On Abnormally Strong Currents Observed on the Northern Coast of Peru during the 2015-2016 El Niño

The northern coast of Peru is a region that can rapidly detect the impact of an El Niño. To investigate the effects of the 2015-2016 El Niño on the oceanographic environment of the northern coast of Peru, the temperature and current data obtained from moored equipment at an oil platform were analyzed. Strong coastal along-shore currents of more than 0.60 m·s-1 were observed three times, although the mean current speed was 0.10 m·s-1 flowing toward the south-southwest. After the first strong current, the bottom temperature increased and the mixed layer deepened and remained there during the El Niño event. The temperature reached a maximum after the strong coastal current, then decreased gradually. An analysis of wind and sea surface height anomalies revealed that the coastal strong current was caused by Kelvin waves and the deepening of the mixed layer was not related to local winds, but to coastal Kelvin waves from the equator during the El Niño event.

Salinity drift prevention experiments in the Korea ocean research stations and suggestions for high quality salinity observation

The importance of salinity has been highlighted to cope with climate changes and disaster prevention. The salinity of accuracy up to 0.005 is normally required in an open ocean to understand various oceanic and climatic phenomena; however, the reliability of salinity measured on the coast and open seas around Korea was low due to the lack of a standardized observation system and post-processing of quality verification. Korea Ocean Research Stations (KORS) has been producing salinity time series since 2003 through the Aanderaa conductivity-temperature (CT) 3919 inductive sensors, which have an advantage of on-site maintenance but tend to drift toward a lower conductivity because of biological attachments to the sensor. This study applied copper taping and UV light exposure techniques to the sensors and then compared its salinity measurements with RBR CTD mooring observations and SeaBird19 CTD profiles to assess a biofouling effect on salinity observations. This experiment shows that the salinity from the CT sensor without biofouling prevention starts to drift in a week, particularly for a surface sensor. This biofouling induced the decrease of salinity up to 10 in a month. The copper taping methodology efficiently suppressed the biological attachment but disturbed an electromagnetic field around the sensor, thus resulting in unrealistic salinity values. When UV light was periodically exposed at a distance of about 5 cm away from the CT sensor, relatively stable salinity could be observed without significant drift at least in two months. Besides, the SBE37 CTD, an electrode-type sensor, seems to be relatively free from biofouling but has difficulties in sensor maintenance and a sensor calibration process. Our results underline a double installation of salinity observation equipment with UV light exposure. In addition, the pre-calibration of a CT(D) sensor and post-verification should be included in a standard procedure for high-quality salinity measurement.

Analysis of the tsunami amplification effect by resonance in Yeongil Bay

Predicting tsunami hazards based on the tsunami source, propagation, runup patterns is critical to protect humans and property. Potential tsunami zone, as well as the historical tsunamis in 1983 and 1993, can be a threat to the east coast of South Korea. The Korea Meteorological Administration established a tsunami forecast warning system to reduce damage from tsunamis, but it does not consider tsunami amplification in the bay due to resonance. In this study, the Numerical model, Cornell Multi-grid Coupled Tsunami model, was used to investigate natural frequency in the bay due to coastal geometry. The study area is Yeongill bay in Pohang, southeast of South Korea, because this area is a natural bay and includes three harbors where resonance significantly occurs. This study generated a Gaussian-shaped tsunami, propagated it into the Yeongill bay, and compared numerical modeling results with data from tide gauge located in Yeongill bay during several storms through spectral analysis. It was found that both energies of tsunamis and storms were amplified at the same frequencies, and maximum tsunami wave height was amplified about 3.12 times. The results in this study can contribute to quantifying the amplification of tsunami heights in the bay.

Hidden Markov Model(HMM)-Based Fishing Activity Prediction Using V-Pass Data

Illegal fishing has been a serious threat to the conservation of seafood resources and provoked the importance of marine surveillance. There are several types of fishing vessel monitoring systems operated by Republic of Korea, for example, Vessel Monitoring System(VMS), Automatic Identification System (AIS), V-Pass and VHF-DSC. However, those methods are not adaptable directly to fishing activity monitoring. The limitation requires more human resources to determine fishing status. Thus, this study proposes a method of estimating fishing activity from V-Pass, fishing vessel position reporting system, using Hidden Markov Model (HMM). HMM is a model to determine status through probability distribution for a sequence of time-series data. First of all, fishing activity status was labeled on V-Pass data. The distribution of speed on fishing activity was computed from the labeled data and HMM was constructed from the data obtained at Socheongcho Ocean Research Station (SORS). The model was first applied to the data of SORS for a test, and then Busan for validation. The model showed 99.4% and 89.6% as test and validation accuracy, respectively. It is concluded that the HMM can be applicable to predict a fishing activity from vessel tracks.

Estimation of Overtopping Discharges with Deep Neural Network(DNN) Method

An Artificial Intelligence(AI) study was conducted to calculate overtopping discharges for various coastal structures. The Deep Neural Network(DNN), one of the artificial intelligence methods, was employed in the study. The neural network was trained, validated and tested using the EurOtop database containing the experimental data collected from all over the world. To improve the accuracy of the deep neural network results, all data were non-dimensionalized and max-min normalized as a preprocessing process. L2 regularization was also introduced in the cost function to secure the convergence of iterative learning, and the cost function was optimized using RMSProp and Adam techniques. In order to compare the performance of DNN, additional calculations based on the multiple linear regression model and EurOtop’s overtopping formulas were done as well, using the data sets which were not included in the network training. The results showed that the predictive performance of the AI technique was relatively superior to the two other methods.

