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Tilt current meter array: Field validation

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Tilt current meter array: Field validation

MAX RADERMACHER(1), ZANE THACKERAY(2), MATTHIEU DE SCHIPPER(1), LEIGH GORDON(2), CLINTON CHRYSTAL(3), RIO

LEUCI(2) & AD RENIERS(1) (1)

Civil Engineering & Geosciences, Delft University of Technology, Delft, Netherlands, m.radermacher@tudelft.nl

(2) Environmental Mapping & Surveying, Durban, South-Africa

(3) Coastal, Stormwater & Catchment Management, eThekwini Municipality, Durban, South-Africa

ABSTRACT

Measurements of nearshore currents can be performed using a range of existing measurement techniques. Although every technique has its specific benefits, capturing strong spatial gradients in a flow field with sufficiently high spatial resolution often proves to be difficult due to high costs or practical difficulties associated with these techniques. In this study, the use of an array of Tilt Current Meters is explored as a way of measuring these spatial gradients. Observed tilt angle and direction have a high correlation with flow velocity magnitude and direction measured with acoustic instruments. Furthermore, the capabilities of a dense spatial grid of Tilt Current Meters are demonstrated in a spatially variable flow field.

Keywords: Field measurements, Nearshore currents, Instrumentation, Tilt Current Meter

1. INTRODUCTION

Measuring and analyzing flow fields in the nearshore area is often found to be a difficult task. Complex bathymetric patterns, like shoals, bars, channels, reefs, groynes or breakwaters have a large impact on nearshore currents and often give rise to a complex flow field with large spatial and temporal gradients. Various in-situ measurement techniques are available, all having their own benefits and drawbacks. Acoustic or electromagnetic sensors, inferring Eulerian flow velocity in a point or along a straight line, can achieve a high accuracy and a high resolution in time, but yield limited spatial resolution because of the high costs per unit and the effort required to rigidly mount them on the sea bed. GPS-tracked Lagrangian instruments, commonly referred to as ‘drifters’ (e.g. MacMahan et al., 2009), are advected with near-surface flows and are therefore able to measure currents over a large area. However, as drifters still only measure along a line in the space-time continuum, they perform best in (quasi-)stationary flow fields. Furthermore, the continuous involvement of a considerable field crew for deployment and recovery of drifters restricts the duration of a drifter campaign.

Flow fields can as well be measured using tilt as a proxy for currents, as was done by Sheremet (2010), Marchant et al. (2014) and Korotkina et al. (2014). Such a Tilt Current Meter (TCM) consists of a tilt-corrected compass in a buoyant casing, attached to a mooring (e.g. a small concrete tile) at the seabed. When exposed to a current, the casing tilts under influence of its own drag and the tilt magnitude and direction can be related to the flow velocity and direction. TCM’s have relatively low costs per unit, allowing for deployment of many units in one campaign. This yields a combination of high spatial resolution, large spatial extent and long temporal duration. This study aims to explore the accuracy of tilt as a measure for flow velocity. Uncertainties about the achievable temporal resolution are omitted here by averaging in time over several minutes. Furthermore, the potential of deploying an array of TCM’s is demonstrated.

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2. METHODOLOGY

For the purpose of measuring nearshore currents with a high spatial resolution, long duration and large spatial extent, a set of 42 TCM’s was constructed, see Figure 1. Inside the custom-made cylindrical plastic housing a single-board micro controller was placed, running a tilt-corrected compass. After calibration, compass readings yield heading with respect to magnetic North and pitch and roll with respect to the unit’s intrinsic coordinate system.

The compass sampled at 4Hz in bursts of 1024 samples (4 minutes and 16 seconds), every new burst starting 5 minutes after the start of the previous burst. The housing was attached flexibly to a 4kg concrete anchor plate. The total height of a unit in upright position was approximately 50 cm. When submerged, the buoyancy of the housing keeps it in a vertical orientation. In the presence of an ambient current, the housing tilts under influence of its own drag. The static tilt angle obtained by the housing in case of a stationary current is a balance between drag, buoyancy and mooring tension. Time-averaging of the east and north components of the tilt angle on a scale much longer than a short wave period yields a mean tilt magnitude and direction close to the static response.

