Journal of Sea Research最新文献

The Southern Indonesian (SI) region is known for its high-intensity coastal upwelling caused by monsoonal wind. Interannual phenomena such as El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) also influence upwelling activity in this region. This study analyzed the relationship between upwelling intensity (UI_sst) and those variables and their impact on oceanographic features such as Sea Surface Temperature (SST) and chlorophyll-a concentration. We used satellite imagery data, including SST from the National Oceanic and Atmospheric Administration (NOAA) and chlorophyll-a from MODIS, to analyze the aforementioned issue. To identify the impact of wind patterns on coastal upwelling, we analyzed using zonal wind stress from ERA-5 Data. Quantification of UI_sst is defined as the SST gradient between the coastal and open ocean waters. Linear and partial correlation analysis between UI_sst with the Ocean Niño Index (ONI) and Dipole Mode Index (DMI) were conducted to see the influence of ENSO and IOD phenomena. Anomaly analysis was also conducted on SST, chlorophyll-a concentration, zonal windstress and UI_sst to see how large the values were during the years of the ENSO and IOD events. Upwelling in the SI region typically occurs during southeast monsoon (SEM) periods, starting earlier in the East side (Nusa Tenggara Islands) and moving towards the West side (South Coast of Java). The correlation analysis (both linear and partial) indicates that the IOD has a stronger influence on UI_sst in the SI region compared to ENSO, especially during June to October (SEM periods). This finding is confirmed by anomaly analysis, which reveals significant changes in SST, chlorophyll-a concentration, zonal windstress, and UI_sst during ENSO and IOD events. The magnitude of the anomalies is generally stronger during IOD events than those observed under ENSO conditions.

Internal waves are easily recognized features of remote sensing images. They occur below the sea surface and can be observed using optical and radar sensors due to their interactions with surface waves. Nonlinear internal waves, known as Internal Solitary Waves (ISW), maintain their coherence and visibility through nonlinear hydrodynamics and appear as long quasilinear stripes in images. Optical sensors can capture changes in sea surface roughness modulated by ISW when their location is close to specular reflection from the sun. Optical imagery with wide area coverage and high temporal resolution has the potential to track and analyze ISW dynamics. However, a comprehensive analysis of the mechanisms underlying ISW manifestation patterns in optical images is necessary. The GCOM-C/SGLI satellite, equipped with a visible-near infrared radiometer and an infrared scanner, provides a detailed view of ISW manifestations using various scanning techniques. By analyzing SGLI products that detect ISW patterns, this study investigated how these waves manifest on the sea surface. The comparison between Level-1B data and Level-2 Ocean products observed by the SGLI sensor reveals that ISW patterns significantly affect ocean color parameters and thermal channel data. The consistent ISW manifestation pattern detected in TOA radiance and ocean color products suggests that ISWs impact sea surface roughness. Additionally, the detection of ISW patterns in SST data is a notable finding, highlighting the potential influence of ISWs on air-sea interactions and the atmospheric boundary layer. Understanding these impacts is crucial for remote sensing applications, particularly for long-term internal wave monitoring and ensuring that smaller-scale internal wave signals do not interfere with large-scale satellite estimations of ocean color.

As global concerns about carbon emissions mount, Automated Guided Vehicles (AGVs) have made a significant transition from reliance on petroleum fuel to predominantly utilizing electric power. However, in past port settings, the majority of Automated Guided Vehicle (AGV) control strategies have overlooked the impact of AGV charging and have not taken energy consumption into account. Furthermore, the AGV's electricity consumption is uncertain. Recognizing AGVs as the primary energy-consuming equipment in automated dockyards, this paper introduces a novel AGV resilient scheduling problem that integrates charging constraints and formulates a corresponding model that encompasses these limitations. Building upon established loading or unloading tasks, this model allocates AGV scheduling, including charging requests, to adhere to battery constraints and minimize AGV energy consumption costs. Moreover, a mathematical method based on Large Neighborhood Search (LNS) has been developed to address this issue. Finally, numerical experiments were conducted at a genuine large-scale automated port in China, meticulously analyzing the layout of charging areas, the establishment of charging thresholds, and the deployment of AGVs, thus highlighting the paramount significance of the operational framework of automated ports.

Coastal zones play a crucial role in China's marine economy and ecological security. However, the intensification of the human activities has increased the burden on the ecosystems and carbon storage capacity of the coastal zones. In this pursuit, a case study was conducted in Lianyungang, wherein the carbon stocks were assessed using ArcGIS and InVEST model in view of the carbon neutrality targets. Remote sensing data for the years 2010, 2015, 2018, and 2020 was analyzed to assess the carbon storage capacity in the coastal zones of Lianyungang, and the causes of variation and the spatial evolution patterns were studied. The results showed that the carbon storage capacity of the coastal zones of Lianyungang showed a progressive decline with time. The carbon stock in 2020 was 6.245 × 10⁶ TC (measured by CO₂), which was more as compared to that of a decade ago. Based on estimation of the carbon stocks, several ecological restoration strategies were proposed for coastal zones of Lianyungang. The study area was divided as: ecological control space, ecological restoration space and ecological governance space. Ecological management requirements and suggestions were proposed for each type of space. Our research not only contributes to the sustainable management of coastal zones of Lianyungang, but also provides a scientific basis for achieving the carbon neutrality targets.

