Published in Soil Sci. Soc. Am. J. 68:1461-1469 (2004).
© 2004 Soil Science Society of America
677 S. Segoe Rd., Madison, WI 53711 USA
DIVISION S-10—WETLAND SOILS
Calibrating Hydric Soil Field Indicators to Long-Term Wetland Hydrology
M. J. Vepraskasa,*,
X. Hea,
D. L. Lindboa and
R. W. Skaggsb
a Dep. of Soil Science, Box 7619, North Carolina State Univ., Raleigh, NC 27695
b Dep. of Biological and Agricultural Engineering, Box 7625, North Carolina State Univ., Raleigh, NC 27695
* Corresponding author (michael_vepraskas{at}ncsu.edu).
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ABSTRACT
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Jurisdictional wetlands are required to be saturated to the surface for 5% or more of the growing season in 5 out of 10 yr, but practical field methods for confirming this are lacking. This study determined whether hydric soil field indicators were related to wetland hydrology requirements. Water table levels were monitored daily for 2.5 yr in a toposequence of nine soil plots that included well to poorly drained members (Oxyaquic Paleudults and Typic Albaqualfs). Monitoring data were used to calibrate a hydrologic model that simulated water table levels from inputs of hourly rainfall data. Forty years of rainfall data were then used with the model to compute long-term daily water-table levels in each plot. These data were summarized as "saturation events", which are the frequency that water tables were at or above preselected depths for at least 21 d. Twenty-one days was the average period needed for Fe reduction to begin in these saturated soils. This condition must occur for hydric soil field indicators to form. Regression equations were developed to relate saturation events to percentages of redoximorphic features. The r2 values for relationships between percentages of redoximorphic features and saturation events were >0.80 for depths of 15 cm, and >0.90 for depths between 30 and 90 cm. Results showed that the depleted matrix field indicator, in which redox depletions occupy >60% of the horizon, occurred in soils that were saturated for 21 d or longer at least 9 yr out of 10. This indicated the depleted matrix indicator occurred in soils that were saturated nearly twice as long, and more frequently, than the minimum requirements needed to meet wetland hydrology requirements.
Abbreviations: LDS, longest duration of a single period of saturation (in days) during the period of interest • NPS, number of times the soil was saturated for periods lasting 21 d or longer during the period of interest • NSE, number of saturation events
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INTRODUCTION
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SECTION 404 OF THE CLEAN WATER ACT requires that dredge or fill material not be discharged into waters of the USA, including regulated wetlands, unless the action is permitted by the U.S. Army Corps of Engineers (National Research Council, 1995). As part of the permitting process, the boundaries of jurisdictional wetlands must be delineated on the basis of three parameters: (i) hydrophytic vegetation, (ii) wetland hydrology, and (iii) hydric soils (Environmental Laboratory, 1987). Hydrophytic vegetation is adapted to saturated anaerobic soil conditions. Wetland hydrology requires that an area be inundated or saturated to the surface for at least 5% of the growing season with a frequency of at least 5 yr in 10. Hydric soils are those that formed under conditions of saturation, flooding, or ponding long enough during the growing season to develop anaerobic conditions in the upper part (Federal Register, 1994).
Jurisdictional wetland boundaries are placed around areas that meet the three parameters. Evidence of each parameter must be present for an area to be considered a jurisdictional wetland. Lists of plant species that occur in wetlands are available for use in wetland identification (Reed, 1988). Hydric soils are commonly identified by looking for field indicators, generally layers of soil with specific color patterns, which have been identified for most areas of the USA (USDA-NRCS, 2002).
