Cathy A. Seybold

Temporal and spatial variation in active layer depth in the McMurdo Sound Region, Antarctica

Abstract A soil climate monitoring network, consisting of seven automated weather stations, was established between 1999 and 2003, ranging from Minna Bluff to Granite Harbour and from near sea level to about 1700 m on the edge of the polar plateau. Active layer depth was calculated for each site for eight successive summers from 1999/2000 to 2006/2007. The active layer depth varied from year to year and was deepest in the warm summer of 2001–02 at all recording sites. No trends of overall increase or decrease in active layer depth were evident across the up-to-eight years of data investigated. Average active layer depth decreased with increasing latitude from Granite Harbour (77°S, active layer depth of > 90 cm) to Minna Bluff (78.5°S, active layer depth of 22 ± 0.4 cm), and decreased with increasing altitude from Marble Point (50 m altitude, active layer depth of 49 ± 9 cm) through to Mount Fleming (1700 m altitude, active layer depth of 6 ± 2 cm). When all data from the sites were grouped together and used to predict active layer depth the mean summer air temperature, mean winter air temperature, total summer solar radiation and mean summer wind speed explained 73% of the variation (R2 = 0.73).

Atrazine and Metolachlor Sorption to Switchgrass Residues

Abstract Herbicide retention by residue mulch in vegetative filter strips could be an effective attenuation mechanism for removing herbicides from runoff. Adsorption studies were conducted to quantify the amount of atrazine and metolachlor that can be adsorbed and removed from runoff by thatch or fresh switchgrass residue. Adsorption of C14‐atrazine and metolachlor on thatch or fresh switchgrass residue was conducted by using concentrations of 2.5, 7.5, 13.2, and 26.4 µmol L−1 and a 24‐h equilibration period. Adsorption coefficients (Kd) decreased in the order, atrazine sorption on fresh switchgrass residue (81.1 L−1 kg−1), metolachlor sorption on fresh residue (32.9 L−1 kg−1), atrazine sorption on thatch residue (21.4 L−1 kg−1), and metolachlor sorption on thatch switchgrass residue (15.1 L−1 kg−1). On a volumetric basis (Kd-vol), only atrazine showed a significantly greater Kd-vol value on fresh residue than on the thatch residue. Absorption through cut ends of the residues (especially the fresh residue) may have produced adsorption capacities that would not be observed under field conditions. Fresh or thatch switchgrass residue in vegetative filter strips can help abate atrazine and metolachlor by intercepting and sorbing some of the herbicides.

Degradation of metolachlor in bare and vegetated soils and in simulated water-sediment systems

A study was conducted to determine the half-life (t1/2), degradation rate, and metabolites of metolachlor in a water-sediment system and in soil with and without switchgrass. Metolachlor degradation in a laboratory was determined in sediment from Bojac sandy loam soil incubated at 24 degrees C. The study also was conducted in a greenhouse on tilted beds filled with Bojac soil and planted with switchgrass. In both experiments, samples were collected at days 0, 7, 14, 28, 42, 56, and 112 and analyzed for metolachlor and its major metabolites. The water-sediment oxidation-reduction potential took 28 d to reach -371 mV and the pH increased from 5.6 to 6.5 by the last sampling day (day 112). The average soil temperature of the tilted beds with or without switchgrass during the study was 21degrees C and the soil moisture content was 23% by volume. The t1/2 of metolachlor was 34 d in sediment and 8 d in the water phase. The t1/2 of metolachlor in soil from the switchgrass filter strip (6 d) was not different from that in soil without grass (9.6 d). The metolachlor metabolites ethanesulfonic acid (ESA) and oxanilic acid (OA) were detected in the water-sediment system and in soil from tilted beds. In both sediment and soil from tilted beds, the two metabolites peaked by day 56 of incubation and declined after that, indicating transformation to other products. In the water-sediment system, greater quantities of OA and ESA were detected in sediment than in the aqueous phase. The production of OA and ESA in the watersediment system occurred in the first 28 d, when the system was at an aerobic redox state. Metolachlor can degrade in sediment and the relatively high soil temperature and moisture level accelerated its breakdown in beds with and without switchgrass. Under warm and moist soil conditions, the presence of switchgrass has no effect on the degradation of metolachlor.

