Water, Air, & Soil Pollution

, 225:1860 | Cite as

Comparative Analysis of Metal Concentrations and Sediment Accumulation Rates in Two Virginian Reservoirs, USA: Lakes Moomaw and Pelham

  • Elyse V. Clark
  • Ben K. Odhiambo
  • Matthew C. Ricker
Article

Abstract

Lacustrine sedimentation and trace metal accumulation are naturally occurring processes that can be altered by anthropogenic activities. Indices of sediment or metal dynamics are important for the management and operational use of man-made reservoirs and their drainage basins. In this study, we compared two reservoirs in Virginia, USA, to quantify the effect of varying watershed characteristics on sediment and metal fluxes. Lake Pelham is a human-impacted reservoir surrounded by agricultural fields and anthropogenic developments, whereas Lake Moomaw is an undeveloped reservoir surrounded by moderate to extremely sloping forested landscapes. Three sediment cores were taken from each reservoir to estimate 210Pb-based sediment accumulation rates, organic matter content, and indices of trace metal enrichment and accumulation. The average 210Pb-based sediment accumulation rates were 0.348 ± 0.053 and 0.246 ± 0.043 g cm−2 year−1 for Lake Pelham and Lake Moomaw, respectively. The sediment trace metal results showed strong correlation with sediment organic content, and both reservoirs had moderate to high enrichment of Cu and little enrichment of Zn and Pb. Overall, Lake Moomaw had relatively low sediment accumulation and metal enrichment. Comparatively, Lake Pelham had significantly greater metal concentrations, which were highest in the upper reaches of the reservoir. Lake Pelham also had higher sediment accumulation rates and higher metal enrichment, reflecting the impact of human development within the greater watershed. Results from this study suggest that urbanization can increase reservoir sediment and metal fluxes, but atmospheric deposition is also important in forested watersheds that have not undergone anthropogenic land-use change.

Keywords

Reservoir sedimentation 210Pb sediment accumulation Trace metals Enrichment factors 

1 Introduction

Anthropogenic alteration of land since the European settlement of the eastern USA has disrupted the natural cycles of watersheds by affecting sedimentation rates, watershed ecology, and the quality of the water in aquatic systems (Middleton 1953; Dean and Gorham 1998; Walling 2006; Conrad et al. 2007; Trimble 2008; Balogh et al. 2010). Water bodies such as lakes and artificial reservoirs are especially subjected to the consequences of human landscape alteration, which accelerates erosion and sediment fluxes to surface water bodies (F’inkenbine et al. 2000; Newman et al. 2006; Colosimo and Wilcock 2007; Walter and Merritts 2008). Sediments have a major impact in lakes and reservoirs because they contribute to a loss of storage capacity (Odhiambo and Boss 2004, 2006; Newman et al. 2006; Odhiambo and Ricker 2012), which affects the longevity of a reservoir and its potential use for municipal water consumption. Sediments are also the main conveyors of sediment-bound nutrients, metals, and other persistent pollutants to surface waters (Walling 2004; Wang and Cui 2005; Houser et al. 2006; Odhiambo and Ricker 2012). Sediment core analyses are important in establishing historical sediment accumulation rates and pollutant loading (e.g., trace metals) history to a water body.

Metals are introduced into a reservoir in either a soluble or particulate form through various natural and anthropogenic sources such as watershed erosion, point source pollution, and wet deposition (Mueller et al. 1989). Wet deposition occurs when precipitation is enriched with anthropogenic trace elements that become concentrated on atmospheric fine particles and form condensation (Conko et al. 2004). Trace metal contamination usually occurs within industrialized areas and the metals can enter a reservoir through waste effluents, mining activities, fossil fuel combustion, sewage discharge, fertilizers, and pesticides (Förstner and Wittmann 1979).

A fundamental problem with trace metals is that they are not biodegradable, and therefore are persistent in the environment. Once a trace metal has been introduced into a lacustrine system the metals are distributed into the water column, settle on the bottom, and accumulate in sediments (Fichet et al. 1998). As metals adsorb to clays and other particles, the sediments in lakes and reservoirs contain a historic signature of trace metal fluxes (Crecelius and Piper 1973; Shirahata et al. 1980; Renberg 1986; Swain et al. 1992; Foster and Charlesworth 1996; Engstrom and Swain 1997; Brännvall et al. 2001; Balogh et al. 2010). Lacustrine sediment cores have shown increases in metal concentrations since the 1800s and even larger increases in the 1900s (Conrad et al. 2007; Balogh et al. 2010). With the onset and expansion of industrialization, metal concentrations dramatically increased but have recently declined because of the implementation of environmental laws and the banning of leaded gasoline (Conrad et al. 2007).

There are multiple sediment core methods appropriate to determine trends in trace metal fluxes and sediment accumulation. Concentrations of fallout 137Cs and 210Pb are often used to estimate the rates of sedimentation in coastal waters, lakes, and wetlands on scales of several decades to 100 years (Odhiambo et al. 1996; Mizugaki et al. 2006; Conrad et al. 2007; Odhiambo and Ricker 2012). 210Pb is a naturally occurring radionuclide which comes from the decay series of 238U and has a half-life of 22.3 years. 210Pb can attach to the sediment from 222Rn decay (naturally occurring gas found in soil or the atmosphere from 238U decay) and also from 226Ra in the soil. Unsupported or excess 210Pb comes from wet precipitation or atmospheric fallout, and supported 210Pb comes from naturally occurring 222Rn and 226Rn in the soil (Appleby and Oldfield 1992; Jaeger et al. 2009). The total 210Pb in the sediment contains both unsupported and supported 210Pb. 210Pb was used in this study to provide a timeline for studying the historical loading of metals into the study reservoirs.

The objective of this work was to examine sediment deposition in two reservoirs in Virginia, USA, and analyze the historical trends and concentrations of trace metals in the reservoirs. The study watersheds have varying levels of human development, local geology, soil types/erodibility, and topography. One reservoir, Lake Moomaw, is located in the forested, protected Blue Ridge Mountains, but may be subjected to atmospheric influxes of metals from coal production and paper mills in the region. The contrasting reservoir, Lake Pelham, is surrounded by industrial complexes, suburban development, and agricultural fields. This study seeks to establish historical trends of metal fluxes and compare the concentrations to background levels in order to quantify the extent of metal enrichment in modern sediments.