Wetland hydrology is defined as periodic inundation or saturation to the surface for at least 5% of the growing season (Environmental Laboratory, 1987). Areas that are saturated for at least 12.5% of the growing season will usually be in a jurisdictional wetland. In cases where areas are saturated for between 5 to 12.5% of the growing season the area may or may not be within a jurisdictional wetland depending upon whether the area contains hydric soils and hydrophytic vegetation. These durations of saturation should represent average conditions, which are assumed to recur with a frequency of at least 5 out of 10 yr (Williams, 1992; National Research Council, 1995). Soils meeting the requirements for wetland hydrology are identified in the field using primary or secondary indicators (Environmental Laboratory, 1987). Primary indicators are direct evidence of saturation. For soils affected by shallow ground water, the sole primary indicator of hydrology is direct observation of the water table within 30 cm of the surface (Environmental Laboratory, 1987). This is an impractical indicator in most cases unless one happens to be at the site at the time water tables are high. Two secondary indicators of hydrology can be substituted for a single primary indicator of hydrology. Secondary indicators of hydrology for areas affected by shallow ground water include oxidized rhizospheres (Fe oxide accumulations around channels containing live roots), soil survey data on water tables, or measurements of the abundance of certain plants (National Research Council, 1995). Wetland regulators assume that the presence of these primary and secondary indicators of hydrology show that the area meets the duration and frequency requirements for saturation specified for wetland hydrology, but this has not been verified to our knowledge.
Frequency and duration of saturation in soil horizons can be determined with long-term (>15 yr) monitoring of water table levels. This is expensive as well as time-consuming, and is impractical for general use because landowners as well as regulators usually want land assessments completed in <6 mo. Simulation modeling can be used instead to produce faster results at individual sites, although it too can be expensive because the models are site-specific once calibrated using time-consuming measurements of pore-size distribution, particle-size distribution, saturated hydraulic conductivity, and precipitation, as well as water table measurements.
A more practical approach for determining saturation frequency and duration for individual horizons is to use a calibrated simulation model along with historic rainfall data to compute daily water table levels over long (i.e., 40 yr) periods of time in common soils for a region. The saturation data can then be correlated to the abundance of redoximorphic features that form in similar soils of the area. This process would correlate the features, and hydric soil field indicators they comprise, to saturation frequencies and durations. Once this has been achieved, a wetland delineator could predict the saturation frequency and duration in similar soils by simply measuring the percentage of redoximorphic features at a certain depth. Thus, correlating features to simulation results provides an inexpensive way to extrapolate the results of simulation models to similar soils.
Daniels et al. (1971) used a statistical modeling method to compute water table levels for Paleudults and Paleaquults and showed that soil colors could be related to the proportion of time soil horizons were saturated. Simonson and Boersma (1972) related a long-term record of saturation to soil color patterns. While they showed general relationships occurred, no specific correlation was completed between saturation frequency and color because they did not quantify color abundance. Additional studies have related soil morphology to water table fluctuations (e.g., Pickering and Veneman, 1984; Evans and Franzmeier, 1986; Khan and Fenton, 1994; Thompson et al., 1998; Veneman et al., 1998), but none of these has developed quantitative relationships between soil color patterns and long-term saturation frequency and duration since the work of Daniels et al. (1971) or Simonson and Boersma (1972) to our knowledge.
He et al. (2002)(2003) extended the work of Daniels et al. (1971) and Simonson and Boersma (1972) by quantifying both saturation duration and the abundance of redoximorphic features. Saturation durations were simulated over a 40-yr period using a calibrated hydrologic model and historic rainfall data. Saturation frequency was estimated by computing the probability that a soil horizon would saturate for 21 d or longer. These probability values were then correlated with the percentage of redox depletions and also the percentage of redox concentrations in these soils. This work showed that there was a linear relationship between percentage of redoximorphic features and average number of saturation events per year, but relationships differed by depth. To produce a certain percentage of redox depletions for example required fewer saturation events at 45 cm than at 90 cm.
He et al. (2002)(2003) showed that results of simulation modeling could be correlated with percentages of redoximorphic features for a single toposequence of soils in the fine-loamy particle-size class. The objective of this investigation was to determine if the method developed by He et al. (2002)(2003) could be used at a different site to relate hydric soil field indicators to long-term wetland hydrology.
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MATERIALS AND METHODS
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The site selected for this study was located at Bertie County, NC at N 76° 48' 00'', W 36° 5' 30''. The toposequence on the site includes the well-drained Noboco series (fine-loamy, siliceous, subactive, thermic Oxyaquic Paleudults), moderately well-drained Goldsboro series (fine-loamy, siliceous, subactive, thermic Aquic Paleudults), somewhat poorly drained Lenoir series (fine, mixed, semiactive, thermic Aeric Paleaquults) and poorly drained Leaf series (fine, mixed, active, thermic Typic Albaquults). The vegetation on the site was forest consisting of loblolly pine (Pinus taeda L.), red maple (Acer rubrum L.), sweet bay (Magnolia virginiana L.), white oak (Quercus alba L.), red oak (Quercus borealis L.), and black cherry (Padus serotona L.). Two transects were established on the site with each having five plots, with one plot in the Noboco soil being shared by both transects (Fig. 1).
