribution, a non-parametric Mann-Whitney U test was performed to assess differences in water quality variable distributions based on location in the lake. Three Mann-Whitney U tests per predictor variable were conducted to evaluate differences between the upper and mid, upper and lower, and mid and lower-lake sections.

3.2 High-frequency dataset High-frequency sampling was conducted from July 13th, 2016 through October 5th, 2016 (NC DEQ 2017d). Samples were collected every hour from surface and bottom lake waters using a YSI multiparameter sonde. Data was collected from a stationary platform at lake station YAD

152C, a mid-lake sampling station, and from a roaming platform which spanned stations: YAD 169A, YAD 169B, and HRL 051. Hourly samples were collected from 7/13/2016 – 8/10/2016, 8/10/2016 – 9/15/2016, and 9/15/2016 – 10/5/2016 at stations YAD 169A, YAD 169B, and HRL 051 respectively. Measurements for dissolved oxygen, temperature, pH, specific conductivity, total dissolved solids, and chlorophyll (RFU) were retrieved. Chlorophyll RFU values were corrected, and chlorophyll measurements were converted to units of micrograms per liter by multiplying the RFU values by 9.5 (µg/L) (ISB 2017). The first analysis of the high-frequency data aimed to assess how chlorophyll-a varied with discharge from the Yadkin River. Corresponding discharge data was retrieved from the USGS gage station: Yadkin College Gage 02116500. Discharge was measured hourly and spanned from 7/13/2016 – 10/5/2016. Analyses were conducted on the daily average data as well as the raw dataset. Mean, median, minimum, and maximum values were determined for chlorophyll-a and discharge. The 25th, 50th, and 75th percentile values for discharge were calculated. Chlorophyll-a was then separated into two categories based on whether the measurement was taken during “high” or “low” flow. High and low flow were dependent on discharge. For example, in one analysis, high flow was distinguished as discharge values greater than median flow and low flow was distinguished as discharge values less than or equal to median flow. The data failed to meet the assumptions of normality and unequal variance required for a T-test. Therefore, a non-parametric Mann-Whitney U test was conducted to compare chlorophyll-a values between high and low flow conditions. The second analysis of the high-frequency data aimed to assess the strength of the relationships between chlorophyll-a and discharge, total dissolved solids, temperature, and dissolved oxygen. The complete hourly dataset, not solely daily values, were used for this analysis. Cross-correlation and cross-covariance were calculated to explain how the variables deviated from their expected values in similar ways as a function of a time lag. A two-week lag was included in the analysis: one week forward and one week backward.

3.3 Phytoplankton dataset Phytoplankton taxonomic data were collected from June 16th, 2004 through September 13th, 2011 (Kroeger 2015). Data were collected from various stations throughout the High Rock Lake reservoir, but solely the main stem stations were analyzed. Data for upper-station HRL 051

were missing from this dataset. Data included algal group, genus, species, cells and units, cell density, unit density, and biovolume. Analyses of cell density and biovolume were conducted. Cell density is the number of the taxon’s cells in one milliliter of water. Biovolume is the volume of the taxon in cubic millimeters per cubic meter of water. The main stem station data for cell density and biovolume did not meet assumptions of normality or homogeneity of variance which is required to conduct an Analysis of Variance (ANOVA) regardless of outlier removal and transformations. Mann-Whitney U tests were conducted to assess differences in cell density and biovolume based on location in the lake. Three Mann-Whitney U tests per predictor variable were conducted to evaluate differences between the upper and mid, upper and lower, and mid and lower-lake sections. Lake station YAD 152C had a more comprehensive dataset than many of the other lake stations, and thus could be used to evaluate a relationship between biovolume and discharge. Chlorophyll-a exceedances typically occurred in mid-lake sections, and thus a more detailed look at the data was warranted. Total biovolume was calculated per each date. Corresponding discharge data was retrieved from USGS gage station: Yadkin College Gage 02116500. A test of correlation was conducted with and without outlier removal, as well as a non-parametric Spearman Rank test. A linear regression was conducted to determine the relationship between discharge and total biovolume, regardless of the violation of normality.

