Offshore China Research Articles

Offshore aquaculture in China

AbstractThe mariculture industry is planning to move offshore due to the decline of China's inshore fishery resources, the deterioration of the water environment, inefficient industrial structure and other influencing factors. This article first analyses the imbalance between supply and demand of aquatic products, the development space of offshore aquaculture and the supporting policies, thereby concluding that China has significant potential to develop offshore aquaculture. Subsequently, the development status of offshore aquaculture in China is examined. The research progress of China's offshore aquaculture facilities, marine hydrology, environmental carrying capacity, aquaculture technology and the status of aquaculture operation equipment are also summarized. Furthermore, the problems existing in the development of offshore aquaculture are pointed out. On this basis, future development ideas for China's offshore aquaculture can be planned in terms of sea area layout, optimized and improved seed production systems, and research and development of offshore aquaculture technology and pellet feed. The relationship between the development of offshore aquaculture and ecological protection should be coordinated. Additionally, an energy security system can be built based on clean energy, and the development of related industries can be driven through the complementary industrial division of labour. The present work aims to provide a reference for promoting the development of offshore aquaculture in China.

Abundance, diversity, and community structure of comammox cladeA in sediments of China's offshore continental shelf

Nitrification is an important link for environmental nitrogen cycling, the appearance of comammox updates our traditional cognition about nitrification. Yet comammox has been poorly studied in marine sediments. This study explored the differences in abundance, diversity, community structure of comammox cladeA amoA in the sediments from different offshore areas of China (the Bohai Sea (BS), the Yellow Sea (YS), and the East China Sea (ECS)) and revealed the main driving factors. The abundance of comammox cladeA amoA was 8.11 × 103–4.96 × 104, 2.85 × 104–4.18 × 104, and 5.76 × 103–4.91 × 104 copies/g dry sediment in BS, YS, and ECS, respectively. The OTU (operational taxonomic units) numbers of comammox cladeA amoA in the BS, YS, and ECS were 4, 2, and 5 respectively. There were negligible differences in the abundance and diversity of comammox cladeA amoA among the sediments of the three seas. The subclade of comammox cladeA amoA, cladeA2 is the dominant comammox flora in the offshore area sediments of China. Noticeable differences in the community structure of comammox were observed among these three seas, where the relative abundance of cladeA2 in comammox was 62.98 %, 66.24 %, and 100 % in ECS, BS, and YS respectively. pH was found as the main factor affecting the abundance of comammox cladeA amoA and showed a significant positive correlation (p < 0.05). The diversity of comammox decreased with the increase of salinity (p < 0.05). NO3−-N is the main factor affecting the community structure of comammox cladeA amoA.

A High Precision Tidal Model Based on Multisource Tidal Harmonic Constants for Offshore China

As the accuracy of analytical instruments improve, the accuracy of ocean tide load displacement (OTLD) in geodesy and ocean dynamics is becoming increasingly demanding. The method of integrating through the load Green’s function using the ocean tide model is the main means of OTLD correction. However, although different tidal models have high accuracy in open ocean regions, they are less precise and less practical in the offshore areas of China, making it difficult to correct OTLDs accurately in complicated coastline areas of China. In this work, we evaluate the accuracy of 13 different tidal models in offshore China, and construct a new tidal model, new.chinasea.2022, based on the combination of high-precision tidal harmonic parameters. The OTLD correction efficiency of new.chinasea.2022 and conventional tidal models was assessed by wRMS analysis of GPS coordinate time series from the Crustal Movement Observation Network of China (CMONOC). It turns out that (1) the newly released tidal model performs better than the old model in offshore China, and there are differences in the performance of different models for each tidal constituent in different seas; (2) The OTLD correction of new.chinasea.2022 performed better in the offshore region of China, improving the correction of FES2004 by 1%-12% and osu.chinasea.2010 by 1%-6.5%.

Seismic response analysis and distribution prediction of source rocks in a survey of the South China Sea

Identification and prediction of high-quality source rocks is the key to obtaining new resources in the exploration area of Cenozoic basins in offshore China. We research the seismic response and distribution of hydrocarbon source rocks using seismic data, well curves, lithologic interpretation, and geochemical analysis. The target is the source rock development zone of the W Formation in a survey of the South China Sea. The results show that the seismic response of thick layer source rocks differ from surrounding rocks in the seismic profile (strong reflections with opposite polarity at the top and bottom and messy or chaotic reflections inside). Seismic reflections of interlayer source rocks have the characteristics of low frequency and continuous strong amplitude. The dominant frequency and maximum amplitude decrease as the number of mudstone layers increases. Through seismic petrophysical analysis, we have obtained three sensitive parameters of source rock in this survey: clay content, P-wave impedance, and elastic impedance. Different classification methods can realize the classification and prediction of hydrocarbon source rocks, among which the Kernel Fisher discriminant analysis method is the best. The prediction results are consistent with the geological background, geochemical information, and well curves.

