acoustic doppler velocimetry (adv) - CiteSeerX

3954 September 11~16, 2005, Seoul, Korea

ACOUSTIC DOPPLER VELOCIMETRY (ADV) IN A SMALL ESTUARINE SYSTEM. FIELD EXPERIENCE AND "DESPIKING" HUBERT CHANSON1, MARK TREVETHAN1 and SHIN-ICHI AOKI2 1

Dept of Civil Engineering, The University of Queensland, Brisbane QLD 4072, Australia (e-mail: [email protected]) 2 Department of Architecture and Civil Engineering, Toyohashi University of Technology, Tempakucho, Toyohashi 441-8580, Japan (e-mail: [email protected]) Abstract Estuarine mixing and dispersion are turbulent processes. Present understanding of estuary turbulence remains however limited, partly because long-duration studies of turbulent properties are difficult and rare. Herein, some long-duration turbulence data recorded at highfrequency using acoustic Doppler velocimetry (ADV) are analysed. The data sets were collected in a small sub-tropical estuary. A new ADV data post-processing technique is developed for turbulence analysis of estuarine flows. The results show that acoustic Doppler velocimetry data cannot be used without suitable post-processing. Even classical "despiking" techniques are not simply applicable to natural unsteady estuary flows. Keywords: Turbulence; Sub-tropical estuary; Acoustic Doppler Velocimetry(ADV); Postprocessing; Despiking. 1. INTRODUCTION Dispersion of matter in estuarine systems is of considerable importance, for example in terms of sediment transport, stormwater runoff during floods, and release of nutrient-rich wastewater into the ecosystem (e.g. treated sewage effluent). Basic literature includes Ippen (1966), Fischer et al. (1979), Rutherford (1994), Lewis (1997) and Chanson (2004). In Nature, estuarine flows are turbulent flows, and mixing and dispersion are turbulent processes. Present understanding of the turbulence field remains limited, partly because long-duration studies of turbulent properties at high-frequency are extremely limited. Most measurements were conducted for short-periods or in bursts : e.g. Bowden and Ferguson (1980), Kawanisi and Yokosi (1997). Herein long-duration turbulence data were collected continuously at high-frequency using acoustic Doppler velocimetry (ADV) in a small sub-tropical estuary. The instrumentation is well-suited to study turbulent velocities in shallow-waters, and the paper focuses on a new ADV data post-processing technique for turbulence analysis. Field work data were systematically analysed. Several post-processing techniques were tested and a new method was developed. The results will show that acoustic Doppler velocimetry data should not be

XXXI IAHR CONGRESS 3955 used without suitable post-processing and that all turbulent velocity properties are affected by the post-processing. 1.1 ACOUSTIC DOPPLER VELOCITY METROLOGY Acoustic Doppler velocimetry (ADV) is designed to record instantaneous velocity components at a single-point with a relatively high frequency. Measurements are performed by measuring the velocity of particles in a remote sampling volume based upon the Doppler shift effect (e.g. Voulgaris and Trowbridge 1998, McLelland and Nicholas 2000). The probe head includes one transmitter and three receivers. The sampling volume is located either 5 or 10 cm from the tip of the probe, but some studies showed that the distance might change slightly (e.g. Chanson et al. 2000). Its size is determined by the sampling conditions. In a standard configuration, the sampling volume is about a cylinder of water with a diameter of 6 mm and a height of 9 mm, although Wahl (2003) argued its exact shape. An ADV system records simultaneously nine values with each sample: three velocity components, three signal strength values, and three correlation values. Signal strengths and correlations are used primarily to determine the quality and accuracy of the velocity data, although the signal strength (acoustic backscatter intensity) may related to the instantaneous suspended sediment concentration with proper calibration (e.g. Fugate and Friedrichs 2002, Nikora and Goring 2002, Voulgaris and Meyers 2004). Herein the study is focused on the velocity signals. Past and present experiences demonstrated recurrent problems with "raw" ADV velocity data that are evidenced by high levels of noise and spikes in all velocity components. In turbulent flows, the ADV velocity fluctuations characterise the combined effects of the Doppler noise, signal aliasing, velocity fluctuations, installation vibrations and other disturbances. Lemmin and Lhermitte (1999) and Chanson et al. (2000,2002) discussed the inherent noise of an ADV system. Spikes may be caused by aliasing of the Doppler signal. Nikora and Goring (1998) and Goring and Nikora (2002) developed techniques to eliminate these in steady flow situations.