Deployment was done from a small vessel by dropping the units down from the surface at the desired GPS position. The weight of the tile and the buoyancy of the casing made sure that the TCM’s landed on the bed in upright position. All TCM’s were marked with a small (2 Liter) buoy, that was attached to a second tile, connected to the first tile by a line. The second tile was needed to keep the buoy line at a distance and avoid tangling of the line and the TCM housing.

The full set of 42 TCM’s was deployed twice during the Mega Perturbation Experiment (MegaPEX) in fall 2014 at the Sand Motor mega-nourishment in the Netherlands (Stive et al., 2013). Tidal currents in alongshore direction interact with the hook-shaped beach nourishment (~21 Mm3 of nourished sand), making it an interesting study area with potentially large spatial and temporal gradients in the flow field. A grid of 10 Acoustic Doppler Current Profilers (ADCP’s) was also part of the measurement campaign, allowing for calibration and accuracy estimation of the TCM’s. An overview of the instrument positions is given in Figure 2.

Figure 2. Location of the Sand Motor and instrument setup during the MegaPEX field campaign. Shading represents bed level in meters with respect to the Dutch datum (~ mean sea level).

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3. RESULTS

The first TCM deployment had a duration of 115 hours (28 September – 3 October) and yielded 9 TCM-ADCP pairs for comparison. Time series of the pair with the highest correlation between tilt magnitude and flow velocity are shown in Figure 3. ADCP A3 is the shallowest station in the western cross-shore array. The bottom bin of the measured velocity profile is used, which stretches between 0.26-0.61 cm from the bed. This roughly coincides with the part of the velocity profile which acts on the TCM housing. The upper panel represents simultaneous measurements of 5-minute averaged TCM tilt magnitude (green line, right axis) and 5-minute averaged ADCP flow velocity magnitude in the lower ADCP bin (blue line, left axis). Tidal water level gradients are the main forcing mechanism for the currents measured near the Sand Motor, resulting in a tidal modulation of the flow quantities (refer to the lower panel for the filtered water level as measured with the ADCP). There is a remarkable resemblance between both parameters. Consecutive peak values scale proportionally for both instruments. The tilt magnitude also follows a large part of the variability in the velocity magnitude on timescales shorter than the tidal period. Only the smallest scales that are present in these 5-minute averaged series seem to exhibit larger deviations.

In the middle panel, compass directions (0 degrees North, clockwise increasing) of tilt and flow velocity are presented. Generally, tilt direction is in agreement with the tidally modulating flow direction. As flow direction is ill-defined during low velocities associated with slack tide, the periods of flow reversal show less resemblance between both series.

Figure 3. Time series of velocity magnitude and direction (ADCP) versus tilt magnitude and direction (TCM). The lower panel shows water levels as observed with the ADCP. All series represent 5-minute averages.

A direct comparison of both instruments regarding measured magnitude and direction is presented in Figure 4. Tilt magnitude has a strong correlation with flow velocity magnitude (left panel), but the relation between both parameters is not fully linear for the range of parameter values considered here. A comparison of tilt direction and flow velocity direction seems to exhibit larger deviations (right panel). However, since compass directions are circular, data points located in the shaded areas may be mapped (phase shifted by 360 degrees) to a corresponding location in the unshaded area. This yields a correlation coefficient in the same order as the correlation of magnitudes. There is a bias of 9.8° towards high tilt direction, which is possibly related to imperfect compass calibration of either instrument.

As mentioned in the introduction, the unique selling point of TCM’s compared to other instrumentation is their ability to capture highly dynamic flow fields with a high spatial resolution. This property is illustrated using a snapshot of measured tilt at all stations during the second TCM deployment, see Figure 5. Tilt vector arrows show part of a separating tidal flow field at the lee side of the Sand Motor during flood flow (Radermacher et al., submitted). Near the tip of the Sand Motor, the main flow turns obliquely off-shore, creating a shadow zone further to the North-West.

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Figure 4. Direct comparison of flow quantities observed with TCM and ADCP. The left panel shows tilt magnitude versus flow velocity magnitude, the right panel shows tilt direction versus flow velocity direction. Colors indicate the density of data points.

Figure 5. Spatial view of 5-minute averaged tilt magnitude and direction during the flood period. Colors and contour lines (0 m to -4 m w.r.t. mean sea level) indicate underlying bathymetry.