Characterization of active layer water contents in the McMurdo Sound region, Antarctica

Abstract The liquid soil water contents in the seasonally thawed layer (active layer) were characterized from seven soil climate monitoring sites - four coastal sites from south to north (Minna Bluff, Scott Base, Marble Point and Granite Harbour), and inland sites from low to high altitude (Wright Valley, Victoria Valley and Mount Fleming). Mean water contents ranged from 0.013 m3 m-3 near the surface at Victoria Valley to 0.33 m3 m-3 near the ice-cemented layer at Granite Harbour. The coastal sites have greater soil water contents than the McMurdo Dry Valley and Mount Fleming sites, and moisture contents increase with depth in the active layer. The Wright Valley site receives very little infiltration from snowmelt, with none in most years. All other sites, except Mount Fleming, received between one and four wetting events per summer, and infiltrated water moved to greater depths (≈ 10–25 cm). The Scott Base and Granite Harbour sites are on sloping ground and receive a subsurface flow of water along the ice-cemented permafrost. Our findings indicate that water contents are low with very little recharge, are greatly influenced by the local microclimate and topography, and show no significant increasing or decreasing trend over 10 years of monitoring.

Loss of heavy metals by runoff from agricultural watersheds

The loss of agricultural chemicals in runoff from agricultural land is a major cause of poor surface water quality in the United States. A technique using climatic, hydrologic, and soil survey information was developed to estimate the impact of agricultural watersheds on natural water resources. The objectives of this study were to apply this technique on the Wagon Train watershed to predict loss of eight elements (Al, Fe, Si, Cd, Cu, Ni, Pb, and Zn) by runoff from soils and to estimate elements loading into Wagon Train reservoir. The predicted losses of Al, Fe, and Si by runoff were 25.3, 13.7, and 28.9 kg ha−1 year−1, respectively. The corresponding values for Cd, Cu, Ni, Pb, and Zn were much smaller at 0.61, 52.0, 21.3, 1.40, and 37.4 g ha−1 year−1, respectively. These data give a total annual loss (from the entire watershed) of 98.3, 53.2, and 112 Mg for Al, Fe, and Si, respectively. The total annual loss was 2.4, 202, 82.7, 5.4, and 147 kg for Cd, Cu, Ni, Pb, and Zn, respectively. The predicted Cd, Cu, and Pb concentrations in runoff were in reasonable agreement with the concentrations observed in the main stream in the watershed. However, the predicted concentration for other elements (Al, Fe, Si, Ni, and Zn) investigated in runoff was greater than that observed in the stream water. Elements uptake by algae, weeds, and aquatic plants and/or precipitation due to high pH in water might explain the lower element concentrations. We concluded that the technique could provide an estimation of elements loss in runoff from agricultural watersheds. The loading into surface water bodies could be predicted for Cd, Cu, and Pb. For other elements (Al, Fe, Si, Ni, and Zn), the loading could be estimated when factors affecting element concentration in streams are considered.

Effects of gypsum addition on solubility of nutrients in soil amended with peat.

It is widely accepted that the accumulation of gypsum in gypsiferous soils results in very low fertility, even with application of fertilizers and organic amendments. The objectives were to investigate, in laboratory experiments, the effect of gypsum on the solubility of 13 nutrients and how amending the soil with organic peat moss may mitigate the impact of gypsum on nutrients and soil fertility. A 100-g sample of gypsum-free soil (Sharpsburg Fine, montmorillonitic, mesic Typic Argiudolls) was treated with increasing amounts of gypsum (0, 1, 5, 10, 15, 20, 30, and 50 g), then water was added to the mixtures to reach 50% of the water saturation capacity. Another set of soil/gypsum mixtures received 5-g peat to study the effect of peat application. All mixtures were incubated at 32°C for 15 weeks. After incubation, the concentration of water-soluble nutrients was measured. In general, the addition of gypsum increased the solubility of N, K, Ca, Mg, Mn, Cl, and S, whereas it decreased the solubility of P, Na, Fe, Cu, Zn, and B. The application of peat increased the solubility of all nutrients investigated, except for N and S. Chemical reactions and mechanisms were applied to interpret the effects of both gypsum and peat treatments on nutrient solubility and their relationship to soil fertility and crop production. The application of peat improved the solubility of most nutrients and proved to be useful as an amendment for gypsum-rich soils and increases its productivity.

Annual Precipitation and Effects of Runoff Nutrient From Agricultural Watersheds on Water Quality

Abstract Declining surface water quality from agricultural nonpoint sources is of great concern across the Great Plains. Trends in the earth climate create abrupt changes in domestic weather (i.e., precipitation) that can alter the impact of the nonpoint sources on water quality. A 2-year (dry 2009 and wet 2010) study was conducted to assess the impact of soil C, N, and S losses by runoff on water quality of Salt Creek in the Roca watershed, Nebraska. Average dissolved nutrient concentrations in runoff were 95.4 and 94.9% of the total for the dry and wet years, respectively. The remaining nutrients in runoff were associated with sediment. Nutrient concentrations during the dry year were generally greater than those during the wet year. Average concentrations for 2009 were 63.2, 1.87, and 53.5 mg/L for C, N, and S, respectively, whereas concentrations for 2010 were 54.0, 3.0, and 16.6 mg/L, respectively. Total soil nutrient losses were greater for the wet year than those for the dry year. The dry year nutrient losses were 607, 19,978, and 441,569 metric tons for C, N, and S, respectively, whereas losses for the wet year were 1,997, 138,380, and 608,172 metric tons, respectively. These losses could be considered as the annual nutrient loadings for Salt Creek. Concentrations of C, N, and S measured in Salt Creek during the study were not expected to have any adverse effect on human/animal health or aquatic life. We concluded that greater precipitation during the wet year increased the impact on water quality and soil fertility in the Roca watershed.