Accurate water depth estimation is crucial in coastal environmental management, resource exploration, and ecological protection. Traditional water depth measurement methods are often time-consuming and costly, especially in vast sea areas where their application is limited. However, with the rapid development of remote sensing technology, particularly the widespread use of high-resolution satellite imagery, water depth remote sensing has emerged as a more efficient, economical, and widely applicable solution. In this study, we utilized Sentinel-2 satellite data and applied various algorithms to accurately estimate water depth in the Nanshan Port area. The results showed that the Gradient Boosting Machine (GBM) model excelled in monitoring shallow water and coastal environments, effectively addressing challenges such as light attenuation and water scattering in turbid waters. Compared to traditional methods, GBM-generated predictions were smoother and more detailed. This study not only demonstrates the significant potential of satellite remote sensing for water depth measurement but also points to future directions for algorithm optimization and the integration of remote sensing technologies. It is expected to bring revolutionary progress to oceanic scientific research and coastal management.

Fisheries activites and oceanographic conditions have a strong relationship. Understanding the complex interplay between fisheries and oceanographic conditions is essential for effective fisheries management. The aim of this research is to analyze the in-situ fishing activities with oceanographic conditions in the Fisheries Management Area (FMA) or WPP-NRI 718 located in the Aru Sea and its surroundings. The main data source is from open global data ship tracking and oceanographic conditions from satellite data. In general, fishing is conducted around the waters of Aru Island. The fishing grounds are strongly influenced by a combination of environmental factors, including sea surface temperatures, chlorophyll-a (Chlor-a) concentrations, sea surface height, and current velocities. A decrease in fishing patterns around Aru Island waters occurs in the eastern season, where fishing tends to occur in the western region (near Timor-Leste). Based on the oceanographic conditions, fishing tends to occur in regions with warmer conditions ranging from 27 to 29 °C, moderate Chlor-a (1.02–3.01 mg/m³), a relatively high surface height (0.17–0.32 m), and slow surface currents.

Artificial reefs are basic fishery facilities for marine habitat conservation and construction. In order to enhance fishery resources and restore the ecological environment in Laizhou Bay, where is an important fishing ground in China, an assembly-type oyster reef was designed based on the biological community, water depth and sea current in Laizhou Bay. This paper studied the effect of filling oyster shell in the assembly-type oyster reef on the flow field distribution by computational fluid dynamics (CFD), optimized the structure of reef, and presented the construction deployment of reef habitat and assessed potential of carbon fixation of oyster reefs. Indexes of upwelling, slow flow and vortex were chosen to describe the flow field effect of oyster reefs. The distribution characteristics of flow field under three types of filling oyster shell were analyzed: filling no shell (UAR), filling shells with an 83.6 void ratio (OAR), and filling shells with a 0 void ratio (FAR). The results showed that the upwelling, vortex and slow flow efficiency indicators of the OAR had obvious advantages compared with the other two filling methods, and the efficiency indicators of OAR with the spacing between basic elements of 280 m and deployment angle of 0° were higher than the others. Finally, according to the study result of filling method, spacing and deployment of oyster reef, the assessment showed that reefs could fix 2178.9 t carbon by themselves on the basis of national marine ranching demonstration area regulations in China.

Indonesian coastal waters include several marine megafauna biodiversity hotspots. Several fish populations of ecological and socio-economic importance, such as elasmobranchs (sharks and rays), have experienced rapid decline due to unsustainable human activities, primarily overfishing. Small-scale fisheries (SSF) are currently exempt from governmental fisheries management measures despite contributing a significant proportion of a total catch. The Generalised Additive Models were used to investigate the effect of variations in oceanographic parameters of the Teluk Penyu fishing ground, south of central Java, on the magnitude of Mobulidae (Mobula spp.) catch based on its landings data over ten years (2009–2018) from one of Indonesia's largest ports, Cilacap, Central Java, Indonesia. Mobulidae catch from Teluk Penyu fishing ground was generally higher from June to November when the water exhibited relatively high sea surface salinity (sal >34.1 ‰), chlorophyll (0.32–0.45 mg/m³), and nitrate (nit >0.0045 mg NO₃/m³), water speed (>0.29 m/s) and eddy kinetic energy (>0.04 m³/s²) levels, and relatively low sea surface temperature (<28 °C), oxygen (<0.182 mg O₂/m³) and sea surface height (<0.9 m) levels than the other months of the year. This study reveals that satellite Earth Observation (EO) data provided a preliminary relationship between oceanographic conditions and the amount of catch for developing more effective management and conservation measures for endangered species like Mobulidae. Utilizing EO data may also be applied to help inform much-needed ecosystem-based management measures, including habitat protection and bycatch reduction for conserving endangered Mobulidae species in the Southeast Indian Ocean. The in-situ onboard ocean observation and temporal species-specific catch data will greatly complement the current work.

The La Niña event not only affected global ocean dynamics but also marine productivity. Due to its importance to the life of organisms and ecosystems, the biophysical aspects should be analyzed. One of the important regions in the eastern region of the Indian Ocean is located in the upwelling system and central marine biodiversity. The study aims to investigate several parameters, including SSTs, dissolved oxygen levels, nitrate distribution, and Chlor-a concentration, which are combined with ocean currents. These parameters are then analyzed in the period 2020 to 2022, which is La Niña condition. Based on the results, significant changes occur in SST during the first transitional season of 2022, where the increase reaches 1–4 °C. There was an increase in La Niña during this period. For marine productivity parameters, the recorded DO is in the range of 197 to 218 mmol/m³, nitrate with a value range of 0 to 0,02 mmol/m³, nanoplankton with a value range of 0 to 0.03 mg/m³, and Chlor-a with a value range of 0 to 4 mg/m³. We also found that changes in ENSO events affect the productivity of the Eastern Region of the Indian Ocean, especially in the Chlor-a parameter, where the occurrence of La Niña extreme is the most important parameter.