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Journal of Environmental Quality 32:325-334 (2003)
© 2003 American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America

TECHNICAL REPORTS
Waste Management

Patterns of Short-Term Sedimentation in a Freshwater Created Marsh

Sarah K. Harter and William J. Mitsch*

School of Natural Resources, The Ohio State University, 2021 Coffey Road, Columbus, OH 43210

* Corresponding author (Mitsch.1{at}osu.edu)

Received for publication September 17, 2001.

   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
This study investigated different sedimentation measurement techniques and examined patterns of short-term sedimentation in two 1-ha replicate created freshwater marshes in central Ohio, USA. Short-term (one-year) sediment accumulation above feldspar, clay, glitter, and sand artificial marker horizons was compared at different water depths and distances from wetland inflow. A sediment budget was also constructed from turbidity and suspended sediment data for comparison with marker horizons. Glitter and sand marker horizons were the most successful for measuring sediment accumulation (81–100% marker recovery), while clay markers were completely unsuccessful. The sedimentation rate for both wetlands averaged 4.9 cm yr-1 (36 kg m-2 yr-1), and ranged from 1.82 to 9.23 cm yr-1 (12.4 to 69.7 kg m-2 yr-1). Sedimentation rates in deep, open water areas were significantly higher than in shallow, vegetated areas for both wetlands (t test, p < 0.05). However, observed sedimentation patterns may be attributed more to preferential flow through open water areas than to water depth or presence of vegetation. Contrary to the expected spatial distribution, sedimentation was highly variable within the wetlands, suggesting that bioturbation and turbulence may cause significant resuspension or that high hydrologic loads may distribute sediments throughout the basins. A sediment budget estimated sediment retention of approximately 740 g m-2 yr-1 per wetland (43% removal rate), yet gross sediment accumulation was 36 000 g m-2 yr-1 measured by marker horizons. These results suggest that erosive forces may have influenced sedimentation, but also may indicate problems with the sediment budget calculation methodology.

Abbreviations: ORWRP, Olentangy River Wetland Research Park • TSS, total suspended solids


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
SEDIMENTARY PROCESSES within wetlands are intimately connected with many wetland functions, the most important effect of which is their influence on water quality (Johnston, 1991; Gilliam, 1994; Mitsch and Gosselink, 2000). Since wetlands function as sources, sinks, and transformers of materials, they have the potential to positively or negatively affect water quality by trapping or transporting excess nutrients, harmful chemicals, and other high material loads. Low water velocities cause wetlands to act as depositional environments for sediments suspended in water, and thus for nutrients and other chemicals sorbed to sediments (Phillips, 1989).

Much of the existing sedimentation research comes from work in coastal marshes and river deltas and examines the relationship between marsh or land accretion and coastal subsidence (Cahoon and Turner, 1989; Knaus and Van Gent, 1989; Cahoon, 1994; Roman et al., 1997; Reed et al., 1997; Hensel et al., 1999; Day et al., 1999; Yang, 1999). This research has generated most of the current knowledge of wetland sedimentary processes and sediment measurement techniques.

A much smaller proportion of sedimentation research has focused on freshwater wetlands. The focus and outcome of many of these sedimentation studies has been to demonstrate that freshwater wetlands are highly effective in nutrient retention, especially as phosphorus sinks (Mitsch et al., 1977, 1979a,b; Craft and Richardson, 1993; Meeker, 1996). Other studies have examined the physical factors that affect sedimentation in freshwater systems (Kadlec and Robbins, 1984; Hupp and Blazemore, 1993; Kleiss, 1996; Wardrop and Brooks, 1998; Braskerud et al., 2000; Braskerud, 2001). These studies have recognized the importance of factors such as basin morphology, hydrology, and biota, but further research is needed to determine how these factors interact together to influence sediment dynamics at the ecosystem level. Only very limited research has been done to date that examines sedimentation in created freshwater wetlands (Brueske and Barrett, 1994; Fennessy et al., 1994; Braskerud et al., 2000; Braskerud, 2001). More in-depth knowledge of sedimentary processes in freshwater wetlands is needed for not only answering questions of basic wetland science, but also for practical applications as more natural and created freshwater wetlands come into use for water quality improvement. Understanding freshwater wetland sedimentary processes gives insight into the complexity of organic and inorganic matter cycles, improves created wetland design, and refines predictions about the functional lifetime of these systems.

