Meizhou Bay Research Articles

Resilience Measurement and Enhancement Strategies for Meizhou Bay Port Enterprises

The measurement of resilience in port enterprises has seldom been studied and understood. To assist port enterprises in formulating scientifically sound resilience enhancement strategies, this paper aims to develop a resilience measurement framework. The entropy-weighted TOPSIS method is utilized to measure the resilience of Meizhou Bay Port, effectively extending the application of resilience theory in the port sector and providing a crucial reference for the resilience measurement of port enterprises. The results reveal that the resilience of Meizhou Bay Port decreased from 0.4049 in 2018 to 0.34013 in 2022, indicating a current low level of resilience that requires a series of measures to enhance. Analyzing different dimensions, absorptive capacity experienced the most significant decline at the onset of the pandemic and then stabilized; adaptive capacity decreased the most, falling below absorptive capacity by 2022; and recovery capacity remained the most stable, with the least decline. This reflects the vulnerability of absorptive and adaptive capacities under significant shocks, necessitating attention and improvement in daily port operations.

The Offset Position Prediction of Light Buoy Based on Grey Optimization Multiplicative Seasonal Model

Light buoy is a navigation aid sign to guide ship navigation, which plays an important role in ensuring the safety of ship navigation. To predict the offset distance of light buoy and provide accurate position information of light buoy for ship navigation safety, and to solve the problem of low prediction accuracy caused by the excessive amplitude of initial training data in the traditional multiplicative seasonal model, a grey optimization multiplicative seasonal model is proposed. By analyzing the characteristics of the time series of the light buoy offset data, as well as the regularity and seasonal characteristics of the light buoy offset distance, an optimization model is established. Based on the real offset distance data of the 1 # light buoy in Meizhou Bay, the model is simulated, and the prediction accuracy of the model is evaluated by MAPE, RMSE, and the Monte Carlo sampling method. The results show that, compared to the traditional multiplicative seasonal model, the average absolute percentage error of the grey optimization multiplicative seasonal model is reduced by 6.66%, and the root mean square error is reduced by 2.96. It shows that the model can effectively deal with the problem that the error of the prediction results caused by the instability of the initial time series of the traditional multiplicative seasonal model is too large, which provides a new idea for the prediction of the offset distance of the light buoy and the navigation safety of the ship.

The Offset Azimuth Prediction of Light Buoy Based on Markov Chain Optimization Multiplicative Seasonal Model

Aimed at the problem of the large error caused by uncertain factors in the fitting process of the traditional multiplicative seasonal model, the advantages of the Markov chain in this study are applied to the multiplicative seasonal model to optimize the prediction results. Based on the residual value between the theoretical and actual values, the values of different intervals are divided into states. The transition probability matrix is established through different probabilities; then, the weighted sum of different prediction probabilities is carried out to select the optimal prediction state. The real number of Meizhou Bay portlight buoys is used to verify the prediction effect of the model, and MAE, MAPE, RMSE, RRMSE, SSE, R2 are used to calculate the error between the predicted value and the actual value. The results show that compared to the traditional multiplicative seasonal model and other prediction models, the prediction MAE of the MC-SARIMA model is decreased by 2.19003794, the MAPE is decreased by 0.66%, the RMSE is decreased by 2.092671823, the RRMSE is decreased by 0.006221352, the SSE is decreased by 404.0231931, and the R2 is increased by 0.224686247. It shows that the multiplicative seasonal model optimized by the Markov chain can predict the azimuth data of the light buoy more effectively than the traditional multiplicative seasonal model and other prediction models.

Marine spatial planning for transboundary issues in bays of Fujian, China: A hierarchical system

Transboundary issue is one of the main concerns of marine spatial planning (MSP) studies around the world, including China. With few studies on the effective approaches to address the transboundary issues in MSP reported, this study aims to assess the coordination effectiveness of transboundary bays at both municipal level MSP and provincial level MSP, using Xiamen Bay, Meizhou Bay, and Xinghua Bay in Fujian province as the study areas. To conduct this study, a method of sea use intensity and conflict was applied and developed to evaluate the coordination effectiveness of MSP at the municipal and provincial levels. A scoring method was applied to obtain each sea use intensity value (based on marine resources and impacts on marine environment) and the sea use pair conflict value (based on the influence or interference of two adjacent sea use types). Afterward, the outcome of this work was calculated and visualized using GIS tools. The results revealed that both the sea use intensity and conflict at municipal were higher than that of the provincial level MSP, which clearly indicates the existence of conflict between hierarchical MSP, furthermore, this study also revealed the necessity for transboundary coordination analysis since the highest sea use conflict was observed at the cross-boundary area of the provincial level MSP and in the city interior area of the municipal level. Based on the overall study, it was observed that the sea use conflict value had a negative relationship with sea use intensity value, most of which were showcased in Xiamen Bay having the lowest sea use intensity but the highest sea use conflict at both hierarchical levels MSP (SUIV, 3.87 and 4.61. SUCV, 8.60 and 9.38 at the municipal and provincial level MSP respectively), this is believed to be impacted by the increased marine industrial structure and a lack of spatial coordination. The results of this study will help the government to improve the MSP coordination in transboundary bays at the hierarchical systems, and inform potential future revisions of the coastal zone utilization at local, regional, and national scales.