3956 September 11~16, 2005, Seoul, Korea Moreton Bay North Coastline

Tropic 23?27' S

QLD

Low flow channel

Field work

Salt marsh

40? S

Legend Koala sighting on 4/4/03 Sunfish sightings on 24/11/03

Tree line Orana Str eet

1 km Site 1

Point Halloran Conservation Area

Boat yards

Clevela

Site 2

Ba edland nd to R

Riffle

Site 2B

Site 3B

y Road

Site 3 Site 4 Eprapah Environmental Training Centre nu Ave n r u b Col

Point Victoria Sewage Treatment Plant

Point Hall oran Roa d

Beveridge Street

e

Fig. 1 Map of Eprapah Creek estuarine zone - Dark blue circles: water quality and fish sampling sites - Red squares: instantaneous velocity and physio-chemistry measurement sites 2. CASE STUDY: EPRAPAH CREEK ESTUARY A series of turbulent velocity measurements were conducted in the estuarine zone of Eprapah Creek (Australia) in 2003 and 2004. Eprapah Creek (Long. 153.30º, Lat. -27.567º) is a sub-tropical stream located in the Redlands shire close to Brisbane city. Eprapah Creek flows directly to the Moreton Bay at Victoria Point. It is 12.6 km long with about 3.8 km of estuarine zone (Fig. 1). Its catchment area is 39 km2. The most upstream extent of estuary corresponds to Sites 3B to 4 depending upon the tide conditions (Fig. 1). In the estuarine zone, the water depth is typically about 1 to 2 m mid-stream, the width is about 20-30 m and the tides are semi-diurnal with a typical range of about 1.5 to 2 m.

XXXI IAHR CONGRESS 3957 Field works took place on four different days (Table 1). Tidal conditions are summarised in Table 1 (2nd line). Acoustic Doppler Velocimetry was performed mid-estuary at locations AMTD 2 and 2.1 km corresponding to Sites 2 and 2B respectively, where AMTD is the upstream distance from river mouth. Both sites are shown in Fig. 1. The cross-sectional surveys are presented in Fig. 3. For each field work, a 3-D Acoustic Doppler Velocimeter (ADV) SonTek UW ADV (serial No. 0510), equipped with a 5-cm downlooking sensor mounted on a rigid stem, was deployed and data-logged continuously at 25 Hz. The velocity range was 0.3 or 1.0 m/s (Table 1). The probe was installed about the middle of the channel in a moderate bend to the right when looking downstream. The ADV was held by a stiff metallic frame sliding on two poles (Fig. 2). The poles were driven into the river bed, and the frame and pole system did not move during the data logging. The probe was installed outside of the support system to limit the effects of support wake. In the first 3 studies, the sampling volume was located 0.50 m beneath the free-surface. The probe position was manually adjusted with the tide, by lowering or raising the frame every 20 to 60 minutes, to maintain the probe sensor position relative to the free-surface (Fig. 2B). For the last study, the probe sampling volume was located 0.055 m above the bed. Further details on the experimental procedures are available in Chanson et al. (2003, 2004) and Brown et al. (2004).

Fig. 2 Acoustic Doppler velocimetry in Eprapah Creek estuary ; (A) Field study E2, Site 2, looking upstream - Boat passing next to ADV probe (arrow) around 13:30 (early ebb tide). (B) Field study E1, Site 2B, view from left bank - Vertical probe adjustment near end of flood tide. 3. VELOCITY MEASUREMENTS The acoustic Doppler velocimetry system provided instantaneous values of the three velocity components. It was oriented with the xy-plane being horizontal, the x-direction aligned with the flow direction and positive downstream, and the z-direction positive upwards.