The goals of this study were to (i) describe the patterns of short-term (one-year) sedimentation in created freshwater wetlands and (ii) investigate different methods that can be used to measure sedimentation processes in created freshwater wetlands.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Site Description
The Olentangy River Wetland Research Park (ORWRP) is a 10-ha experimental wetland facility located north of The Ohio State University in Columbus, OH. (See the cover photo of the July–August 2001 issue of JEQ for an illustration of the study site.) The experimental wetland basins at the ORWRP used in this study are two identical 1-ha freshwater marshes that were constructed in 1994. River water is pumped almost continuously from the adjacent Olentangy River into the 1-ha basins, flows naturally through the basins, exits the two wetlands through weirs, and finally discharges back into the Olentangy River. The two experimental wetland basins offer a unique setting for studying sedimentary processes because the hydrology of the basins is controlled, which allows for an enhanced understanding of sediment flux.

Both experimental wetland basins are composed of three basic habitat zones: shallow areas, deepwater areas, and a mudflat area. The shallow zones occupy approximately 65% of each wetland basin, the deepwater areas occupy approximately 25%, and the mudflat zone occupies approximately 10% of each basin. Water depths in the mudflat zones are typically 0 to 0.3 m, shallow zones are 0.15 to 0.4 m, and depths in the deepwater areas are approximately 0.4 to 0.8 m. The wetlands are perched above the local ground water and cause a slight mounding in ground water beneath the wetlands. Studies published on the experimental wetlands include those on aquatic system modelling (Metzker and Mitsch, 1997), algal dynamics (Wu and Mitsch, 1998), the planting experiment (Mitsch et al., 1998), hydrology (Koreny et al., 1999), water quality (Kang et al., 1998; Nairn and Mitsch, 2000; Spieles and Mitsch, 2000a), and benthic macroinvertebrates (Spieles and Mitsch, 2000b).

In the overall experiment, Wetland 1 was planted with macrophytes in 1994 while Wetland 2 was left as an unplanted control. Since that time the two basins converged in function and have become similar in terms of their vegetative cover (Mitsch et al., 1998), so in this study we treat the basins as replicates. Wetland 1 had a 39% vegetation cover in 1996, which increased to 54% in 1997, and Wetland 2 had a 35% vegetation cover in 1996, which increased to 58% in 1997 (Mitsch et al., 1998). These figures do not include algal cover, which is also similar between the two basins. Dominant species in the two wetlands during the study period were soft-stem bulrush [Schoenoplectus tabernaemontani (Gmel.), also known as Scirpus validus (Vahl.)] and cattail (Typha spp.). Most of the total vegetation cover for the two wetlands is located in the mudflat and shallow zones, while the deep areas support little or no vascular vegetation (Fig. 1) .



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  		Fig. 1. Location of horizon marker sites and bulk density–organic matter sampling plots in the experimental wetland basins. Locations of horizon marker plots are indicated with numbers. Bulk density and organic matter sampling plots are indicated by letters. Emergent vegetation cover based on 1997 aerial photos is represented by shaded areas. The spheres in the interior of the basins indicate approximate locations of deep areas. The dashed areas indicate approximate mudflat zones.

 
The wetland basins remained flooded for the majority of the study. Pumping rates were adjusted two to three times weekly according to the flow of the adjacent Olentangy River to create a more natural wetland hydroperiod. Pumped inflow to the two wetlands averaged 36.3 and 37.0 m yr-1, and outflow averaged between 26.1 and 27.8 m yr-1 during the study period (Wang et al., 1998). The average daily inflow hydraulic loading rate for the two wetlands was approximately 10 cm d-1 and the average daily outflow rate was approximately 7 cm d-1 for the two wetlands.

Marker Horizon Installation
Sixteen sedimentation sites were chosen per wetland basin in July 1996 (Fig. 1). Sites were arranged in the same pattern in each basin, and site location was based on three criteria: distance from the inflow, water depth, and accessibility from the boardwalk. A larger proportion of the sites were concentrated in the area nearest the inflow since it was anticipated that the greatest sedimentation rates would occur in this area. Sites were divided between deep areas (Sites 1, 2, 3, 4, 6, 7, 11, 12, 15, and 16 on Fig. 1) and shallow areas (Sites 5, 8, 9, 10, 13, and 14 on Fig. 1) of each basin. No sites were located in the mudflat areas. At the time of core sample collection, all of the shallow sites were moderately to densely vegetated, while deep sites were in open water areas that contained no vegetation, with the exception of algal mats. At each site a permanent support structure was constructed before the marker horizons were installed. This structure enabled a portable plank to be used for core sampling from above the wetland surface without disturbance of the surrounding sediments (Fig. 2) .



