A dataset of the high water lines extracted from 113 Landsat images from 1986 to 2019 and the measured profile data from 2015 to 2019 were used to examine the middle-term to long-term shoreline process and driver at the embayment scale in this paper. The results show that the western and eastern beaches of the Qiwang Bay, which is separated by one small bedrock headland, have four and three different spatial characteristics, respectively. More than half of the shorelines behaved nonlinear in their variation trends. Thus, we use the Mann-Kendall method to solve the problem of the lack of basis for the division of time periods. In addition, the east breakwater resulted in the unstable embayment planform due to changing the position of the controlling “headland” and therefore the longshore sediment transport from west to east is the main driver of the most recent shoreline. And the intervening small bedrock headland also influenced the spatial variability of erosion and accretion at the Qiwang Bay. These findings will have important theoretical and practical significance for predicting further shoreline position and reducing the risk of shoreline erosion.

Based on the sea surface temperature (SST), which is the most dominant environmental climate factor affecting the distribution of squid, the potential habitat changes of Ommastrephes bartramii in July to October in 1996−2005, 2021−2030, 2051−2060 and 2090−2100 are analyzed using maximum entropy (MaxEnt) model with the historical climate data from 1996 to 2005 and the projection climate data from RCP4.5 and RCP8.5 scenarios. The results show that the fishing grounds of O. bartramii performs a seasonal north-south migration. Meanwhile, as the seasonal north-south migration of O. bartramii may be affected by the suitable SST range in fishing season, with the feature climate change the potential habitat distribution of O. bartramii from July to September in 2021−2030, 2051−2060 and 2090−2100 will move northward and the suitable habitat area will increase compare to 1996−2005 under both scenarios of RCP4.5 and RCP8.0. Under scenario of RCP4.5, the potential most suitable habitat for O. bartramii will move northward by 1°−2° and the suitable habitat area will increase by 3%−13% by the end of the 21st century. Under scenario of RCP 8.5, the potential most suitable habitat for O. bartramii will move northward by 3°−5° and the suitable habitat area will increase by 42%−80% by the end of the 21st century.

Sillago sihama is an important fishery species in China and plays an important role in the marine ecosystem of the Yellow Sea. Species distribution models can be used to predict its distribution by establishing the relationships between its abundance and environmental factors. However, due to high mobility of the marine animals, the relationship between their distribution and environmental factors is often nonlinear and variable with spatial locations. Based on data collected from bottom trawl survey in the Shandong coastal waters in autumn of 2016, both generalized additive model (GAM) and geographically weighted regression (GWR) model were used to analyze nonlinear and spatial nonstationary relationships between distribution of the species and environmental factors, and results from the two models were compared. Results from the GAM indicated that the main environmental factors were depth, sea bottom temperature and salinity, and depth had the largest deviance explained (23.50%). GWR model results showed that there were spatial non-stationary relationships between distribution of the species and depth and sea bottom temperature. GWR model results indicated a negative correlation between depth and biomass of the species, and a positive correlation between sea bottom temperature and biomass of species. Regarding performance of the models, GWR model showed advantages over GAM in identifying influencing factors and predicting distribution, and GWR model was recommended for use in similar applications.

In this study, four samples of Gymnothorax mucifer were collected from the fishery market of Xiamen City, Fujian Province during the year 2020 to 2021, which were newly recorded in the coastal waters of China. Previously, the species had only been recorded in Australia and Hawaii, and was considered to be a synonym of Gymnothorax kidako. Detailed morphological characteristics of four G. mucifer species were analyzed, and the molecular identifications as well as phylogenetic constructions were also carried out basing on DNA barcode COI gene in this study. The main distinguishing characteristics of G. mucifer were as follow: the colour of the body was yellowish brown, the front of the head was slightly purple, the whole body was covered with slender, sparse, irregular branch-liked brown marking and the markings became darker and thicker near the tail, forming clear net-liked patterns; the margin on the anal fin was white, and became serial pale blotches on posterior part of the tail; total length was 1.01 times of standard length and 8.00−8.39 times of head length; the maxillary teeth were 8−10 and dentary teeth were 14−20 on each side, both teeth were uniserial; the median inter maxillary teeth were slender and uniserial; the total vertebrae were 117−139 and mean vertebral formula was 6-47-130. Basing on the COI gene analysis, the genetic distance between G. mucifer and G. kidako was 0.074, which was greater than the value 2% (0.020) suggested by Herbert as minimum genetic distance value to distinguishing different species, revealing that the two species might be two independent species. Morphologically, G. mucifer could also be distinguished from G. kidako by certain external characteristic: the body markings of G. mucifer were slender, sparse and inconspicuous, the front of the head was slightly purple, and the white margin of the anal fin broke into series of pale blotches on posterior part of the tail; the markings of G. kidako were obvious and thick with darker colour, the front of the head was yellow-white, the white margin on the anal fin continuous to the tip of the tail. The results of the study provided a taxonomic basis for the systematic classification and the species list revision of the Gymnothorax fish in our country.