Estimating Total Acidity From Soil Properties Using Linear Models

Currently, there is no national or comprehensive model for estimating total acidity (extractable acidity) that uses basic soil properties obtained in soil survey. The aim of this study was to develop total acidity prediction models from readily available soil properties. Measured data in the National Soil Survey Characterization Database were used to develop the total acidity prediction equations. The data set was stratified primarily by taxonomic order. Strata were also separated by texture modifiers of hydrous, medial, and ashy, and by different organic layers. Prediction equations were developed for each strata (or data set) using general linear model procedures. Organic C, pH (in H2O), and cation exchange capacity (CEC) were the most highly correlated and most important variables in predicting total acidity. Two sets of total acidity prediction equations were developed. One set uses CEC as a predictor variable, and the second set provides total acidity estimates for low pH soils (pH <5.5) where CEC is not available. The two sets of equations allow total acidity to be predicted for all soils in soil survey. The coefficient-of-determination (R2) ranged from 0.55 to 0.93 for prediction equations using CEC as a variable and from 0.44 to 0.86 for prediction of total acidity for low pH soils, where CEC is not used as a predictor variable. Validation of the equations indicated that these models can be useful in estimating total acidity with decreasing reliability at lower pH (when CEC is not used). The most useful equations are those with R2 > 0.60, which can be useful in estimating total acidity for soil survey when there are no measured data available.

Nonpoint source of nitrogen contamination from land management practices in Lost River basin, West Virginia.

Poultry production in Hardy County, West Virginia, has increased considerably since the early 1990s. The Lost River basin contains the highest density of poultry facilities in the county. Most of the N-rich poultry litter produced is land applied, and concerns over water quality are widespread. The objective was to apply the Natural Resources Conservation Service exploratory technique on two watersheds (Cullers Run and Upper Cove Run) in the Lost River basin to estimate the loss of nitrate-N from soils by runoff and leaching and to predict the impact on water quality. The predicted annual nitrate-N loss by runoff was 192 Mg, whereas that by leaching was 764 Mg, and their combined amount represented the annual loading for the Lost River. The predicted averages of nitrate-N concentration in runoff and leaching water were 2.57 and 45.1 mg/L, respectively. These data would give an estimated average nitrate-N concentration of 10.4 mg/L in the Lost River. The observed nitrate-N concentration in 12 monthly samples collected from the Lost River ranged from 2.41 to 19.9 mg/L, with an average of 7.11 mg/L (S.D., 4.68 mg/L). The relatively low nitrate-N concentrations observed in the river could be attributed to assimilation by algae, weeds, and aquatic plants, as well as denitrification in stream water under anaerobic conditions. When factors affecting N concentration in streams are considered, the technique could estimate the impact on water quality. We concluded that the exploratory technique could provide a quick estimation and identify hot spots for large areas of agricultural land. Thus, lengthy and site-specific studies could be focused on certain areas of high risk.

Soil Survey: Pedotransfer Function of Linear Extensibility Percent for Soils of the United States

ABSTRACT Soil survey is an ongoing process from initial soil mapping through soil survey updates. A national model of linear extensibility percent (LEP) is needed to improve this process. The objective of this work was to develop and validate models for estimating LEP using general linear models and readily available soil survey properties. Measured data from the Kellogg National Soil Survey Laboratory database (Lincoln, Nebraska) were used to develop the prediction models. Twenty LEP prediction equations were developed based on pH and major mineralogy classes. Noncarbonate clay and, depending on the soil pH, either cation-exchange capacity or effective cation-exchange capacity explained between 42% and 86% of the total variation in LEP. Model equations using cation-exchange capacity as a predictive variable collectively produced a prediction root mean square error (RMSEP) of 1.44% and mean error (ME) of −0.16%. For low pH soils, the model equations using effective cation-exchange capacity as a predictive variable collectively produced an RMSEP of 1.29% and ME of −0.034%. The small negative MEs indicate an overall underestimation of LEP. Breaking down the validation results further among the different mineralogy groups produced a range of RMSEp from 0.42% to 1.80%. The smectitic group had the largest and the siliceous group had the lowest RMSEp. The prediction accuracy is considered adequate for soil survey purposes, and it is expected that LEP estimates will ultimately enhance soil survey interpretations. The models will be added to the soil survey database for soil scientists to use when measured data are not available.