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  		Fig. 2. Horizon marker station showing (a) the four marker materials immediately after installation and prior to flooding and (b) layout of the artificial soil horizon markers at each station within the experimental wetland basins. The orientation of the markers within the grid remains the same at each site when viewed from the boardwalk 2.4 m away.

 
Four 0.25-m2 plots, each consisting of either glitter, feldspar, kaolinite clay, or silica sand were arranged together in a 1-m2 grid at each site (Fig. 2). The four marker types were arranged in the same pattern in each plot relative to the boardwalk. Feldspar, clay, and sand were applied to the sediment surface in a nearly uniform 1-cm layer. Glitter was distributed in a thin layer until the sediment surface was completely covered.

Core Retrieval
Core samples were removed from each 0.25-m2 plot approximately one year after the marker horizons were installed. During July and August 1997, core samples were collected from each marker plot with a cryogenic coring device (Cahoon et al., 1996).

Core locations were randomly chosen within each 0.25-m2 plot. Cores were collected to a depth that allowed a visible marker horizon layer to be obtained until two successful cores were retrieved. If two successful cores were not retrieved from a marker plot, that particular plot was disregarded from further analysis.

Sediment accumulation depth data were converted to sedimentation rates by estimating the bulk density of the sedimented material. The cryogenic coring device was also used to collect sediment samples for measuring bulk density according to the method of Knaus and Cahoon (1990). Three replicate bulk density samples were collected in seven locations throughout Wetland 1, and six locations throughout Wetland 2 (Fig. 1). In the laboratory the frozen cores were cut into segments comprising the top 5 cm of the surface sediment. Bulk density was estimated by drying the samples at 105°C until constant weight (Parent and Caron, 1993). Percent organic matter of the bulk density samples was also estimated by ashing 2 g of each sample at 600°C for 6 h (Goldin, 1987). A summary of the bulk density and organic matter content analysis data is given in Table 1.


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  		Table 1. Organic matter content and bulk density (average ± standard error) for sampling plots within the experimental wetlands. See Fig. 1 for location of sampling plots.

 
Sediment Budget
A statistical relationship between total suspended solids (TSS) and turbidity was determined for water samples from the wetland basins. Water samples were collected at various times throughout 1997 and early 1998 from the inflow and outflow of both wetland basins. Water samples were divided for separate turbidity and total suspended solids analysis. Turbidity of the water samples was measured in the laboratory with a Hach (Loveland, CO) turbidimeter. Total suspended solids analysis was performed with a gravimetric procedure (American Public Health Association, 1998). Regression analysis was used to determine the statistical relationship between TSS and turbidity. Estimated total flux of sediments to and from the basins was then determined with the TSS–turbidity relationship and daily turbidity and flow data collected concurrently during the marker horizon study. The percent retention calculated by this method was compared with the sedimentation rate measured by the marker horizons.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
Sediment Accumulation Rates
Overall, 53% of the individual cores that were collected recovered a visible marker layer. Unsuccessful cores resulted either from a missing marker layer or from loss of the core during freezing or retrieval from the sediment surface. Glitter marker plots had the highest retrieval success of the four marker types, with 81% success in Wetland 1 and 100% success in Wetland 2 (Table 2). Core retrieval success was 81% for the sand marker plots in both wetlands. Feldspar marker plots were moderately successful, as a distinct feldspar layer was recovered in only 31% of Wetland 1 plots and 50% of Wetland 2 plots. No visible clay markers were retrieved in any of the marker plots.


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  		Table 2. Summary of sediment accretion rates and mass accumulation rates (average ± standard error).

 
In general, all marker types produced similar estimations of sediment accretion rates. Significant differences between marker types were detected within only 4 of the 27 plots in which more than one marker type was recovered (one-way analysis of variance; p < 0.05). Because differences between accretion rates were small among marker types and followed no consistent pattern, data from each marker type were treated as replicates for the plot in further analyses.