4. RESULTS 4.1 Long-term chemical and physical dataset Mann-Whitney U tests identified differences in turbidity, TN, TP, and chlorophyll-a in accordance with lake location (Table 5). Turbidity, TN, and TP concentrations followed a similar decreasing pattern as distance to the High Rock Lake Dam decreased (Figures 4, 5, & 6). Approximately 16.4 percent of main stem turbidity samples exceeded the 25 NTU standard for reservoirs. Chlorophyll- a concentration was greatest in the mid-lake section, but each section experienced chlorophyll-a standard exceedances (Figure 7). Relationships between chlorophyll-a and total nitrogen and total phosphorus were examined, but were not strong (Appendix Figures 1A-6A). Roughly 31 percent of chlorophyll-a samples exceeded the 40 µg/L standard for surface water. For this long-term data set there was a negative correlation between discharge and chlorophyll-a (Figures 8 & 9). Chlorophyll-a concentrations differed significantly according to high and low discharge conditions

for the long-term dataset (Figure 10). This relationship is further analyzed with the high-frequency dataset.

Table 5. Results of the Mann-Whitney U tests to determine differences in turbidity, total nitrogen, total phosphorus, and chlorophyll-a based on lake section.

Lake Section Comparison Variable p-value Median Upper-Lower Turbidity (NTU) < 2.2e-16 Upper (30) – Lower (6) Upper-Mid Turbidity (NTU) 2.387e-12 Upper (30) – Mid (11) Mid-Lower Turbidity (NTU) 4.417e-14 Mid (11) – Lower (6) Upper-Lower TN (mg/L) 4.554e-16 Upper (1.185) – Lower (0.77) Upper-Mid TN (mg/L) 1.027e-06 Upper (1.185) – Mid (1.0) Mid-Lower TN (mg/L) 1.37e-05 Mid (1.0) – Lower (0.77) Upper-Lower TP (mg/L) < 2.2e-16 Upper (0.15) – Lower (0.06) Upper-Mid TP (mg/L) 1.888e-12 Upper (0.15) – Mid (0.09) Mid-Lower TP (mg/L) < 2.2e-16 Mid (0.09) – Lower (0.06) Upper-Lower Chlorophyll-a (µg/L) 9.327e-05 Upper (15) – Lower (30) Upper-Mid Chlorophyll-a (µg/L) 1.076e-05 Upper (15) – Mid (39) Mid-Lower Chlorophyll-a (µg/L) 0.03101 Mid (39) – Lower (30)

Figure 4. Turbidity decreases as the dam is approached. The horizontal dashed line represents the 25 NTU turbidity standard for North Carolina reservoirs. Turbidity sampling occurred between 7/21/1981 and 9/13/2011.

Figure 5. Total nitrogen decreases as the dam is approached. Nitrogen sampling occurred between 7/21/1981 and 9/13/2011.

Figure 6. Total phosphorus decreases as the dam is approached. Phosphorus sampling occurred between 7/21/1981 and 9/13/2011.

Figure 7. Chlorophyll-a concentration was highest in the mid-lake section, with nearly half the data points exceeding the chlorophyll-a standard. The horizontal dashed line represents the 40 µg/L chlorophyll-a standard for North Carolina waterbodies. Chlorophyll-a sampling occurred between 7/21/1981 and 9/13/2011.

Figure 8. In the mid-section of High Rock Lake, the majority of chlorophyll-a standard exceedances occurred when discharge fell beneath the long-term median discharge value. One extreme discharge value (19,200 cubic feet/s (cfs), chlorophyll-a=9.0 µg/L) was excluded from the figure to help zoom in on the majority of the data. The dashed vertical line represents the long term median discharge value of 2230 cfs for discharge data collected from 8/1/1928-2/28/2017. High flow refers to flow exceeding the long-term median discharge value. The chlorophyll-a data was collected from 7/21/1981 – 9/13/2011.