Tsunami is one of the disasters that seriously endanger the safety of human life and property among natural disasters. In the context of global warming and increasing economic development, more and more people, infrastructure and wealth are exposed to tsunami disasters, greatly increasing the risk and vulnerability of personal and property safety in coastal and delta areas. The analysis of temporal and spatial variation of historical tsunami disasters can help us understand the evolutionary laws of tsunami disasters, and provides a useful reference for more accurate disaster warning, disaster prevention and control, etc. A study on the temporal and spatial variation of global tsunami by extracting complete and homogeneous data is conducted in this paper. The results show that: (1) for 0.1 m≤RH<0.5 m, 0.5 m≤RH<1 m, 1 m≤RH<5 m, 5 m≤RH<10 m, 10 m≤RH<20 m and 20 m≤RH intervals, the tsunami catalogues can be considered complete since 1963, 1940, 1950, 1946, 1922 and 1885 respectively; (2) from time changes it can be seen that there is a certain increasing trend in the occurrence of global tsunamis. Approximately 7 more wave runup events are observed every year. At the same time, in different intensity intervals, the frequency of tsunamis has different changes. In the intervals of 0.1 m≤RH<0.5 m, 0.5 m≤RH<1 m, and 1 m≤RH<5 m, the tsunami have a certain periodicity, showing two obvious peaks, but when the RH is greater than 5 m, the periodicity of the tsunami is no longer obvious, and it shows a clear increasing trend at this time; (3) there is a certain increasing trend in the occurrence of tsunamis in East Asia, South Pacific, South America, and Indian Ocean. However, in North America, there is a decreasing trend, and there is no significant change in Europe; (4) except for North America, tsunami events in other regions show a good power law distribution relationship, indicating that the occurrence of tsunamis follows certain self-organized critical behavior. In comparison, small tsunami events are more likely to occur in Europe, while tsunami events in East Asia and the Indian Ocean are more prone to various types of tsunami events, of which large tsunami events occupy a larger portion.

The internal solitary wave and mesoscale eddy are common mesoscale dynamic processes in the northern South China Sea. In this paper, we use the Terra/Aqua-MODIS, ENVISAT ASAR and multi-source satellite altimeter data from 2010 to 2015 to realize remote sensing of isolated waves and mesoscale eddy in the South China Sea, and analyze the influence of mesoscale eddy on the propagation direction of internal solitary wave. The results show that the mesoscale eddy and the internal solitary wave coexist mainly in the northeastern part of the South China Sea. When the two coexisted, the cyclone (cold eddy) caused the internal solitary wave to deviate from the original propagation direction and propagation and spread to the west-south direction. The anticyclonic (warm eddy) causes the internal solitary wave to spread westward to the north, and the cyclone and the anticyclone change the direction of the internal solitary wave propagation is just opposite. The coexistence time of internal solitary wave and mesoscale eddy is mainly concentrated from March to September, and the propagation direction of internal solitary wave is almost unchanged in March due to the interaction of cyclone and anticyclone. In April and May, the internal solitary wave deviated from its original propagation direction and propagated southward mainly due to cyclone. From June to September, the internal solitary wave deviated from its original direction and propagated northward, mainly under the influence of anticyclone. In April and May, the internal solitary wave deviated from its original propagation direction and propagated southward mainly due to cyclone. From June to September, the internal solitary wave deviated from its original direction and propagated northward, mainly under the influence of anticyclone. The effect of mesoscale eddy on the propagation direction of internal solitary wave is investigated by remote sensing, and the results are in agreement with the field observation.

