Water Depth Estimation Research Articles

Planning Navigation in Inland Waterways with Tidal Depth Restrictions

The planning of vessel navigation along a tidal river is a complex task that can affect the efficiency of inland ports and intermodal chains. The availability of water may represent a significant restriction to port accessibility, having an impact on waiting times, cost and even safety. This paper presents a heuristic procedure to schedule vessels on a tidal waterway, which seeks to optimise navigation according to a multi-criteria objective function combining the number of vessels serviced, the total waiting time, the waterway occupation time and the number of crossing operations, where the term “crossing” implies inbound and outbound vessels passing each other. The procedure requires a previous step of estimation of real-time water depth, which identifies the critical points or navigation bottlenecks along the waterway, and contemplates the possibility of vessels having to anchor in the middle of their journey and wait for next tide rise. We validate the procedure through its application to a set of real and test problems and show that its results are reliable in terms of performance and solution quality.

Backreef and beach carbonate sediments of the Red Sea, Saudi Arabia: impacts of reef geometry and currents on sediment composition

Three sites in the Red Sea were investigated to assess the variability of composition in Holocene sediments of the backreef environment within 0–2 m of water depth. This is important because composition of the sediment is commonly used to estimate water depth in ancient carbonate rocks. The site located at the King Abdullah Economic City (Saudi Arabia) contains a fringing reef with the reef tract located very close to the beach at the north end, flaring to the south to produce a narrower backreef area compared to the other two sites. This geometry produces a north to south current with a velocity of up to 15 cm s−1, particularly during high onshore winds. The sediments contain predominantly non-skeletal grains, including peloids, coated grains, ooids, and grapestones that form on the bottom. The percentage of coralgal grains in the sediment was significantly lower than at the other two sites studied. Om Al Misk Island and Shoaiba have a much lower-velocity current within the backreef zone and contain predominantly coralgal sediments from the beach to the landward edge of the reef tract. The two locations containing the predominantly coralgal microfacies were statistically similar, but the King Abdullah Economic City site was statistically different despite having a similar water depth profile. Slight differences in reef configuration, including reef orientation and distance from the shore, can produce considerable differences in sediment thickness and composition within the backreef environment, which should induce caution in the interpretation of water depth in ancient carbonate rocks using composition.

IN-SITU MEASUREMENT OF DIFFUSE ATTENUATION COEFFICIENT AND ITS RELATIONSHIP WITH WATER CONSTITUENT AND DEPTH ESTIMATION OF SHALLOW WATERS BY REMOTE SENSING TECHNIQUE

Diffuse attenuation coefficient, Kd(λ), has an empirical relationship with water depth, thus potentially to be used to estimate the depth of the water based on the light penetration in the water column. The aim of this research is to assess the relationship of diffuse attenuation coefficient with the water constituent and its relationship to estimate the depth of shallow waters of Air Island, Panggang Island and Karang Lebar lagoons and to compare the result of depth estimation from Kd model and derived from Landsat 8 imagery. The measurement of Kd(λ) was carried out using hyperspectral spectroradiometer TriOS-RAMSES with range 320 – 950 nm. The relationship between measurement Kd(λ) on study site with the water constituent was the occurrence of absorption by chlorophyll-a concentration at the blue and green spectral wavelength. Depth estimation using band ratio from Kd(λ) occurred at 442,96 nm and 654,59 nm, which had better relationship with the depth from in-situ measurement compared to the estimation based on Landsat 8 band ratio. Depth estimated based on Kd(λ) ratio and in-situ measurement are not significantly different statistically. Depth estimated based on Kd(λ) ratio and in-situ measurement are not significantly different statistically. However, depth estimation based on Kd(λ) ratio was inconsistent due to the bottom albedo reflection because the Kd(λ) measurement was carried out in shallow waters. Estimation of water depth based on Kd(λ) ratio had better results compared to the Landsat 8 band ratio.