Analysis of Allowable Berthing Velocity by Ship Size considering Designed Energy

The berthing velocity is the factor that has the greatest influence on the berthing energy. For the vessel to berth safely, it should not exceed the appropriate berthing velocity. In addition, when the vessel is berthing, it should be berthed with berthing energy smaller than the energy absorption of the fender. This study intends to derive the allowable berthing velocity by ship size considering the berthing capacity. When a small vessel berth, the allowable berthing velocity is greater than when a relatively large vessel berths. In this study, the extrapolated velocity is defined as the relative value of the ship’s berthing velocity when considering the ship's size and the berthing capacity. A regression equation for the allowable berthing velocity by ship size was derived by calculating the designed berthing energy for each fender performance. It was also verified whether any ships were exceeding the allowable berthing velocity by comparing it with the measured data for each jetty. In addition, the extrapolated velocity was proposed using the regression equation, and as a result of applying the measured data, 11 ships exceeded the designed velocity in jetty 1, but it was confirmed that all ships were safely berthed in jetty 2,3. Therefore, the target pier of this study was evaluated as a pier where ships can be berthed safely. A safer berthing velocity operation guideline can be suggested if the allowable berthing velocity by ship size is analyzed and utilized at various piers. Extrapolated velocity can also be used for risk analysis of berthing.

Numerical simulation for increasing the sand mastic adaptation of repairing the breakwater

As a breakwater gradually becomes obsolete, it becomes vulnerable to loss of its original functions and finally occurs corruption due to cavitation, scours inside, etc. The mortar grouting method, which has been in general applied in many cases, would invoke serious issues such as coastal environmental pollutions because of spilled-out cement before curing on the near sea. Thus, the sand mastic that utilizes the mastic asphalt becomes focused on as a substitute. However, the related study is hard to find in the domestic literature. In this study, therefore, the workability of sand mastic when filling up the cavitation inside a breakwater was evaluated with a 3-D numerical model, FLOW-3D. It was intended to propose the workability index (WI) of sand mastic based on the diffusion diameter. It has been shown that the temperature and the composition ratio of the asphalt are the most significant parameters on the rheologic characteristics of the sand mastic. As a result, it is recommended that the asphalt composition above 16% and the initial temperature above 150℃ when applying with a breakwater with inside cavitation.

Projection of future sea level rise in the East Asian Seas based on Global Ocean-Sea Ice Coupled Model with SRES A1B Scenario

To project the future sea level rise in the East Asian Seas due to global warming, regional sea level variations are downscaled from three climate system models (GFDL-CM2.1, ECHAM5/MPI-OM, MIROC3.2(hires)) using a global ocean-sea ice coupled model with non-Boussinesq approximation. Based on the SRES A1B Scenario, the projected ensemble mean sea level rise (rate of rise) for the East Sea, Yellow Sea and East China Sea from 1995 to 2050 is 15.60cm (2.84mm/year), 16.49cm (3.0mm/year) and 16.43cm (2.99mm/year), respectively. With the inclusion of the future change of land ice melting and land water storage, the mean sea level rise (rate of rise) increases to 33.55cm (6.10mm/year) for the East Sea, and 34.38~34.44cm (6.25~6.26mm/year) for the Yellow and East China Seas. The present non-Boussinesq ocean model experiment shows that the future sea level rise in the East Sea is mainly due to the steric component changes by heat content increase. On the other hand, the future sea level rise in the Yellow and East China Seas appears to be mainly associated with the non-steric component change by water mass convergence.

A study on risk assessment of complex disasters in Busan coast

In the vicinity of the coast, there is a risk of complex disasters in which inland flooding, wave overtopping, storm surge, and tsunami occur simultaneously. In order to prepare for such complex disasters, it is necessary to set priorities for disaster preparedness through risk assessment and establish countermeasures. In this study, risk assessment is carried out targeting on Marine city, Centum city, and Millak waterside parks in Busan, where complex disasters have occurred or are likely to occur. For risk assessment, inundation prediction map constructed by the Ministry of Public Administration and Security in consideration of sea level rise, rainfall and storm surge scenarios and authorized data on social and economic risk factors were collected. The socioeconomic risk factors selected are population, basements, buildings, sidewalks, and roads, and the risk criteria for damage targets are set for each risk factors. And it was assessed considering the maximum inundation depth and maximum flow velocity of the inundation prediction map. Weights for each factor were derived through expert questionnaires. The risk assessment index that was finally evaluated by calculating the risk index for each element and applying weights was expressed as a risk map by different colors into four levels of attention, caution, alert and danger.

Development of Physics-Based Morphology Model with an Emphasis on the Interaction of Incoming Waves with Transient Bed Profile due to Scouring and Accretion using Dynamic Mesh

A physics-based morphology model [Seoul Foam] was developed using the dynamic mesh technique to explain the interaction between the sea bed, which undergoes deformation due to siltation and scouring, and the incoming waves. In doing so, OlaFlow, an Open Foam-based toolbox, was used as a hydrodynamic model. To verify the proposed physically-based morphology [Seoul Foam] in this study, numerical simulations of the shoaling process over the beach of the uniform slope were implemented. The numerical result shows that the formation process of a sand bar over the foreshore was successfully simulated. As can be easily anticipated, the size of the sand bar was closely linked to the nature of incoming waves, and in the case of a rough sea, the foreshore slope was rapidly deformed due to scouring. In mild seas, several sand waves were formed near the shoreline, and when the exposure time was the same, the size of the sand waves was not as large as in rough seas.