The average sedimentation rate for both experimental wetland basins, calculated with data combined from all plots, was 4.90 cm yr-1 (36.3 kg m-2 yr-1) with values ranging from 1.82 to 9.23 cm yr-1 (12.4 to 69.7 kg m-2 yr-1) (Table 2). The mean sedimentation rates for deep and shallow plots were 6.15 and 3.61 cm yr-1 (26.5 and 39.8 kg m-2 yr-1) in Wetland 1 and 5.05 and 4.29 cm yr-1 (32.4 and 40.9 kg m-2 yr-1) in Wetland 2 (Fig. 3) . No significant difference in sedimentation rate was detected between the two wetland basins (two-sided t test, p > 0.05). This is consistent with measurements taken at the same time in each wetland for aboveground net primary productivity of emergent macrophytes. The macrophyte productivity in each basin was not significantly different from the other basin (p > 0.05). A comparison of deep and shallow plots showed that sedimentation rates in deep areas were significantly higher than in shallow areas for both wetland basins (one-sided t test, p < 0.05) (Fig. 3).



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  		Fig. 3. Comparison of average sedimentation rates (cm yr-1) between deep and shallow plots for Wetlands 1 and 2. Error bars indicate standard error. Differences in letters above the bars indicate significant differences between plots within each wetland.

 
Figure 4 shows the relationship between sedimentation rate and distance from the inflow for the two wetland basins. The distribution of sediment accumulation in the two basins was highly variable. In Wetland 1, sedimentation rates generally decreased with distance from the inflow in both deep and shallow portions of the basin. The pattern of sedimentation in Wetland 2 differed from that of Wetland 1. In the deep areas of Wetland 2, sedimentation rates first decreased with distance from the inflow and then increased with distance (>25 m) from the inflow. In the shallow areas, average sedimentation rates increased slightly and then decreased near the outflow. The highest sediment accumulation measured in Wetland 2 occurred in the deep plots located nearest the outflow.



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  		Fig. 4. Average sedimentation rates (cm yr-1) with increasing distance from the inflow for (a) deep and (b) shallow areas of Wetland 1, and (c) deep and (d) shallow areas of Wetland 2. Error bars indicate standard error.

 
Wetland Sediment Budget
A significant positive relationship was found between TSS concentration and turbidity of the wetland water samples. However, a plot of the data suggested that the relationship between TSS and turbidity was better described by splitting the data into two separate plots above and below 100 NTU turbidity. Linear regression produced a strong correlation between TSS and turbidity for samples with turbidities greater than 100 NTU (Fig. 5) . Variability of the data points below 100 NTU turbidity was much greater than that of the high-turbidity samples. A power regression produced the strongest correlation between TSS and turbidity at turbidities less than 100 NTU (Fig. 5). Predicted TSS concentrations were not significantly different from measured TSS concentrations for either of the regression equations (paired t test, p > 0.05).



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  		Fig. 5. Regression of total suspended solids (mg L-1) and turbidity (NTU) for samples (a) above 100 NTU (n = 23), and (b) below 100 NTU (n = 51).

 
Summary data used to calculate the wetland sediment budget are given in Table 3. The hydrologic load for both wetlands was similar, with inflow approximately 10 cm d-1 and outflow approximately 7 cm d-1 for both basins during the study period. Flow-weighted average turbidity for both wetlands was 34 NTU in the inflow and approximately 30 NTU in the outflow. Conversion of turbidity to TSS with the equations described in Fig. 5 resulted in flow-weighted average TSS of 47 g m-3 in the inflow and 35 to 38 g m-3 in the outflow of Wetlands 1 and 2, respectively.


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  		Table 3. Summary of data used to calculate sediment budget. Values are averages ± standard deviation; the number of samples or readings is listed in parentheses.

 
Estimates of wetland sediment flux based on the TSS–turbidity relationship and daily turbidity and flow data were much lower than those suggested by core samples. The total inflow sediment load was calculated as 1707 g m-2 yr-1 for Wetland 1 and 1740 g m-2 yr-1 for Wetland 2 (Table 3). An estimated 735 g m-2 yr-1 of sediment were retained in Wetland 1 and 747 g m-2 yr-1 in Wetland 2. Each wetland retained 43% of the sediments that entered it.