1.1 Background and Regional Setting

Lake Pelham (Fig. 1) is a reservoir used for drinking water in Culpeper County, Virginia. It was created in 1972 and is 1.06 km2, with a watershed of 67.81 km2. The reservoir is located in the Piedmont physiographic region and the geology of the area consists of Triassic conglomerate, shale, quartzite, granite, gneiss, and metabasalt (VDMME 2012). The common soil complexes within the watershed include the Rapidan-Penn Complex, Edgement-Culpeper Complex, and Culpeper sandy loam (Soil Survey Staff 2011). Historically, the watershed of Lake Pelham was agricultural; however, the basin has become more developed due to southward expansion of the suburbs of Washington, DC. Over 20,000 people utilize Lake Pelham for drinking water and thus the reservoir is regulated by the Lake Pelham Watershed Management Plan, which sets regulations on natural buffers and goals for nutrient and hazardous material inputs (Regional Water Supply Plan 2011).
Fig. 1

Location map of Lakes Pelham and Moomaw showing the sampling sites within the two lakes. In Lake Moomaw, cores 1 = dam (lower), 2 = middle, and 3 = upper. In Lake Pelham, cores 1 = upper, 2 = middle, and 3 = dam (lower)

Lake Moomaw (Fig. 1) is a 10.24-km2 reservoir located in the Shenandoah Valley region of western Virginia and impounds the Jackson River of the greater James River system. The lake was constructed in 1978 for downstream water quality augmentation, flood control, and recreation. The 857-km2 watershed is largely forested because it lies within the Gathright Wildlife Management Area and the George Washington National Forest (VDGIF 2009). The regional geology is primarily limestone and dolomite and the major soil complexes include the Dekalb-Lily Complex and Weikert-Berks-Rough Complex (Soil Survey Staff 2011). Although the watershed and area surrounding the reservoir are largely undeveloped, there is a large pulp and paper mill approximately 30.6 km downstream of the reservoir. The locale produces “activated carbons” used for chemical production, food purification, and other materials (MWV Specialty Chemicals 2012). The emissions from the paper mill include sulfuric acid, lead compounds, zinc compounds, ammonium, manganese compounds, and many others (US EPA 2010).

2 Sampling and Methods

2.1 Field Sampling

A gravity coring device with plastic liners was used to collect three sediment cores from Lake Moomaw and a manual coring device with plastic liners was used to collect three sediment cores from Lake Pelham (Fig. 1). The sampling site selections were based on water depth and reservoir geomorphology, which influences sediment deposition. After retrieval, the cores were transported in ice to the Earth and Environmental Sciences Laboratory at the University of Mary Washington (Fredericksburg, Virginia, USA), where each core was extruded and subsampled at increments of 2 cm down the core. A fraction of each subsample was used in 210Pb analysis, and the remaining materials were used for trace metal and organic matter analysis.

2.2 Laboratory Analysis

2.2.1 210Pb Analysis and Sediment Accumulation Model

Samples for 210Pb analysis were sent to CORE International Research Labs, Winnipeg, Canada. The 210Pb analysis is based on the method of Eakins and Morrison (1978) in which 210Po is distilled out of sediments at a high temperature, digested by acid, and then plated onto silver disks for alpha spectrometry analysis. The 210Pb is assumed to be in equilibrium with the 210Po, which occurs when sediments are greater than 2 years old. The minimum detection limit for a 0.5-g dry sample was approximately 0.2 dpm 210Po/g dry sample at a confidence level of 95 % for a counting time of 30,000 s. A duplicate was run every 10th sample, a blank run every 20th sample, and detector blanks run every 90 days for quality assurance.

The sediment chronology and accumulation rates were estimated using a regression model based on Matsumoto and Wong (1977) and Odhiambo and Ricker (2012). The regression model assumes that: 210Pb flux to the sediments is constant over the time interval being considered, 210Pb does not or minimally migrates after deposition, and the accumulation rate of sediments is constant over time. With these assumptions, the dependence of excess 210Pb on mass depth is:
$$ {\mathrm{A}}^{210}{\mathrm{Pb}}_{\mathrm{exc}.}(m)=\left(P/w\right){e^{-}}^{\lambda m/w} $$
where, m is mass depth (grams per square centimeter), λ is the radioactive decay constant for 210Pb (0.0311/year), P is the 210Pb flux to the sediment-water interface, w is the sediment accumulation rate (grams per square centimeter per year) and m is the integrated mass of sediments above a depth z. The values of P and w are obtained from In (210Pb excess) versus mass depth plot, where intercept = In(Pw−1) and slope = (−λw−1). The time (T) associated with sediment strata at any given mass depth is given by: T = m(z)w−1 The constant rate supply (CRS) model was also applied, which allows for variable sedimentation rates at different depths and dates. CRS model equations are detailed in Nriagu 1979; Appleby and Oldfield 1978. The CRS model assumes a constant supply of 210Pb to the sediment-water interface, which allows for variable accumulation rates with depth in a core (Appleby and Oldfield 1978; Nriagu 1979; Odhiambo and Ricker 2012).

2.3 Trace Metal Analysis

The concentrations of Fe, Al, Ba, Cd, Cr, Cu, Pb, Mn, and Zn were analyzed in all core sections. Based on the method of Zwolsman et al. (1993), subsamples from each 2 cm portion were dried at 100 °C in an oven overnight. The dry sediment was then disaggregated with a mortar and pestle and 1 g of <63 μm size sediments was digested with 20 mL of aqua regia acid solution of three parts hydrocholoric acid: one part nitric acid: one part nanopure water (3HCl/1NO3/3H2O) in a 32.2 °C water bath for 2 h, left in a shaker overnight, and centrifuged for 3 h. The leachate was then filtered into acid resistant bottles and refrigerated to preserve the samples. Each sample was diluted to 3 % concentration solution using nanopure ultra-deionized water. Analysis for trace metals was done using a Thermoscientific iCAP 6000Series ICP-OES. The following wavelengths (nm) were used for analysis to avoid interferences: 396.1 (Al), 233.5 (Ba), 226.5 (Cd), 267.7 (Cr), 224.7 (Cu), 239.5 (Fe), 259.3 (Mn), 220.3 (Pb), and 213.8 (Zn). Recovery analysis was performed using the 0.1 μg/g Cd, 0.1 μg/g Pb, 0.024 μg/g Cd, and 0.024 μg/g Pb standards. The results indicated that the intensity data is substantially consistent with only 0.64 % error for 0.100 μg/g Cd, 0.10 % error for 0.100 μg/g Pb, 1.40 % error for 0.024 μg/g Cd, and slightly greater error of 18.74 % for 0.024 μg/g Pb. Though Cd was analyzed and used for recovery analysis, the analyzed samples were below detection limit and therefore Cd is not discussed in the results section.