Figure 9. Mean discharge and chlorophyll-a over time in mid-sections of High Rock Lake. Daily discharge data is depicted by the blue line, and average mid-section chlorophyll-a is depicted by the green points. The dashed horizontal line represents the state 40 µg/L chlorophyll-a standard. Mean daily discharge data was retrieved from the USGS Yadkin River-Yadkin College gage station from 7/21/1981 through 9/13/2011. Chlorophyll-a sampling occurred between 7/21/1981 and 9/13/2011.

Figure 10. Boxplot of daily chlorophyll-a concentrations at low and high flow conditions based on the long term median discharge value (2230 cfs) for discharge data collected from 8/1/1928-2/28/2017. High flow refers to flow exceeding the long-term median value. The chlorophyll-a data was collected from 7/21/1981 – 9/13/2011. The median values under these conditions were significantly different (p-value = 0.009706).

4.2 High-frequency dataset Chlorophyll-a concentrations between the high and low discharge conditions did not differ significantly (p-value = 0.2903) for the high-frequency dataset. Low flow conditions led to more variable concentrations in chlorophyll-a, but the median values of chlorophyll-a at high and low flow conditions were not statistically different (Table 6, Figures 11 & 12). However, when the time series were plotted against each other, it appeared that one elevated chlorophyll-a event in late July was washed downstream during a large flow event and the second major elevated chlorophyll-a event (presumably a bloom) occurred in early to mid-September after a period of minimal precipitation and low storm discharge. Thus, the high-frequency data also suggests that discharge (and residence time) plays an important role in chlorophyll-a dynamics.

Table 6. Calculated statistics for daily discharge (cfs), daily chlorophyll-a (µg/L), and chlorophyll-a at low and high flow conditions at Station YAD 152C. Low flow refers to chlorophyll-a measurements when discharge was less than or equal to the median discharge value (1520 cfs). High flow refers to measurements above the median discharge value. The data was collected hourly from 7/13/2016 – 10/5/2016.

Statistic Daily Discharge (cfs) Daily Low Flow – High Flow – Chlorophyll-a Chlorophyll Chlorophyll (µg/L) concentrations concentrations (µg/L) (µg/L) Mean 1829.26 93.34 112.99 71.24 Median 1510 61.63 56.24 63.74 Maximum 12,600 488.03 488.03 187.14 Minimum 971 33.17 36.05 33.17

Figure 11. Scatter plot of daily discharge (cfs) and daily chlorophyll-a concentrations (µg/L) in High Rock Lake, North Carolina, at Station YAD 152C. The vertical lines represent the 25th, 50th, and 75th percentiles for discharge. The horizontal line represents the state standard for chlorophyll-a (40µg/L). However, due to issues of in situ fluorometry, chlorophyll-a sonde data should be considered qualitative and not used for assessment purposes (ISB 2017). Markers above the green horizontal line represent exceedances of the standard.

Figure 12. Boxplot of daily chlorophyll-a concentrations at low and high flow conditions at Station YAD 152C. The median values under these conditions were not significantly different (p-value = 0.2903).

High-frequency discharge and chlorophyll-a were negatively correlated, but the least correlated of the other water quality parameters (Table 7, Figure 13). Intuitively, discharge and chlorophyll-a would be highly negatively correlated because as discharge increases, turbidity would increase and chlorophyll production would be stunted. However, this could be site dependent within the lake and further analyses should be conducted on other lake sampling stations. Looking at the raw data, you can pick out two major elevated chlorophyll-a (bloom) events during the high-frequency data collection period (Figure 14). It appears that the first bloom event occurred in July-August, and was washed downstream with a storm event. The second bloom occurred in September after a period of minimal precipitation and low storm discharge. Other variables that were correlated with chlorophyll-a included total dissolved solids, temperature, and dissolved oxygen. The cross-correlation coefficient for total dissolved solids and chlorophyll-a was large and positive (0.1692) (Table 7, Figure 15). Temperature and dissolved oxygen were the most correlated with chlorophyll-a (Table 7, Figures 16 & 17). The negative cross-correlation value associated with temperature and chlorophyll-a indicated that temperature may influence phytoplankton dynamics in the lake. The most highly correlated pairing, dissolved oxygen and chlorophyll-a, is not surprising as dissolved oxygen is a byproduct of the process of photosynthesis.

