Tidal Data Research Articles

Three-Dimensional Hydrodynamic Modelling to Estimate Sediment Rate in Lamong Bay

Abstract Lamong Bay Terminal, part of Tanjung Perak Port in Surabaya, functions as a container terminal. The port in the Surabaya area causes high ship traffic activity in the waters of Lamong Bay and sediment may be carried away from rivers heading towards the sea. The sedimentation process in waters can cause problems because it can cause shallowing of the waters, so it is necessary to maintain and monitor the depth of shipping lanes to maintain the safety of sea traffic. Therefore, understanding the hydrodynamics of seawater and sediment movement in the water region is necessary for successful dredging operations and assessing the impact of silt on port areas. In this research, the approach used to determine current patterns and sediment distribution was through the application of a numerical model with three– dimensional baroclinic hydrodynamic equations. The numerical modeling study in this research uses tidal data, sediment samples, salinity, and temperature to determine current patterns and the rate of sediment distribution. This process is carried out periodically and continuously as part of the evaluation of Lamong Bay Terminal. The results can serve as a reference for dredging planning to maintain the depth of the waters at the Lamong Bay Terminal. In this study, the highest current velocity was obtained at the time of spring tide reaching 0.9 ms−1 and at the neap tide of 0.4 ms−1. The sediment distribution pattern in the waters of Lamong Bay affected the existence of the pier and the morphological conditions of the seabed. The largest siltation or sedimentation that has occurred at Lamong Bay Port is 0.055 m/month near the jetty, thus depth monitoring is needed in this area, regularly. This study supports SDG 9 by advancing resilient infrastructure solutions to manage the sedimentation process in waters.

[formula omitted]Beach: Self-attention-based spatiotemporal network for skillful prediction of shoreline changes multiple days ahead

We developed a self-attention-based spatiotemporal network called alphaBeach that uses spatiotemporal representation learning for skillful prediction of shoreline changes multiple days ahead. The proposed model predicts the spatiotemporal position of the shoreline up to seven consecutive days in the future based on hydrodynamic forcing of ocean waves and tide data for the past 30 consecutive days. It is further divided into alphaBeach-w/oIC and alphaBeach-w/IC depending on whether or not the beach state of the antecedent historical shoreline information is used as the initial condition. alphaBeach-w/oIC, which does not incorporate this information, learns the sequential relationship between hydrodynamic forcing and shoreline to estimate overall trends of shoreline changes including seasonal oscillation from the point in time after model training, given only the ocean waves and tides. alphaBeach-w/IC does incorporate antecedent historical shoreline information to greatly enhance its predictive accuracy of shoreline progradation, retreat, and beach rotation for short-term time scales and for extreme storm events. The proposed model was applied to Tairua Beach, New Zealand, and it demonstrated superior predictive accuracy compared to previous methods and matched current understanding of accretion-dominated and oscillation-dominated shoreline changes.

Bacterial communities on giant kelp in the Magellan Strait: Geographical and intra-thallus patterns.

The giant kelp Macrocystis pyrifera is categorized as a keystone species, forming highly productive forests that provide ecosystem services and host a remarkable marine biodiversity of macro and microorganisms. The association of microorganisms with the algae is close and can be functionally interdependent. The Magellan Strait, a natural marine passage between the Atlantic and Pacific oceans, harbours extensive giant kelp forests. However, information related to the diversity of bacterial communities in this region is still scarce. In this study, 16S rRNA gene metabarcoding was used to characterize the diversity and composition of bacterial communities associated with apical blades and sporophylls of M. pyrifera from different sites (Bahía Buzo, San Gregorio, and Buque Quemado). Additionally, data from satellites and reanalysis, as well as tide data, were used to characterize the environmental variability. The findings revealed discernible local variations in bacterial taxa across sampling sites, with consistent dominance of Proteobacteria, Verrucomicrobia, Bacteroidetes, and Planctomycetes. Furthermore, a distinctive bacterial community structure was identified between apical and sporophyll blades of M. pyrifera. This research marks the inaugural characterization of bacterial community diversity and composition associated with M. pyrifera in the remote and understudied sub-Antarctic region of the Magellan Strait.

