2022 Vol. 44, No. 7
Display Method:
2022, 44(7): 1-3.
Abstract:
2022, 44(7): 1-16.
doi: 10.12284/hyxb2022108
Abstract:
The Yellow Sea presents unique topographic conditions, and the tidal wave movement in this area has unique characteristics. In this paper, Geostationary Ocean Color Imager (GOCI) inversion and Oregon State University (OSU) tidal current model are used to obtain the sea surface currents field in the Yellow Sea. Based on the unique tidal wave system in the sea area, the tidal wave interference area is proposed and identified, and then the currents field of GOCI inversion is extracted. And partition of two kinds of trend data usability evaluation, through the validation of the drifting buoy data evaluation. The results show that the sea surface currents field obtained by GOCI inversion and OSU tidal current model has a certain degree of reliability. The AME value of sea surface currents field velocity obtained by GOCI inversion is 0.77, and that obtained by OSU tidal model is 0.49. On the whole, the currents field data obtained by GOCI inversion and OSU tide model are reliable to a certain extent. In the central area of the Yellow Sea near the tidal wave interference area, the consistency between GOCI tidal currents data and OSU tidal currents data is better than that of OSU tidal currents data, and their AAE values are 48.45° and 63.10°, respectively. In the coastal area of the Yellow Sea far from the tidal wave interference area, the consistency between the OSU tidal currents data and the measured data is better than that of the GOCI tidal currents data in terms of velocity magnitude and direction.
The Yellow Sea presents unique topographic conditions, and the tidal wave movement in this area has unique characteristics. In this paper, Geostationary Ocean Color Imager (GOCI) inversion and Oregon State University (OSU) tidal current model are used to obtain the sea surface currents field in the Yellow Sea. Based on the unique tidal wave system in the sea area, the tidal wave interference area is proposed and identified, and then the currents field of GOCI inversion is extracted. And partition of two kinds of trend data usability evaluation, through the validation of the drifting buoy data evaluation. The results show that the sea surface currents field obtained by GOCI inversion and OSU tidal current model has a certain degree of reliability. The AME value of sea surface currents field velocity obtained by GOCI inversion is 0.77, and that obtained by OSU tidal model is 0.49. On the whole, the currents field data obtained by GOCI inversion and OSU tide model are reliable to a certain extent. In the central area of the Yellow Sea near the tidal wave interference area, the consistency between GOCI tidal currents data and OSU tidal currents data is better than that of OSU tidal currents data, and their AAE values are 48.45° and 63.10°, respectively. In the coastal area of the Yellow Sea far from the tidal wave interference area, the consistency between the OSU tidal currents data and the measured data is better than that of the GOCI tidal currents data in terms of velocity magnitude and direction.
2022, 44(7): 17-24.
doi: 10.12284/hyxb2022112
Abstract:
The loading tides in the South China Sea and adjacent straits are calculated by means of the Green’s function method based on a high-resolution regional ocean tide model for the South China Sea, the DTU10 global ocean tide model, and the Gutenberg-Bullen A Earth model. The results show that the maximum amplitude of M2 vertical displacement loading (VDL) tide exceeding 18 mm appears in the Taiwan Strait; the second maximum exceeding 14 mm appears off the north-west coast of Kalimantan. The maximum amplitudes of the K1 and O1 VDL tides, exceeding 18 mm and 14 mm respectively, appear near the southern South China Sea; the second maximum exceeding 8 mm, appears in the Beibu Gulf. The distribution patterns of self-attraction and loading (SAL) tides are very similar to those of VDL tides in that the SAL tides have amplitudes about 1.2 times to 1.7 times the corresponding VDL tides and have phases basically opposite to corresponding VDL tides. The maximum amplitude of M2 SAL tide also appears in the Taiwan Strait and off the north-west coast of Kalimantan, with a magnitude exceeding 24 mm and 18 mm respectively.