Physical and Numerical Investigations on Wave Run-Up and Dissipation under Breakwater with Fence Revetment

Revetment elements and protective facilities on a breakwater can effectively weaken the impact of waves. In order to resist storm surges, there is a plan to build a breakwater on the northern shore of Meizhou Bay in Putian City, China. To better design it, considering different environmental conditions, physical and numerical experiments were carried out to accurately study the effects of the breakwater and its auxiliary structures on wave propagation. In the experiments, the influence of the wave type, initial water depth, and the structure of the fence plate are considered. The wave run-up and dissipation, the wave overtopping volume, and the structure stability are analyzed. The results indicate that the breakwater can effectively resist the wave impact, reduce the wave run-up and overtopping, and protect the rear buildings. In addition, under the same still water depth and significant wave height, the amount of overtopped water under regular waves is larger than that under irregular waves. With the increase of the still water depth and significant wave height, the overtopped water increases, which means that when the storm surge occurs, damage on the breakwater under the high tide level is greater than that under the low tide level. Besides, the fence plate can effectively dissipate energy and reduce the overtopping volume by generating eddy current in the cavity. Considering the stability and the energy dissipation capacity of the fence plate, it is suggested that a gap ratio of 50% is reasonable.

Bottom Detection from Backscatter Data of Conventional Side Scan Sonars through 1D-UNet

As widely applicated in many underwater research fields, conventional side-scan sonars require the sonar height to be at the seabed for geocoding seabed images. However, many interference factors, including compensation with unknown gains, suspended matters, etc., would bring difficulties in bottom detection. Existing methods need manual parameter setups or to use postprocessing methods, which limits automatic and real-time processing in complex situations. To solve this problem, a one-dimensional U-Net (1D-UNet) model for sea bottom detection of side-scan data and the bottom detection and tracking method based on 1D-UNet are proposed in this work. First, the basic theory of sonar bottom detection and the interference factors is introduced, which indicates that deep learning of the bottom is a feasible solution. Then, a 1D-UNet model for detecting the sea bottom position from the side-scan backscatter strength sequences is proposed, and the structure and implementation of this model are illustrated in detail. Finally, the bottom detection and tracking algorithms of a single ping and continuous pings are presented on the basis of the proposed model. The measured side-scan sonar data in Meizhou Bay and Bayuquan District were selected in the experiments to verify the model and methods. The 1D-UNet model was first trained and applied with the side-scan data in Meizhou Bay. The training and validation accuracies were 99.92% and 99.77%, respectively, and the sea bottom detection accuracy of the training survey line was 99.88%. The 1D-UNet model showed good robustness to the interference factors of bottom detection and fully real-time performance in comparison with other methods. Moreover, the trained 1D-UNet model is used to process the data in the Bayuquan District for proving model generality. The proposed 1D-UNet model for bottom detection has been proven effective for side-scan sonar data and also has great potentials in wider applications on other types of sonars.

Predicting potential mangrove distributions at the global northern distribution margin using an ecological niche model: Determining conservation and reforestation involvement

Mangroves play an important role in maintaining coastal wetland ecosystem functions, but they are highly threatened by anthropogenic activities. Predicting the potential distributions of mangroves is vital for policy makers and stakeholders to enforce conservation and reforestation measures. China is at the global northern margin of mangrove distribution. In this study, we used the maximum entropy (MaxEnt) model to predict potentially suitable habitats for mangroves based on current data of mangrove distributions in mainland China. For modeling, we grouped the native and exotic mangrove species in China into five groups and used 30 bioclimate, topographic, substrate, and sea surface temperature variables to predict mangrove distributions. The results show that bioclimate and sea surface temperature are both important factors that determine mangrove distribution. The largest suitable area modeled for mangrove species in the coastal zone was 2705 km2. About 14.8% of the predicted suitable habitat for the five mangrove groups is under protection in mangrove nature reserves. Along China’s coastline, 15 sites were identified as hotspots for mangrove conservation and reforestation. By comparing these results with current conservation efforts, we identified that protection priority should be given to the Beilun River Estuary to Fangcheng Harbor coastal zone in Guangxi Province, the east coast of the Leizhou Peninsula in Guangdong Province, and the Meizhou Bay to Xinghua Bay area in Fujian Province. In addition, suitable species selection should also be considered to achieve successful mangrove reforestation.