Table 7. High-frequency data cross-correlation values and associated lag.

Pairing Largest Cross-Correlation Associated Lag (days) Discharge and Chlorophyll-a -0.1472 6.542 Total dissolved solids and Chlorophyll-a 0.1692 7.000 Temperature and Chlorophyll-a -0.2317 -1.500 Dissolved oxygen and Chlorophyll-a 0.2380 1.875

Figure 13. Subplot 1 depicts discharge (cfs) and chlorophyll-a (µg/L) over time in High Rock Lake, North Carolina, at Station YAD 152C. Subplot 2 depicts the total cross covariance and total cross correlation over a 2-week lag for discharge and chlorophyll-a.

Figure 14. The first bloom occurs in late July – early August. This is followed by a peak in discharge which appears to wash the bloom downstream. The second bloom occurs in early to mid-September after a period of minimal precipitation and low storm discharge.

Figure 15. Subplot 1 depicts total dissolved solids (mg/L) and chlorophyll-a (µg/L) over time in High Rock Lake, North Carolina, at Station YAD 152C. Subplot 2 depicts the total cross covariance and total cross correlation over a 2-week lag for total dissolved solids and chlorophyll-a.

Figure 16. Subplot 1 depicts temperature (ºC) and chlorophyll-a (µg/L) over time in High Rock Lake, North Carolina, at Station YAD 152C. Subplot 2 depicts the total cross covariance and total cross correlation over a 2-week lag for temperature and chlorophyll-a.

Figure 17. Subplot 1 depicts dissolved oxygen (mg/L) and chlorophyll-a (µg/L) over time in High Rock Lake, North Carolina, at Station YAD 152C. Subplot 2 depicts the total cross covariance and total cross correlation over a 2-week lag for dissolved oxygen and chlorophyll-a.

4.3 Phytoplankton dataset The Mann-Whitney U tests indicated differences in biovolume and cell density based on location in the lake (Table 8, Figures 18 & 19). The mid and lower-lake sections were not significantly different for either cell density or biovolume. However, both the mid and lower-lake sections experienced a far greater range of cell density and biovolume than the upper-lake section (Figures 18 & 19).

Table 8. Results of the Mann-Whitney U tests to determine differences in algal prevalence based on lake section.

Lake Section Variable p-value Median Comparison Upper-Lower Biovolume (mm3/m3) 9.88e-14 Upper (5.79) – Lower (22.36) Upper-Mid Biovolume (mm3/m3) 1.281e-11 Upper (5.79) – Mid (20.87) Mid-Lower Biovolume (mm3/m3) 0.3061 Mid (20.87) – Lower (22.36) Upper-Lower Cell Density (#cells/mL) < 2.2e-16 Upper (121.84) – Lower (455.35) Upper-Mid Cell Density (#cells/mL) 9.162e-14 Upper (121.84) – Mid (422.62) Mid-Lower Cell Density (#cells/mL) 0.2098 Mid (422.62) – Lower (455.35)

Figure 18. Biovolume (mm3/m3) in High Rock Lake according to lake section. Note the extreme variability. Biovolume axis was adjusted to depict majority of the data. Maximum biovolume = 11700.43 mm3/m3.

Figure 19. Cell density (#cells/mL) in High Rock Lake according to lake section. Note the extreme variability. Cell density axis was adjusted to depict majority of the data. Maximum cell density = 781384.92 cells/mL.