Underwater Topography Detection in Coastal Areas Using Fully Polarimetric SAR Data

Fully polarimetric synthetic aperture radar (SAR) can provide detailed information on scattering mechanisms that could enable the target or structure to be identified. This paper presents a method to detect underwater topography in coastal areas using high resolution fully polarimetric SAR data, while less prior information is required. The method is based on the shoaling and refraction of long surface gravity waves as they propagate shoreward. First, the surface scattering component is obtained by polarization decomposition. Then, wave fields are retrieved from the two-dimensional (2D) spectra by the Fast Fourier Transformation (FFT). Finally, shallow water depths are estimated from the dispersion relation. Applicability and effectiveness of the proposed methodology are tested by using C-band fine quad-polarization mode RADARSAT-2 SAR data over the near-shore area of the Hainan province, China. By comparing with the values from an official electronic navigational chart (ENC), the estimated water depths are in good agreement with them. The average relative error of the detected results from the scattering mechanisms based method and single polarization SAR data are 9.73% and 11.53% respectively. The validation results indicate that the scattering mechanisms based methodology is more effective than only using the single polarization SAR data for underwater topography detection, and will inspire further research on underwater topography detection with fully polarimetric SAR data.

Foraminifera as markers of Holocene sea-level fluctuations and water depths of ancient harbours — A case study from the Bay of Elaia (W Turkey)

The absence of common sea-level indicators in the study area of Elaia, Pergamum's harbour city in Hellenistic and Roman times, forced to establish a new reliable indicator, which was found in the foraminifera associations in connection with the transgressive contact. The strength of this indicator is the exclusion of post-depositional compaction. Accompanied by a well-dated archaeological index point at a breakwater, the micropalaeontological indicator enabled the establishment of a reliable regional sea-level curve (RSL curve) for the Bay of Elaia. It is in good agreement with other curves for the Aegean region and in general agreement to the glacio-hydro-isostatic model for the region. Our sea-level curve proves, for the first time at a continental site on the Turkish Aegean coast, the today's sea-level peak. Water-depth modelling for the so-called closed harbour of Elaia reveals the capacity to fully accommodate the common ship classes of Hellenistic and early Roman times until around 150CE, while water depth estimates for the so-called open harbour of the city verifies the usage of the adjacent ship sheds during Elaia's prime.

An efficient and stable hydrodynamic model with novel source term discretization schemes for overland flow and flood simulations

AbstractNumerical models solving the full 2‐D shallow water equations (SWEs) have been increasingly used to simulate overland flows and better understand the transient flow dynamics of flash floods in a catchment. However, there still exist key challenges that have not yet been resolved for the development of fully dynamic overland flow models, related to (1) the difficulty of maintaining numerical stability and accuracy in the limit of disappearing water depth and (2) inaccurate estimation of velocities and discharges on slopes as a result of strong nonlinearity of friction terms. This paper aims to tackle these key research challenges and present a new numerical scheme for accurately and efficiently modeling large‐scale transient overland flows over complex terrains. The proposed scheme features a novel surface reconstruction method (SRM) to correctly compute slope source terms and maintain numerical stability at small water depth, and a new implicit discretization method to handle the highly nonlinear friction terms. The resulting shallow water overland flow model is first validated against analytical and experimental test cases and then applied to simulate a hypothetic rainfall event in the 42 km2 Haltwhistle Burn, UK.

Proof‐of‐concept for low‐cost and non‐contact synoptic airborne river flow measurements

ABSTRACTThis article presents an example for an image-based method to determine a small rivers’ surface velocity field, bathymetry, and its flow discharge derived thereof. While common river measurement techniques typically need to be in contact with the waterbody, at least to measure transects of water depths, the new approach is completely without direct contact to water. The scenery is recorded by an off-the-shelf action camera mounted to a low-cost quadcopter. During the analysis, image frames are orthorectified and georeferenced by an approach that combines structure from motion and multiview stereo algorithms. Particle image velocimetry based on tracer particles present in the river is utilized to compute flow velocities. Instantaneous surface flow velocity fields are used to compute the mean velocity field as well as to derive water depth estimates by turbulence metrics. The latter provide a basis to verify the bathymetry gained from the reconstructed subaqueous three-dimensional scenery. Finally, flow discharge is estimated based on the above findings. The new method will expand the scientific knowledge on river flows for diverse disciplines such as hydrology, biology, and river engineering. Due to the low cost of the measurement instrumentation being deployed, it has the potential to be applied by a broad user group.