Metal accumulation rates were also calculated in order to further quantify metal fluxes into the two reservoirs. These rates can be used to show the impact of metals by relating them to sediment accumulation rates:
$$ \mathrm{Metal}\kern0.5em \mathrm{accumulation}\kern0.5em \mathrm{rate}\left(\upmu \mathrm{g}\kern0.5em {\mathrm{cm}}^{-2}\kern0.5em {\mathrm{year}}^{-1}\right)=\mathrm{Sediment}\kern0.5em \mathrm{accumulation}\kern0.5em \mathrm{rate}\left(\mathrm{g}\kern0.5em {\mathrm{cm}}^{-2}\kern0.5em {\mathrm{year}}^{-1}\right)\times \mathrm{Metal}\kern0.5em \mathrm{concentration}\left(\upmu \mathrm{g}/\mathrm{g}\right) $$
In order to distinguish between background concentrations of metals in the sediments and concentrations induced by anthropogenic processes or pollution/contamination, an enrichment factor (EF) was utilized. Calculating EF involves normalizing each metal or element to a naturally occurring or lithogenic element such as Fe, Al, or Mn. Aluminum was chosen in this study as it is the most abundant metal in the Earth’s crust and is representative of aluminosilicates, which are major carriers for adsorbed metals (Qi et al. 2010). The EF for a given trace metal (Me) is calculated as follows (after Rule 1986; Conrad et al. 2007):
$$ \mathrm{EF}=\left(\left[{\mathrm{Me}}_{\mathrm{s}}\right]/\left[{\mathrm{Al}}_{\mathrm{s}}\right]\right)/\left(\left[{\mathrm{Me}}_{\mathrm{cr}}\right]/\left[{\mathrm{Al}}_{\mathrm{cr}}\right]\right) $$
where the subscripts (s) represent the sample trace metal concentration and (cr) denotes the crustal abundance of the trace metal (from Taylor 1964). A second EF was calculated using regional abundances from a US Geological Survey report for comparison purposes (Table 1). The EF results were interpreted based on categories of Mmolawa et al. 2011, where EF values of <2 are enrichment deficient, 2–5 moderate enrichment, 5–20 significant enrichment, 20–40 very high enrichment, >40 extreme enrichment. The EF analysis was only applied to Zn, Cu, and Pb because these are known to come from anthropogenic activities, rather than natural sources, in excess amounts.
Table 1

Average metal concentrations in the Lake Pelham, Lake Moomaw, natural sediments, and regional areas (micrograms per gram for all elements except Al and Fe)

 

Ba

Cr

Cu

Mn

Pb

Zn

Al%

Fe%

Average crusta

425

100

55

950

12.5

70

8.23

5.63

Blue Ridgeb

445

36.5

15

2335

40

76.5

5.44

2.76

Piedmontb

241

197

6.5

225

34

29

2.84

0.058

Lake Moomaw

146

16

152

515

21

101

3.47

5.57

Lake Pelham

157

46

51

321

19

86

1.84

3.44

aTaylor (1964)

bSmith (2006): Blue Ridge used for Lake Moomaw regional comparison and Piedmont used for Lake Pelham regional comparison

2.4 Organic Content Analysis

Percent organic matter was determined by weight using Loss on Ignition (LOI) (Dean 1974; Heiri et al. 2001), where samples from each 2-cm increment of cores (LM1, LM2, LM3, LP1, LP2, and LP3) were placed in a weighed crucible and oven dried for 24 h at 105 °C to remove any moisture. The dry samples were then weighed, placed in a muffle furnace and combusted at 550 °C for 4 h, and weighed again. LOI was calculated by the following equation:
$$ \mathrm{LOI}550=\left(\left(\mathrm{DW}105-\mathrm{DW}550\right)/\mathrm{DW}105\right)\ast 100 $$

Where LOI 550 is the percent organic matter, DW105 is the weight of the initial dry sample, and DW550 is the sample weight after combustion.

2.5 Statistical Analysis

A (2 × 3) two-way analysis of variance (ANOVA) test was conducted in Sigma Plot 11.2 (Systat Software, Inc., San Jose, CA) in order to examine the relationship between the two reservoirs (Lake Pelham and Lake Moomaw) and the average metal concentrations (Cu, Pb, and Zn) by core location (cores located at the upper, middle, and dam sections). Metal concentrations were aggregated into mean values using the individual 2-cm subsamples (N = 60) from each study core. Interaction and main effects were analyzed for all cores. If interaction effects were not significant, the main effects were analyzed with Tukey’s honestly significant difference tests. Pearson product–moment correlation coefficients (r) were also quantified for each 2-cm subsample to elucidate the relationships among lacustrine sediment characteristics (sample depth, sedimentation rate, organic matter) and trace metal concentrations. All statistical tests were considered significant at α = 0.05.