3958 September 11~16, 2005, Seoul, Korea Typical results are shown in Fig. 4. Fig. 4 presents the Vx velocity component recorded during the field study E2 for 7 h 44 min. starting at low tide (t = 24,240 s). The velocity data are un-processed. In Fig. 4, the right vertical axis corresponds to the sampling volume depth below the free-surface. The vertical see-saw steps were manual vertical displacements of the velocimeter (Fig. 2A). Navigation events are also marked with an asterisk (*). For all field works, present experience demonstrated recurrent problems with the velocity data, including large numbers of spikes (e.g. Fig. 4, t = 39,000 to 41,000 s). Some problem was also experienced with the vertical velocity component, possibly because of the effects of the wake of the stem. Since the probe was mounted vertically down-looking, vertical velocities were small and these effects were deemed negligible. Table 1. Field investigations at Eprapah Creek in 2003 and 2004 Field study reference Date Tides (Victoria Point)

E1

4 April 2003 05:16 (0.67 m) 11:03 (2.22 m) 17:24 (0.57 m) 23:31 (2.41 m) Study period 06:00-18:00 Study focus Full tidal cycle ADV sampling 10:08-10:42 period(s) 10:43-10:44 11:45-12:18 11:19-11:57 11:58-12:29 12:29-12:52 12:53-13:11 13:12-13:53 13:53-14:09 ADV velocity range 0.3 / 1.0 / 0.3 / (m/s) 0.3 / 0.3 / 1.0 / 1.0 / 1.0 / 1.0 Sampling frequency 25 (Hz) Sampling volume Site 2B, 0.50 m location below surface, 14.2 m from left bank Water temperature (ºC) 23.7 (mid-estuary, Site 2) [20.4-28.4]

E2

E3

E4

17 July 2003 00:00 (2:63 m) 06:44 (0.60 m) 12:19 (1.92 m) 18:01 (0.59 m) 06:00-14:00 Flood tide 6:26-14:10

24 Nov. 2003 03:27 (0.21 m) 09:50 (2.74 m) 16:29 (0.46 m) 21:53 (2.11 m) 08:00-16:00 Ebb tide 8:25-15:35

2 Sept. 2004 06:02 (0.40 m) 11:52 (2.21 m) 18:02 (0.56 m) 11:59 (2.29 m) 06:00-18:00 Full tidal cycle 7:51-13:40 14:26-17:57

0.3

1.0

0.3

25

25

25

Site 2, 0.50 m below surface, 8.0 m from left bank 16.7 [15.5-18.5]

Site 2B, 0.50 m below surface, 10.8 m from left bank 25.5 [22.7-28.0]

Site 2B, 0.0525 m above bed, 10.8 m from left bank 17.14 [15.9-18.1]

XXXI IAHR CONGRESS 3959 Conductivity (mS/cm) 34.5 (mid-estuary, Site 2) [23.9-48.3]

37.2 [29.8-48.4]

50.0 [42.7-55.1]

48.6 [41.0-53.6]

Notes: water temperature and conductivity measured with YSI6600 probe; mean values [extreme values in square brackets] for the study period. Practical problems were further experienced. For the first field work, two notebook computers were used alternately to data log the ADV outputs and to backup the data. The interchange of computers lasted less than 2 minutes and was carefully recorded. During the last field study, the computer lost power and it could not be reconnected to the ADV for nearly 50 minutes. For the other field works (E2 and E3), the velocity data were recorded continuously into a single data file. Details of data records are given in Table 1. For the first three field trips, the ADV sampling volume was maintained about 0.5 m below the freesurface, implying the need to adjust the vertical probe position up to 3 times per hour at midtide (Fig. 2B). Lastly, navigation and aquatic life were observed during all field works (Fig. 2A). They were found to have some impact on the turbulence data. In a few instances, birds were seen diving and fishing next to the ADV location. Elevation (m AHD)

Right bank

1.5 1 0.5 0 -0.5 -1 -1.5 -2 -2.5 -3 -3.5 -4

High tide on 28/8/04

Site 2B 28/8/04 Site 2B 27/5/03 Site 2 16/7/03 0

5

10

15 from left20 Distance bank (m)

25

30

Fig. 3 Surveyed creek cross-sections at Sites 2 and 2B, looking downstream

35


Vx (cm/s) Sampling volume depth (cm) Navigation event

85

High tide

32

80

24

75

16

70

8

65

0

60

-8

55

-16

50

-24

45

-32

40

-40 24000

27000

30000

33000

36000 39000 Time (s)

42000

45000

48000

Sampling volume depth (cm)

Vx (cm/s)

