3.1. Instrumentation and Measurements
 During the spring and summer of 2005, instrumented moorings were deployed along three cross-estuary transects designated New Castle (NC1), Blackbird Creek (BC1−3), and Bombay Hook (BH1−5) (Figure 1). Station locations were selected to bracket the ETM zone as mapped during prior shipboard surveys (reported by Cook et al. ). Two mooring deployments extending from 8 March to 2 June (yearday 67–153) and from 2 June to 27 October (yearday 153–300) were completed. During the second deployment, mooring disturbances by ship traffic compromised data recorded at Station BC3, and at Stations BH1 and BH5 biological fouling reduced the data quality. For these reasons, data collected only during the first deployment at these stations are reported herein. RD Instruments 1200 kHz (NC1) and 600 kHz (BC2 and BH3) acoustic Doppler current profilers (ADCP) mounted on bottom frames were deployed at three channel stations along the estuary in 10−12 m water depths. These moorings were sited just adjacent to the channel axis to avoid the heavily trafficked midchannel shipping lane. The lowermost ADCP bin at the channel mooring sites fell 1−1.5 m above the seabed, but no attempt was made to extrapolate the velocity and SSC profiles to the bottom. We estimate that loss of the lowermost profile underestimated the depth-averaged current and sediment flux by <5% of the reported values.
 At Stations BH2 and BH3 the frames were outfitted with a SBE-37 conductivity and temperature (CT) sensor and an OBS-3 optical backscatter sensor mounted 0.5 m above the bottom (mab). At all of the midchannel stations SBE-37 and OBS-3 sensors were mounted on a mooring cable approximately 5−6 mab. On transects BC and BH, InterOcean S4 current meters with integrated CT sensors were deployed on the channel flanks to obtain additional information on flow and salinity, but the data are not discussed in this paper. Instrument packages consisting of a Sontek Ocean Probe acoustic Doppler velocimeter (ADV) with integrated OBS-3 turbidity and SBE-37 CT sensors were deployed at the both ends of transect BH on subtidal flats (2−3 m water depths). The ADV probe and OBS-3 and SBE-37 sensors were mounted on a frame and positioned at 1 mab. The velocity and OBS-3 turbidity sensors were similarly programmed to sample in 2-minute bursts at sampling rates of 1−6 Hz every 15 min, whereas the SBE-37 CT sensors sampled in 3 s bursts every 5 min.
 To generate profiles of suspended sediment concentration (SSC), ADCP echo intensity was calibrated against optical backscatter data recorded by the moored OBS-3 sensor, which was oriented to sample the water mass insonified by the ADCP beam. The calibration was performed in two steps. First, OBS-3 voltages were calibrated against gravimetrically determined SSC using water samples collected and filtered during two hydrographic surveys of the study area in 2005. In the laboratory, OBS-3 sensors were immersed in water baths of known SSC determined gravimetrically, the baths gently stirred to maintain a suspension, and a 2 min average OBS-3 voltage was recorded. This procedure was repeated for a suite of SSC standards over a 10−200 mg/L concentration range. The voltages were linearly regressed against gravimetric SSC to generate a calibration curve for each of the OBS-3 units used in the study. OBS-3 voltage was strongly correlated with gravimetric SSC (r2 = 0.97−0.99) and exhibited a linear relationship over the full range of concentrations.
 Second, ADCP echo intensity was converted to SSC following a procedure adapted from Holdaway et al.  and Gartner . The sonar equation was used to compute SSC from acoustic backscatter as
where SSC is the mass concentration of suspended solids, RB is the relative backscatter, and A and B are constants determined by regression of ADCP relative backscatter against SSC as determined by optical backscatter (SSCobs). ADCP relative backscatter was computed as
where Kc is the signal strength scale factor used to convert backscatter counts to dB (0.45 for our ADCPs), E is the received ADCP echo intensity, Er is the background echo intensity (46−47 counts), R is the slant range of the insonified volume (m), and α is the water absorption coefficient (dB/m). The second and third terms on the right-hand side of equation (2) comprise the two-way transmission loss of the acoustic signal. The slant range was determined from the ADCP bin depth and beam angle relative to vertical, and α was computed following Schulkin and Marsh . Although we included a correction for the near-field nonspherical spreading, it did not significantly improve the correlation between SSCobs and ADCP echo intensity.