3 Results and Discussion

3.1 Sediment Accumulation Rates

Sediment depth profiles of 210Pb activities for the six cores from Lakes Pelham and Moomaw show the expected exponential decline with depth (Fig. 2). The profiles also show a delineation between lacustrine and pre-impoundment deposition, with a slight change of slope in 210Pb profile (Fig. 2), implying that the cores captured both the pre-impoundment soil surfaces and post-impoundment lacustrine sediment layers. As the focus of this study is the post-inundation lacustrine sediments, the regression and CRS models were only applied to the top 20 cm for Lake Pelham and top 10 cm for the Lake Moomaw cores. The deepest lacustrine sediment samples in both reservoirs had not reached 210Pb background levels; therefore a value that minimized the standard error of estimate for the linear regression versus mass depth was used in all cores; and thus the average background used were 1.41 ± 0.10 and 2.29 ± 0.11 dpm/g for Pelham and Moomaw, respectively. The surface 210Pb activities of the cores were about 5–11 times the background levels and thus were deemed suitable for CRS model application.
Fig. 2

Excess 210Pb profiles for Lake Pelham and Lake Moomaw cores. The red dotted line shows the transition from pre- to post-impoundment sediment deposits. Regression model sediment accumulation rates (S) and CRS accumulation rates are in parentheses

The regression analysis results for Lake Pelham cores LP1, LP2, and LP3 indicated sediment accumulation rates of 0.313, 0.483, and 0.692 g cm−2 year−1, respectively (Fig. 2; Table 2). The average CRS accumulation rates were 0.288 g cm−2 year−1 for LP1, 0.371 g cm−2 year−1 for LP2, and 0.386 g cm−2 year−1 for LP3. The historical CRS accumulation results show that modern accumulation rates have slightly increased relative to the base of the lacustrine sediments, by approximately 0.10 g cm−2 year−1 in the upper reaches and a slightly greater increase (0.19 g cm−2 year−1) in the lower reaches of the reservoir near the dam. The average increase in sediment accumulation for the whole of Lake Pelham was 0.14 g cm−2 year−1 since the 1970’s. Historically, the watershed of Lake Pelham has been increasingly urbanized as human developments and industrial areas have been established on agricultural land, which most likely contributed to the historical increase in sediment accumulation. The results show that the upper parts of Lake Pelham (LP1) have the lowest sediment accumulation rates (0.343 g cm−2 year−1) compared with the area closest to the dam (LP3) that had the highest sediment accumulation rate (0.692 g cm−2 year−1). This suggests that the majority of the incoming sediment is likely being transported in suspension past the deltaic area in the upper reaches and are depositing in the deeper parts of the reservoir near the dam. Furthermore, this spatial pattern may reflect variable sediment trapping efficiencies between the upper and lower parts of the reservoir, which would influence where and when sediment may be deposited.
Table 2

Comparison of the models-Pb-210 Regression (grams per square centimeter per year) and Pb-210 CRS Model (grams per square centimeter per year)

 

Core 1

Core 2

Core 3

Lake Pelham

 Pb-210 regression model

0.313

0.483

0.692

 Pb-210 CRS model average

0.288

0.371

0.386

Lake Moomaw

 Pb-210 regression model

0.601

0.335

0.402

 Pb-210 CRS model average

0.295

0.230

0.212

The regression model results from Lake Moomaw showed an accumulation rate of 0.601 g cm−2 year−1 at LM1 near the dam in the deepest part of the reservoir (Fig. 2; Table 2). The mid-section of the reservoir at LM2 had an accumulation rate of 0.335 g cm−2 year−1, whereas the upper reaches at LM3 had an accumulation rate of 0.402 g cm−2 year−1 (Fig. 2; Table 2). The CRS average accumulation rates for the three sites, LM1 (0.295 g cm−2 year−1), LM2 (0.231 g cm−2 year−1) and LM3 (0.212 g cm−2 year−1) are slightly lower than the regression model results, but show similar spatial patterns. The temporal variation depicted in the CRS models shows that accumulation rates have not changed significantly in this basin, with a small modern increase of about 0.06 g cm−2 year−1 estimated for the upper reaches of the reservoir (LM3). The modern accumulation increase relative to the base of lacustrine sediments is significantly higher, 0.12 g cm−2 year−1, in the lower part of the reservoir near the dam (LM1). The spatial pattern in accumulation rates in this reservoir also suggests the dominance of suspended sediment influx, with higher accumulation in the deeper area near the dam. In addition to external fluvial sources, the higher rate of accumulation in the lower reaches may also be attributed to extensive, visible shoreline erosion from the reservoir’s steeply sloping shores. Sedimentation from shoreline erosion has been commonly observed in other regional mountain reservoirs. For example, Fayyad (2010) reported sedimentation from shoreline erosion concentrated along the entire reservoir margins in both Smith Mountain and Leesville lakes in southwestern Virginia. The majority of eroded shoreline materials tend to be concentrated as bench deposits in the littoral areas of mountain reservoirs, but significant amounts of sediment may be redistributed beyond the shallow littoral zones depending on shore slope steepness, slumping, and the intensity of wave action. In addition, shoreline erosion may be prevalent in the early years after reservoir construction, but typically decreases as more resistant underlying rocks are encountered (Fayyad 2010).

Total sediment accumulation was calculated using Lake Pelham and Moomaw surface areas (LP = 8.96 × 105 m2; LM = 1.02 × 107 m2), average lacustrine sediment densities, and the average sedimentation rate at the three locations in each reservoir. Annual accumulation rates of 6,837 and 70,178 m3/year were estimated for Lakes Pelham and Moomaw, respectively. The total annual accumulation rates translate to basin sediment yields of 1.01 and 0.82 mm m−2 year−1 for Lake Pelham (67.8 km2 watershed) and Moomaw (857 km2 watershed), respectively. The impact of the estimated annual accumulation rates is about 1 % annual loss of storage capacity in both reservoirs, not taking sediment compaction into account. The two reservoirs show comparable sediment accumulation rates and the associated loss of capacity using 210Pb regression model estimates. This is unusual because although the two watersheds have a similar climatic environment and similar sandy or silt loam top soils (soil erodibility Kf = 0.41 − 0.45), they have vastly different geomorphic and land-use characteristics. The accumulation rates in Lake Moomaw are likely attributed to highly erodible soils on the steep (>20°) slopes that dominate the watershed as well as significant lake shoreline erosion. However, the sediment flux rates are likely to be lessened by the dense vegetated land cover and the thin soils that characterize the basin. By contrast, the Lake Pelham watershed is relatively flat topographically (0–5° slopes), and the lacustrine sediment fluxes are most likely influenced by land use rather than geologic or geomorphologic characteristics. The absence of a continuous vegetated riparian zone around the reservoir, which currently consists of a major roadway, golf course, agricultural fields, and a residential development, is probably a source of sediment into the reservoir. The sediment fluxes into Lake Pelham are also likely curtailed by a well developed deltaic-wetland zone in the mouth of the main channel where significant amounts of sediments may be trapped before reaching the reservoir; unlike in Lake Moomaw where steep sloping energetic tributaries empty sediment loads into the reservoir without impedance. In Lake Moomaw, stream incision will only be a factor in sediment yield until the system is bedrock controlled. Considering the steep, valley-constricted nature of the first- and second-order tributaries to the reservoir, debris flows are likely the source of sediment to the valley floor rather than vertical incision (Taylor and Kite 2006). Intrinsic stream sediment production is likely important in both basins, although for different reasons. In Lake Moomaw, the basin contains steep high velocity streams and thus higher rates of stream bed incision (until bedrock is reached), sediment transport, and bank erosion (i.e., valley-stream widening) can occur. Whereas in Lake Pelham impervious surfaces associated with human establishments likely magnify runoff and bankfull flooding in reservoir tributaries after storm events, leading to stream incision and internal stream sediment production as well.