40

35 51000

Fig. 4 Instantaneous velocity data before post-processing during the field study E2 (Vx component) and probe sampling volume depth - Time is expressed in seconds since midnight Present experience suggested that turbulence properties could not be extrapolated from the unprocessed data sets (see Discussion). Classical ADV despiking techniques were tested indepth, including acceleration thresholding and phase-space thresholding methods (Goring and Nikora 2002, Wahl 2003). The results demonstrated systematically that "conventional" ADV despiking techniques were not suitable for velocimetry data collected in a natural estuarine system. Indeed, velocity fluctuations might be induced by aquatic life, navigation and experimental procedure as observed first-hand by the writers. Even in optimum conditions, natural estuarine systems are characterised by unsteady flows, and the hydrodynamics cannot be assumed to be quasi-steady over a statistically-meaningful data sample. However the selection of more appropriate techniques is difficult since no independent data sets are available. Existing comparisons between despiking techniques are often limited to a comparison of the number of removed spikes, and of the differences in turbulent velocity fluctuations and in Reynolds stresses. 4. ADV DATA POST-PROCESSING TECHNIQUE Turbulent velocity analyses were conducted systematically for all field data. Present experience yields a new three-stage post-processing method. The post-processing technique

XXXI IAHR CONGRESS 3961 includes (1) an initial velocity signal check, (2) some "pre-filtering" and (3) some despiking. Each stage comprises two steps: velocity error detection and data replacement. (1) Velocity signal check. The ADV velocity data are "cleaned" by removing communication errors, low signal-to-noise ratio data (< 5 dB) and low correlation samples (< 70%). (2) "Pre-filtering" (Event detection and removal). The effects of major disturbances are removed. Such disturbances may include navigation, probe movement, aquatic life activities. For each velocity component, the signal is filtered with a low-pass/high-pass filter threshold F (0.001 ≤ F ≤ 1 Hz, Fref = 0.1 Hz). The occurrence of navigation, probe motion and other events is tested by comparing the ratio of local standard deviation to the event search region standard deviation of high-pass filtered signal with a threshold value CE (1.2 ≤ CE ≤ 1.8, CEref = 1.5). Exceeding implies disturbance. Note that local standard deviations are calculated for WS data points (100 ≤ WS ≤ 5000, WSref = 1000). (3) Despiking. The phase-space thresholding technique is used. For each velocity component, the signal is filtered with a low-pass/high-pass filter threshold F (0.001 ≤ F ≤ 1 Hz, Fref = 0.1 Hz). The same frequency threshold F is used for "pre-filtering" and despiking. The high-pass filtered signal is tested with an 'universal' criterion (Goring and Nikora 2002). In Stages 1, 2 and 3, all erroneous data are replaced by an overall mean of the signal between end points. This technique was selected for its simplicity, reliability and suitability to very-large data sets. Replacement is performed on the velocity signal in Stage 2 and on the high-pass filtered signal in Stage 3. Stage 3 is iterated until the number of errors converge to zero. At the end of Stage 3, the low-passed filtered signals are added back in before further turbulence analysis. Further, all velocity components are considered erroneous if anyone velocity component is replaced in Stages 1, 2 or 3. The justification is based upon the ADV transformation of radial velocities into Cartesian coordinates, implying that a corrupted Cartesian velocity component must derive from corrupted radial components (e.g. McLelland and Nicholas 2000). In Stage 3, present experience and data analyses suggest that the initial pre-filtering phase is most important for estuarine data sets. Further the acceleration thresholding technique was thoroughly tested with acceleration threshold criterion a between 0.012 and 1.5. The technique seems not suited to the estuarine flow conditions, while the phase-space thresholding method appears more robust. 5. DISCUSSIONS The new ADV post-processing method was developed based upon the experience gained during the study E1, and it was successfully validated with the data sets E2, E3 and E4. A systematic sensitivity analysis was conducted for all listed parameters within the indicated ranges (see previous section). For the tested data sets, optimum coefficients are deduced and they are given with the subscript "ref" (for reference) above. Importantly it was found that the selection of the low-pass/high-pass filter frequency threshold F has a significant effect on the pre-filtering, but little impact on the despiking. Frequency thresholds within 0.1 to 0.01 Hz


-2

2

-5

-1

-8

-4

-11

-7

Vx Unprocessed

-14 28100

Vx Post-processed 28200

28300

28400

28500

28600

28700

28800

28900

29000

-10 29100

Vx (cm/s) Post-processed

Vx (cm/s) Unprocessed

were found most suitable for this small estuarine system. It is likely that the optimum parameter F is a function of topographic and hydrodynamic characteristics of the estuary.