Accurate mapping of seaweed farms with high-resolution imagery in China

Seaweed aquaculture is vital in protecting the marine eco-environment and mitigating climate change. China generates more than half of the world’s total seaweed production. However, despite multiple local studies, accurate and reliable information on broad-scale seaweed farms is still scarce. Using an object-based method to classify 3 m spatial resolution Planet Scope images along offshore China, a total of 129,494 ha of cultured seaweed was identified and delineated with an overall accuracy of 95.70% and a KAPPA index of 0.912, respectively. Then, a seaweed map in offshore China in 2018–2019 was developed. The results provided basic information about seaweed farms in China. The approach reported in this work is accurate and efficient, which can be used to replace the conventional method to obtain the culture seaweed information. This study can be of reference for mapping seaweed on a broader or global scale.

Evaluation on the Forecast Skills of Precipitation and Its Influencing Factors in the Flood Season in Liaoning Province of China

To clarify the precipitation forecast skills of climate forecast operations in the flood season in Liaoning Province of China, this study examines the forecast accuracies of China’s national and provincial operational climate prediction products and the self-developed objective prediction methods and climate model products by Shenyang Regional Climate Center (SRCC) in the flood season in Liaoning. Furthermore, the forecast accuracies of the main influencing factors on the precipitation in the flood season of Liaoning are assessed. The results show that the SRCC objective methods have a relatively high accuracy. The European Centre for Medium-Range Weather Forecasts (ECMWF) sub-seasonal forecast initialized at the sub-nearest time has the best performance in June. The National Climate Center (NCC) Climate System Model sub-seasonal forecast initialized at the sub-nearest time, and the ECMWF seasonal and sub-seasonal forecasts initialized at the nearest time, perform the best in July. The NCC sub-seasonal forecast initialized at the sub-nearest time has the best performance in August. For the accuracy of the SRCC objective method, the more significant the equatorial Middle East Pacific sea surface temperature (SST) anomaly is, the higher the evaluation score of the dynamic–analogue correction method is. The more significant the North Atlantic SST tripole is, the higher the score of the hybrid downscaling method is. For the forecast accuracy of the main influencing factors of precipitation, the tropical Atlantic SST and the north–south anti-phase SST in the northwest Pacific can well predict the locations of the southern vortex and the northern vortex in early summer, respectively. The warm (clod) SST in China offshore has a good forecast performance on the weak (strong) southerly wind in midsummer in Northeast China. The accuracy of using the SST in the Nino 1+2 areas to predict the north–south location of the western Pacific subtropical high is better than that of using Kuroshio SST. The accuracy of predicting northward-moving typhoons from July to September by using the SST in the west-wind-drift area is better than using the SST in the Nino 3 area. The above conclusions are of great significance for improving the short-term climate prediction in Liaoning.

Modeling the leeway drift characteristics of persons-in-water at a sea-area scale in the seas of China

Drowning events are becoming more common. It is important to accurately predict the drift trajectory of floating objects. This study proposes a sea-area-scale drift modeling method to determine the drift trajectory of persons-in-water in offshore China. The proposed method divided offshore China into 18 areas, and field experiments were carried out in the northern East China Sea (N_ES) and the Taiwan Strait (TS). First, a series of models were created, namely N_ES_I (N_ES upright), N_ES_II (N_ES facedown), TS_I (TS upright), TS_II (TS facedown), C_I (comprehensive upright), and C_II (comprehensive facedown). The leeway coefficients and jibing frequencies were then determined, and the positive crosswind speed (+CWL) probabilities under different marine environments were analyzed. A large volume of information from open-source channels was used to establish a database of historical drift cases. The driven model was validated using a combination of field experiments and historical drift information. The results indicate that the trajectories simulated using the sea-area-scale models proposed in this study are more consistent with the actual trajectories than those using the constant coefficients. The prediction areas are sensitive to the +CWL probability and the jibing frequencies. This study can help to improve the ability of the drift trajectory in China.