Atmospheric correction (AC) is the basis and premise of quantitative remote sensing of water column. The effects of different AC models on water depth inversion from the four aspects of AC model, AC model parameters, water component differences, and water depth inversion band combination are discussed in this paper. The research uses 6S, FLAASH, ACOLITE and QUAC four AC models, select continental, marine and urban aerosol patterns, and the shallow waters around the northwest side of Oahu Island and Shemya Island are used as the study area of clean water, while the shallow waters around Liaodong Shoal and Penang Strait are used as the study area of turbid water. AC is performed based on Landsat-8 multispectral images, and eight wavebands are used for bathymetric remote sensing inversion. The results show that: (1) all the four AC models can weaken the atmospheric influence on the water signal to some extent; the correction results of different models are somewhat different depending on the parameter selection and the components of the water column. And the peak reflectance of the two types of water column occurs in the blue and green bands, respectively. (2) The 6S model is more robust, and the bathymetric inversion results of this model are less volatile than the rest of the models due to the changes in the components of the water column. The water depth inversion results of the two aerosol models of the FLAASH have more obvious differences in turbid water, and the difference of MRE in shallow water of Liaodong Shoal is 7.9%; the ACOLITE model is significantly influenced by the water column type and has superiority and stability for turbid water, and the MRE is 5.6% lower than that of FLAASH. (3) The accuracy of multi-band water depth inversion is generally better than that of single-band, but there is no significant correlation between the accuracy of inversion and however, there is no significant correlation between the inversion accuracy and the number of bands; the combination of bathymetric inversion bands has different sensitivity to different study areas, the inversion accuracy of the three-band model is better in clean water, and the inversion accuracy of the four-band model is optimal in turbid water, and the MRE is reduced by 5.6% compared with the three-band model.

Sea ice thickness is one of the main sea ice parameters. Automatic recognition of sea ice thickness in video is a significant component of sea ice parameters extraction. In this paper, the machine vision method based on Hough transform is used to recognize the surface contour of sea ice, so as to obtain the sea ice thickness parameters. According to the characteristics of sea ice image, the overall recognition process is divide into image edge recognition, approximate line segment recognition and sea ice contour segment group recognition. In the process of line segment identification, three parameters of line segment group including angle, length and spacing are established based on the geometric characteristics of sea ice. In order to verify the reliability of the method, this method is applied to analysis the field survey data of Xuelong icebreaker’s eighth Arctic expedition. The results show that the three parameters have the optimal threshold value. When it is lower than this value, increasing the threshold will increase the effective recognition rate; when it is higher than this value, increasing the threshold will increase the false recognition rate. The ice thickness recognition rate can reach more than 90% by using the optimal threshold. Therefore, the ice thickness identification method based on Hough transform can realize the real-time monitoring of sea ice thickness.

In order to quantitatively study the sheltering effect between multiple ridges keel on sea ice drift, the laboratory experiment is carried out in a tank, which is 0.45 m deep. The shape of keel models is a triangle with 45° slope angle, 4 keel depths and 9 keel spacings are selected in the experiments. The variations of the front and back keel drag force and its ratio under wake effect is investigated. The drag force on the front keel is not affected by the back keel and keeps a linear relationship with the square of keel velocity; however, the drag force of back keel appears negative value (opposite direction) when the keel spacing is small. With the increase of the spacing the drag coefficient of the back keel first decreases and then increases to a constant. The variation of the ratio of drag forces between the front and back can be described by an exponential sheltering function, which is related to keel spacings and keel depths, and independent of keel velocity. Compared with the sheltering functions which are used in present sea ice models, the exponential formula is given and improves our understanding about sheltering function in sea ice dynamic model.

Tidal-current-asymmetry (TCA) influences sediment transport and geomorphologic changes. It is of paramount importance to understand the current asymmetry in this area in context of a long-term scale with consideration of development and protection of the coastal resources. The radial sand ridges (RSR) in the South Yellow Sea is patterned with strong tidal forcing and complex hydrodynamic environment. This paper simulated tidal current field in the RSR based on the Delft3D model and used combined harmonic analysis and skewness theory to analyze the spatial distribution of the TCA under varied shoreline conditions. The results show that peak-current-asymmetry (PCA) in the RSR is mostly flood-dominant and slack-water-asymmetry (SWA) also shows positive, meaning the flooding duration is shorter than the ebbing duration. Both the positively-dominant PCA and negatively-dominant SWA are mainly affected by the nonlinear interactions between the semidiurnal diurnal tides (M₂, S₂) and shallow water tides (M₄, MS₄). As the shoreline gradually moves towards sea during 1984 to 2014, although the nature of $ {\gamma }_{\mathrm{P}\mathrm{C}\mathrm{A}} $ remains, the magnitude of which increases by up to 25%. Meanwhile,$ {\gamma }_{\mathrm{S}\mathrm{W}\mathrm{A}} $ decreases by up to 20%, which intensifies its shorter-flooding-duration pattern in the core area of the RSR.