The loading tides in the South China Sea and adjacent straits are calculated by means of the Green’s function method based on a high-resolution regional ocean tide model for the South China Sea, the DTU10 global ocean tide model, and the Gutenberg-Bullen A Earth model. The results show that the maximum amplitude of M2 vertical displacement loading (VDL) tide exceeding 18 mm appears in the Taiwan Strait; the second maximum exceeding 14 mm appears off the north-west coast of Kalimantan. The maximum amplitudes of the K1 and O1 VDL tides, exceeding 18 mm and 14 mm respectively, appear near the southern South China Sea; the second maximum exceeding 8 mm, appears in the Beibu Gulf. The distribution patterns of self-attraction and loading (SAL) tides are very similar to those of VDL tides in that the SAL tides have amplitudes about 1.2 times to 1.7 times the corresponding VDL tides and have phases basically opposite to corresponding VDL tides. The maximum amplitude of M2 SAL tide also appears in the Taiwan Strait and off the north-west coast of Kalimantan, with a magnitude exceeding 24 mm and 18 mm respectively.
2022, 44(7): 25-36.
doi: 10.12284/hyxb2022096
Abstract:
The changes of shoreline caused by human activities affect the kinematic characteristics of tidal wave in the propagation process. Based on the hourly tidal level data from five tidal stations in the Wenzhou Bay from 1984 to 2019, the temporal and spatial variation of tidal wave patterns in this area and deconstructed the contribution of major tidal clusters to the tidal asymmetry is analyzed in this study . The results show that the tidal patterns in Oujiang Estuary and Yueqing Bay, two semi-enclosed embayments of the Wenzhou Bay, are obviously different. The tidal symmetry of Oujiang Estuary is flood-dominant tide and the tidal asymmetry increases continuously in the upstream direction, whilst tide is ebb-dominant in Yueqing Bay. Moreover, the tidal asymmetry shows distinct seasonal variation. The skewness (\begin{document}$ \gamma $\end{document} ![]()
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The changes of shoreline caused by human activities affect the kinematic characteristics of tidal wave in the propagation process. Based on the hourly tidal level data from five tidal stations in the Wenzhou Bay from 1984 to 2019, the temporal and spatial variation of tidal wave patterns in this area and deconstructed the contribution of major tidal clusters to the tidal asymmetry is analyzed in this study . The results show that the tidal patterns in Oujiang Estuary and Yueqing Bay, two semi-enclosed embayments of the Wenzhou Bay, are obviously different. The tidal symmetry of Oujiang Estuary is flood-dominant tide and the tidal asymmetry increases continuously in the upstream direction, whilst tide is ebb-dominant in Yueqing Bay. Moreover, the tidal asymmetry shows distinct seasonal variation. The skewness (
2022, 44(7): 37-46.
doi: 10.12284/hyxb2022120
Abstract:
Estuarine morphologies play an important role on tidal asymmetry. A two-dimensional numerical model is established with the Humber Estuary, UK as a reference site. A series of simulations are designed to examine the effects of the estuary cross-section shape, planform and convergence on the development of tidal asymmetry, whilst maintaining the same tidal prism. Model results show that deeper channels result in the lag and enhancement of phase difference whilst shallower channels result in a decline in the maximum ebb-tide velocity and longer period of ebb tide, and the estuary tends to be flood-dominated; narrow tidal flat tends to favour ebb dominance while broad tidal flat tends to favour flood dominance. Flood dominance is strongest in the convergent and long estuary. In addition, narrowing the estuary width will enhance the residual flow velocity of the main channel but weaken the residual flow velocity of the tidal flat. With the increase in estuary convergence, the residual flow velocity of the main channel increases but decreases on the tidal flat, and strengthen the flood dominance of the tidal flat. This paper further improves the research on the influence of estuary landforms on tidal asymmetry, which has certain guiding significance for reclamation and coastal engineering.