The sediment accumulation estimates for both reservoirs in this study are comparable to regional values for reservoirs located in the Piedmont province of Virginia (Lake Anna, Ni Reservoir) that have a sediment accumulation range of 0.023–1.02 g cm−2 year−1 (Odhiambo and Ricker 2012; Pope and Odhiambo 2013). Other regional reservoirs with steeper slopes and anthropogenic alterations, such as Smith Mountain and Leesville, have undergone >5 % storage capacity reduction due to sedimentation (Fayyad 2010). The spatial and temporal patterns in sedimentation in most regional surface water bodies seem to be correlated with anthropogenic stresses and associated land-use and cover changes within the drainage basins (Fayyad 2010; Odhiambo and Ricker 2012; Ortt et al. 2000; Pope and Odhiambo 2013; Saenger et al. 2010).

The Lake Moomaw accumulation rates, even the lower CRS results, seem relatively high compared with other mountainous lakes where natural geomorphic conditions and climate variability are the dominant factors controlling short and long term sediment yields. Appleby and Piliposian (2006) estimated sedimentation in the Tatra Mountain lakes and reported mean rates ranging from 0.0055 to 0.046 g cm−2 year−1 and Guevara et al. (2010) also estimated sedimentation of about 0.013 g cm−2 year−1 in the Patagonia lakes. These other mountain lakes, however, are located in younger geologic landscapes compared with Lake Moomaw and should be expected to yield more sediments. These data suggest that although the valley and ridge province of Virginia is dominated by highly erodible colluviums (Mills 1988), the three cores used here might be overestimating sediment accumulation rates in Lake Moomaw. Possible explanations for the highest sediment accumulation recorded (closest to the dam) may be that the LM1 core captured a relict fluvial channel or an area containing slumping shoreline materials. If this were the case, the LM1 core may not be a true reflection of the entire lower reaches of the basin. Future close core sampling intervals and our ongoing high resolution geophysical sediment surveys in these reservoirs will likely provide more clarity regarding spatial variation in sediment thicknesses.

3.2 Metal Concentrations

The average trace metal concentrations for Lake Pelham are listed in Table 1. The concentration of Cu in the cores was highly variable, ranging from 32 to 475 μg/g. The other metals were not as variable and showed a narrower range of concentrations. Depth profile plots showing historical metal concentrations are presented in Fig. 3. The metal concentrations generally show recent increases near the top of most cores. The recently elevated concentrations are especially evident in the profiles of Fe, Zn, Mn, and Cu. By contrast, Al, Ba, and Cr concentrations have remained relatively constant historically. Pb is the only profile that decreased in concentration during modern times, which may be attributed to the discontinued use of leaded gasoline and the development of environmental regulations controlling Pb emissions during the 1970s (Griffin et al. 1989). A spike in all metal concentrations was also evident between 10 and 14 cm (Fig. 3), which most likely reflects the change in sedimentation following the creation of Lake Pelham. Thus, the initial disturbance of the land during construction of the reservoir may have loosened the soil and increased lower reservoir sediment and metal fluxes at the 10- to 14-cm depth. The spike in metal concentrations in sediments may also be associated with diagenetic processes (correlation between trace metals and Fe ranged from 0.34 ± 0.29 for Pb to 0.74 ± 0.10 for Zn), variations in grain sizes, specific flooding events transferring metal-adsorbed sediment to the reservoir, or changes in sediment flux rates to the reservoir (Odhiambo et al. 2013).
Fig. 3

Trace metal concentration versus sediment depth profiles for Lake Moomaw and Lake Pelham. The dashed red lines indicate the transition from impoundment to pre-impoundment deposits

The average metal concentrations for the three Lake Moomaw cores are shown in Table 1 and the depth profiles in Fig. 3. The concentrations of all the analyzed metals were highly variable temporally and spatially. The highest concentrations in all cores were just below the bottom of the lacustrine sediments and relatively lower in most of the overlying lacustrine layers, which correlates to the trends in organic matter accumulation as shown in Fig. 4. The higher metal concentrations below the lacustrine sections of the cores are probably former soil surface horizons with metals adsorbed to the organic-rich clay particles. After the creation of the reservoir, the amount of sediment accumulation and metal concentration likely decreased because sediment transport dynamics shifted to favor deposition of metal-deficient silts and sands over pre-lacustrine soil surfaces.
Fig. 4

Sediment organic content depth profiles for Lake Moomaw and Lake Pelham sediment cores showing temporal changes in percent organic content

3.3 Organic Matter

The lacustrine organic matter results are presented in Fig. 4. Lake Moomaw had lower organic matter content compared with Lake Pelham, ranging from approximately 3 to 9 % at all core depths. All three Lake Moomaw cores showed >2 % increase in organic content with depth, peaking at the 8- to 12-cm interval, corresponding to the pre-/post-impoundment boundary (Figs. 2 and 4). Increased organic matter towards the bottom of the three cores may represent buried soil surface horizons (O or A horizons) and relict vegetation left from reservoir construction that are overlain by clastic mineral lacustrine sediments.

