Data Collection And Analysis
Automated monitoring stations were installed at the lower reaches of both watersheds. Stage was measured continuously at 15 minute intervals using ISCO 4230 Bubbler Flowmeters. Stage/discharge relationships were developed using a Swoffer current velocity meter to measure discharge at a variety of stages. Stage/discharge curves were comprised of two separate equations for each site - one to predict discharge at lower stages and one to predict discharge at the higher stages. Flowmeters were downloaded monthly. Data were edited and stored in QuattroPro data sets. Data analysis was performed using PC SAS.
Total Suspended Solids Concentrations
Biweekly grab samples were collected manually at the monitoring stations to establish baseflow (non-storm) water quality conditions. Storm event samples were collected by the ISCO 6700 portable samplers. The samplers were programmed to be stage activated, based on detecting a .05' rise in stream level. Twenty-four (24) samples were automatically collected at half hour intervals after the sampler was enabled. From these, at least three were selected for analysis; one from the rising limb, one at or near the peak, and one from the falling limb of the storm hydrograph. All samples were filtered in the field using GF/F Whitman 47mm diameter pre-weighed filters, and mailed to Chesapeake Biological Laboratories for analysis. Total suspended solids (TSS) were measured for each water quality sample.
Loading Estimate Methods
Annual and monthly load estimates were calculated for each station. TSS load estimates were generated using Beale’s Ratio Estimator. Beale’s Ratio Estimator was developed for situations with an abundance of flow information and relatively little concentration data. The Ratio Estimator assumes a positive relationship between concentration and flow, and the variance in concentration is proportional to the magnitude of flow (Preston and Summers 1992). The estimate is derived by multiplying the mean measured loads (concentration x flow) by the ratio of the average flow for the year, divided by the average flow on days when concentrations were measured (Dolan et al. 1981).
Paired Watershed Data Comparison
The TSS concentration data collected during this study were collated into pairs, one measurement from the control watershed and one measurement from the treatment watershed. For grab samples the pairs were created based on same day collection, with the time interval between the collection of the two samples being the amount of time needed to travel from one site to the other. Storm event samples were paired based on same storm, same day collection and relative position on the hydrograph. The paired TSS concentration data were then segregated into two data sets, one for the calibration period and one for the treatment period. Simple linear regressions were used to describe the relationships between the TSS concentrations leaving the treatment watershed and TSS concentrations leaving the control watershed for both the calibration and treatment periods. The regression relationships for the calibration and treatment periods were then compared using analysis of covariance as described by Grabow et al. (1998). The paired water quality and flow data were analyzed using Statistical Analysis Systems Inc. software (SAS Institute 1982).
Habitat and Benthic Macroinvertebrates
Benthic macroinvertebrate communities were sampled quantitatively with Surber samplers during the spring and fall at the single water quality monitoring site in each watershed. Samples were preserved in 70% ethanol and returned to the laboratory for sorting and identification. All samples were identified to the genus level and a suite of metrics calculated from the taxa lists. The metrics calculated were taxa richness, EPT (Ephemeroptera, Plecoptera, Trichoptera) taxa richness, percent of sample as EPT, EPT/Chironomidae ratio, percent dominant taxa, and total rapid bioassessment (RBP) score as a percent of reference. Semi-quantitative habitat assessments were also conducted at the time of macroinvertebrate sampling. The habitat assessment used seven metrics that rated primary instream habitat, secondary bank and riparian zone habitat, and tertiary watershed characteristics. Macroinvertebrate and habitat metrics followed those described by Plafkin et al (1989) for Rapid Bioassessment Protocol III.
Various physical features of the riparian zone, banks and channel were scored. The scores were used to develop a habitat assessment index (HAI) following the Rapid Bioassessment Protocol-Habitat, as developed for Piedmont Ecoregions in Maryland (Plafkin et al. 1989). The HAI was be used with the IBI to develop a relationship between habitat and the benthic community structure in the stream. Sampling was conducted twice yearly at a minimum.
A total of 5 temperature sensors - Ryan Tempmentors - were placed in the field. Two were located on the control watershed - one on an upper reach and one on a lower reach. Three were placed on the treatment watershed - one on an upper reach, one on a lower reach, and one at the upper edge of a proposed harvest site. Temperature was measured at 20 minute intervals throughout the growing season. Temperature sensors were downloaded monthly. Data was edited and stored in QuattroPro and analyzed using PC SAS.
The efficiency of individual BMPs was evaluated via on-site inspections during and/or immediately following storm events. Permanent photo points were established shortly after BMP installation. Using a Pentax IQ Zoom-90 Weathermatic camera, the successes or failures of individual Best Management Practices were documented by taking repeated shots from the same vantage point during the course of the study. A log book was maintained containing 35 mm slides, organized by specific BMP type (culvert, bridge, rolling dips, etc). In addition, visual observations were made during and immediately after storm events at many locations, particularly along roads, trails, and landings, and along the nearby streams. This was to identify any sources of possible sediment pollution which could reach the waterway.
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This study was funded through a Clean Water Act Section 319(h) Grant from the U.S. Environmental Protection Agency
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