Evaluation of optical remote sensing-based shallow water bathymetry for recursive mapping

Water depth estimation using optical remote sensing offers a reliable and efficient means of mapping coastal zones. Here, we aim to find a suitable model for fast and practical bathymetry of an estuary using Indian Remote Sensing Satellite (IRS) Linear Imaging Self Scanning Sensor (LISS-3) images. The study examines three different models; (1) least square regression model, (2) spectral band-ratio method and (3) multi-tidal bathymetry model. The findings are supported with in situ observed depth values and statistical estimates. Although the least square regression model has provided best results with root mean square error (RMSE) of 0.4 m, it requires a large number of observed data points for absolute depth estimation. Spectral band-ratio and multi-tidal model provides results with RMSEs 2.1 and 0.9 m, respectively. The present investigation demonstrates that multi-date imagery exploitation at disparate tide levels is the best estimation technique for recursive shallow water bathymetry where in situ observation is not possible.

Performance Assessment of ANN in Estimating Remotely Sensed Extracted Bathymetry. Case Study: Eastern Harbor of Alexandria

The water depth extraction of shallow water plays an important role for marine safety. It is considered a useful reconnaissance tool to save time and cost to be used in preliminary survey. This paper aims to assess the performance of Artificial Neural Networks (ANN) in estimating the bathymetry of the Eastern harbor of Alexandria Egypt as a case study. This area of the case study represents a low turbid, mud bottom and shallow water area. The estimation of shallow water depth is based on ANN fitting algorithms using the logarithms of multispectral bands reflectance value. The estimation of water depths using optical bands of Landsat-8 multispectral images is extracted directly without regard to other environmental factors (bottom type and sea sediments). The images are first corrected for the effects caused by atmospheric conditions and sun specular. The bands are then calibrated using reference measurements obtained using GPS and single beam echo sounder in the study area. The estimated depths using ANN based on bands 1 &3, 3 only and 2 &3 show higher correlations and lower root mean square error compared the estimation made by previously developed statistically equations which were updated using the same data sets used in developing the ANNs. The ANN has a better capability to estimate the bathymetry using remotely-sensed data extracted from Landsat-8 images.

Towards a semi-empirical model of the sea ice thickness based on hyperspectral remote sensing in the Bohai Sea

Sea ice thickness is one of the most important input parameters for the prevention and mitigation of sea ice disasters and the prediction of local sea environments and climates. Estimating the sea ice thickness is currently the most important issue in the study of sea ice remote sensing. With the Bohai Sea as the study area, a semiempirical model of the sea ice thickness (SEMSIT) that can be used to estimate the thickness of first-year ice based on existing water depth estimation models and hyperspectral remote sensing data according to an optical radiative transfer process in sea ice is proposed. In the model, the absorption and scattering properties of sea ice in different bands (spectral dimension information) are utilized. An integrated attenuation coefficient at the pixel level is estimated using the height of the reflectance peak at 1 088 nm. In addition, the surface reflectance of sea ice at the pixel level is estimated using the 1 550–1 750 nm band reflectance. The model is used to estimate the sea ice thickness with Hyperion images. The first validation results suggest that the proposed model and parameterization scheme can effectively reduce the estimation error associated with the sea ice thickness that is caused by temporal and spatial heterogeneities in the integrated attenuation coefficient and sea ice surface. A practical semi-empirical model and parameterization scheme that may be feasible for the sea ice thickness estimation using hyperspectral remote sensing data are potentially provided.