Estuarine morphologies play an important role on tidal asymmetry. A two-dimensional numerical model is established with the Humber Estuary, UK as a reference site. A series of simulations are designed to examine the effects of the estuary cross-section shape, planform and convergence on the development of tidal asymmetry, whilst maintaining the same tidal prism. Model results show that deeper channels result in the lag and enhancement of phase difference whilst shallower channels result in a decline in the maximum ebb-tide velocity and longer period of ebb tide, and the estuary tends to be flood-dominated; narrow tidal flat tends to favour ebb dominance while broad tidal flat tends to favour flood dominance. Flood dominance is strongest in the convergent and long estuary. In addition, narrowing the estuary width will enhance the residual flow velocity of the main channel but weaken the residual flow velocity of the tidal flat. With the increase in estuary convergence, the residual flow velocity of the main channel increases but decreases on the tidal flat, and strengthen the flood dominance of the tidal flat. This paper further improves the research on the influence of estuary landforms on tidal asymmetry, which has certain guiding significance for reclamation and coastal engineering.
2022, 44(7): 47-57.
doi: 10.12284/hyxb2022110
Abstract:
Current CMIP6 climate models (such as CESM2 and NESM3) use constant snow density, while those models that focus on snow depth and density changes (such as SnowModel-LG) use empirical snow density formulas. Comparing the modeled snow depth with those observed by the CryoSat-2 satellite, it is found that from the perspective of the spatial distribution and average value of the snow depth, it is difficult to detect the effects of varying snow density on the simulation of snow depth in the Arctic Ocean. The model improvement and its mechanism from varying snow depth is still to be further studied. Here an empirical snow density model considering meteorological factors such as air temperature, wind etc., is applied to the SNOTEL observational site to carry out the following sensitivity experiments for different factors: A. snow density model considering all meteorological factors; B. constant snow density model; C. same as A but the influence of wind on the densification is not considered and D. same as A but the influence of temperature on the densification is not considered. The root mean square error of snow depth simulated by experiments A, B, C and D from November 1, 2018 to May 10, 2019 are 4.2 cm, 4.8 cm, 25.9 cm, and 4.2 cm, respectively. The results show that the mean snow density and depth simulated by the varying snow density model are close to the results using constant snow density, but the root mean square error of the simulated snow depth from Case A is the smallest, and the Case A simulation can reproduce the high frequency variations of snow depth on the time scale of several days to ten days. In the meantime, the relative errors in the period with high-frequency snow depth variations are also reduced as they are found to be related. In addition, it is also found that the influence of temperature on snow densification is much smaller than that of wind.
Current CMIP6 climate models (such as CESM2 and NESM3) use constant snow density, while those models that focus on snow depth and density changes (such as SnowModel-LG) use empirical snow density formulas. Comparing the modeled snow depth with those observed by the CryoSat-2 satellite, it is found that from the perspective of the spatial distribution and average value of the snow depth, it is difficult to detect the effects of varying snow density on the simulation of snow depth in the Arctic Ocean. The model improvement and its mechanism from varying snow depth is still to be further studied. Here an empirical snow density model considering meteorological factors such as air temperature, wind etc., is applied to the SNOTEL observational site to carry out the following sensitivity experiments for different factors: A. snow density model considering all meteorological factors; B. constant snow density model; C. same as A but the influence of wind on the densification is not considered and D. same as A but the influence of temperature on the densification is not considered. The root mean square error of snow depth simulated by experiments A, B, C and D from November 1, 2018 to May 10, 2019 are 4.2 cm, 4.8 cm, 25.9 cm, and 4.2 cm, respectively. The results show that the mean snow density and depth simulated by the varying snow density model are close to the results using constant snow density, but the root mean square error of the simulated snow depth from Case A is the smallest, and the Case A simulation can reproduce the high frequency variations of snow depth on the time scale of several days to ten days. In the meantime, the relative errors in the period with high-frequency snow depth variations are also reduced as they are found to be related. In addition, it is also found that the influence of temperature on snow densification is much smaller than that of wind.