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
Spatial Distribution of Sedimentation
Most wetlands receiving surface inflow from adjacent rivers or tidal creeks display distinct spatial patterns of sedimentation because of the settling properties of suspended sediments. Greatest sediment accumulation usually occurs near the inflow source, with sedimentation rates decreasing rapidly with distance from the sediment source (Brueske and Barrett, 1994; Cahoon, 1994; French et al., 1995; Reed et al., 1997). However, the spatial distribution of sedimentation in the wetland system in this study was highly variable. Although Wetland 1 generally demonstrated the expected pattern of decreasing sedimentation rates with increasing distance from the inflow, results from Wetland 2 showed the opposite pattern. Sediment accumulation rates increased toward the outflow of Wetland 2 and were as high or higher than rates seen near the inflow. Fennessy et al. (1994) also observed spatial variability in sedimentation rates in a similar experimental wetland system and attributed erratic sediment distributions in that study to flow channelization. If the dominant factor affecting sedimentation in this system was its role as a low-velocity environment compared with inflow water, then we would expect the spatial pattern seen in Wetland 1 to be more pronounced and we would also expect Wetland 2 to exhibit the same spatial distribution as Wetland 1. The spatial variability in sedimentation between the two wetlands indicates that other factors are influencing sedimentation in this system. The variability between the two basins cannot be explained by differences in hydrology or vegetation, as both experienced the same hydrologic conditions during the study period and both had similar vegetative cover (Mitsch, unpublished data, 2002).

Bioturbation
Bioturbation may have played a role in the observed variability of sediment distribution. Benthic fish species, including carp, are known for causing sediment resuspension and for maintaining increased levels of turbidity in wetlands (Wilcox and Hornbach, 1991; Breukelaar et al., 1994; Cline et al., 1994). During the study period, both wetlands supported small populations (10–20 individuals) of large-sized common carp (personal observation) and also contained active muskrat huts (Svengsouk et al., 1997). During a drawdown at the end of the study period it was observed that one of the sedimentation plots in Wetland 1 was partially destroyed by a muskrat path that had been scoured into it, and carp in both basins were observed stirring up the sediments during low-flow periods. Metzker and Mitsch (1997) closely linked turbidity in the system with carp biomass in a simulation model of the aquatic community in the ORWRP. Results of their model predicted a steady state fish community in the wetlands dominated by carp. Significant carp and muskrat activity in the wetlands suggests that bioturbation indeed caused resuspension of the sediments, and therefore could have influenced the observed depositional patterns.

Hydrologic Loading
Ulbrich et al. (1997) found that hydrologic load can also influence the spatial distribution of sediments within a wetland. The authors' spatial sedimentation model showed that wetlands with lower retention times had a more even spatial distribution of sediments throughout the entire basin. Conversely, wetlands with high hydrologic retention tended to have concentrated sediment deposition near the inflow. The experimental wetland basins at ORWRP experienced a relatively high hydrologic load during the study period. Hydrologic retention in the experimental wetland basins at the ORWRP averaged only 2.1 d for the study period. This relatively low hydrologic residence time for the wetlands helps to explain the low sediment retention observed (42%) during this study. Hey et al. (1994) found much higher sediment retention (76–99%) in a similar experimental wetland system in Illinois that experienced an average hydrologic residence time of 11 d. The high hydrologic load probably caused sedimentation to occur more evenly throughout the wetland basins, and thus accounts for much of the variability in sediment distribution observed in the wetlands in this study. We would expect the observed sedimentation pattern to change and sediment removal efficiencies to improve if hydrologic loads were decreased significantly.

Effect of Water Depth and Vegetation
Most of the shallow plots in this study were moderately to densely vegetated with emergent macrophytes, whereas none of the deepwater plots contained emergent vegetation. Deep, open water areas had higher sedimentation rates than shallow, vegetated areas in the two wetlands. This result contradicts the findings of studies that have shown vegetated areas to enhance sedimentation in wetlands (Carpenter and Lodge, 1986; Dieter, 1990; Braskerud, 2001). Braskerud (2001) argued that enhanced sedimentation rates in vegetated areas may be more due to the vegetation mitigating resuspension rather than increasing sedimentation. However, our results are consistent with studies of other freshwater wetlands that found higher sedimentation rates in open water areas (Brueske and Barrett, 1994; Fennessy et al., 1994; Meeker, 1996). Fennessy et al. (1994) attributed the higher rates to preferential flow through open water areas and to greater insulation from resuspension. Preferential flow probably occurred in the two experimental wetlands at the ORWRP as dense macrophyte growth covered a majority of the shallow portion of each basin, leaving a relatively unobstructed flow path in the deepwater areas in the middle of each basin. The effect of flow channelization on sedimentation could have been further compounded by the high hydrologic loading to the wetlands.

