• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.26 no.1
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• pp.1-10
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• 2021

In this study, Information for the case of seawater flooding and observation data over a period of 10 years (2009~2018) was collected. Using machine learning algorithms, the characteristics of the types of seawater flooding and observations by type were classified. Information for the case of seawater flooding was collected from the reports of the Korea Hydrographic and Oceanographic Agency (KHOA) and the Korea Land and Geospatial Informatics Corporation. Observation data for ocean and meteorological were collected from the KHOA and the Korea Meteorological Agency (KMA). The classification of seawater flooding incidence types is largely categorized into four types, and into 5 development types through combination of 4 types. These types were able to distinguish the types of seawater flooding according to the marine weather environment. The main characteristics of each was classified into the following groups: tidal movement, low pressure system, strong wind, and typhoon. Besides, in consideration of the geographical characteristics of the ocean, the thresholds of ocean factors for seawater flooding by region and type were derived.

• Journal of the Korean Geotechnical Society
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• v.30 no.12
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• pp.5-14
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• 2014

Most of slope failures have taken place between June and September in Korea, which cause a considerable damage to society. Rainfall intensity and duration are very significant triggering factors for landslide. In this paper, landslide-triggering rainfall threshold consisting of rainfall intensity-duration (I-D) was proposed. For this study, total 255 landslides were collected in landslide inventory during 1999 to 2012 from NDMI (National Disaster Management Institute), various reports, newspapers and field survey. And most of the required rainfall data were collected from KMA (Korea Meteorological Administration). The collected landslides were classified into three categories: debris flow, shallow landslide and unconfirmed. A rainfall threshold was proposed based on landslide type using statistical method such as quantile-regression method. Its validation was carried out based on 2013 landslide database. The proposed rainfall threshold was also compared with previous rainfall thresholds. The proposed landslide-triggering rainfall thresholds could be used in landslide early warning system in Korea.

• ALGAE
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• v.35 no.4
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• pp.361-373
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• 2020

The community dynamics of benthic diatoms in the hypersaline environment are investigated to advance our understanding how salinity impacts marine life. Diatoms were sampled in the two salterns encompassing salt Ponds, ditches, and seawater reservoirs (n = 11), along the salinity gradient (max = 324 psu), and nearby tidal flats (n = 2). The floral assemblages and distributions across sites and stations showed great variations, with a total of 169 identified taxa. First, not surprisingly, higher diversity of benthic diatoms was found at natural tidal flats than salterns. The saltern diatoms generally showed salinity dependent distributions with distinct spatial changes in species composition and dominant taxa. Biota-environment and principal component analysis confirmed that salinity, mud content, and total nitrogen were key factors influencing the overall benthic community structure. Some dominant species, e.g., Nitzschia scalpelliformis and Achnanthes sp. 1, showed salinity tolerance / preference. The number of diatom species at salinity of >100 psu reduced over half and no diatoms were found at maximum salinity of 324 psu. The highest salinity for the observed live diatoms was 205 psu, however, a simple regression indicated a theoretical salinity threshold of ~300 psu on the survival. Finally, the indicator species were identified along the salinity gradient in salterns as well as natural tidal flats. Overall, high species numbers, varying taxa, and euryhaline distributions of saltern diatoms collectively reflected a dynamic saltern ecosystem. The present study would provide backgrounds for biodiversity monitoring of ecologically important microalgal producers in some unique hypersaline environment, and elsewhere.

• Journal of the Korean Society for Marine Environment & Energy
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• v.13 no.3
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• pp.165-173
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• 2010

A cloud detection method is introduced to improve the reliability of NOAA/AVHRR Sea Surface Temperature (SST) data processed during the daytime and nighttime in the TeraScan System. In daytime, the channels 2 and 4 are used to detect a cloud using the three tests, which are spatial uniformity tests of brightness temperature (infrared channel 4) and channel 2 albedo, and reflectivity threshold test for visible channel 2. Meanwhile, the nighttime cloud detection tests are performed by using the channels 3 and 4, because the channel 2 data are not available in nighttime. This process include the dual channel brightness temperature difference (ch3 - ch4) and infrared channel brightness temperature threshold tests. For a comparison of daytime and nighttime SST images, two data used here are obtained at 0:28 (UTC) and 21:00 (UTC) on May 13, 2009. 6 parameters was tested to understand the factors that affect a cloud masking in and around Korean Peninsula. In daytime, the thresholds for ch2_max cover a range 3 through 8, and ch4_delta and ch2_delta are fixed on 5 and 2, respectively. In nighttime, the threshold range of ch3_minus_ch4 is from -1 to 0, and ch4_delta and min_ch4_temp have the fixed thresholds with 3.5 and 0, respectively. It is acceptable that the resulted images represent a reliability of SST according to the change of cloud masking area by each level. In the future, the accuracy of SST will be verified, and an assimilation method for SST data should be tested for a reliability improvement considering an atmospheric characteristic of research area around Korean Peninsula.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.6
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• pp.303-314
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• 2022

The persistence analysis of marine physical environment factors is a basic analysis that must precede the use of sea areas as an analysis required in the coastal engineering such as downtime and design. In this study, the persistence analysis was implemented for wind speed and significant wave height data from four observation points of Deokjeokdo, Oeyeondo, Geomundo, and Geojedo among the marine meteorological observation buoys of the Korea Meteorological Administration. The persistence time means the consecutive time of observation data beyond specific level. The threshold wind speed and significant wave height were set in the range of 1~15 m/s and the range of 0.25~3.0 m, respectively. Then, the persistence time was extracted. As a result of the analysis, the persistence time of wind speed and significant wave height decreased rapidly as the reference value increased. The median persistence times under the maximum reference thresholds were assessed as a maximum of 5 hours for wind speed and a maximum of 8 hours for significant wave height. When the reference wind speed and significant wave height were 15 m/s and 3 m, respectively, the persistence time that could occur with a 1% probability were 52 and 56 hours. This study can be expanded to all coastal areas in Korea, and it is expected that various engineering applications by performing a persistence analysis of the metocean data.