Analysis of Tidal Energy Potential in the Merauke Papua River Waters Indonesia

The purpose of this study is as a source of information to study the potential of tidal energy at the estuary of the Maro River in the waters of Merauke Regency. This study uses a quantitative method, while the method for determining the location of the study used is the purposive sampling method where the data collection point is right at the end of the estuary of the Maro River because it faces directly onto the Arafura Sea. Tide data for 5 months, namely September 1, 2023 to January 31, 2024 with a pool area of 1,260,000 m2, with the consideration that from September to January there is a change of seasons that can significantly affect the tidal pattern. The tides are measured in two periods, namely the first tidal period starting at 01.00 AM to 12.00 AM and the second tidal period occurs at 01.00 PM to 12.00 PM. From the research data, it was obtained that the highest tides were in January 2024, namely the first-period tidal height difference of 5.333 meters and the energy produced was 5.292 kWh, and the second-period tidal height difference was 5.383 meters the energy produced was 5.349 kWh. The results of this study can encourage diversification of energy sources in Merauke and increase regional energy security as well as provide the data needed for further research and development of renewable energy technology, which can accelerate innovation of new technologies in the Merauke Papua region.

Calculating carbon: The value of information in precision for blue carbon restoration projects

Coastal wetland restoration projects can receive payments for ecosystem services but often occur in regions with limited data, and additional data collection can be financially prohibitive. Value of Information analysis can quantify the difference between the expected value of an action before and after new information has been collected, aiming to understand how much data is required to make decisions that balance the costs of implementation versus the benefits of the project. The Australian carbon market provides a method that uses reintroduction of tidal flows to restore coastal wetland ecosystems for their carbon sequestration functions. The method requires a hydrological assessment of prospective sites, which is employed to estimate carbon sequestration potential. This research investigates how different amounts of data collection and different levels of complexity in the hydrological assessment influence the carbon abatement emissions estimated using the method. The results indicate that tidal restoration for blue carbon credits on grazing land may not be financially viable. We found that tidal data collected onsite were important for decision-making while complex hydrological models have low value compared to more simplistic approaches. While investing in data collection provides more value than increasing the complexity of modelling approaches, the value of information was still low. Additionally, restoration of coastal wetlands is unlikely to be financially attractive at current carbon prices, and the land would have to be unsuitable for cattle to become profitable for restoration. This work provides a framework for evaluating the financial benefit of collecting on-site data and using robust methods for estimating inundation, that can be used to guide decision-making to achieve optimal income.

Optimization of Prevention of Hazards MV. Meratus Kariangau Ship Running Across Entering the Narrow Waterflow of the Barito River

This research aims to Optimize the Prevention of the Occurrence of Shipwreck Hazard of MV Meratus Kariangau when Entering the Narrow Shipping Channel of the Barito River. This research method uses a qualitative method with a descriptive approach. For primary data collection techniques obtained from the results of interviews and observations, while for secondary data collection techniques obtained from tidal data in the Barito river, then from journals related to this research, books and others. The results of this study indicate are a). Indication of overdraft when entering the narrow shipping channel, b). Lack of attention to UKC and Tidal Tables, c). Human error from the watch officer who did not pay attention to the tide list. Preparations that must be made by the MV. Meratus Kariangau before entering the narrow shipping channel of the Barito river to avoid the danger of running aground are a) The duty officer and the skipper must operate the navigation equipment on the ship, for example Radar, Echo sounder, GPS. b) The duty officer prepares a map of the narrow shipping channel to be passed. c) The duty officer asks the Engine Control Room (ECR) to ensure that the engine is ready to pass through the narrow shipping channel d) The duty officer calculates the UKC and Squat on the shipping channel to be passed e) The crew conducts a grounding drill to know their duties and responsibilities when running aground f) The skipper and duty officer apply P2TL rule 9 on Narrow channel.