Neither discharge nor biovolume met the assumption of normality, but the data was most normal when square-root-transformed. A non-parametric Spearman Rank correlation indicates a negative relationship between discharge and total biovolume (rho = -0.56) (Figure 20). The chosen linear model excluded one potential outlier due to extreme discharge (discharge = 19200 cfs; biovolume = 71.06 mm3/m3) and further analysis disregards this point (Appendix Figure 7A). The linear model was conducted using the square-root transformed data, and was deemed most appropriate in comparison to other models based on diagnostic plots (Appendix Figure 8A, 9A, & 10A).

Figure 20. Linear relationship between square-root-transformed mean daily discharge and square-root- transformed biovolume at lake station YAD 152C (adj. r2 = 0.3321, p-value = 4.799e-05). Biovolume values ranged from 11.11 – 11415.70 mm3/m3, and mean discharge values ranged from 519 – 7790 cfs with the removal of one data point. Mean discharge data was retrieved from the USGS Yadkin River-Yadkin College gage station for corresponding biovolume sampling dates between 7/21/2004 and 9/13/2011.

Phytoplankton taxonomic assemblage appears to be location dependent within the lake. Dominant phytoplankton vary depending on the use of cell density or biovolume as the metric (Figure 21). Cyanobacteria are the most dominant in each lake section when measured by cell density (Figure 21a, 21c, & 21e). Biovolume of cyanobacteria becomes more prevalent with increasing proximity to the High Rock Lake Dam (Figure 21b, 21d, & 21f).

a. b.

c. d.

e. f.

Figure 21. Algal dominance by cell density and biovolume in High Rock Lake.

5. DISCUSSION & CONCLUSIONS The analyses of the long-term, high-frequency, and phytoplankton datasets have helped shed light on water quality dynamics in High Rock Lake, North Carolina. Despite previous management efforts, the lake continues to experience exceedances in the state’s standards for turbidity, pH, and chlorophyll-a. The results of these analyses suggest the importance of lake location and Yadkin River discharge on water clarity, nutrients, and algal growth. The spatial patterns in HRL water quality data are in part explained by the change from a riverine to a lacustrine system, with a transitional zone that varies in extent depending on the discharge magnitude. What was referred to as the “upper”, “mid”, and “lower” lake sections throughout this study, are explained by Cooke et al. as riverine, transitional, and lacustrine lake zones (2005). These lake zones are characterized by varying chemical and physical properties. Chlorophyll-a varies in accordance with lake zone; with the riverine zone experiencing the least photosynthesis due to light limitations, the transitional zone experiencing high rates of photosynthesis, and the lacustrine zone experiencing nutrient limited photosynthesis and algal cell loss, presumably due to grazing and sedimentation (Figure 22).

Riverine Transitional Lacustrine Zone Zone Zone

Figure 22. Lake and Reservoir zones (modified from Cooke et al. 2005).

Analyses suggest that algal growth is influenced by riverine discharge, as demonstrated by differences in chlorophyll-a concentration, biovolume, and cell density throughout the lake (Figures 7, 18, 19). However, effect of discharge on chlorophyll-a concentration appears to be spatially and temporally dependent. Discharge and chlorophyll-a appeared to be more strongly inversely correlated in the long-term dataset, but there was a small cross correlation value between discharge and chlorophyll-a in the high-frequency dataset (Figures 8, 10, 11 & 12). Over the longer-term phytoplankton dataset, a significant linear relationship was found between the square- root transformed daily discharge and square-root transformed biovolume (Figure 20). This linear relationship aligns with results from a previous study that indicated the importance of increasing discharge on decreasing chlorophyll concentration (Worth 1995). Chlorophyll-a concentrations were highest in the mid-lake section, also known as the transitional zone (Figure 7). This is likely attributed to decreasing influence from the Yadkin River and more light availability as the water becomes less turbid. Chlorophyll-a concentration declines in the lower, lacustrine, lake section, which is likely due to nutrient limitations as the dam is approached and cell loss by grazing (Cooke et al. 2005). While several parameters correlated with chlorophyll-a concentration, dissolved oxygen had the strongest cross-correlation value with chlorophyll-a in the mid-lake section (Table 7, Figure 17). As discharge increases, turbidity and nutrient loads may increase, and chlorophyll-a may decrease due to light limitations and dilution. The magnitude of discharge from the Yadkin River appears to significantly influence turbidity levels in the different lake zones (Figure 23). There are shorter residence times in the upper reaches of the reservoir and less time for algal growth before transport downstream during high discharge periods. These data suggest that riverine discharge and residence time may be important variables to consider when developing nutrient criteria for this and other NC reservoirs.