Sediment organic content in Lake Pelham ranged from 2 to 13 %, with LP1 location recording the highest values (Figs. 1 and 4). The temporal trends also showed >2 % increases in organic content at the pre/post-inundation boundary in all the cores (Fig. 4). These data indicate that organic matter flux has increased after the creation of Lake Pelham. The progressive increase in organic matter may be associated with greater allochthonous C fluxes, derived from watershed sources (including soil erosion), or autochthonous C in the shallow areas of the reservoir from the phytoplankton, periphyton, and other organisms residing in the reservoir itself (Kraus et al. 2011). Studies have shown that reservoirs damming fluvial waterways typically receive large allochthonous organic matter loads (Wetzel 1975; Groeger and Kimmel 2009); therefore organic matter inputs from terrestrial sources are likely the main source of the increase in organic matter within Lake Pelham. For both reservoirs, the apparent shift in lacustrine sediment organic matter concentration correlates to the pre-/post-impoundment boundary conditions, with the less disturbed Lake Moomaw receiving less external nutrient fluxes that support aquatic vegetation production.

3.4 Statistical Analysis of Metal Distributions

Two-way ANOVA analysis of mean trace metal concentrations indicated significant interaction effects between the two study lakes and the core positions within each lake for Pb and Zn (Table 3). Mean Cu concentration did not show a significant interaction (p = 0.345) but had significant main effects for the lake and core positions (Table 3). Figure 5a is a graphical representation of the significant ANOVA interaction effects. Lake Pelham has significantly higher concentrations of Pb and Zn in the upper reaches as compared with the middle and lower (dam) reaches of the reservoir. There is significant disordinal interaction between the two lakes, with Lake Pelham having less Pb and Zn in the middle core, yet greater concentrations at the upper and dam positions compared with Lake Moomaw. Cu concentrations showed no significant interaction effects, but the main effects indicated Lake Pelham has significantly (p < 0.001) more Cu than Lake Moomaw, as shown in Fig. 5b. In addition, Cu concentrations were significantly greater (p = 0.002) in the upper cores versus the middle or dam positions. The significantly higher Cu concentration in Lake Pelham may be a reflection of the watershed development and Cu sourcing from vehicle parts, metal corrosion, and pesticides, among other sources. Figure 5a shows that the trends in metal concentrations are similar in both reservoirs, with the metal concentrations generally decreasing from the upper reaches towards the dam sections of the reservoirs. This relationship suggests that there are fluvial interactions in the upper reaches of the reservoirs and the metals are settling out of suspension before reaching the lower sections. In Lake Pelham, the upper section of the reservoir is crossed over by a 4-lane road, which may contribute abraded and corroded metals to the upper reaches via road runoff during storm events. Similar to this, a developed boat marina is in the upper section of Lake Moomaw, which may similarly lead to a higher concentration of metals in the upper reaches of the basin.
Table 3

Summary of (2 × 3) two-way ANOVA analysis for major trace metal concentrations (micrograms per gram) in Lakes Pelham and Moomaw

Source of variation

df

SS

MS

F

P

Element (Cu)

 Lake

1

91,431

91,431

15

<0.001

 Core positiona

2

85,990

42,995

7

0.002

 Lake × position

2

13,578

6,789

1

0.345

 Residual

54

337,955

6,258

  

 Total

59

566,262

9,598

  

Element (Pb)

 Lake

1

52

52

3

0.081

 Core positiona

2

1,152

576

35

<0.001

 Lake × position

2

316

158

10

<0.001

 Residual

54

889

16

  

 Total

59

2,740

46

  

Element (Zn)

 Lake

1

3,072

3,072

5

0.036

 Core positiona

2

30,677

15,338

23

<0.001

 Lake × position

2

15,727

7,863

12

<0.001

 Residual

54

35,814

663

  

 Total

59

83,949

1,423

  

aCorresponds to general core position within the lakes (upper, middle, and dam sections)

Fig. 5

a Relationship between average metal concentration (Cu, Pb, and Zn; micrograms per gram) and core location. b Columns with different letters imply a significant difference between the two variables

The general trends of metal concentrations are similar to those of many reservoirs situated on fluvial waterways, where sediments drop from suspension before reaching the lower sections of the lake (Shotbolt et al. 2005). Metal concentrations in Lake Moomaw tended to strongly reflect this relationship, with progressively less metals from the upper sections down towards the dam core position. In Lake Pelham there was a more variable relationship from the upper to dam core positions. There was a significant drop in Pb and Zn concentrations from the upper to middle cores (Fig. 5a) but an increase in these metals in the dam core. The upper core of Lake Pelham receives fluvial influx from adjacent roadways and agricultural fields, while the middle core is disconnected from fluvial inputs and surrounded by patches of forested land (Fig. 1). The forested buffer and distance to upper fluvial waterways has likely contributed to lower metal concentrations in the center of the lake. By contrast, the dam core is subjected to metal influx from a small 2nd order tributary creek (Vaughn Branch) that enters the lower lake from the north (Fig. 1). Small tributary creeks can be significant sources of sediment to large reservoirs in the region (Odhiambo and Ricker 2012), and this creek drains extensive low- to medium intensity developments (Homer et al. 2007) with many road crossings that may have contributed to the higher Pb and Zn levels observed at the dam core position (Yesilonis et al. 2008).

Pearson correlation analyses among intrinsic sediment properties and metal concentrations showed distinct patterns between the two reservoirs (Table 4). Lake Pelham showed distinct negative correlations between sample depth and metal concentrations, indicating that shallow samples had greater concentrations than deep samples, especially with Cu, Fe, and Mn. By contrast, there were no significant correlations with sample depth in Lake Moomaw, suggesting that metals are not concentrated in the surface sediments. Similar correlations were found between organic matter and depth, with significant positive correlations (r = 0.64, p < 0.001) for Lake Moomaw and significant negative ones (r = −0.34, p = 0.04) for Pelham. These results highlight the fact that organic matter fluxes were greater in the past at Moomaw and greatest in modern times at Pelham, as shown by higher organic matter concentrations towards the sediment surface (Fig. 4). These trends could reflect periods of large nutrient inputs that increased net primary productivity or times where organic-rich sediment fluxes have occurred. In Lake Moomaw, the deeper metal and organic-rich sediments may reflect time periods of soil disturbance, such as those when the dam was constructed in the 1970s. For Lake Pelham, increases in algal and plant productivity may have occurred in recent times as the region has undergone anthropogenic land-use change, which has been shown to increase fluxes of both nitrogen and phosphorus to surrounding water bodies (Jones et al. 2004). In addition, both lakes displayed significant positive correlations with total organic matter and metals, but negative correlations between sedimentation rates and metal concentrations (Table 4). These data suggest that metals accumulate in both lakes during periods of low mineral sedimentation and high organic matter inputs. These trends may reflect the fact that metals in these systems are bound to organic particles, or that prolonged periods of organic matter production and low sedimentation allow for increased metal fluxes from atmospheric sources (Chillrud et al. 1999). Although these analyses provide some insights into relationships between intrinsic sediment properties and metal concentrations, additional studies are needed to understand the processes driving both historical and contemporary organic matter and metal accumulation in these two reservoirs.
Table 4