Tidally modulated seismic velocity changes observed using submarine dark fiber and the virtual-source method

Natural cyclical stress perturbations, including wet and solid earth tides, coupled with repeatable seismic monitoring approaches, provide a tool for understanding the elastic properties of rocks at depth. Ocean tides, in particular, perturb the overburden and pore pressure, affecting hydraulic and elastic rock properties. The recent emergence of distributed acoustic sensing (DAS) and seismology using existing dark telecom fiber offers an unprecedented opportunity to instrument the seas and oceans with seismic monitoring networks of large aperture, fine spatial resolution, and broadband sensitivity. We use a submarine dark-fiber array to methodologically assess whether the changes in seafloor seismic velocities are modulated by ocean tidal loading. Considering oceanic ambient noise (AN) in the frequency range between 1 and 5 Hz, we find it possible to retrieve reliable surface-wave estimates using relatively short time windows (approximately 60 min). Next, using the power of linear arrays to capture AN energy from the stationary-phase zones and AN processing techniques commonly used in DAS applications for subsurface monitoring in urban settings, we introduce a methodological approach to turn each segment of dark fiber into a short-offset monitoring array (2 km), providing redundant, hourly, surface-wave estimates. Using four days of AN data recorded by the Monterey Accelerated Research System (MARS) 20 km section offshore cable, we generate the virtual-source gathers for 10 segments spanning the whole MARS cable. We then use virtual-source data from one segment to estimate the hourly velocity changes that are then quantitatively compared with the tidal data. The results suggest that changes in seafloor seismic velocities are likely modulated by tidal height, even in regions without large tidal excursions. This advance demonstrates a new application of submarine telecom fibers for monitoring the seismic stress response of near-seafloor sediments.

A Conterminous United States–Wide Validation of Relative Tidal Elevation Products

Recent large-scale spatial products have been developed to assess wetland position in the tidal frame, but nationwide comparisons and validations are missing for these products. Wetland position within the tidal frame is a commonly used characteristic to compare wetlands across biogeomorphic gradients and factors heavily into wetland vulnerability models. We utilize a dataset of 365 surface elevation table stations across the conterminous USA containing ground-surveyed tidal datum and elevation data to validate two gridded, conterminous USA–wide relative tidal elevation products. We identified substantial differences between our ground-surveyed dataset and the gridded products, with the Gulf coast exhibiting the greatest error (p < 0.0001, n = 140). Error in relative tidal elevation products varied by coast, tidal range, and latitude. These differences in errors indicate that gridded relative tidal elevation products may be more accurate in coastal wetlands with larger tidal ranges (> 30 cm) and are less accurate in freshwater wetlands near the coast. This paper makes advances in understanding why relative tidal elevation differences occur among national datasets and identifies areas of future work that could support more robust vulnerability models.

INUNDATION PREDICTION AS THE EFFECT OF RISING MEAN SEA LEVEL AND HIGH ASTRONOMICAL TIDE IN NORTH JAKARTA BASED ON 2013-2021 TIDAL DATA

Future sea level rise in North Jakarta is one of the potential hazards that threaten the safety of coastal communities and infrastructure. Prediction of sea level rise is needed to reduce the vulnerability of the people living on the coast. This study was conducted to estimate the height of sea level rise in 2045 using linear regression analysis of hourly tidal data for 2013-2021 coupled with the highest astronomical tide value from the results of tidal harmonic analysis in 2021 using the t_tide application in matlab. The water elevation was then projected on the Digital Elevation Model to obtain the inundation area in 2045. The result of this study is an inundation area of 56 km2 in North Jakarta in 2045 due to an increase in total sea level of 117 cm at high tide.