Real-Time Bottom Tracking Using Side Scan Sonar Data Through One-Dimensional Convolutional Neural Networks

As one of the most commonly used acoustic systems in seabed surveys, the altitude of the side scan sonar from the seafloor is always difficult to determine, especially when raw signal levels and gain information are unavailable. The inaccurate sonar altitudes would limit the applications of sonar image geocoding, target detection, and sediment classification. The sonar altitude can be obtained by using bottom tracking methods, but traditional methods often require manual thresholds or complex post-processing procedures, which cannot ensure accurate and real-time bottom tracking. In this paper, a real-time bottom tracking method of side scan data is proposed based on a one-dimensional convolution neural network. First, according to the characteristics of side scan backscatter strength sequences, positive (bottom sequences) and negative (water column and seabed sequences) samples are extracted to establish the sample sets. Second, a one-dimensional convolution neural network is carefully designed and trained by using the sample set to recognize the bottom sequences. Third, a complete processing procedure of the real-time bottom tracking method is established by traversing each side scan ping data and recognizing the bottom sequences. The auxiliary methods for improving real-time performance and sample data augmentation are also explained in detail. The proposed method is implemented on the measured side scan data from the marine area in Meizhou Bay. The trained network model achieves a 100% recognition of the initial sample set as well as 100% bottom tracking accuracy of the training survey line. The average bottom tracking accuracy of the testing survey lines excluding missed pings reaches 99.2%. By comparison with multi-beam bathymetric data and the statistical analysis of real-time performance, the experimental results prove the validity and accuracy of the proposed real-time bottom tracking method.

Composition and distribution characteristics of macroinvertebrates in subtidal zone of the main marine bays in Fujian Province, China

With data for distributions and diversities of macroinvertebrates from 12 main subtidal zones in the bays of Fujian on August 2010, we investigated species composition, biodiversity and community structure, as well as their relationships with environmental factors. The results showed that 382 macroinvertebrates were recorded, which included 170 annelids, 75 crustaceans, 78 mollusks, 19 echinodermata, and 40 other species. The species richness, individual abundance, biomass and biodiversity indices showed significantly spatial variability. The average of species richness was (55±21), with the highest (92) in Luoyuan Bay and the lowest species (25) in Jiuzhen Bay. Polychaetes was dominant species in each bay, with an average percentage of (51.8±5.5)%. Zhaoan Bay had the highest average individual abundance with (1330±1094) ind·m-2, followed by Fuqing Bay, Xiamen Bay and Meizhou Bay, while Quanzhou bay had the lowest. Xinghua Bay had the highest average biomass with (821.2±2387.7) g·m-2, followed by Fuqing Bay and Xiamen Bay. Both richness index and Shannon diversity were much higher in Luoyuan Bay, Meizhou Bay, Shenhu Bay, Xiamen Bay and Dongshan Bay, and their values were low in Fuqing Bay and Jiuzhen Bay. The mean value for d and H across all bays was (0.80±0.09) and (2.73±0.64), respectively. The macroinvertebrates of the study area were divided into 14 groups using a criterion of 20% similarity. The stations in Luoyuan Bay had the highest similarity and the lowest spatial variability, and followed by Sansha Bay, Fuqing Bay, Shenhu Bay and Zhaoan Bay. The higher variability of community composition was found among the stations for the rest bays. On the basis of Spearman correlations among species richness, biodiversity indices and environmental factors, as well as PCA analy-sis, Cu in the sediment, water depth, and dissolved inorganic phosphorus in bottom water were the main factors driving the spatial variability of composition and distribution of macroinvertebrates in the study area.

