To isolate the effects of bio-solids and TCS amendments on microbial community composition, the data was analyzed using pCCA considering TCS and bio solid amendment as environmental variables, and incubation time as a covariable . This confirmed the results of the CCA indicating that the strongest determinant of microbial community composition was addition of bio-solids to soil. TCS concentration, on the second axis, described only 3.6% of the variation, showing TCS effects were overshadowed by the effects of bio-solids amendment. Bio-solid amendments caused an approximately two-fold increase in PLFA biomarkers for Gram-positive bacteria, actinomycetes and eukaryotes in SB compared to soil samples . Even larger increases were observed in biomarkers for fungi and Gram-negative bacteria, which were up to three times higher in SB than soil. Again, these changes were likely due to increased nutrient availability in the bio-solid amended samples and/or the biomass added along with the bio-solids, consistent with previous studies that found that the fatty acid 18:2 ω6, 9c and monounsaturates were increased by addition of these materials . The effect of TCS on microbial community composition was greater in soil than SB. Spiking with 10 or 50 mg/kg TCS decreased the abundance of Gram positive and Gram negative bacteria as well as fungi, with reductions ranging from 14 to 27% by day 30. Additionally, actinomycetes, which are Gram positive bacteria,plant pots with drainage were reduced in the 50 mg/kg TCS samples after 30 days of incubation . Eukaryotes were negatively affected after 7 and 30 days of incubation at both concentrations of TCS in soil but not SB samples.
Biomass results for all microbial groups were consistent in suggesting that the presence of bio-solids mitigated the potential toxicity of TCS. It is important to note that the spiking levels used here are similar to levels found in the upper half of U.S. bio-solids, but would be unlikely to be achieved in bio-solid amended soils even after continued long term application. Therefore, the effects observed at the 10 or 50 mg/kg spiking levels should be viewed as a conservative upper bound on potential effects expected in the field. In addition, since all of the results in this study are based on an observation period of 30 d, the extent to which the observed effects persist is not known. Future studies should, in particular, investigate longer term changes in community structure in response to addition of bio-solids both with and without specific contaminants. There have been many efforts across the world to mitigate wetland habitat lost over the past century. This movement is echoed in California’s Central Valley where stakeholders have established the goal of creating and protecting over 60,000 ha of new wetland habitat in the state . Many of these wetlands are, or will be, ephemeral, flow through wetlands receiving irrigation return flows during the growing season . Most wetlands in CA are restored with the primary objective of enhancing waterfowl habitat, however, these systems also have the potential to retain and remove nutrient loads that would otherwise be exported directly into major waterways . Therefore, wetland treatment of agricultural return flows is being considered as a beneficial management practice to reduce algal and nutrient loads that contribute to seasonally low dissolved oxygen in the lower San Joaquin River, California . Many studies have demonstrated that natural and constructed wetlands are generally effective at removing nitrogen from municipal and agricultural waste waters . Removal efficiencies as high as 98% have been reported, though other studies report significantly lower N removal rates typically between 35 and 55% .
A study of three wetlands used to treat subsurface tile drainage water in the Midwestern, USA demonstrated NO3 removal rates of 28% . Similarly, high but variable NO3 removal rates have been documented from water seeping through side berms of a constructed wetland in Illinois . Variation in nitrate removal is a result of many factors such as hydraulic residence time, soil properties, vegetation characteristics, variability in input loads, N loading, temperature, dissolved oxygen concentration, climate and nitrogen form in input waters . Using wetlands as a beneficial management practice to reduce non-point source pollution from agricultural drainage waters may introduce a problem as these wetlands could leach contaminants such as nitrate directly into the groundwater. This could compound an existing problem in California where groundwater NO3-N loading rates of 200 Gg per year have been reported in areas of intensive agriculture such as the Salinas Valley and Tulare Lake Basin . Several studies of dairy lagoons summarized in Harter et al. document high seepage rates , and elevated groundwater N concentrations beneath lagoons. Similarly, Huffman found NO3-N concentrations exceeding the EPA drinking water standard beneath two thirds of 34 swine lagoons in North Carolina. More studies of nitrogen fate and transport in wetlands receiving tail water from cropland are needed because the existing literature base for this topic encompasses a wide range of environmental characteristics that govern nitrogen transformations . The primary objectives of this study were to determine the fate of nitrogen in seepage waters of a restored surface-flow through wetland and to determine the importance of hydrologic- as well as soil- and bio-geochemical-factors that regulate nitrate removal. We addressed these objectives by: monitoring nitrogen concentration in nested piezometers throughout the wetland and comparing them to surface water; measuring spatial patterns in selected soil and hydrological characteristics; and, developing wetland hydrologic and nitrogen mass balances to evaluate the fate of nitrate. The results from this study provide information relevant to the optimization, design, and management of restored wetlands for nitrate removal. Moreover, these findings expand upon the limited number of published studies that document nitrate removal by constructed wetlands receiving nitrate runoff from irrigated agriculture .