4. DISCUSSION

The direct comparison between measured tilt magnitude and flow velocity magnitude, which was presented in the previous section, illustrates a fairly strong relationship between both parameters. It was noted that this relation is not perfectly linear. For higher flow velocities than considered in this study, tilt magnitude should asymptotically approach zero. As a first order approximation, an appropriate fitting function can be determined from the static balance of forces (Marchant et al., 2014).

Several factors could potentially disturb the determination of such a general relationship. Mechanical second order effects account for a variable drag coefficient and frontal surface area of the TCM housing as a function of its tilt angle. Furthermore, the connection between the TCM and its mooring might have a significant stiffness, which increases for larger tilt angles. Due to practical concerns, it is rather difficult to locate a TCM within several meters of a reference instrument without diving assistance. Spatial gradients in the flow field (see Figure 5) introduce deviations and potentially a bias in the comparison of flow velocities and tilt angles. In a marine environment, the presence of waves and even wave breaking in the nearshore adds to that complexity.

These aspects will be addressed in further research, aiming to (1) establish a suitable relationship between tilt angle and flow velocity, (2) determine the accuracy of this relationship and of tilt directions with respect to flow directions and (3)

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5. CONCLUSIONS

A set of 42 Tilt Current Meters was deployed in the nearshore area around the Sand Motor mega-nourishment in the Netherlands. Acoustic Doppler Current Profilers were used for comparison of measured tilt and flow velocity quantities. Strong correlations were found between flow velocity magnitude and tilt magnitude, as well as between flow velocity direction and tilt direction. Several processes introduce non-linearities in the relation between velocity magnitude and tilt magnitude. Fitting of a non-linear relationship between both parameters might yield even higher correlations, allowing for a better prediction of flow velocities using TCM’s.

Using a large set of TCM’s it is possible to observe spatial gradients in a highly variable flow field, as was demonstrated with the separating tidal flow field at the lee side of the Sand Motor. This is the main added value of TCM’s with respect to the existing range of instruments.

Future efforts will be directed at quantifying the accuracy of flow velocities derived with a TCM. The modulation of flow quantities over a large range of timescales promotes a timescale dependent analysis.

ACKNOWLEDGMENTS

MR was supported by STW Nature-driven nourishments of coastal systems (NatureCoast), S1: Coastal Safety, STW projectnr. 12686. MdS was supported by ERC-Advanced Grant 291206 - Nearshore Monitoring and Modeling (NEMO). We thank our colleagues who assisted in the field: Ronald, Roeland, Tycho, Rosaura and Bonnie. Furthermore, we thank the Naval Postgraduate School and Rijkswaterstaat for the use of their current profilers.

REFERENCES

Korotkina, O. A., Zavialov, P. O. and Osadchiev, A. A. 2014. Synoptic variability of currents in the coastal waters of Sochi. Oceanology, 54(5), 545-556.

MacMahan, J., Brown, J. and Thornton, E. 2009. Low-Cost Handheld Global Positioning System for Measuring Surf-Zone Currents. Journal of Coastal Research, 253, 744-754.

Marchant, R., Stevens, T., Choukroun, S., Coombes, R., Santarossa, M., Whinney, J. and Ridd, P. 2014. A buoyant tethered sphere for marine current estimation. IEEE Journal of Oceanic Engineering, 39(1), 2-9.

Radermacher, M., Zeelenberg, W., De Schipper, M. A. and Reniers, A. J. H. M. 2015. Field observations of tidal flow separation at a mega-scale beach nourishment. Submitted to Proceedings of Coastal Sediments 2015, San Diego, CA.

Sheremet, V. A. 2010. Observations of near-bottom currents with low-cost seahorse tilt current meters. Technical report, Graduate School of Oceanography, University of Rhode Island, RI.

Stive, M. J. F., De Schipper, M. A., Luijendijk, A. P., Aarninkhof, S. G. J., Van Gelder-Maas, C., Van Thiel de Vries, J. S. M., De Vries, S., Henriquez, M., Marx, S. and Ranasinghe, R. 2013. A New Alternative to Saving Our Beaches from Sea-Level Rise: The Sand Engine. Journal of Coastal Research, 29(5), 1001-1008.

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