Vx Unprocessed

-5 -10 -15 -20

5 0 -5 -10

Vx Post-processed

-25 -30 -35 -40 33100

33200

33300

33400

33500

33600

33700

33800

33900

34000

-15 -20 -25 -30 34100



T ime (s)

T ime (s) Vx Unprocessed 0

20

-10

10

-20

0

-30

-10

-40

-20 39150

39250

39350

39450

39550

39650

39750

39850

39950

40050

-50 40150



Vx Post-processed 30

T ime (s)

Fig. 5 Comparison of original and post-processed velocity signals - Field study E2, Vx velocity component - Time is expressed in seconds since midnight (GPS time) Fig. 5 illustrates some comparison of the velocity signal for three 1000 seconds segments before and after post-processing. In each graph, the curves are offset vertically for clarity and the range of both vertical scales is the same (left axis for un-processed data and right axis for post-processed data), although the range differs between Figs. 5A, 5B and 5C. Fig. 5A corresponds to the early flood tide; Fig. 5B, the mid flood tide; Fig. 5C, the end of flood tide (Fig. 4). For these 1000 seconds samples, about 1%, 2% and 18% of data points were replaced respectively. However Fig. 5C illustrates a situation corresponding to some problem with the instrumentation, for which we should have no confidence in all velocity data set, unless they

XXXI IAHR CONGRESS 3963 are validated with an independent instrument. Table 2 lists the statistical properties of each velocity component for the same data sets before and after post-processing. The results illustrate the impact of post-processing on all turbulent flow properties, including on the timeaverage velocity components. Table 2 Turbulent velocity statistics for three time intervals (Field study E2): (1) t = 28,148 to 29,148 s; (2) t = 33,148 to 34,148 s; (3) t = 39,148 to 40,148 s (expressed since midnight, GPS time) Un-processed Post-processed Remarks Vx Vy Vz Vx Vy Vz (A)Average t = 28148 to 29148 -5.203 0.322 -0.254 -5.210 0.321 -0.255 (cm/s) s (A) Std dev. 1.388 0.610 0.142 1.374 0.607 0.140 1.1% of data errors (cm/s) (A) Skewness -0.909 0.0214 -0.306 -0.965 0.020 -0.342 (A) Kurtosis 0.856 -0.476 0.710 0.809 -0.501 0.620 Excess kurtosis (B) Average (cm/s) (B) Std dev. (cm/s) (B) Skewness (B) Kurtosis

t = 33148 to 34148 s

-21.21

3.566

-1.499 -21.21

3.567

-1.500

3.293

2.234

1.608 3.276

2.220

1.586 2.0% of data errors

0.241 0.0853 -0.191 0.234 -0.196 -0.0431 1.389 -0.270

0.080 -0.109

-0.209 1.151

-6.066

0.675

1.191

-0.995

4.99

3.20

1.36

4.729

2.410

(C) Skewness

0.421

-4.34

0.423 0.328

-0.341

(C) Kurtosis

10.37

162.7

80.2 -0.269

0.104

(C) Average (cm/s) (C) Std dev. (cm/s)

-0.982 -4.858

Excess kurtosis

t = 39148 to 40148 s 18.4% of data 0.683 errors, but 99.9% data error on 0.031 Vx 1.368 Excess kurtosis

Table 3 Post-processing of acoustic Doppler velocity data during the entire field studies E2, E3 and E4: summary of each post-processing stage Field study Total Number of data points (1) Number data points with communication errors, low signal to noise ratio and low correlation

Study E2 Study E3 Study E4 (17/07/2003) (24/11/2003) (2/9/2004) 696,129 5,580

593,297 12,762

841,807 441

Single data file. Using WindADV.

3964 September 11~16, 2005, Seoul, Korea (1)+(2) Number of removed/replaced data points after "pre-filtering" (1)+(2)+(3) Number of removed/replaced data points after "pre-filtering" & despiking (1)+(3) Number of removed/replaced data points after despiking BUT NO "prefiltering"

83,847

66,820

25,572

137,181

75,938

86,779

Complete postprocessing.