2022, 44(7): 58-70.
doi: 10.12284/hyxb2022102
Abstract:
With the intensification of global warming, the source sink process of carbon in the Arctic shelf-edge sea is becoming more and more important in the study of global carbon cycle. As a typical continental shelf marginal sea in the Arctic Ocean, the source, transportation and burial of sedimentary organic carbon in this area are unique under the influence of rivers, sea ice, marine primary productivity and coastal erosion. Based on the sampling of suspended particulate matter (SPM) and hydrological data obtained from the second Sino-Russian Arctic joint expedition during late summer and early fall in 2018, we foucus on the distribution characteristics, sources and influencing factors of particulate organic carbon (POC) in the Laptev Sea. The results show that POC ranges from 35.27 μg/L to 1 185.58 μg/L, with an average of 172.65 μg/L. Under the effect of river input, coastal erosion and marine primary productivity, the distribution of surface POC shows a decreased trend from near shore towards offshore; the bottom POC is mainly controlled by sediments resuspension, and the high content of POC appears in the east of Lena River Delta. There was a significant positive correlation between SPM concentration and POC concentration, indicating its direct impact on the occurrence of POC; a more positive relation is found among the bottom layer samples, which may indicate the varied origin of POC in different layers. The value of δ13CPOC in study area value is between −31.03‰ and −25.79‰, and the value of δ13C in surface layers is obviously depleted compared with the bottom layer, which is even lower than the end-member of the surrounding terrestrial contributor, suggesting that these POC is not derived from land-based origin. The utilization of the terrestrial POC degraded dissolved inorganic carbon by offshore phytoplankton maybe responsible for this depletion of δ13C offshore, which could also be an important process on the supply and source apportionment of POC in this Arctic coastal area.
With the intensification of global warming, the source sink process of carbon in the Arctic shelf-edge sea is becoming more and more important in the study of global carbon cycle. As a typical continental shelf marginal sea in the Arctic Ocean, the source, transportation and burial of sedimentary organic carbon in this area are unique under the influence of rivers, sea ice, marine primary productivity and coastal erosion. Based on the sampling of suspended particulate matter (SPM) and hydrological data obtained from the second Sino-Russian Arctic joint expedition during late summer and early fall in 2018, we foucus on the distribution characteristics, sources and influencing factors of particulate organic carbon (POC) in the Laptev Sea. The results show that POC ranges from 35.27 μg/L to 1 185.58 μg/L, with an average of 172.65 μg/L. Under the effect of river input, coastal erosion and marine primary productivity, the distribution of surface POC shows a decreased trend from near shore towards offshore; the bottom POC is mainly controlled by sediments resuspension, and the high content of POC appears in the east of Lena River Delta. There was a significant positive correlation between SPM concentration and POC concentration, indicating its direct impact on the occurrence of POC; a more positive relation is found among the bottom layer samples, which may indicate the varied origin of POC in different layers. The value of δ13CPOC in study area value is between −31.03‰ and −25.79‰, and the value of δ13C in surface layers is obviously depleted compared with the bottom layer, which is even lower than the end-member of the surrounding terrestrial contributor, suggesting that these POC is not derived from land-based origin. The utilization of the terrestrial POC degraded dissolved inorganic carbon by offshore phytoplankton maybe responsible for this depletion of δ13C offshore, which could also be an important process on the supply and source apportionment of POC in this Arctic coastal area.