Measurement of seawater average velocity using water bottom multiples from vertical seismic profile surveys

Previous diagnoses of surface seismic velocity models with vertical seismic profile (VSP) data in the Gulf of Mexico have indicated that shallow velocities were poorly constrained by VSP due to ringing caused by multiple casing strings. This ringing also hampered direct measurement of the seawater average velocity (SWAV) at a rig site with direct arrivals of a zero-offset VSP (ZVSP). We have directly measured the SWAV at a rig site with a known water depth by using differential times between primary water bottom multiples (WBMs) and direct first arrivals acquired in a marine VSP survey. We developed a procedure to process ZVSP-WBM signals for SWAV measurement. This WBM method is successfully applied to VSP data recorded at 27 rig sites in the deep-water environments of North and South America. Our results suggest that VSP processors should implement this method and add the SWAV measurement in their future velocity survey reports. We have estimated water bottom depths using differential times. We found that the estimated water depths are comparable with those acquired from sonar measurements by autonomous underwater vehicles, but with large uncertainties. The WBM method is extended by using data from a vertical incidence VSP to measure a profile of the SWAV along the path of a deviated well and evaluate possible lateral variations of SWAV. This method can potentially be applied to a time-lapse VSP to monitor temporal variations of SWAV. We also evaluated the application scope and limitations of the WBM method.

SATELLITE-DERIVED BATHYMETRY USING RANDOM FOREST ALGORITHM AND WORLDVIEW-2 IMAGERY

In empirical approach, the satellite-derived bathymetry (SDB) is usually derived from a linear regression. However, the depth variable in surface reflectance has a more complex relation. In this paper, a methodology was introduced using a nonlinear regression of Random Forest (RF) algorithm for SDB in shallow coral reef water. Worldview-2 satellite images and water depth measurement samples using single beam echo sounder were utilized. Furthermore, the surface reflectance of six visible bands and their logarithms were used as an input in RF and then compared with conventional methods of Multiple Linear Regression (MLR) at ten times cross validation. Moreover, the performance of each possible pair from six visible bands was also tested. Then, the estimated depth from two methods and each possible pairs were evaluated in two sites in Indonesia: Gili Mantra Island and Panggang Island, using the measured bathymetry data. As a result, for the case of all bands used the RF in compared with MLR showed better fitting ensemble, -0.14 and -1.27m of RMSE and 0.16 and 0.47 of R2 improvement for Gili Mantra Islands and Panggang Island, respectively. Therefore, the RF algorithm demonstrated better performance and accuracy compared with the conventional method. While for best pair identification, all bands pair wound did not give the best result. Surprisingly, the usage of green, yellow, and red bands showed good water depth estimation accuracy.

Satellite-Derived Bathymetry using Adaptive Geographically Weighted Regression Model

ABSTRACTThe common practice adopted in previous attempts on Satellite-Derived Bathymetry (SDB) has been to calibrate a single set of coefficients using global regression model. In this study we propose an Adaptive-Geographically Weighted Regression (A-GWR) model that takes into account local factors in determining the regression coefficients. A-GWR model is examined as an effective solution for addressing heterogeneity and could provide better water depth estimates in near-shore region. The study has been carried out for a 30-km stretch and covers 160 km2 of a complex near-shore coastal region of Puerto Rico, Northeastern Caribbean Sea. Medium-resolution (Landsat-8) and high-resolution (RapidEye) images were used to estimate water depth. Results demonstrate that the A-GWR model performs well in estimating bathymetry for shallow water depths (1–20 m), showing the correlation coefficient (R) of 0.98 and 0.99, determination coefficient (R2) of 0.95 and 0.99 and Root Mean Square Error (RMSE) of 1.14 and 0.4 m for Landsat-8 and RapidEye, respectively. The data-processing workflow has been entirely implemented in an Open-Source GIS environment and can be easily adopted in other areas.

Retrieval of Water Depth of Coastal Wetlands in the Yellow River Delta From ALOS PALSAR Backscattering Coefficients and Interferometry

Coastal wetland ecosystems are among the most productive yet highly threatened systems in the world, and population growth and increasing economic development have resulted in extremely rapid degradation and loss of coastal wetlands. Synthetic aperture radar (SAR) has proved to be of great potential in wetland applications, such as characterizing wetland types and mapping wetland inundation extent, based on the fact that the SAR backscatter signal from the wetland depends mainly on the wetland vegetation and hydrodynamic. However, the absence of ground observations has limited calibration and validation of water depth estimated from satellite SAR data. This letter aims to explore the potential for retrieving the water depth in freshwater marshes using L-band SAR backscattering coefficients. We present an innovative approach for combining backscattering coefficients and interferometric data to estimate water depth from L-band SAR data. The technique was applied to freshwater marshes in the Yellow River Delta using an Advanced Land Observing Satellite Phased Array L-band SAR data set acquired between 2007 and 2010. It is shown that the combination of L-band backscattering coefficients and interferometric data could provide information on the hydrodynamic of the Yellow River Delta with high spatial resolution.