Computational investigation on hydrodynamic and sediment transport responses influenced by reclamation projects in the Meizhou Bay, China

Reclamation projects are the main method of coastal exploitation, and the hydrodynamic environmental effect, together with the sediment transport response of the reclamation project, is important to the project’s site selection and environmental protection. Herein, a 3D numerical model based on the finite volume community ocean model (FVCOM) is applied to simulate the changes in the Meizhou Bay’s hydrodynamic environment and sediment transport after a reclamation project. The reclamation project greatly alters the shape of the shoreline and narrows the bay, leading to a significant change in its hydrodynamic environment and sediment transport. After the project, the clockwise coastal residual current in the corner above the Meizhou Island gradually disappears. An obvious counter-clockwise coastal residual current emerges around the rectangular corner. The tidal prism decreases by 0.65 × 109 and 0.44 × 109 m3 in the spring and neap tides, respectively. The residence time presents a major increase. These changes lead to the weakening of the water exchange capacity and the reduction of the self-purification capacity of the bay. Currents in the tidal channel weaken, whilst currents in the horizontal channel strengthen. The strength and scope of particle trajectories around the horizontal channel and the Meizhou Island enhance. The suspended sediment concentration (SSC) increases in the majority of the Meizhou Bay but decreases in the lateral bay. The eastern corner of Z2 shows a tendency to erode. The western region of the Meizhou Island, the upper portion of the rectangular corner and the western corner of Z4 show a tendency to deposit. The reclamation project increases the maximum storm surges by 0.06 m and decreases the maximum significant wave heights by 0.09 m.

Simulation research on the influence of special ships on waterway through capacity for a complex waterway system: a case study for the Port of Meizhou Bay

The study of waterway through capacity for ports is a challenging problem due to the randomness and complexity of the waterway system, which needs to be analyzed by simulation technology. This paper quantitatively studies the influence of special ships on waterway through capacity and provides corresponding measures to improve waterway through capacity. The complex waterway system in the Port of Meizhou Bay is employed as a case study. Considering the actual conditions in the Port of Meizhou Bay, including the ships, berths, waterways, and natural conditions, a Simio-based simulation model is established. The real operation data from the Port of Meizhou Bay in 2015 are used to verify the correctness and effectiveness of the model. The simulation results show that special ships reduce the waterway through capacity by 4.9% and suggest that circumnavigation strategies that can be adopted after the extension and new construction of waterway systems can improve the waterway through capacity by 5.9%.

A new species of Cymbasoma Thompson, 1888 (Copepoda: Monstrilloida) from the Fujian coast, China

A new monstrilloid copepod species, Cymbasoma cheni sp. nov., from Meizhou Bay (an embayment in Fujian Province, southeastern China) is described and illustrated. The diagnostic character of the new species is the structure and armature of the fifth leg, which is represented by a single lobe armed with three naked setae subequal in length. The new species closely resembles Cymbasoma bowmani Suarez-Morales and Gasca, 1998 in the structure of the fifth legs, and the body proportions, including total body length, and relative lengths of the cephalothorax and the genital double somite. However, Cymbasoma cheni sp. nov. is distinguished by lack of cuticular ornamentation on the cephalothorax, the position of the oral papilla, and the structure of the fifth leg with three naked setae. Although the structure of the fifth legs is similar in Cymbasoma cheni sp. nov. and Cymbasoma quintanarooense (Suarez-Morales, 1994), the new species can be easily distinguished from Cymbasoma quintanarooense by the relative length of the antennule, differences in the genital double-somite and the ovigerous spines, and the shape of ocelli. This is the sixth record of this genus from China seas.

Mining Channel Water Depth Information From IoT-Based Big Automated Identification System Data for Safe Waterway Navigation

Internet of Things technology has been widely used in water traffic research. Many critical waterways in the world are becoming more crowded due to many factors in waterway environments, such as invisibility, variability, and uncertainty. Accurate water depth information is necessary to improve navigation safety. Water depth information of electronic charts cannot be updated in a timely way, while the actual water depth is unpredictable, and this factor threatens the safety of vessels in waterway environments. Based on the shore-based network, ship navigation data and other big data can be integrated to vessels navigation environments in real time. In this paper, we present a new scheme to quickly and accurately construct a vessel safety navigation depth reference map, which contains appropriate channel water depth information. This effective scheme is based on automated identification system (AIS) data and increases the travel safety through crowded waterways. AIS data include rich maritime traffic information. Both the static and the dynamic information about vessels through waterways can be extracted and processed from big real-time AIS data. Based on extensive actual experiments, we apply data mining techniques to extract the waterway depth information both draft-depth and vessel trajectories based on AIS data. The data are collected from vessels in both locations: 1) the Nantong port, in Jiangsu Province, China and 2) Meizhou Bay waterway, in Fujian Province, China. The Hermite interpolation scheme is used to patch the trajectories of vessels, and the BP neural network model is introduced to predict the maximum vessel draft. Clustering and data fusion methods are employed to construct a vessel safety navigation depth reference map according to the cluster area of vessel trajectories and draft information. The experimental results demonstrate that the vessel safety navigation depth reference map accurately reflects the current water depth profile of channels. This paper can provide accurate and timely channel water-depth information for the vessel navigation and the maritime supervision. The proposed scheme in this paper can also provide reference for trajectory data processing and mining.