Analysis of Variation Characteristics and Driving Factors of Precipitation Isotopes in the Monsoon Region of Offshore China—A Case Study of Hong Kong

To explore the isotopic composition of precipitation in the monsoon region of offshore China, this paper takes Hong Kong, China as the study area. Based on the Global Network of Isotope in Precipitation (GNIP), the data about hydrogen and oxygen stable isotopes in the precipitation of Hong Kong from 1961 to 2022 were collected, from which its time variation trend was obtained via linear regression. Further, the distribution characteristics and influencing factors of hydrogen and oxygen stable isotopes in the precipitation of Hong Kong were analyzed. According to the results, the precipitation isotopes and d-excess in Hong Kong have no significant inter-annual variability. The seasonal variation of precipitation isotope and d-excess is monthly apparent, both of which are lower in the rainy season and higher in the dry season. In addition, the seasonal periodicity of isotope and d-excess proves that the main source of precipitation is marine water vapor, and the source of water vapor controlling precipitation in Hong Kong remains stable as a whole. The global meteoric water line in Hong Kong is δD=8.17δ18O+11.82, which is very close to the global one. Meanwhile, δ18O in precipitation is negatively correlated with the temperature, precipitation, and water vapor pressure. As the main driving force to control its isotope variation, precipitation conceals the effect of temperature. Taking Hong Kong as an example, the above research reveals some characteristics of monsoon regions in offshore China, which is of positive significance for further investigating the influencing factors of the hydrologic cycle and isotope change at regional and local scales in the future.

Development Strategy of China's Offshore Oil and Gas Equipment

Development Strategy of China's Offshore Oil and Gas Equipment

Analysis and Effect Evaluation of Offshore Wind Power Output Characteristics Based on Gaussian Mixed Clustering

China's offshore wind power (OWP) has become an important part of China's energy strategy and marine strategy, so studying the output characteristic curve of offshore wind power is of great significance for the development of offshore wind power. In this paper, a Gaussian Mixture Model (GMM) based on QAIC (Quasi-AIC, Akaike Information Criterion) was proposed. The original output curve of offshore wind power was classified and the characteristic curve was extracted. The characteristic curve of offshore wind power which can reflect the characteristics of different wind areas is obtained. At last, taking the actual wind power in Coastal Jiangsu Province as the research object, the results of this clustering model and the Gaussian Mixture Model (GMM) based on BIC (Bayesian Information Criterion) are compared via the CH score (Calinski Harabasz Score) to evaluate the effect of this clustering model for the intention of verifying the effectiveness of the method in this paper.

Offshore wind power prediction method considering typhoon, cold wave and other meteorological features under transitory weather

With the large-scale development of offshore wind farms, China's offshore wind power process is becoming more and more perfect. How to accurately forecast offshore wind power, especially under the influence of transitional weather, is a difficult problem to be solved. Therefore, in order to accurately forecast offshore wind power in the extreme small sample event, this paper proposes a method for predicting wind power before the turning weather based on meteorological element selection and small sample learning and expansion. The method improves the prediction accuracy of offshore wind power under typhoons and cold waves by constructing meteorological features in transitional weather such as typhoons and cold waves, expanding the small sample using time series, and modelling the relationship between the expanded meteorological factors and wind power.

Projected harmful algal bloom frequency in the Yangtze River Estuary and adjacent waters

Harmful algal blooms (HABs) are a frequent occurrence in China's offshore waters due to climate change and human activity, particularly in the Yangtze River Estuary and adjacent waters. Here, we studied HABs and their relationship with climatic and environmental factors in these waters from 1979 to 2016 using historical observations and reanalysis data. We then projected HABs frequency under various climate scenarios using the “environmental impact factor-frequency of HABs” mathematical model built using the BP neural network method and CIMP5 model data (RCP 2.6, RCP 4.5, and RCP 8.5). The results suggest a significant positive correlation between HABs frequency and seawater nutrient concentration, winter sea surface temperature, and low-wind days, and HABs frequency is anticipated to increase significantly by the 2040s compared with that of the historical era. Furthermore, future phytoplankton conditions are predicted to favor HAB species.