The methods used for this study were the same as those described by He et al. (2002)(2003) and only a summary will be provided here. Water table levels were monitored daily to depths of 2-m in each of the plots using electronic recording wells (Remote Data Systems, Inc., Wilmington, NC). The water table data were collected from May 1998 to October 2000. To ensure that the recording wells were monitoring daily water levels accurately, a manual check well was installed at each plot to a depth of approximately 127 cm below the mineral soil surface. Every 2 to 3 wk the check wells were measured to compare with the water table data from the recording wells. Rainfall was also measured daily at each site using recording gauges.
Soil profiles were described from pits placed in each plot at the site. Pits (1.5 by 1.5 by 1.0 m) were dug within 10 m of each plot to identify and describe soil horizons and the redoximorphic features without affecting the hydrology near the well. The abundance and size of redoximorphic features were estimated visually by comparing the features with proportion charts by two persons separately (Schoeneberger et al., 1998). The results from both descriptions were averaged for each 15-cm-depth increment in each plot.
Soil samples were taken in each horizon to determine the particle-size distribution, water characteristic, and saturated hydraulic conductivity. In situ lateral saturated hydraulic conductivity was measured at each plot using Compact Constant Head Permeameter (Amoozegar, 1992). Data were reported previously by He et al. (2002).
Redox Potentials, Soil pH, and Soil Temperature
Five platinum electrodes were inserted at each of the following depths—15, 30, and 60 cm—in each plot to measure oxidation–reduction (redox) potential. Field voltage was measured weekly at each depth in each plot using an Accumet 1002 pH/mV meter (Fisher Scientific Co., Pittsburgh, PA) and a Ag/AgCl reference electrode (Jensen Instruments, Tacoma, WA). Salt bridges were used to make electrical contact between the reference electrode and the soil solution (Pickering and Veneman, 1983). To interpret redox potentials all the field readings were converted to EH values (standard H electrode potential) by adding a temperature-dependent conversion factor to the voltages measured in the field (Patrick et al., 1996). In the summer of every year all the electrodes were removed from the soils. The platinum tips were cleaned, and the electrodes were tested for accuracy with a redox buffer and water. The EH measurements were made weekly for 2.5 yr.
Soil pH values at depths of 15, 30, and 60 cm were also measured on soil slurries (1:1 soil/ water ratio) in each plot twice per year (when saturated and unsaturated) from 1998 to 1999. Soil pH was read using the same Accumet 1002 pH/mV meter and a glass pH electrode. Soil temperature was measured weekly with thermocouples at depths of 15, 30, and 60 cm of each plot for the 2.5-yr duration of the study.
Iron reduction must occur for low chroma colors or redox depletions to develop in a saturated soil (Vepraskas, 1996). The beginning of Fe reduction was determined from redox potentials (EH) using a threshold EH value for the reduction of Fe3+ in the mineral Fe(OH)3 that can be computed from (Vepraskas and Faulkner, 2001):
 | [1] |
The pH values determined for each plot were used for the estimation of EH(Fe2+). Average soil pH values at depths of 15, 30, and 60 cm ranged from 3.8 to 4.9 across all soil plots.
Hydrologic Simulation
A hydrological model, DRAINMOD (Skaggs, 1978), was calibrated for each plot using the measured well data and the process that was outlined by He et al. (2002). Following calibration, the simulated water levels differed from measured water table levels by an average of <20 cm over a 2.5-yr period of calibration. Long-term (40 yr) historic hourly rainfall data were used to predict the historic water table fluctuations. Daily rainfall data were available from 1 Jan. 1959 through 31 Dec. 1998 from a weather station 95 km from the site. It was assumed that over the 40-yr period the distribution of rainfall was similar between the research site and weather station, although daily rainfall levels would differ between the two locations. This assumption was verified using rainfall probability maps compiled by Hershfield (1961). The maps showed that the average amounts of precipitation that fell at the research site were equal to those that fell at the weather station.