Fusion of LiDAR Orthowaveforms and Hyperspectral Imagery for Shallow River Bathymetry and Turbidity Estimation

We propose an approach to voxelize bathymetric full-waveform LiDAR (Light Detection and Ranging) to generate orthowaveforms and use them to estimate shallow water bathymetry and turbidity with a nonparametric support vector regression (SVR) method. Two distinct shallow rivers were investigated ranging from clear to turbid water; hyperspectral imagery and traditional full-waveform LiDAR processing were also investigated as a baseline for comparison with the proposed orthowaveform strategy. The orthowaveform showed significant correlation to water depth in both scenarios and outperformed hyperspectral imagery for water depth estimation in more turbid water. The orthowaveforms showed similar performance to full-waveform LiDAR point observations for bathymetry estimation in clear water and outperformed the bathymetry performance of full-waveform processing in turbid water. The orthowaveforms also showed similar performance to hyperspectral imagery for predicting water turbidity in turbid water, with a root mean square error (RMSE) of 1.32 NTU. The fusion of both hyperspectral imagery and orthowaveforms was also investigated and gave superior performance to using either data set alone. The fused data set was able to estimate depth in clear and turbid water with an RMSE of 10 and 21 cm, respectively, and turbidity with an RMSE of 1.16 NTU.

BATHYMETRY MAPPING USING HYPERSPECTRAL DATA: A CASE STUDY OF YAMADA BAY, NORTHEAST JAPAN

Abstract. This study aims to examine if the inversion method using hyperspectral data is applicable in Japan. Nowadays, overseas researchers are mainly applied an inversion method for accurately estimating water depth. It is able to gain not only water depth, but also benthic spectral reflection and inherent optical properties (IOPs) at the same time, based on physics-based radiative transfer theory for hyperspectral data. It is highly significant to understand the possibility to develop the application in future for coastal zone of main island, which is a common water quality in Japan, but there is not any case study applied this method in Japan. The study site of Yamada bay in Iwate Prefecture is located in northeast of Japan. An existed analytical model was optimized for mapping water depth in Yamada bay using airborne hyperspectral image and ground survey data which were simultaneously acquired in December, 2015. The retrieved remote-sensing reflectance (Rrs) is basically qualitatively appropriate result. However, when compared with all ground survey points, the retrieved water depth showed low correlation, even though ground points which are selected sand bottom indicates high relationship. Overall, we could understand the inversion method is applicable in Japan. However, it needs to challenge to improve solving error-caused problems.

BATHYMETRY MAPPING USING HYPERSPECTRAL DATA: A CASE STUDY OF YAMADA BAY, NORTHEAST JAPAN

This study aims to examine if the inversion method using hyperspectral data is applicable in Japan. Nowadays, overseas researchers are mainly applied an inversion method for accurately estimating water depth. It is able to gain not only water depth, but also benthic spectral reflection and inherent optical properties (IOPs) at the same time, based on physics-based radiative transfer theory for hyperspectral data. It is highly significant to understand the possibility to develop the application in future for coastal zone of main island, which is a common water quality in Japan, but there is not any case study applied this method in Japan. The study site of Yamada bay in Iwate Prefecture is located in northeast of Japan. An existed analytical model was optimized for mapping water depth in Yamada bay using airborne hyperspectral image and ground survey data which were simultaneously acquired in December, 2015. The retrieved remote-sensing reflectance (R<sub>rs</sub>) is basically qualitatively appropriate result. However, when compared with all ground survey points, the retrieved water depth showed low correlation, even though ground points which are selected sand bottom indicates high relationship. Overall, we could understand the inversion method is applicable in Japan. However, it needs to challenge to improve solving error-caused problems.