A systematic simulation methodology for LNG ship operations in port waters: a case study in Meizhou Bay

ABSTRACTWith the increment for liquefied natural gas (LNG) demand, LNG carriers are becoming larger in size. The operational safety of the carriers and the associated terminals is increasingly attracting attention. This is particularly true when a large LNG vessel approaches a terminal, requiring a detailed investigation of ship handling in port waters, especially in certain unusual cases. A full mission simulator provides an effective tool for research and training in operations of both port terminals and ships. This paper presents an experimental design methodology of the full mission simulation. The details as to how the simulation is achieved are described, and the simulation strategies applicable to LNG ships are specified. A typical case study is used to demonstrate and verify the proposed design methodology. The proposed methodology of the full mission simulation provides guidance for port safety research, risk evaluation and seafarer training.

Sensitivity Analysis on Key Factors of Sea-Rail Intermodal Transport System of Dry Bulk

With the growing demand of dry bulk in China, sea-rail intermodal transport gets more attention. In order to define the key factors of sea-rail intermodal transport of dry bulk , system dynamic and modeling software VENSIM were used to establish system dynamic model of sea-rail intermodal transport of dry bulk, and the case of sea-rail intermodal transport of dry bulk of Meizhou Bay Port in Fujian was used to simulate and check the model, the result shows that the model is feasible and effective. Finally, the key factors in the model were sensitively analyzed , and suggestions of promoting the development of sea-rail intermodal transport in Meizhou Bay port were made.

Evaluation of Pollution Source of the Bays in Fujian Province

Abstract Based on investigation data of pollution sources of seven bays in Fujian province (Luoyuan Bay, Quanzhou Bay, Xiamen Bay, Sansha Bay, Xinghua Bay, Meizhou Bay and Dongshan Bay), the pollutant source composition, total amount and distribution character of pollution sources are evaluated in this article. The result shows that: Pollution Sources of the Bays in Fujian province are mainly land-based pollution. Agricultural pollution source makes up the largest percentage of the land-based pollution sources, followed by domestic pollution source and soil erosion while industrial pollution source makes up the smallest percentage. Sea-based pollution sources come mainly from aquaculture pollution while vessel-source makes up only a very small percentage. Among the seven bays, Meizhou Bay has the largest amount of COD discharged into sea and Dongshan Bay the smallest; Xinghua Bay has the largest amount of TN, TP and Luoyuan Bay the smallest. The concept of pollutant load per unit tidal prism is introduced to evaluate the pollution pressure of each bay. The research can be a scientific support of the total amount control of pollution discharged into bay and promote the socioeconomic sustainable development in Fujian coastal area.

Heavy metal concentration and its evaluation in the organisms from Meizhou Bay

The present paper reports Zn, Cu, Pb, Cd, Ni, Fe, Mn and Co contents in the tissues of oyster, solen, red-tail prawn, sea eel and kelp, taken from Meizhou Bay (and analysed by flame atomic absorption spectrophotometry after wet digestion) in June 1992, and also the concentration factors estimated from the mean metal concentrations in the organisms and water there. Heavy metal concentrations in every species of the organisms followed the pattern: Fe, Mn, Cu, Zn>Pb, Cd, Ni, Co and in various organisms showed considerable variation. In general, levels of most of these metals were in the order. soft tissues of the bivalves>the kelp>muscles of the red-tail prawn, the sea eel. The greatest concentration of most metals was found in the gill or viscera of the sea eel, whereas the muscle tissues, in general, contained only low concentrations of them. The Cu, Zn concentration factors of the oyster were higher by 1–2 orders of magnitude than that of the other organisms. The observed heavy metal levels were close to those reported from various waters throughout the world, far lower than “Evaluation Standard for Polluting Substances in Marine Organisms” and “Medical Standard for Human Consumption”. This study showed that marine organisms from Meizhou Bay are hardly polluted by heavy metals.

The strategic role of ecological research in the design of an environmentally comprehensive plan for a new economic-development area?Meizhou Bay, China

The Government of China is planning a new economic-development area, located at Meizhou Bay on the Chinese mainland, opposite the island of Taiwan. Aspects of this development plant will be subject to an assessment of the potential environmental effects. Especially important considerations are changes in land use associated with urbanization and industrial developments, and any activities that could degrade air and water quality, with potential risks for human health, aquaculture, agriculture, and wildlife. During 1988 to 1990, we conducted studies related to meteorology, environmental geology and engineering, physical oceanography, and marine chemistry and biology.