Hydrodynamic and turbulence associated with tidal bore propagation in an amazonian macrotidal system

The study analyzed the hydrodynamic and turbulence characteristics of the Tidal Bore (TB) associated with Sucuriju River Coastal System (SRCS), a macrotidal estuarine system located north of the Amazon River mouth. Two points were sampled using ADCP at a frequency of 0.5 Hz for 13 hours, one at the mouth (P1) and the other upstream (P2). The Tidal Gauge (TG) located at the mouth collected tidal data continuously for three months at a 30-second rate. The instantaneous hydraulic jump velocities (HJ) and the hydraulic jump resultant (HJRES) were calculated for TG. The Tidal Bore Froude Number (Fr), Turbulent Kinect Energy – TKE (q2/2), TKE Production (Pτ), Reynolds stress (τx and τy), and Quantity S were calculated for P1 and P2. Over 70 TB occurrences were identified during spring tides, with the highest HJRES of 2.23 observed in March. The U̅ component showed greater results during ebb tide, reaching 1.48 and 1.00 m s−1 for P1 and P2 respectively, with a rapid current inflow associated with TB. The highest TKE and Reynolds stress parameters were observed during ebb tide, with TKE reaching up to 1.80 J m−3 in P1 and 1.12 J m−3 in P2. After the TB these values decreased to almost zero, resulting in lower energy associate with a rapid increase in water level, indicates a transition from supercritical (Fr>1) to subcritical flow (Fr<1). Based on the Fr value, the TB showed characteristics of a Weak Breaking Tidal Bore / Breaking Bore in P1 (1.2 or 1.3 < Fr < 1.5), and Cross waves / shock waves / undular bore for P2 (1.0 < Fr < 1.2 or 1.3).

Enhancing Assessments of Coastal Wetland Migration Potential with Sea-level Rise: Accounting for Uncertainty in Elevation Data, Tidal Data, and Future Water Levels

Enhancing Assessments of Coastal Wetland Migration Potential with Sea-level Rise: Accounting for Uncertainty in Elevation Data, Tidal Data, and Future Water Levels

Instrumentation for Monitoring and Early Warning of Tidal Flood Using ESP32S2 Microcontroller and A01NYUB Ultrasonic Sensor in Tambakrejo, Semarang

Abstract A tidal flood early warning system is crucial to minimize the impact and loss in tidal flood-prone areas. This research proposes an instrumentation and information system for tidal flood early warning monitoring by optimizing tidal data in the local area. The efficiency of the instrumentation depends on the accuracy of the sensors installed. This research presents the testing and application of The A01NYUB ultrasonic sensor with The ESP32S2 microcontroller for real-time technology-based water level monitoring and The Internet of Things concept. The collected sensor data is analyzed with an algorithm that has also been proposed in this research. The results show that the ultrasonic sensors can provide a reliable and adequate tide monitoring scheme with an accuracy of RMSE value of 0.08943 and bias value of – 2×10−16. The developed system provides early warning when the sea level reaches 260-280 cm with the MSL datum reference value range of -20 cm to 40 cm. The system has been tested at the Fisherman Boat Harbor, Tambakrejo, Semarang, Central Java, Indonesia. The test has shown the system’s accuracy and has proven that the developed system will help minimize the impact of the tidal flood disaster.

Quasi-Continuous Tidal Datum for Peninsular Malaysia using Tide Gauge, Satellite Altimetry, and Tide Model Driver (TMD) Data

Quasi-Continuous Tidal Datum for Peninsular Malaysia using Tide Gauge, Satellite Altimetry, and Tide Model Driver (TMD) Data

Coastal Zone Management in Response to Sea Level Rise in the 21st Century: A Study from Hurst Spit to Lymington, South England

This study examines the coastal region spanning from Hurst Spit to the mouth of the Lymington River along the Western Solent coast in Hampshire, South England. The area comprises critical habitats for international bird species on the seaward side and is protected by a seawall on the landward side. Rising sea levels pose a significant threat to this area, including habitat loss and potential seawall breaches. To address the uncertainty in sea level rise projections for the 21st century, this study utilises data processing in ArcGIS, including LiDAR data, tidal data, and sea level rise projections. It adopts contingency allowances for sea level rise, resulting in a projected 0.89 metre by 2100. Analysis reveals a significant transformation in habitat distribution, with standing water and mudflats expanding while salt marshes and dry land areas diminish. Salt marsh areas are projected to contract by 64.6%, with the pioneer salt marsh facing the greatest loss. The report recommends a proactive approach, including realigning the seawall in vulnerable areas, allowing for the creation of new salt marshes. This managed intervention strategy can reduce habitat loss to approximately 17.43%, mitigating the potential ecological and human habitat impacts of rising sea levels in that region.