56,069

24,248

58,769

Improper postprocessing without "pre-filtering".

The post-processing technique was applied thoroughly to the field studies E2, E3 and E4 using the reference post-processing coefficients. The total number of erroneous data points is listed in Table 3 for each field study. In Table 3, the first line gives the total number of data points per velocity component. The second and third lines are respectively the number of data errors after velocity signal check, and after velocity signal check and "pre-filtering". The fourth line presents to total number of data errors after the entire three-stages post-processing method. For comparison, the last line gives the number of data errors after an improper postprocessing, performed without "pre-filtering". For the field trip E2, such an improper postprocessing would accept 81,112 erroneous data points, that would be otherwise rejected by the new post-processing method. This would represent nearly 12% of erroneous data in the entire data set ! Comparative turbulence analyses of unprocessed and post-processed signals were conducted systematically in terms of the first four statistical moments (mean, standard deviation. skewness and kurtosis) of each velocity component and of the Reynolds stresses. Statistical quantities were integrated over 5,000 data points corresponding to 3 min. 20 s, and calculations were repeated along each data set. Systematic comparisons demonstrated that all turbulence characteristics were affected by the post-processing (e.g. Table 2). In plain words, turbulent properties including the time-average velocity were improperly estimated from unprocessed data sets. More generally, the results highlighted that turbulent velocities in unsteady estuarine flows could not be simply deduced from unprocessed acoustic Doppler velocimetry data. 6. SUMMARY AND CONCLUDING REMARKS This study is focused on the analysis of turbulent velocity measurements in small estuarine systems. Past and present experience have shown that acoustic Doppler velocimetry (ADV) is a well-suited metrology for such shallow-water systems. Long-duration velocity records were conducted at high frequency in such a small estuary. Herein the data analysis shows conclusively that turbulence properties cannot be derived from unprocessed ADV signals and

XXXI IAHR CONGRESS 3965 that even "classical" despiking methods are not directly applicable to unsteady estuary flows. Instead a detailed post-processing technique is developed and applied. A new three-stages post-processing method is presented. The technique includes (1) an initial velocity signal check, (2) some "pre-filtering" and (3) some despiking, while each stage includes velocity error detection and data replacement. The method is applied to three longduration field studies. Reference coefficients are derived for a small subtropical estuary. Comparative analyses of un-processed, "despiked-only", and post-processed velocity data highlight the necessity for an advanced post-processing method. While the acoustic Doppler velocimetry is a relatively simple technique, present results demonstrate that unprocessed ADV data should not be used, even for a study of time-averaged velocity components. Importantly, further field data are necessary to validate the post-processing technique, by comparing post-processed data with independent data acquired simultaneously at the same location in the natural system. At present, the selection of more appropriate techniques is intricate since no independent data set (i.e. 'true data set") is available. Comparisons between post-processing techniques are basically limited to an assessment of the number of removed spikes, and some subjective evaluation of differences in turbulent velocity properties. ACKNOWLEDGMENTS The writers thank Dr Richard Brown (QUT), Dr Ian Ramsay (Qld EPA) and John Ferris (Qld EPA) for their contributions. They acknowledge the technical assistance of Dave McIntosh (QUT) and Clive Booth (UQ). Hubert Chanson acknowledges the assistance of all field work participants, in particular his CIVL4140 and CIVL4120 students and the ECCLA group. REFERENCES Bowden, K.F., and Ferguson, S.R. (1980). "Variations with Height of the Turbulence in a Tidally-Induced Bottom Boundary Layer." Marine Turbulence, J.C.J. NIHOUL, Ed., Elsevier, Amsterdam, The Netherlands, pp. 259-286. Brown, R., Ferris, J., Warburton, K., and Chanson, H. (2004). "Hydrodynamic, Water Quality and Ecological Study of Eprapah Creek Estuarine Zone: a Multi-Disciplinary, CrossInstitutional Approach." Proc. 8th National Conference on Hydraulics in Water Engineering, IEAust., Gold Coast, Australia, H. Chanson and J. Macintosh Ed., 8 pages (CD-ROM). Chanson, H. (2004). "Environmental Hydraulics of Open Channel Flows." Elsevier Butterworth-Heinemann, Oxford, UK, 483 pages (ISBN 0 7506 6165 8). Chanson, H., Aoki, S., and Maruyama, M. (2000). "Unsteady Two-Dimensional Orifice Flow: an Experimental Study." Coastal/Ocean Engineering Report, No. COE00-1, Dept. of Architecture and Civil Eng., Toyohashi University of Technology, Japan, 29 pages. Chanson, H., Aoki, S., and Maruyama, M. (2002). "Unsteady Two-Dimensional Orifice Flow: a Large-Size Experimental Investigation." Jl of Hyd. Res., IAHR, Vol. 40, No. 1, pp. 63-71. Chanson, H., Brown, R., Ferris, J., and Warburton, K. (2003). "A Hydraulic, Environmental and Ecological Assessment of a Sub-tropical Stream in Eastern Australia: Eprapah Creek,