The wetland received agricultural return flows during the irrigation season from April to September, with no rainfall occurring during this time. Surface water inflow and outflow volumes were measured at 30-min intervals using v-notch weirs and barometric pressure compensated water level loggers . A digital elevation model was created using a Trimble RTK GPS with 3 cm accuracy. The DEM was used to relate water depth measured at two locations with water depth throughout the wetland,plastic plant pots as well as to determine changes in the wetted surface area throughout the irrigation season. Vertical hydraulic gradients were calculated at 12 piezometric monitoring locations in the southern section of the wetland, using biweekly water height measurements at 10- and 100-cm depths . Surface water residence time was calculated using a plug-flow model . Temperature was measured at 15-min intervals near the output. Wetland evapotranspiration was estimated using meteorological data obtained from the California Irrigation Management Information System Patterson station, approximately 15 km from the study site. ET rates for vegetated upland areas were presumed to approximate the CIMIS values calculated for grass cover. Evaporation for the sparsely vegetated wetland area was assumed to be 1.28 times that of the grass ET value . ET volumes were calculated at 30-min intervals to account for fluctuations in the wetted surface area. A season-long seepage volume was calculated by subtracting total outflow volume from total inflow volume, accounting for water loss due to ET. An independent measurement of the seepage rate for the northern and southern sections of the wetland was determined on 6/4/2007 through 6/9/2007 by preventing all inflow and outflow, and measuring the rate of water level drop over a 120- h period. Seepage volumes were then calculated for each 30-min interval by multiplying the seepage rate by the wetland wetted surface area . Assuming similar seepage rates across the different hydrologic zones, we calculated the percentage of the water surface area covering each hydrologic zone at 30-min increments based on the high-resolution DEM and water height at the output location. The seepage volume was summed for each 30- min increment to obtain a total seepage volume for each hydrologic zone.Pore water was collected from piezometers at 12 locations on a biweekly basis at depths of 10, 50 and 100 cm below the soil surface. Screened sections of the piezometers were surrounded in a layer of pure silica sand and sealed above and below with bentonite clay to prevent water intrusion from adjacent horizons . Prior to sampling, piezometers were purged and allowed to recharge for 1–2 h. Water samples were maintained at 3 C between the time of collection and analysis . Aliquots of samples were filtered through a prerinsed 0.4mm polycarbonate membrane filter for quantification of NO3-N , NH4-N , and DOC . Determination of NO3 was made using the vanadium chloride method and NH4 using the Berthelot reaction with a salicylate analog of indophenol blue . DOC was measured using a Dohrmann UV enhanced-persulfate TOC analyzer .
A non-filtered sample was used to determine total N following oxidation with 1% persulfate using the method described above for NO3-N. Surface water samples were collected adjacent to the piezometers and at input and output locations on a weekly basis and were analyzed as described above. Depth splines were used to model nitrate distribution over the 100-cm depth of the piezometer monitoring nests. The segmentation procedure involved fitting an equal-area or mass-preserving quadratic splineacross the discreteset ofporewaterNO3-N sampling depths , producing a continuous depth function segmentedat1-cmintervals . Mean values at each1-cmdepth increment were calculated across all sampling dates and sampling locations within each hydrologic zone. The segmenting algorithm was implemented using the ‘GSIF’ and ‘aqp’ packages for R .Inflow and outflow seasonal loads for total nitrogen, nitrate, and ammonium were calculated using the period-weighted approach from weekly constituent concentration and weekly water flux . Nitrate seepage loads for each hydrologic zone were also calculated with the period-weighted approach using average biweekly nitrate concentration at the 100- cm depth and weekly seepage flux.Linear mixed effects models were used to analyze data from water analysis and DNP incubations using S-Plus . As samples were taken at the same location several times throughout the season, location was treated as a random effect in the model to account for auto correlation between measurements at the same site. The NH4-N, NO3-N, DNP and DOC values were log transformed prior to statistical analysis to better approximate a normal distribution. For each analysis, the initial model accounted for main effects, as well as all possible two-way interactions between main effects. Interactions that were not significant were removed from subsequent models to gain sensitivity. Mean separation was determined using a conditional t-test. Raw are reported in Tables 4 and 5 to reflect measured field conditions. The water sampled from piezometers was termed seepage water. Nitrate concentration was markedly lower in seepage water than in surface waters . Concentrations of NO3-N were significantly lower at the 50-cm depth than the 10-cm depth, but there was not a significant difference in NO3-N concentrations between the 50- and 100-cm depths among the three hydrologic zones . Modeled nitrate removal rates from Fig. 4 in the top 10-cm soil depth relative to the water column were 932, 631 and 143 mg NO3- N m 2 d 1 in the flowpath, finger and upland zones, respectively. In the wettest hydrologic zones there was a significant increase in NH4-N concentrations from the surface water to the 10-cm depth . NH4-N concentrations decreased at the 50- and 100-cm depths and were not significantly different from those in the surface waters . DOC concentration in seepage water ranged from 3.2 to 6.0 mg L 1 . There were no significant differences in DOC between the surface water, 10-, and 50-cm depths; however, DOC concentration decreased significantly at the 100-cm depth of the upland sites. Among the hydrologic zones, DOC in seepage water was significantly higher in the uplands .Soil texture was generally similar among hydrologic zones and no abrupt changes in texture were observed with depth . Sedimentation was highest in the flowpath zone totaling over 35 kg m 2 yr 1 compared to sedimentation rates <5 kg m2 yr 1 in the fingers and uplands. Saturated hydraulic conductivities estimated for these textural classes were similar to measured seepage rates . Average soil organic carbon concentration was relatively low in all hydrologic zones . Organic carbon decreased with depth in all hydrologic zones.