Assessment of Wave Energy Resources in China

The evolution of renewable energy technologies may surmount fossil fuel disadvantages. Wave energy is considered one of the best alternatives to fossil energy due to its advantages. The 40-year (1979–2018) spatio-temporal distribution of wave energy is presented using European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5) datasets. In addition, the common formula used for wave energy evaluation is derived from the linear wave theory in deep water, which is not applicable in shallow water. Therefore, a new equation that is suitable for both shallow and deep water is derived, which improves the accuracy of the wave energy evaluation for various water depths. The main aim is to investigate the spatio-temporal wave energy for offshore China from 1979 to 2018 and combine the new standard of classification to recommend the optimal area. The nearshore zone from Zhejiang province to Guandong province is considered the ideal zone, and the average annual wave energy density in this area is above 10 kW/m.

Projections of coastal flooding under different RCP scenarios over the 21st century: A case study of China's coastal zone

Among sea level rise (SLR)-induced threats to coastal regions, flooding inundation is considered the most serious, especially in China's coastal zone (CCZ). Previous attempts to simulate the inundation area caused by SLR at the macro spatial scale usually employed the bathtub model based on a large number of historical tide station data. However, these efforts mainly focused on simplifying the calculation of the inundation process at a large scale, but failed to improve the accuracy mainly due to the failure to exclude isolated depressions. Here, based on regional sea level data of the Integrated Climate Data Center (ICDC), the University of Hamburg, a physical ocean model (Finite Volume Coast and Ocean Model, FVCOM) was employed to simulate the maximum possible regional SLR in offshore China from 2021 to 2100 under the representative concentration pathways (RCPs) 2.6, 4.5, and 8.5 scenarios, respectively, and the hydraulic connectivity model was applied based on multi-source data to improve the simulation accuracy of the inundation area. Through these improved methods, the maximum possible inundation characters of CCZ over the 21st century were observed as follows: (1) Under RCP2.6/4.5/8.5 scenarios, the macro spatial patterns of inundation areas are similar, with the inundation area mainly distributing in the coastal areas around the Bo Hai, the coastal areas from Jiangsu to the estuary of the Yangtze River, the Pearl River Delta, and the western coastal areas of Taiwan, and the inundation area gradually expands and spreads over time. (2) Under the three scenarios, the maximum possible inundation area shows a wavelike rising trend, and by 2100, the inundation area is expected to exceed 48.89 × 103 km2 (RCP 2.6) and reach a maximum of 53.50 × 103 km2 (RCP 8.5). (3) There are significant differences in the inundation depth and flood frequency under the three scenarios, with the inundation characters of the high-emission scenario being the most extreme. Overall, our work can provide meaningful information for proper coastal urban planning, disaster prevention, and mitigation measures selection in China. The methodology can also be used for predicting the inundation areas in other coastal countries facing the threat of SLR.

Interannual, Seasonal, and Monthly Variability of Sea Surface Temperature Fronts in Offshore China from 1982–2021

The offshore China (OC) region is a significant sea area in the Western Pacific and many researchers have been interested in the distribution of sea surface temperature (SST) fronts in this area. In this study, the Cayula and Cornillon single image edge detection algorithm was used to detect SST fronts using the Daily Optimum Interpolation Sea Surface Temperature data from 1982 to 2021. The results revealed that there are eighteen SST fronts in OC— three in the Bohai Sea, seven in the Yellow Sea, two in the East China Sea, five in the South China Sea, one in the Pacific Ocean east of Taiwan province, China—and among them a new front was detected in the Yellow Sea and named the Yellow Sea Ring Front. The frequency of most fronts showed a tendency of initially increasing and then decreasing from January to September, followed by a trend of growing steadily from October to December. The frequency of a few fronts showed a decreasing tendency from January to September and an increasing tendency from October to December. The frequency of most fronts is highest in winter and lowest in summer. In spring and autumn, the frequency of most fronts is lower than that in winter and higher than that in summer. The annual average frontal probability of five-ninths of the fronts showed an upward trend, and the annual average frontal probability value of one-third of the fronts showed a downward trend. The rest of the fronts showed a stable trend. The results of this paper also showed that the Liaodong Bay Front and the Bohai-Laizhou Bay Front did not form a complete front, as previously reported. In addition, the frontal probability of the Bohai Front to the north of 39° N was in the tendency of decreasing.