PENGEMBANGAN ARDUINO DATA LOGGER MENGGUNAKAN TDR H3CR UNTUK SIMULATOR PASANG SURUT

Tides, crucial natural phenomena, significantly impact various aspects of life. Recognizing their importance, this study presents the development of a tidal simulator leveraging Arduino data logging and TDR H3CR technology. The simulator aims to mimic tidal processes, crucial for educational and research purposes. Traditional methods of acquiring tidal data are time-consuming and expensive. Thus, a simulator proves advantageous in reducing research time and costs. At Raja Ali Haji Maritime University, a tidal simulation model exists but with manual operation and limited data capture capabilities. To address these limitations, this study designed a new simulator utilizing H3CR, DC Water Pump, and DC Selenoid Valve for automated tidal circulation. The research method involved system design, component integration, and laboratory experiments. Calibration of components like the ultrasonic sensor HC-SR04 ensured accurate data collection. The overall system experiment validated the simulator's functionality, demonstrating its ability to replicate tidal processes effectively. Results indicated that the simulator produced tidal patterns resembling sinusoidal waves, with slight noise attributed to sensor limitations. The designed simulator serves as an efficient learning tool for understanding tidal phenomena, exhibiting comparable results to natural tidal data. This study contributes to the advancement of tidal simulation technology, offering a cost-effective and accessible solution for educational and research purposes.

Tidal Characteristic Analysis Utilizing Radar Tide Gauge in Cirebon Seawater

Radar-based tide gauges are one approach in measuring water level offering easier installation and maintenance. Tidal data recording that has been done commonly applies tide staff or pressure tide gauge. In this study, a radar tide gauge was installed at Cirebon port, northern part of Java island, to determine the tidal characteristics in Cirebon seawaters. Water elevation data was recorded every 15 minutes from July 2022 to November 2023. The tidal component is calculated using least squares method while the tidal type is determined using the Formzahl number. The dominant tidal component known consists of semidiurnal component i.e. M2, S2, N2, K2, 2N2; diurnal component, K1, O1, P1, Q1, J1, TAU1; and shallow water component SSA components with a height of 11.98, 5.58, 2.91, 2.11, 1.45, 11.80, 3.89, 6.11, 2.08, 1.56 and 3.11 (in cm), respectively. Tidal type in the study area is mixed type prevailing Semidiurnal. The tidal range is around 0.8-1 m high with high tide conditions at 6.00-9.00 and 18.00 - 21.00, while low tide conditions are within 11.00 - 14.00 and 01.00 - 04.00. Elevation height calculation based on datum is done by combining the tidal components. Tidal measurement data using radar can be an alternative data to support and complement data recorded in Cirebon and may become a consideration for development and other maritime activities.

Nutrient dynamics in wetland systems associated with hydrological and anthropogenic variations in the south of Samborombón Bay, Argentina

Wetlands provide numerous ecosystem services to the environment, such as nutrient removal and storage. The aim of this work is to evaluate the nutrient dynamics in different sectors within wetland systems in the south of the Samborombón Bay (Argentina) based on hydrological and/or anthropogenic variations. For this purpose, the hydrological features of the wetland were defined through the analysis of satellite images, precipitation and tidal data, and field surveys. Three sectors were identified in the wetland: one with tidal influence, another which is dependent on rainfall, and another that receives inputs from rainfall and from a sewage effluent treatment plant. In order to analyze the nutrient dynamics, samples of surface water, groundwater, and sediments were collected from these sectors. Measurements of pH and electrical conductivity were determined in situ in water samples, while the concentration of inorganic forms of phosphorus and nitrogen, soluble reactive silica, and organic carbon were determined through laboratory analysis. Also, bioavailable phosphorus, organic matter, pH, and electrical conductivity were determined in the sediment samples collected. Statistical analysis of the data reveals differences between the sectors and allows the interpretation of the dynamics of the studied components in the wetland. Electrical conductivity distinguishes the intertidal sectors of the wetland while components associated with P and N discriminate the sectors with inputs from the sewage effluent treatment plant. On the other hand, soluble reactive silica, organic carbon, and organic matter do not seem to be influenced by the tide or effluent discharge. This study demonstrates that the studied wetland works as a nutrient retention area, providing ecosystem services to local inhabitants. Although these services can be utilized, they require a continuous monitoring over time to provide an early warning in case the variations in P and N cycles could lead to eutrophication or wetland degradation.