The daily rainfall data obtained from the weather station were disaggregated into hourly data and converted to a format compatible with DRAINMOD using a computer program developed by Robbins (1988). Daily maximum and minimum temperature data and geographic location were required for the PET (potential evapotranspiration) calculation in DRAINMOD. These data were also obtained from the weather station that was 95 km from the research site.
Daily water table levels for the past 40 yr (1959–1998) were simulated for each plot using the calibrated DRAINMOD model. Required inputs for the hydrology analysis included the starting day and ending day of the simulation, continuous days of saturation, and maximum depth to saturation. DRAINMOD was calibrated for each plot using the measured hourly rainfall data, water table data, along with pore-size distribution and saturated hydraulic conductivity of all soil horizons (He et al., 2002). Simulations were made in two periods, in growing season and out of growing season. The starting and ending dates of growing season (April 3–October 30) were obtained from Soil Survey of Bertie County, NC (Tant et al., 1990). Six depths, ranging from 15 to 90 cm at intervals of 15 cm, were simulated to analyze the hydrology.
DRAINMOD computed the number of times the soil in a plot was saturated for 21 d or longer each year above specific depths. The model also computed the longest continuous period of saturation found during a specific period of the year. Data were summarized by computing the number of saturation events (NSE) that incorporated both the saturation frequency and longest period of duration as computed by DRAINMOD. This variable gave more weight to longer saturation events than to shorter ones. The NSE was calculated from the DRAINMOD output as follows:
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where NSE is the number of saturation events in a given time interval, LDS is the integer of the longest duration of a single period of saturation (in days) during the period of interest, and NPS is the number of times the soil was saturated for periods lasting 21 d or longer during the period of interest. This calculation was done for each year of the 40-yr set of data. Equation [2] simply adjusts the number of times a horizon was saturated. For example, one horizon might have saturated once for 21 d, while another saturated for 84 d. The horizon in the first case would have an NSE of 1, while the second horizon would have an NSE of 4. Adjusting the saturation frequency in this way allowed us to separate those soils that were saturated for very long periods, and had higher percentages of redoximorphic features, from those that were saturated for relatively short periods. If no saturation occurred, then the NSE was set at 0 because the NSE could not realistically be a negative number. These calculations were made for each depth of a soil plot for each of the 40 yr of simulated water data. The yearly NSE values were then averaged and the mean value used to represent the entire 40-yr period of record.
Percentages of redox depletions (with chromas of 2 or less and values of 4 or more) and redox concentrations (i.e., red mottles with values and chromas 
4) were determined for each depth range using an interpolation method based on the soil profile description data (He et al., 2003). Statistical analyses were conducted to correlate the percentages of redox depletions and concentrations to NSE values using SAS program (Version 7.0; SAS Institute, 1998). Saturation events within the growing season, out of the growing season, and in a year were used in the correlation.
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RESULTS AND DISCUSSION
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Soil Properties
Soil profile descriptions for selected plots of the north transect are given in Table 1. Soils had high silt contents compared with the sandy loam-sandy clay loam soils studied previously (He et al., 2003). Leaf soils contained the most redox depletions with percentages exceeding 50% below 15 cm. The depleted matrix (Indicator F3) was the most common hydric soil field indicator found at the site (Table 2). It is defined as a layer of soil that is at least 15 cm thick, whose upper boundary begins within 20 cm of the surface, and whose matrix has a color with chroma 2 or less, and value 4 or more in at least 60% of the layer (USDA-NRCS, 2002). Redox concentrations are required in an abundance of 2% or more if the matrix value is 4 and also 5 when chromas are >1. Redox concentrations are required when the depleted matrix is found within an A or E horizon. A similar indicator, "depleted below dark surface (F4)," occurred when the depleted matrix was found within 30 cm of the surface and was overlain by a layer having a Munsell value of 3 or less and chroma of 2 or less.
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Table 1. Soil profile descriptions of plots in the north transect of the Goldsboro-Lenoir-Leaf catena at the site.
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More plots in the north transect had hydric soil field indicators than in the south transect (Table 2). Slope shape differed between transects and probably influenced which plots contained field indicators (Fig. 2). Plots in the north transect that had the hydric soil field indicators were in a depression which probably allowed water to stagnate and sped development of reducing conditions. Plots on the south transect were not in a large depression and water was more likely to be moving downslope which could slow development of reducing conditions.