Correlation matrices of trace metal and lacustrine sediment characteristics

Sediment properties

Metal concentrationsa

Sediment properties

Al (μg/g)

Cr (μg/g)

Cu (μg/g)

Fe (μg/g)

Mn (μg/g)

Pb (μg/g)

Zn (μg/g)

Depth (cm)

Sediment rate (g cm−2 year−1)

Organic matter (%)

Lake Moomaw (N = 24)

 Sample depth

0.31 (0.13)

0.35 (0.09)

0.11 (0.61)

0.25 (0.23)

0.25 (0.23)

0.31 (0.15)

0.21 (0.33)

1.00 (–)

  

 Sediment rate

−0.63 (<0.01)

−0.61 (<0.01)

−0.56 (<0.01)

−0.81 (<0.0001)

−0.83 (<0.0001)

−0.59 0.0021

−0.82 (<0.0001)

0.16 (0.45)

1.00 (–)

 

 Organic matter

0.66 (<0.001)

0.64 (<0.001)

0.48 (0.02)

0.48 (0.02)

0.37 (0.07)

0.68 (<0.001)

0.42 (0.04)

0.64 (<0.001)

−0.17 (0.43)

1.00 (–)

Lake Pelham (N = 36)

 Sample depth

−0.13 (0.46)

0.05 (0.76)

−0.51 (<0.01)

−0.40 0.02

−0.45 (<0.01)

0.13 (0.45)

−0.31 (0.06)

1.00 (–)

  

 Sediment rate

−0.79 (<0.0001)

−0.77 (<0.0001)

−0.51 (<0.01)

−0.71 (<0.001)

−0.51 (<0.01)

−0.84 (<0.0001)

−0.55 (<0.001)

0.00 (1.00)

1.00 (–)

 

 Organic matter

0.63 (<0.0001)

0.68 (<0.0001)

0.53 (<0.001)

0.65 (<0.0001)

0.69 (<0.0001)

0.72 (<0.0001)

0.55 (<0.001)

−0.34 (0.04)

−0.48 (<0.01)

1.00 (–)

Pearson product–moment correlation coefficients (r) with p values in parentheses, significant correlations are set in italics (α = 0.05)

aNote all metals displayed significant positive correlation (p < 0.01) with one another in all samples from both lakes

3.5 Enrichment Factors

The EF calculations were used to quantify the difference between anthropogenic and natural metal concentrations in the cores. EFs calculated relative to the average crustal abundances for the Lake Pelham cores showed moderate enrichment of Pb and Zn, and significant enrichment of Cu since the 1980s (Table 1; Fig. 6). Relative to regional soils, EFs for Lake Pelham showed no enrichment in Pb and were slightly enriched in Zn in all the three cores. Cu enrichment was extreme in LP1, occurring at 14 cm and above, and significant in LP2 and LP3. The progressive increase in industrial development and population expansion in the region is likely the main source of metal enrichment in this reservoir. Between 2000 and 2007, Culpeper county had a population increase of 38.6 % and housing increase of ∼51 % in the same time frame (Demographic Analysis 2010). The sources of metals may include various auto industries, transportation equipment manufacturers, metal industries, pesticides from agriculture, as well as increased automotive traffic due to suburban population explosion in the region (Yesilonis et al. 2008).
Fig. 6

EF plots for Lake Moomaw and Lake Pelham. A hollow fill indicates pre-impoundment deposits, and a solid fill indicates post-impoundment deposits. The vertical lines correspond to varying levels of enrichment. EF <2 = enrichment deficient, 2–5 = moderate enrichment, 5–20 = significant enrichment, 20–40 = very high enrichment, >40 extreme enrichment (Mmolawa et al. 2011)

The Lake Moomaw EF estimates, relative to average crustal abundances, showed moderate enrichment of Cu with the exception of some spikes at the 10- to 12-cm depth in LM3 and 6- to 8-cm in LM2 (Fig. 6). The cores were significantly enriched in Pb and Zn, ranging from 4.95 to 10.44 for Pb and 5.47 to 7.59 for Zn in LM2 and LM3, respectively. The EFs, relative to regional geochemistry, showed very different results from the average crustal abundances. Pb was deficient in all three cores with EF values of 1.05–2.05. Zn EF values ranged from 0.58 to 4.59 and were deficient to slightly enriched in all three cores. Significant to very high enrichment was observed in the EF values of Cu in LM2 and LM3.

The concentrations of Pb and Zn in Lake Moomaw may be attributed to the second largest pulp and paper mill in Virginia emitting approximately 1,361 metric tonnes of Pb and Zn compounds into the air, causing wet deposition of metals in Lake Moomaw 30.6 km upstream. Lake Moomaw is located north of the pulp and paper mill, and therefore, northerly winds could subject the lake to atmospheric deposition of Pb and Zn. The atmospheric trace metals in Lake Moomaw may also be associated with its proximity to West Virginia, where coal mining processes and coal-fired power generation plants are common (US EPA 2010). The enrichment of Cu in Lake Moomaw may be attributed to any number of sources. Statistical analyses showed that surface concentrations of metals were not uniform spatially or temporally throughout the reservoir. These results may indicate that atmospheric deposition of metals is not the dominant source, because the distribution of metals is fairly heterogeneous. As there are no major industrial operations within the watershed, the Cu enrichment may be attributed to natural parent material sources. Natural sources such as local mineralized lithologic zones, forest fires, biogenic processes, and windborne soil particles may contribute to excess Cu concentrations (Weant 1985) and result in heterogeneous metal accumulation within lacustrine sediments.