 Correlations between relative backscatter and SSCobs were not as strong as those between optical backscatter and gravimetric SSC, perhaps because of the different ways in which acoustical and optical sensors sense suspended particles [Holdaway et al., 1999]. Even so, good correlations (r2 = 0.75−0.81) were obtained for the ADCPs used in this study, and the resulting regression equations for relative backscatter versus SSCobs and SSCobs versus gravimetric SSC were used to compute time series of SSC for each midchannel station. A more direct calibration for SSC would have involved filtering water samples collected directly from the water volume insonified by the ADCP for regression against the corresponding acoustic backscatter intensity [e.g., Fugate and Friedrichs, 2002].
 Time series of SSC where also derived from point velocity ADV data obtained at Stations BH1 and BH5. The ADV backscatter signal was used as surrogate for optical backscatter because the OBS-3 sensors had a tendency to foul rapidly by biological growth. Backscatter intensity was computed from the ADV signal amplitude and calibrated against gravimetrically determined SSC using filtered water samples collected periodically at these stations [Fugate and Friedrichs, 2002; Ha et al., 2009]. Backscatter intensity was well correlated with gravimetric SSC (r2 = 0.90−0.95) on a log-log plot and exhibited a linear relationship over the full range of measured concentrations.
3.2. Sediment Flux Decomposition
 Time series of current velocity and derived SSC were used to compute continuous records of suspended sediment flux at the observational sites. For the midchannel ADCP stations (NC1, BC2, and BH3), sediment fluxes were computed as the product of velocity and SSC for each 50 cm ADCP bin and then integrated over the mean depth of the water column to determine total sediment flux per unit width of flow (mass/length/time). For the subtidal flat sites (BH1 and BH5), the total sediment flux at 1 mab was computed from time series of ADV point velocity and SSC (in mass/area/time). The ADCP and ADV current data were rotated to the dominant axis of tidal flow prior to filtering; thus, the computed sediment fluxes approximate the streamwise flux.
 The instantaneous sediment flux was computed as
where U and SSC are instantaneous values of along-channel velocity and sediment concentration, respectively, and z is depth. The instantaneous velocity is the sum of the tidally varying velocity (U′) and the tidally averaged velocity (), and the instantaneous SSC has a similar composition. Integrating equation (3) over z and averaging over the tidal cycle gives the total residual sediment flux per unit width of flow (FT). Tidal averaging was accomplished by filtering the time series using a 36 h Lanczos low-pass filter; FT was computed as the low-pass filtered product of U and SSC.
 To identify tidal and nontidal mechanisms of residual sediment flux, FT was decomposed into advective (FA) and tidal pumping (FP) components. The advective sediment flux is driven by the tidally averaged (residual) velocity and the tidally averaged SSC and is given by
where the overbars denote tidally averaged (low-pass filtered) values; FA was computed as the product of low-pass filtered U and low-pass filtered SSC. The main source of the advective residual current and sediment flux in the estuary is gravitational circulation, i.e., seaward barotropic flow and landward baroclinic flow. The Stokes Drift component of the residual current was determined to be on the order of 2–3 cm/s at Stations BH3 and BC3 and 3−6 cm/s at NC1. This component of the residual current was not removed from the velocity time series; thus, the sediment flux on the Stokes Drift compensation flow is contained within the record of FA.
 The tidal pumping flux is driven by correlated fluctuations in tidally varying SSC and U and is given by
where the primes denote tidal fluctuations around the tidally averaged values. Tidal values were computed by high-pass filtering timeseries of U and SSC, and FP was computed as the low-pass filtered product of U′ and SSC′. Here it is important to point out that sediment pumping fluxes related to tidal velocity asymmetry and tidal mixing asymmetry are both contained within the record of Fp. In this paper positive and negative values denote seaward (down-estuary) and landward (up-estuary) transports, respectively.