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Fig. 2. Landscape cross-sections showing slope configurations of each transect. Plots in the depression of the north transect contained hydric soil field indicators, while in the south transect only plot 5S contained a field indicator.
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Iron Reduction and Redox Potentials
Means and ranges of weekly redox potentials in Plot 5N are shown in Fig. 3 to illustrate how the length of time needed for a saturated soil to become Fe-reduced was determined. Iron reduction began 20 d after the horizon became saturated at a depth of 15 cm. This is termed the lag time between when a soil became saturated and when it became Fe-reduced. Lag times from all plots having hydric soil field indicators (Table 3) illustrate the periods required for redoximorphic features, and hydric soil field indicators, to begin to form in this landscape. We assumed that periods of saturation <18 d would be too short for redoximorphic features to develop at the 15-cm depth. Shorter lag times were found at depths of 30 and 60 cm. The lag times were determined primarily for the months of January through May because this is when most saturation periods occurred. Average daily soil temperatures remained above biological zero (5°C) throughout the year (data not shown) indicating that low temperatures would not be expected to prevent microorganisms from developing reducing conditions in these soils.
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Fig. 3. Variation in redox potential over time for Plot 5N. The difference between the time saturation began and the start of Fe-reduction is termed a lag period for Fe reduction.
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Table 3. Average lengths of time (lag times) needed to develop Fe-reducing conditions once soil horizons became saturated. Data for plots containing hydric soil field indicators.
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The reported lag times pertain to this landscape and do not necessarily represent conditions found in other areas. Different values may have been found if measurements had been taken more frequently than once per week. The 18-d lag value is similar to the 21 d lag time used by He et al. (2003) for a similar investigation at another site in North Carolina. To compare both studies we used the previous value of 21 d for the hydrologic modeling in this investigation.
Hydrology Simulations
Table 4 shows the average NSE's that were computed for each plot. All plots, with the exception of 2N and 2S, were saturated to within 15 cm of the surface. This shallow saturation occurred both within and outside the growing season. Saturation outside the growing season had the greater saturation event values indicating either more frequent or longer periods of saturation.
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Table 4. The average number of times the soil will saturate for 21 d or longer per year (average NSE values) during the growing season, outside growing season, and total year that were determined for years 1958–1998.
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Plots having average NSE's 0.5 at a depth of 15 cm should meet or exceed wetland hydrology requirements (Table 4). All plots with hydric soil field indicators had NSE's > 0.5. In most cases, plots that did not meet a hydric soil field indicator had average NSE's < 0.5. Plot 4S was an exceptional case because while its NSE was 0.6 it did not meet a field indicator. It was very close to meeting the depleted matrix indicator, but failed because its Bt horizon at 16 to 37 cm had a matrix color of 2.5Y 6/4. Soil horizons below 37 cm had matrix colors of 2.5Y 6/2 but were too deep to meet the indicator. The E horizon above a depth of 16 cm met the color requirements for a depleted matrix, but was too thin to meet the indicator.
Correlation of Redoximorphic Features with Saturation Events
Percentages of redox depletions and redox concentrations were first correlated with the average NSE's occurring during the growing season (April 3–October 30), out of growing season (October 31–April 2) and throughout a year (January 1–December 31) using the basic regression models:
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Regression results were very similar to those found in the earlier study (He et al., 2003). They are shown in Table 5 for the time periods noted above and are graphed in Fig. 4 for growing season data. The r2 values of the regressions were high and slopes were significant at the P < 0.001 level. Linear models did an adequate job of relating redoximorphic features to saturation events. As shown in Fig. 4A, more depletions were generally found near the surface than at depth for a given saturation event. An exception to this rule occurred at 15 cm where fewer depletions occurred for a given saturation event than were found for a horizon at 30 or 45 cm. Soil at 15 cm also had fewer redox concentrations for a given saturation event than found for lower horizons (Fig. 4B). These results are probably related to the lag times for reduction shown in Table 3. Soil at 15 cm took longer to reduce with respect to Fe once saturated than lower horizons. Therefore, a given saturation event produced fewer redoximorphic features than found in deeper horizons.