Figure 23. Turbidity in High Rock Lake. The upper reaches of the reservoir are characterized by more turbid waters, with decreasing turbidity as the HRL Dam is approached. Image captured on 4/8/2017.

Analyses of the phytoplankton dataset indicated differences in phytoplankton assemblage based on lake location, as well as the importance of the metric (cell density or biovolume) used to assess algal abundance. An important finding is the increased biovolume of cyanobacteria as the High Rock Lake Dam is approached (Figures 21b, 21d, & 21f). Differences in phytoplankton assemblages may be a result of differences in residence time and the life history of these organisms. A slow growth rate coupled with high flow and maximized flushing, likely changes the dominant phytoplankton taxonomic group. For example, in the Neuse River Estuary, cyanobacteria dominate in summer months, likely attributed to their slow growth rate, and thus do better during low-flow conditions when residence time is longer (Paerl et al. 2006). Residents of Denton, North Carolina, located in Davidson County, utilize the Yadkin River (Tuckertown Reservoir) downstream of High Rock Lake as a drinking water supply (NC DEQ 2018b). The reservoir is the primary source of water for the Denton population year-round (NC DEQ 2018b). The abundance of cyanobacteria in the lower reaches of the HRL reservoir raise concerns for human health, as microcystins can be a potentially toxic byproduct of cyanobacterial

blooms. Microcystins have been linked to domestic animal and wildlife mortalities and liver damage in humans (Butler et al. 2009). Recent work has demonstrated that microcystins are among the most pervasive cyanotoxins in North Carolina lakes, and suggests continued testing and monitoring to ensure that NC lakes are meeting their designated uses (Wiltsie et al. 2018).

6. FUTURE WORK Reservoirs throughout the state are characterized by distinct discharge and residence times, land uses, and loading of pollutants, highlighting the difficulty of setting numeric criteria based on a single pilot study. Results of this study indicate that elevated chlorophyll-a concentrations are most likely to occur in the middle of the lake under low flow conditions. Water quality data should be collected at a greater sampling frequency in this zone in the future to better understand the relationship between flow and algal blooms. The high-frequency study conducted in 2016 was helpful in understanding lake dynamics for that summer, but total nitrogen and total phosphorus measurements should be included in future data-intensive studies. Due to the spatial variability in turbidity, and the associated light limitations in the upper reaches of the High Rock Lake Reservoir, enhanced monitoring of algal growth should occur in locations that are less influenced by the Yadkin River. A comprehensive understanding of the relationships between Yadkin River discharge and High Rock Lake residence times on nutrient loading and algal growth will shed light on the most appropriate nitrogen and phosphorus standards for this aquatic system, and provide insight on how to address other reservoirs in the state. The mid-lake section, or transitional lake zone, experienced the most exceedances of the state’s 40µg/L chlorophyll-a standard, and numeric nutrient criteria should be developed that aim to reduce the risks for blooms to occur in this section. Because of the interactions between turbidity and algal growth, remote sensing may improve our understanding of the nutrient-chlorophyll relationships in High Rock Lake. It would be beneficial to identify a turbidity threshold in which light becomes a limiting resource within the reservoir. Once a threshold to signify light limitation is established, the data that is not light limited can be parsed out and analyzed to better understand relationships between nutrients and chlorophyll-a.

