T. Haji Mohammadloo
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17 records found
1
The impressive growth of the aviation industry and the number of flights entail several environmental repercussions, such as increased aircraft noise emissions. With the worrying number of complaints from the communities around airports comes also the distrust in numerical models used for aircraft noise prediction. In this study, we compare the ‘Dutch aircraft noise model’ predictions to measured values from the NOise MOnitoring System (NOMOS) around Amsterdam Airport Schiphol between 2012 and 2018. While the model underestimates aircraft noise in 2012, the model prediction improved throughout the years. We observe a decreasing trend of measured aircraft-related Lden values of 0.6dB(A)/year (a total of 3.6dB(A) over the investigation period), although the total number of flight movements increased during the observation time. We propose that a change in fleet mix, as well as the implementation of Noise Abatement Procedures at Schiphol Airport, fuelled this trend.
Multi-frequency multibeam backscatter (BS) has indicated, in particular for fine sediments, the potential for increasing the discrimination between different seabed environments. Fine sediments are expected to have a varying signal penetration within the frequency range of modern multibeam echosounders (MBESs). Therefore, it is unknown to what extent the multispectral MBES data represent the surface of the seabed or different parts of the subsurface. Here, the effect of signal penetration on the measured multi-frequency BS and bathymetry is investigated. To this end, two multi-frequency datasets (90 to 450 kHz) were acquired with an R2Sonic 2026 MBES, supported by ground-truthing, in the Vlietland Lake and Port of Rotterdam (The Netherlands). In addition, a model to simulate the MBES bathymetric measurements in a layered medium is developed. The measured bathymetry difference between the lowest (90 kHz) and highest frequency (450 kHz) in areas with muddy sediments reaches values up to 60 cm dependent on the location and incident angle. In spatial correspondence with the variation in the depth difference, the BS level at the lowest frequency varies by up to 15 dB for the muddy sediments while the BS at the highest frequency shows only small variations. A comparison of the acoustic results with the ground-truthing, geological setting and model indicates that the measured bathymetry and BS at the different frequencies correspond to different parts of the seabed. However, the low-frequency BS cannot be directly related to a subsurface layer because of a significant sound attenuation in the upper layer. The simulation of the MBES bottom detection indicates that the bathymetry measured at the highest and lowest frequency can be used to determine the thickness of thin layers (20 cm). However, with an increasing layer thickness, the bottom detection becomes more sensitive to the incident angle and small variations in the sediment properties. Consequently, an accurate determination of the layer thickness is hampered. Based on this study, it is highly recommended to analyze multi-frequency BS in combination with the inter-frequency bathymetry difference to ensure a correct interpretation and classification of multi-frequency BS data.
Realistic predictions of the contribution of the various sources affecting the quality of the bathymetric measurements prior to a survey are of importance to ensure sufficient accuracy of the soundings. To this end, models predicting these contributions have been developed. The objective of the present paper is to assess the performance of the bathymetric uncertainty prediction model for modern Multi-Beam Echo-Sounder (MBES) systems. Two datasets were acquired at water depths of 10m and 30m with three pulse lengths equaling 27 μs, 54 μs, and 134 μs in the Oosterschelde estuary (The Netherlands). The comparison between the bathymetric uncertainties derived from the measurements and those predicted using the current model indicated a relatively good agreement except for the most outer beams. The performance of the uncertainty prediction model improved by accounting for the most recent insights into the contributors to the MBES depth uncertainties, i.e., the Doppler effect, baseline decorrelation (accounting for the pulse shape), and the signal-to-noise ratio.
Methods for gridding multibeam echo sounder (MBES) measurements to equidistant grids are proposed as alternatives to the shallowest measured depth, which is affected by outliers. The approaches considered use a combination of mean and standard deviation of soundings and the regression coefficient from the best fitted plane. These methods along with mean and shallowest depths were applied to two surveyed areas. Two issues were found to be of importance, that is, a proper distribution of soundings and low uncertainties in the depth measurements. Improper sampling excludes using the method employing regression coefficients. For flat areas, the shallowest measured depth was found to be highly influenced by measurement uncertainties, counteracted when using the mean depth. However, the mean depth underestimates the shallowest depth for areas with slopes. When correcting the mean depth for standard deviation, the effect of slopes is accounted for while the influence of measurement uncertainties is decreased compared to shallowest measured depth. Since the uncertainties are dependent on beam angle, depth, and measurement equipment, these issues need to be accounted for in survey planning.
Comparing Modeled and Measured Bathymetric Uncertainties
Effect of Doppler and Baseline Decorrelation
In this contribution a method for correcting bathymetric measurements affected by inaccurate water column sound speed profiles (SSPs) is presented. The method exploits the redundancy in the multibeam echosounder measurements obtained from the overlap of adjacent swaths by minimizing the difference between depths along overlapping swaths. Two optimization methods are used, i.e., Differential Evolution (DE) and Gauss-Newton (GN). While DE inverts for the sound speed by minimizing the depth variation, GN inverts for both bathymetry and sound speed by minimizing the squared sum of the differences between the modeled and measured travel times. The inversion method assumes a constant SSP in the water column. Applying the method to a salt wedge survey area with large variations in the water column sound speed indicates a good agreement between the original depth measurements and those derived after the inversion with the mean and standard deviation of the depth differences equaling 0.009m and 0.024m, respectively. This indicates that even with a simple parametrization of the sound speed in the water column, the correct bathymetry can be derived from the inversion. The SSP inversion method is also applied to an area with existing refraction artefacts. It corrects the bathymetry and reduces the mean and standard deviation of the depth standard deviation by a factor of around 2.75 compared to the case where the measured SSPs were used. Furthermore, the SSP inversion method neither manipulates the existing morphology nor introduces artificial bathymetric features in the areas where such refraction artefacts are not present. Considering constant SSPs, both DE and GN give almost identical results with GN being faster. However, GN is less flexible with regards to varying sound speed parameterizations.
Multi-beam echo-sounder bathymetric measurements
Implications of using frequency modulated pulses
In this contribution bathymetric uncertainties induced by the use of frequency modulated (FM) signals for multi-beam-echo-sounder (MBES) measurements are quantified and their relevance for MBES bathymetric uncertainty predictions is assessed. When switching to FM, the quality of depth measurements can get deteriorated due to the Doppler effect and baseline decorrelation. The uncertainty due to the former is divided into second-order (imperfectness of the Doppler-range correction) and first-order (effect on beamsteering) effects. The latter also holds for continuous wave (CW) signals. Here, situations of relevance for measurements in the continental shelf and ship dynamics associated to rough and calm sea-states are considered, and the vertical uncertainty induced by the above sources is quantified. The influence of the Doppler effect depends on the sea state, but is found to potentially have a significant contribution to the MBES error budget for both FM and CW [nearly 82% (rough) and 68% (calm) of the total uncertainty]. The effect of baseline decorrelation depends on the actual pulse shape. For the specifications investigated, vertical uncertainties induced by this source are predicted to be larger for FM than that of CW. This is confirmed by a comparison between the modelled and measured effect on depth uncertainties when switching to FM.
n=1,2,…,8 days, are identified in multivariate spectra of both data sets. The oscillation of the draconitic signal is reduced by factors of 1.87, 1.87, and 1.68 in the east, north and up components, respectively. Two other signals with Chandlerian period and a period of 380 days can also be detected. ...
n=1,2,…,8 days, are identified in multivariate spectra of both data sets. The oscillation of the draconitic signal is reduced by factors of 1.87, 1.87, and 1.68 in the east, north and up components, respectively. Two other signals with Chandlerian period and a period of 380 days can also be detected.