3966 September 11~16, 2005, Seoul, Korea Victoria Point QLD on 4 April 2003." Report No. CH52/03, Dept. of Civil Engineering, The University of Queensland, Brisbane, Australia, June, 189 pages. Chanson, H. Brown, R., and Ferris, J. (2004). "Simultaneous Field Measurements of Turbulence and Water Quality in a Sub-Tropical Estuary in Australia." Proc. 15th Australasian Fluid Mech. Conf., AFMC, Sydney, Australia, M. Behnia, W. LIN & G.D. McBain Ed., Paper AFMC00016, 4 pages (CD-ROM). Fischer, H.B., List, E.J., Koh, R.C.Y., Imberger, J., and Brooks, N.H. (1979). "Mixing in Inland and Coastal Waters." Academic Press, New York, USA. Fugate, D.C., and Friedrichs, C.T. (2002). "Determining Concentration and Fall Velocity of Estuarine Particle Populations using ADV, OBS and LISST." Continental Shelf Research, Vol. 22, pp. 1867-1886. Goring, D.G., and Nikora, V.I. (2002). "Despiking Acoustic Doppler Velocimeter Data." Jl of Hyd. Engrg., ASCE, Vol. 128, No. 1, pp. 117-126. Discussion: Vol. 129, No. 6, pp. 484489. Ippen, A.T. (1966). "Estuary and Coastal Hydrodynamics." McGraw-Hill, New York, USA. Kawanisi, K., and Yokosi, S. (1997). "Characteristics of Suspended Sediment and Turbulence in a Tidal Boundary Layer." Continental Shelf Research, Vol. 17, No. 8, pp. 859-875. Lemmin, U., and Lhermitte, R. (1999). "ADV Measurements of Turbulence: can we Improve their Interpretation ? Discussion." Jl of Hyd. Engrg., ASCE, Vol. 125, No. 6, pp. 987-988. Lewis, R. (1997). "Dispersion in Estuaries and Coastal Waters." John Wiley, Chichester, UK, 312 p. McLelland, S.J., and Nicholas, A.P. (2000). "A New Method for Evaluating Errors in HighFrequency ADV Measurements." Hydrological Processes, Vol. 14, pp. 351-366. Nikora, V.I., and Goring, D.G. (1998). "ADV Measurements of Turbulence: can we Improve their Interpretation ?" Jl of Hyd. Engrg., ASCE, Vol. 124, No. 6, pp. 630-634. Nikora, V., and Goring, D. (2002). "Fluctuations of Suspended Sediment Concentration and Turbulent Sediment Fluxes in an Open-Channel Flow." Jl of Hydr. Engrg., ASCE, Vol. 128, No. 2, pp. 214-224. Rutherford, J.C. (1994). "River Mixing." John Wiley, Chichester, USA, 347 pages. Voulgaris, G., and Trowbridge, J.H. (1998). "Evaluation of the Acoustic Doppler Velocimeter (ADV) for Turbulence Measurements." Jl Atmosph. and Oceanic Tech., Vol. 15, pp. 272289. Voulgaris, G., and Meyers, S.T. (2004). "Temporal Variability of Hydrodynamics, Sediment Concentration and Sediment Settling in a Tidal Creek." Continental Shelf Research, Vol. 24, pp. 1659-1683. Wahl, T.L. (2003). "Despiking Acoustic Doppler Velocimeter Data. Discussion." Jl of Hyd. Engrg., ASCE, Vol. 129, No. 6, pp. 484-487.