As plants photosynthesize, dissolved oxygen is generated as a byproduct. The intensive dataset showed the strongest cross-correlation between dissolved oxygen and chlorophyll-a, and suggests that diurnal dissolved oxygen data may be able to provide early warnings of algal blooms if continually monitored. This finding indicates the benefit of implementing a sonde monitoring program to measure dissolved oxygen, chlorophyll-a, and pH especially in the mid-portion of High Rock Lake where blooms are most likely to occur. Differences in biovolume are influenced by discharge and residence time. For this study, due to the lack of available residence time data we used the single USGS Yadkin College gage station discharge data as a proxy for residence time. With time-varying lake volume and discharge data, residence time could be calculated and would be a more direct metric to explain variability in chlorophyll-a. Future analysis should focus on phytoplankton taxonomic assemblage, and how these taxonomic groups vary with time and space in High Rock Lake. There is a stark difference in phytoplankton assemblages in lake sections when based on biovolume, but we still have little understanding as to what causes the algal dominance shift in the different lake sections and with time. Earlier work revealed that cyanobacteria dominance was common during the warmer periods (Tetra Tech 2016). Since cyanobacteria poses threats to human health, it will be important to monitor cyanobacterial blooms in the future and understand when these blooms are most likely to occur. It would be beneficial to conduct a time series analysis to determine the influence of seasonality on the dominant phytoplankton assemblages throughout the lake. A more consistent sampling frequency will be required to fully understand the influence of seasons on dominant algal groups. An important question for future management efforts within the reservoir is whether warming lake temperatures associated with climate change will result in an increased dominance of cyanobacteria.

References

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APPENDIX

Figure 1A. Relationship between molar total nitrogen and chlorophyll-a in the upper-lake section. Sampling occurred between 7/21/1981 and 9/13/2011.

Figure 2A. Relationship between molar total phosphorus and chlorophyll-a in the upper-lake section. Sampling occurred between 7/21/1981 and 9/13/2011.

Figure 3A. Relationship between molar total nitrogen and chlorophyll-a in the mid-lake section. Sampling occurred between 7/21/1981 and 9/13/2011.

Figure 4A. Relationship between molar total phosphorus and chlorophyll-a in the mid-lake section. Sampling occurred between 7/21/1981 and 9/13/2011.

Figure 5A. Relationship between molar total nitrogen and chlorophyll-a in the lower-lake section. Sampling occurred between 7/21/1981 and 9/13/2011.

Figure 6A. Relationship between molar total phosphorus and chlorophyll-a in the lower-lake section. Sampling occurred between 7/21/1981 and 9/13/2011.

Figure 7A. Relationship between square-root-transformed mean daily discharge and square-root- transformed biovolume at lake station YAD 152C including outlier. Discharge value of outlier prior to transformation = 19200 cfs. Biovolume value of outlier prior to transformation = 71.06 mm3/m3. Mean discharge data was retrieved from the USGS Yadkin River-Yadkin College gage station for corresponding biovolume sampling dates between 7/21/2004 and 9/13/2011.

Figure 8A. Diagnostic plots for linear model 1 which included square-root transformed daily discharge and square-root transformed total daily biovolume for lake station YAD 152C. This model was chosen as the most appropriate model based on diagnostic plots, adjusted r2, and p-value (adj. r2 = 0.3321, p-value = 4.799e-05).

Figure 9A. Diagnostic plots for linear model 2 which included the untransformed daily discharge and untransformed total daily biovolume and excluded the outlier for lake station YAD 152C (adj. r2 = 0.22, p- value = 0.001166).

Figure 10A. Diagnostic plots for linear model 3 which included the untransformed daily discharge and untransformed total daily biovolume and included the outlier for lake station YAD 152C (adj. r2 = 0.1523, p-value = 0.006151).

Figure 11A. Mean discharge and total biovolume over time in mid-lake station YAD 152C. Daily discharge data is depicted by the blue line, and biovolume is depicted by the green points. Mean daily discharge data was retrieved from the USGS Yadkin River-Yadkin College gage station from 7/21/2004 through 9/13/2011. Biovolume sampling occurred between 7/21/2004 and 9/13/2011.