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Table 5. Summary of slopes and r2 values for linear regression relationships between saturation event indices and redoximorphic features. All slopes were significant (P < 0.001).
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Fig. 4. Relationships between saturation events and percentages of (A) redox depletions and (B) redox concentrations during the growing season. Data from all plots at the site were used for analysis.
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Percentage of redox depletions and percentage of redox concentrations both were also used in the following model to be regressed with average NSE:
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Parameters C and D are summarized in Table 6. Most R2 values were higher than 0.97. Better relationships were obtained using both redox depletions and concentrations than when either was considered alone in the model. Parameters C and D both were quite constant at depths below 30 cm of the surface.
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Table 6. Summary of parameters (C and D) for relating percentages of redox depletions and redox concentrations to saturation event indices in linear regression models.
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Wetland Hydrology Determinations
Data in Table 6 were used to compare saturation events to hydric soil field indicators. The hydric soil field indicators found at the site occurred between the depths of 15 and 30 cm, and so equations for these depths were used to estimate saturation events for a horizon having 60% redox depletions and 2% redox concentrations. These percentages were selected to represent the minimum requirements of the indicator.
Results are shown in Fig. 5. If a depleted matrix occurred between the depths of 15 and 30 cm, in either of the two indicators found here, then it experienced average NSE's during the growing season that were between approximately 0.9 and 1.1 events yr–1. This means that periods of saturation lasting at least 21 d would occur between 9 to 11 times every 10 yr, or about once per year. Wetland hydrology requirements specify that the minimum period of saturation must be 11 d in this part of North Carolina (5% of the growing season) in at least 5 out of 10 yr. This frequency would be found in soils having an average NSE of 0.5 at a depth of 15 cm. We did not simulate saturation periods of 11 d, and so our results for 21 d of saturation will exceed the minimal saturation duration requirements for wetland hydrology. However, as shown in Fig. 5, wetland hydrology requirements would be met when the NSE is equal to 0.5 and this is found in horizons with approximately 27% redox depletions and 2% redox concentrations. Currently, the depleted matrix field indicator requires that redox depletions occupy 60% of a soil horizon, and this percentage would be found in these soils of North Carolina that are saturated about twice as often and nearly twice as long as needed to meet the minimal requirements of wetland hydrology.
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Fig. 5. Relationship between percentage of redox depletions and saturation events for the 15- and 30-cm depths. Lines were drawn using equations in Table 6 for the growing season. It was assumed that 2% redox concentrations occurred at both depths and remained constant while percentages of redox depletions varied. Wetland hydrology would be met for saturation events of 0.5 event yr–1 or above which correspond to a soil having approximately 30% depletions between the depths of 15 and 30 cm.
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To determine whether these results could be applied to other sites, we combined the data sets from this study with those of a companion site reported by He et al. (2003), which were both inter-stream divide landscapes in the Coastal Plain. The combined data were then used in statistical analyses using Eq. [5] to relate average NSE's to percentages of redox concentrations and redox depletions. Only data for depths 45 cm were used because the companion site did not have redox depletions at depths of 15 or 30 cm. Good correlations were obtained with R2 values 0.94 when NSE's occurring throughout the year were used in the regression equations (Table 7). Regression results were not significant when separate periods such as during the growing season were used. This suggests that the regression results reported in Fig. 5 for the growing season are site specific and cannot be used in other landscapes without verification of their accuracy. However, it is likely that our overall conclusion is valid in that selected hydric soil field indicators such as the depleted matrix will occur in sites that meet or exceed wetland hydrology requirements. We recommend that the method presented here be applied to a wide variety of sites to calibrate all hydric soil field indicators to wetland hydrology requirements. Preferred sites for this would have virtually no hydrologic alteration.
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Table 7. Summary of regression results that combined soils from the current study with those of He et al. (2003) using Eq. [5]. Data came from a total of 21 soil plots and number of saturation events (NSE) were computed for the entire year.
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ACKNOWLEDGMENTS
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Funding for the research was obtained from the U.S. Environmental Protection Agency (contract no. CR 824735-01-0) and the Water Resources Research Institute of the University of North Carolina (WRRI Project no. 70175). Their assistance was greatly appreciated.
Received for publication October 4, 2002.
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ABSTRACT
INTRODUCTION