Methodology Issues
Overall, artificial marker horizons proved to be a useful technique for measuring short-term sedimentation in created freshwater wetlands. Recovery rates for glitter and sand in this study were comparable with the 91 to 100% recovery rates seen in other studies that have successfully used marker horizons to measure sedimentation (French and Spencer, 1993; Cahoon et al., 1995). While glitter markers demonstrated the highest marker recovery, glitter layers were less distinct than sand and feldspar layers as glitter specks were often scattered vertically within the sediment column. Measurement from the glitter layer was therefore more subjective than with other marker types since it was necessary to estimate the most concentrated zone of glitter to measure the sediment depth. Most sand plots produced cores with a visually distinct marker layer; also the textural contrast between sand markers, the clay substrate, and silty sediment helped to distinguish the sand layer. Sand was also a more economical choice of marker material in comparison with glitter. Although retrieval success of the feldspar marker was much lower than that of either glitter or sand, feldspar produced the most distinct marker layer of any marker type because of the stark color contrast between the white feldspar and brownish substrate. The absence of any visible clay markers suggests clay markers are not well suited for freshwater systems, especially those perched on clayey substrates. The marker color and texture may have blended with the clayey substrate or the marker material may have even dissolved in the water column.

The sediment budget estimated that far fewer sediments entered the wetland through the inflow than could account for the high sediment accumulation measured in the core samples. The sediment budget constructed from the TSS–turbidity relationship and turbidity and flow data estimated average accumulation rates of approximately 740 g m-2 yr-1 for each wetland. However, mass accumulation data from the core samples were approximately 48 times higher than the accumulation rates predicted by the sediment budget calculation in both wetlands (Fig. 6) . The discrepancies between the sediment budget and the marker horizon results raise several interesting questions about the sedimentary processes occurring within the wetlands and the methodology used in this study. If our methodological approach is correct, comparison of the sediment budget with the observed sedimentation rate suggests that other sources of sediment inflow, such as overland flow during flood events, could have entered the wetlands. However, this explanation is unlikely as only one minor flood event occurred during the study period, causing a minimum of river flow into only Wetland 1 (Wang et al., 1998). Sediments may also have entered the wetlands from slope erosion of the basin edges. However, contribution from slope erosion was probably not significant, as there is a small swale around Wetland 1 specifically constructed to prevent runoff from entering into the basin and only minor erosion was observed around the edges of both basins during the study period.



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  		Fig. 6. Summary of sediment fluxes measured in this study. All values are estimated as occurring over one year and were similar for both wetlands. Note the high rates of sedimentation and hence by definition resuspension compared with rates of inflow and outflow of sediments.

 
Erosion and resuspension of the existing sediment surface could also have contributed significantly to the observed sedimentation rates. Resuspension of surface sediments through bioturbation has already been suggested as contributing to the observed spatial pattern of sedimentation in the two wetlands. Resuspension of surface sediments during windy days has also been observed at the wetlands countless times. One of the possible disadvantages of the marker horizon technique is that it can only account for resuspension of the sediments to the point where the artificial marker layer was placed on the substrate surface. Any further resuspension erodes the marker layer and destroys the reference point. As Cahoon et al. (1995) point out, marker horizons are inherently biased toward measuring accretion rates while excluding eroded surfaces because those markers are lost. The high retrieval success for glitter and sand markers in this study does not support the idea that erosion played an overwhelming role in the observed sedimentation rates. If erosion were a significant factor in loss of markers, we would expect to see consistent marker loss across all marker types. The complete loss of clay markers, and to a lesser extent feldspar, indicates more of a problem with the marker material itself than with erosion. Thus it does not seem feasible that erosion and resuspension of sediments could fully account for the difference seen between the sediment budget and marker horizon study.

Errors in the methodology used to calculate the sediment budget and mass accumulation rates provide a more realistic explanation for the large difference in sediment budget and mass accumulation results. It is probable that wetland sediment loads were underestimated by the TSS–turbidity equation given the relatively low r2 value of the equation for turbidities less than 100 NTU. The variability in the data at this turbidity range is of particular concern since most of the turbidity data collected from the wetlands during the study fell within this range. Future studies would benefit from a more detailed sediment budget analysis.


   ACKNOWLEDGMENTS
 
The authors wish to thank Don Cahoon and Jim Lynch of the U.S. Geological Survey in Lafayette, Louisiana for use of their cryocorer and for technical advice. Funding for this research was provided in part by a Student Research Grant from the Society of Wetland Scientists. Olentangy River Wetland Research Publication 03-001.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 




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Journal of Natural Resources
and Life Sciences Education		 Vadose Zone Journal
Soil Science Society of America Journal Journal of Plant Registrations The Plant Genome