Flow Simulation in a Rock-Ramp Fish Pass

AbstractThe flow characteristics in a rock-ramp fish pass can be significantly altered by the boulder arrangement. This study used a three-dimensional computational fluid dynamics solver to investigate flow characteristics for variations of discharge, channel slope and boulder size, spacing, and pattern. This study derived relationships for estimating water depth and velocity in a rock-ramp fish pass as a function of discharge and structure geometry. The flow resistance varies significantly with emergent boulder spacing and is nearly constant for submerged boulders. This study derives relationships for the drag coefficient and submergence ratio to forecast average flow velocity using a flow-resistance equation. Based on maximum velocity and a slow velocity zone, this study recommends effective boulder spacing in the longitudinal and transverse directions for two different boulder patterns. Finally, this study developed a design procedure for designing a rock-ramp fish pass.

Impact of eustatic and tectonic processes on the southeastern Mediterranean shelf during the last one million years: Quantitative reconstructions using a foraminiferal transfer function

Benthic foraminifera-based transfer function models provide accurate sea-level reconstructions for shelf and coastal environments around the world. This study presents for the first time results of a foraminiferal transfer function aiming at the reconstruction of relative sea-level in the southeastern Mediterranean shelf during the past one million years. A Weighted Averaging-Partial Least Squares (WA-PLS) regression method was used for the development of the transfer function based on an extensive set of surface samples (modern training data set) from the study area. The transfer function was applied to three shelf sediment successions retrieved from Haifa Bay, Israel. The Modern Analog Technique (MAT) and the random TF test were used to investigate similarity between modern and fossil foraminiferal faunas, testing the reliability and significance of our model for paleowater depth reconstruction. The performance of the WA-PLS transfer functions suggests a strong relationship between the observed and estimated water depths in the modern data set with relatively precise reconstructions of 7.0m (Root Mean Squared error of Prediction) over a water depth range of 3 to 80m. The deepest paleo water depths were reconstructed for the earliest sea-level highstands recorded in the sediment records (MIS 27? and MIS 29?) in the down-faulted boreholes due to tectonic movements, whereas the younger interglacial sedimentary units (MIS 25?, 13, 11, 7, 5.5 and 1) were mostly deposited at <15m water depths or slightly deeper during MIS 7. The relative sea-level history of the southeastern Mediterranean shelf reveals deviations from the global sea-level trend during MIS 5.5, which may have resulted from minor tectonic movements in the study area and/or un-representation of the phase of maximum sea-level in the sediment succession. Our paleowater depth estimates demonstrate a shallowing trend during the Holocene, generally matching other regional Mediterranean sea-level records.

Evaluation and modification of some empirical and semi-empirical approaches for prediction of area-storage capacity curves in reservoirs of dams

The storage capacity of reservoirs is gradually reduced due to sediment accumulation that causes changes in the area-storage capacity (ASC) curves. Establishing these curves and predicting their future change is an important issue for planners, designers and operators of dams. Many empirical and semi-empirical approaches have been suggested for establishing and predicting the future changes for these curves. In this study four empirical and semi-empirical methods were evaluated and three of them were modified to be used for the prediction of changes in the ASC curves due to sedimentation, based on the existing sedimentation survey data for 11 reservoirs in the USA. For evaluation, these approaches were reviewed and used to determine sedimentation depth and establishing the ASC curves for the Mosul dam reservoir (MDR), which is the biggest hydraulic structure on the River Tigris in northern Iraq. MDR started operating in 1986 with a storage capacity of 11.11km3 and a water surface area 380km2 at normal operation stage (330m a.s.l.). The results obtained from these methods were evaluated using observed bathymetric survey data that had been collected in 2011 after 25 years of the operation of the dam. The evaluation results showed three methods had presented more accurate results for estimating water depth or sedimentation depth at dam site with percentage error about 1.06–3.30%. Whilst for establishing ASC curves, one method presented good agreement result with survey data. Furthermore, ASC and sedimentation depths at dam site of MDR for periods 50, 75, 100 and 125 years were estimated using the modified approaches and the area reduction method. The results of the modified methods provided reasonable agreement when compared with the area reduction method proposed by the U.S. Bureau of Reclamation and the agreement became better with an increase in time period.