The Verification of Sea Level Anomaly (SLA) Versus Tide Gauge for Geoid Modelling

The increasing long-term sea level rise is of particular interest and needs a significant investment in coastal protection procedures. The coastal sea level has been verified with tide gauges and well maintained with reliable accuracy of data since a few centuries ago. Satellite altimeter has been used for sea level study and increasingly for operational purposes. However, the precision of altimetry data in coastal areas is frequently eliminated by the geographically correlated orbit errors, which induce a regional inhomogeneous mission bias. This study presents an effort to verify sea level anomaly based on altimetry data with tide gauge stations as an early procedure to provide a good sea level anomaly data for mean sea surface, gravity anomaly, and geoid determination over Malaysian seas. The altimetry data is validated by comparing the sea level anomaly with ground truth data (tidal data) near the coastal area. A total of nine selected areas were chosen to represent the ground truth data. The findings found that the altimetry data over the South China Sea (Pulau Tioman, Geting, Cendering, Bintulu, and Kota Kinabalu) provided a good pattern, high correlation, and a minimum root mean square error (RMSE) value after the verification with tidal sea level anomaly data. However, it clearly shows that Tawau station over the Celebes Sea provides a poor pattern, poor correlation, and a high RMSE value with tidal sea level anomaly data. In conclusion, further enhancements are expected from the refined processing and filtering of altimetry data for the sea level study in the coastal zone.

Comparative Studies Of Residual Water Level In Manado And Melonguane Coastal Area During Tropical Cyclone In 2021

North Sulawesi Province, directly bordering the Pacific Ocean, is located in an area with the highest level of tropical cyclone (TC) activity in the world. As a result, the province is vulnerable to the impacts caused by cyclones, including storm surges. The increase in water levels due to this event has the potential to cause coastal flooding. Previous studies in Manado have identified that sea level rise can be detected through residual water level (RWL), making studying the characteristics of RWL in North Sulawesi important. This research focuses on Manado and Melonguane, allowing for a comparison of characteristics. The data used includes tropical cyclone data from the China Meteorological Administration (CMA) and tidal data from the Geospatial Information Agency. The Unified Tidal Analysis and Prediction (UTide) method is used to identify RWL. The analysis was carried out by using a t-test to compare data at the two locations. The results showed that RWL at those locations had significant differences with Melonguane having the higher value between them. Generally, the increase in RWL in Melonguane occurs shortly after the cyclone period, while the RWL in Manado maximum increases 86 hours after TC's first occurrence. Keywords: tropical cyclone; residual water level; UTide.

An algorithm for constructing spatial vector data storage based on KD-tree and density estimation

With the widespread application of spatial vector data in various fields, this paper proposes a novel algorithm for constructing spatial vector data storage. The algorithm is based on KD-tree and density estimation techniques, aiming to improve the storage efficiency and query performance of large-scale spatial vector data. The algorithm first efficiently organizes spatial vector data using KD-tree, and then performs density estimation based on the Locality Sensitive Hashing (LSH) algorithm. Algorithm optimizations for spatial partitioning are applied to the KD-tree construction algorithm, reducing the search range during queries and improving retrieval speed. By testing with Green Tide data, the algorithm based on KD-tree and density estimation demonstrates higher query efficiency and better scalability across multiple test datasets. Particularly, when dealing with large-scale datasets characterized by non-uniform data distributions, this algorithm significantly improves data retrieval speed while maintaining low storage overhead.