3.6 Metal Accumulation Rates

Table 5 shows the metal accumulation rates for Lake Moomaw and Lake Pelham. The wider the range from background to maximum implies a greater flux of metals to the reservoir and thus a greater impact. Both Lakes Pelham and Moomaw show the greatest impact in Cu and Zn accumulation and less of an impact of Pb. The impact of Pb has decreased in recent times, probably due to the enactment of environmental regulations and the removal of leaded gasoline from the market (Griffin et al. 1989). Zn was also two to three times greater at the maximum concentration relative to the background in Lake Pelham sediments. In addition, the Lake Pelham cores are especially impacted by Cu, with the maximum concentrations between five and eight times greater than the background levels for all three cores.
Table 5

Metal accumulation rates (micrograms per square centimeter per year) for all cores

Core

Cu background

Cu maximum

Pb background

Pb maximum

Zn background

Zn maximum

Accumulation rate

LP1

22

163

9

13

33

68

0.343

LP2

27

167

8

13

29

86

0.692

LP3

21

101

7

10

36

61

0.486

LM1

0

24

5

13

3

43

0.604

LM2

10

50

5

8

28

45

0.335

LM3

12

91

6

12

29

66

0.402

The sources of trace metals tend to differ between relatively pristine and human-impacted watersheds. In forested watersheds with minimal human developments and lack of point source pollution, metal accumulation is associated with local geology, forest fires, or atmospheric deposition from outside sources (Weant 1985; Baron et al. 1986; Scudlark et al. 2005; Odhiambo et al. 2013). Our results suggest that enrichment of Pb and Zn in Lake Moomaw is likely from atmospheric deposition and Cu is likely derived from local mineralized parent materials. Similar observations have been made in other forested lakes of the eastern USA. Abernathy et al. (1984) showed the significance of atmospheric input to Fontana Lake (a forested mountain lake in North Carolina, USA) where the surface sediment concentrations of Cu, Zn, and Mn were found to be similar to areas receiving industrial pollution. High Cu values in their study were also attributed to local mineralized schists, which is a probable source of Cu to many forested lakes of the region. Wet and dry atmospheric deposition has also been observed in other locations of the eastern USA; for example, Dabous (2002) studied metal enrichment in a pristine lake in Florida, USA, and attributed metal enrichment to wet deposition in recharge areas coupled with an increase in sediment input to the lake from bedrock, soils, and surficial sand erosion. The dynamics of atmospheric deposition in remote mountainous landscapes was also detailed by Lovett and Kinsman (1990) who showed that atmospheric inputs are a major source of pollutants in high elevation ecosystems. Their analysis suggested that increases in atmospheric fluxes of Cd, Cu, Pb, and Zn were greatest at high elevations as a function of more precipitation, relative to adjacent lowlands.

Comparatively, the sources of metals in human-impacted reservoirs are diverse and can include waste effluents, fossil fuel combustion, mining activities, and fertilizers (Förstner and Wittmann 1979). There are many human-impacted reservoirs with metal concentrations comparable to those of our human-impacted watershed draining to Lake Pelham. Lake Anna in central Virginia serves as a cooling water supply for a nuclear power plant and has documented enrichment of Pb, Cu, Zn, and especially Cd in the lacustrine sediment attributed to old mine tailings in the basin and waste materials from the power plant (Odhiambo et al. 2013). The sediment of Lake Anna closest to the nuclear power plant has concentrations similar to the developed Lake Pelham basin with concentrations of Cu, Pb, and Zn at 42.6, 118.7 and 253.7 μg/g, respectively (see Table 1; Odhiambo et al. 2013). Elsewhere in the region, the major sources of metals in the Chesapeake Bay have been identified as point sources, storm-water runoff, and atmospheric deposition (Conko et al. 2004; Conrad et al. 2007; Hartwell and Hameedi 2007). According to Hartwell and Hameedi (2007), the trends of metal input to the Chesapeake Bay have been static or decreasing since 1986 following a peak in the 1970s. The modern sediment in the Bay is enriched by 1.5 to 3.5 times the background (natural) concentrations from pre-European settlement. Lake Pelham is likely subjected to metal fluxes from similar sources; however, contrary to regional trends our data indicate that the metal input has been increasing since the 1980s. In the Lake Pelham watershed, development has only recently occurred as the historically agricultural area has developed into a commuter-rich suburb of the greater Washington, DC region. Increased population growth may be contributing metals to the reservoir through fossil fuel combustion, abrasion of road surfaces, and degraded vehicle components (Conko et al. 2004) as commuter traffic has increased in the area. Comparatively, the sources of metals in the Lake Moomaw watershed are less obvious and are likely atmospheric or geochemical, reflecting the undeveloped, forested nature of the watershed.

4 Conclusions

The six sediment cores and 210Pb chronologies provided a framework for spatial and temporal analysis of variations in both sediment and trace metal fluxes in Lakes Pelham and Moomaw. The results imply that although Lake Moomaw is still largely undeveloped, the basin’s steep slopes coupled with highly erodible colluvial soils and the prevalence of shoreline erosion has resulted in lacustrine sediment accumulation rates comparable to the anthropogenically altered Lake Pelham. Most of the trace metals present in the sediments of Lake Moomaw may be attributed to watershed erosion on steep slopes, bank erosion, and local atmospheric deposition from nearby paper mill industries in the region as well as regional atmospheric sources such as West Virginia coal processing plants. The geomorphic configuration and characteristic valley-confined streams in the Lake Moomaw watershed makes the reservoir vulnerable to significant increases in sediment accumulation and metal concentrations, if road construction and urbanization were to occur in the basin. By contrast, Lake Pelham sediments show the impact of recent watershed urbanization, as reflected by the progressive increase in metal concentrations, sediment organic content, and sediment accumulation rates during modern time periods.

Notes

Acknowledgments

The authors would like to thank the University of Mary Washington for their financial support during the course of this project and Dr. L. Giancarlo, Sunnan Yoon, and Laura Pilati for their assistance in field sampling and laboratory analysis. The authors would also like to thank the two anonymous reviewers for their insightful suggestions on the earlier versions of this manuscript.

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Elyse V. Clark
    • 1
  • Ben K. Odhiambo
    • 2
  • Matthew C. Ricker
    • 3
  1. 1.Department of Crop and Soil Environmental SciencesVirginia Polytechnic Institute and State UniversityBlacksburgUSA
  2. 2.Department of Earth and Environmental SciencesUniversity of Mary WashingtonFredericksburgUSA
  3. 3.School of Forestry and Wildlife SciencesAuburn UniversityAuburnUSA

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