E&amp;P Notes (October 2022)

E&amp;P Notes (October 2022)

Technological catch-up and innovations of China's offshore oil and gas equipment-manufacturing industry: The role of the supply chain and government policy

China's offshore oil and gas equipment-manufacturing industry has experienced phenomenal technological catch-up, followed by the development of capacity in both independent innovation and the relevant industrial supply chain. This study aims to reveal the mechanisms behind this phenomenon. Specifically, this study focuses on (1) applying a new theoretical framework, known as the inverted S-curve theory, to the technological catch-up and innovation of the above-mentioned industry; (2) developing the related supply chains for the industry; and (3) exploring the roles the government played when implementing regulations and policies to facilitate the catch-up. An empirical model is derived accordingly to quantitatively determine the contribution of driving factors for the catching up process of the industry in China. The findings suggest that policy alone appears to be a substantial factor. In particular, policies that promote the capacities of the core components of the supply chain are the most effective. The case study confirms such an observation and presents more details of the dynamic catching-up process of the offshore oil and gas equipment-manufacturing industry.The discussion is thus extended to include additional and influential factors that could not be included in the empirical model due to the lack of data, such as financing and entrepreneurship.

Application of resistivity in the characterization of shear failure process of gas bearing marine silt

Gas bearing marine silt is widely distributed in China's offshore areas. The shear failure of gas bearing marine silt may lead to marine engineering geological disasters, such as seabed subsidence and submarine landslides. Monitoring the shear failure process of gassy soil in real time can warn marine geological disasters and ensure the safety of marine engineering. Marine resistivity monitoring has the advantages of a large monitoring range and real time measurement, so it has good application potential. However, the variations in resistivity during the shear failure of gas bearing marine silt are not clear. In this study, we obtained the resistivity changes of gas bearing marine silts during the shear failure process through triaxial experiments combined with resistivity measurements, and we analyzed the factors controlling the resistivity changes. The results show that the shear failure of gas bearing silt samples with different dry densities has stable resistivity characteristics. Moreover, for the two electrical factors in the process of soil shear failure, the evolution of soil cracks and the soil wettability, the change of resistivity is controlled by the change of soil wettability. The failure stage of shear failure can be identified by the change in the resistivity of gas bearing soil.

Impact of Tropical Cyclone Avoidance on Fishing Vessel Activity over Coastal China Based on Automatic Identification System Data during 2013–2018

Tropical cyclones (TCs) may cause severe impacts on the activities of coastal fishing vessels. Due to the unavailability or unacceptability of detailed Automatic Identification System (AIS) data that are capable of differentiating fishing activity from navigation, as well as the lack of detailed models and observation data of TC winds, few studies have provided quantitative and reliable assessment of the impacts of TCs on fishing activities. In this study, we modeled snapshots for the TC winds of 52 TCs over the Northwest Pacific (NWP) basin from 2013 to 2018, as well as daily fishing hours and daily hours of presence (hereafter “vessel hours”) of fishing vessels. Based on these data, the spatiotemporal pattern of fishing vessel activity over offshore China was first analyzed and mapped. Then, a TC wind hazard index and absolute and relative impact indices were proposed to assess the impact of the 52 TCs on fishing and vessel hours. Their relationship was then fitted with the cumulative distribution function (CDF) of the log-normal distribution. The results show that in the 2013−2018 period, the most active fishing areas were located in the South China Sea. In each instance, an increase was first observed in the initial several years; then a decrease followed in the yearly total fishing hours per vessel in the remaining years. The relative impact index was significantly correlated to the TC wind hazard index proposed in this study. Based on the quantitative relationship between the specified TC hazard index and the impact indices, it is possible to implement a pre-cyclone rapid loss assessment due to TC avoidance in the future.

Prediction of Significant Wave Height in Offshore China Based on the Machine Learning Method

Accurate wave prediction can help avoid disasters. In this study, the significant wave height (SWH) prediction performances of the recurrent neural network (RNN), long short-term memory network (LSTM), and gated recurrent unit network (GRU) were compared. The 10 m u-component of wind (U10), 10 m v-component of wind (V10), and SWH of the previous 24 h were used as input parameters to predict the SWHs of the future 1, 3, 6, 12, and 24 h. The SWH prediction model was established at three different sites located in the Bohai Sea, the East China Sea, and the South China Sea, separately. The experimental results show that the performance of LSTM and GRU networks based on the gating mechanism was better than that of traditional RNNs, and the performances of the LSTM and GRU networks were comparable. The EMD method was found to be useful in the improvement of the LSTM network to forecast the significant wave heights of 12 and 24 h.