Variations of suspended sediment concentration of the Mississippi River delivered from land into sea
2022, 44(7): 71-81.
doi: 10.12284/hyxb2022098
Abstract:
The change of fluvial suspended sediment concentration (SSC) to the sea directly reflects the effects of riverine anthropogenic activities and natural force. Based on long-term hydrological data at Tarbert Landing Station of the Mississippi River (MR), statistical means, such as percentile method and Mann-Kendall method are used to detect change process of SSC from the MR entering the Gulf of Mexico in recent 40 years, and associated possible influencing factors. The results show that: (1) SSC from the MR entering the Gulf of Mexico is characterized by a staged decline from 1976 to 2015, in the first stage from 1976 to 1987, the SSC is relatively high with an average value of 0.33 kg/m3; in the second stage from 1988 to 2015, the SSC is much lower with a mean value of 0.25 kg/m3. (2) The relationship between daily SSC and runoff of MR follows Gaussian distribution. Compared with the first stage (1976−1987), the rating curve between SSC and runoff in the second stage (1988−2015) is relatively flat, when the number of high daily SSC event over 0.60 kg/m3 reduces significantly. SSC increases with the runoff in low-action flows and reaches the maximum when the runoff approaches 20 000 m3/s, but decreases with the runoff thereafter. The rating curve between monthly SSC and water discharge of the MR exhibits “double-loop” shape during 1976−1987, but presents clockwise “single loop” with “sediment before water” during 1988−2015. (3) Flood diversion project construction and soil conservation measures dominate the fluvial SSC from the MR into the Gulf of Mexico. The construction of flood diversion engineering reduces the sediment source along the river channel, and the soil conservation measures repress the land erosion, which have combined to keep the SSC at a relatively low level. In addition, SSC in the MR presents minor response to extreme hydrological events.
The change of fluvial suspended sediment concentration (SSC) to the sea directly reflects the effects of riverine anthropogenic activities and natural force. Based on long-term hydrological data at Tarbert Landing Station of the Mississippi River (MR), statistical means, such as percentile method and Mann-Kendall method are used to detect change process of SSC from the MR entering the Gulf of Mexico in recent 40 years, and associated possible influencing factors. The results show that: (1) SSC from the MR entering the Gulf of Mexico is characterized by a staged decline from 1976 to 2015, in the first stage from 1976 to 1987, the SSC is relatively high with an average value of 0.33 kg/m3; in the second stage from 1988 to 2015, the SSC is much lower with a mean value of 0.25 kg/m3. (2) The relationship between daily SSC and runoff of MR follows Gaussian distribution. Compared with the first stage (1976−1987), the rating curve between SSC and runoff in the second stage (1988−2015) is relatively flat, when the number of high daily SSC event over 0.60 kg/m3 reduces significantly. SSC increases with the runoff in low-action flows and reaches the maximum when the runoff approaches 20 000 m3/s, but decreases with the runoff thereafter. The rating curve between monthly SSC and water discharge of the MR exhibits “double-loop” shape during 1976−1987, but presents clockwise “single loop” with “sediment before water” during 1988−2015. (3) Flood diversion project construction and soil conservation measures dominate the fluvial SSC from the MR into the Gulf of Mexico. The construction of flood diversion engineering reduces the sediment source along the river channel, and the soil conservation measures repress the land erosion, which have combined to keep the SSC at a relatively low level. In addition, SSC in the MR presents minor response to extreme hydrological events.
2022, 44(7): 82-94.
doi: 10.12284/hyxb2022100
Abstract:
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.
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.
2022, 44(7): 95-102.
doi: 10.12284/hyxb2022134
Abstract:
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
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
2022, 44(7): 103-111.
doi: 10.12284/hyxb2022146
Abstract:
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.
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.
2022, 44(7): 112-121.
doi: 10.12284/hyxb2022124
Abstract:
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.
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.
2022, 44(7): 122-136.
doi: 10.12284/hyxb2022118
Abstract:
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.
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.
2022, 44(7): 137-144.
doi: 10.12284/hyxb2022106
Abstract:
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.
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.
2022, 44(7): 145-160.
doi: 10.12284/hyxb2022122
Abstract:
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.
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.
2022, 44(7): 161-169.
doi: 10.12284/hyxb2022114
Abstract:
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.
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.
2022, 44(7): 170-176.
doi: 10.12284/hyxb2022104
Abstract:
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.
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.
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