• Korean Journal of Environmental Biology
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• v.36 no.4
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• pp.687-693
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• 2018

The active development of the global marine trade industries has been known to increase the inflows of marine invasive species and harmful organisms into the ecosystem, and the marine ecological disturbances. One of these invasive species, Ciona robusta, has now spread to the Korea Strait, the East Sea, and Jeju Island in connection with the climate change but not the Yellow Sea in Korea. Currently, the spread and distribution of C. robusta is increasingly damaging aquaculture and related facilities. Therefore, this study aims to identify the spread of C. robusta and potential habitats and to secure a data for the prevention of effective management measures due to climate change as well as damage the reduction in future through the prediction of spread. We used environmental variables in BioOracle. Also, the potential habitat and distribution of C. robusta was predicted using MaxEnt, a species distribution model. Two different RCP scenarios(4.5 and 8.5) were specified to predict the future distributions of C. robusta. The results showed that the biggest environmental factor affecting the distribution of C. robusta was the salinity as well as the highest distribution and potential habitats existent in the East Sea and around Jeju Island.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.374-380
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• 2022

This paper shows the results of a study that predicts changes in seawater conditions in sea farms using machine learning-based long short term memory (LSTM) algorithms. Hardware was implemented using dissolved oxygen, salinity, nitrogen ion concentration, and water temperature measurement sensors to collect seawater condition information from sea farms, and transferred to a cloud-based Firebase database using LoRa communication. Using the developed hardware, seawater condition information around fish farms in Tongyeong and Geoje was collected, and LSTM algorithms were applied to learning results using these actual datasets to obtain predictive results showing 87% accuracy. Flask and REST APIs were used to provide users with predictive results for each of the four parameters, including dissolved oxygen. These predictive results are expected to help fishermen reduce significant damage caused by fish group death by providing changes in sea conditions in advance.

• Magazine of the Korean Society of Agricultural Engineers
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• v.43 no.4
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• pp.37-49
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• 2001

This study was performed in order to produce the basic data for developing prediction techniques of desalinization to be applicable to reclaimed tidal lands at the beginning stage. the desalinization experiments were carried out by two water management practices, namely, the leaching method by subsurface drainage and the rinsing method by surface drainage. The 5 soil samples used in this study were collected in 4 tidal land reclamation projects. Regression equations were obtained in order to investigate the changes of electrical conductivity during the desalinization of reclaimed tidal lands and to estimate water requirements for desalinization. The results obtained from this study were summarized as follows: 1. According to USDA Salinity Laboratory classification system of salt affected soils the reclaimed tidal land soils used in this study were saline-sodic soils with the high electrical conductivity and the high exchangeable sodium percentage. 2. With the increase of the water requirements for desalinization the electrical conductivity was decreased with high degree of correlationships and the desalinization effects were remakable in both the leaching method and the rinsing method. 3. In case of the leaching method the electrical conductivity had been reduced below the classification value of salt affected soils when the depth o water leached per unit depth of soil (Dwl/Ds) was 0.3 and the desalinization effects showed a tendency to be much the same in each treatment.

• Ocean and Polar Research
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• v.40 no.1
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• pp.37-48
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• 2018

The purpose of this study is to assess the climate change vulnerability of coastal and offshore fisheries in the South Sea of Korea using the RCP scenarios. Based on the vulnerability defined by IPCC, the indicator-based method was applied. Exposure indicator was calculated through weighted sum of the sea temperature and salinity forecasted by National Institute of Fisheries Science, and the weights were obtained from the time-space distribution of each fisheries. Sensitivity indicator was determined by applying the catch proportion of fisheries to the sensitivity of fish species. The adaptive capacity was measured by survey of fisheries which represent the ability of the fishermen well. As a result of summarizing the above indicators, vulnerability of coastal fisheries is higher than offshore fisheries. This shows that measures against coastal fisheries are needed. In addition, the results of each scenario are somewhat different, so it is considered that accurate prediction of climate change is important for adaptation measures.

• Korean Journal of Remote Sensing
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• v.19 no.1
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• pp.21-30
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• 2003

It was studied the relationship between the red tide occurrence and the meteorological and oceanographic factors, the choice of potential area for red tide occurrence, and the satellite monitoring for red tide. From 1990 through 2001, the red tide continuously appeared and the number of red tide occurrence increased every year. Then, the red tide bloomed during the periods of July and August. An important meteorological factor governing the mechanisms of the increasing in number of red tide occurrence was heavy precipitation. Oceanographic factors of favorable marine environmental conditions for the red tide formation included warm water temperature, low salinity, high suspended solid, low phosphorus, low nitrogen. A common condition for the red tide occurrence was heavy precipitation 2∼4 days earlier, and the favorable conditions for the red tide formation were high air temperature, proper sunshine and light winds for the day in red tide occurrence. From satellite images, it was possible to monitor the spatial distributions and concentrations of red tide. It was founded the potential areas for red tide occurrence in August 2000 by CIS conception: Yeosu∼Dolsan coast, Gamak bay, Namhae coast, Marado coast, Goheung coast, Deukryang bay, respectively.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.14-14
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• 2022

Greenhouse gas emissions are one of the critical factors that drive change in rice cropping systems. Within this changing system, less water irrigation and chemical fertilizer are seriously considered, as well combining precision farming technologies with irrigation control. Water and phosphorus (P) fertilizer are two of the most critical inputs in rice cultivation. Due to the lack of water availability in the system, P fertilizer is not available, especially in acidic soil conditions. Moreover, the various types of abiotic stresses, such as drought, high temperature, salinity, submergence, and limited fertilizer result in significant yield loss in the system. Even in the late stage of growth, the waves caused by diseases and insects make the field more unfruitful. Therefore, agronomists and breeders need to identify the secondary phenotypes to estimate the yield loss of when stress appears. The prediction will be clearer if we have a set of markers tagging the causal variation and the associated precise phenotype indices. Although there have been various studies for abiotic stress tolerance, we still lack functional molecular markers and phenotype indices. This is due to the underlying challenges caused by environmental factors in highly unpredictable regional and yearly environmental conditions in the field system. Pupl (phosphorus uptake 1) is still known as the first QTL associated with phosphorus uptake and have been validated in different field crops. Interestingly, some pyramiding lines of Pupl and other QTLs for other stress tolerances showed preferable phenotypes in the yield. Precise physiological studies with the help of genomics are on-going and some results will be discussed.

• Journal of Korean Tunnelling and Underground Space Association
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• v.17 no.3
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• pp.383-392
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• 2015

In subsea tunnelling, prediction of the fractured zone (or water bearing zone) ahead of tunnel face saturated by seawater with high water pressure has been a key factor for safe construction. This study verified the feasibility of utilizing induced polarization (IP) survey at tunnel face for predicting the ground condition ahead of the subsea tunnel face. A pore model was proposed to compute chargeability in granular material, and the relationship correlating chargeability with the variables affecting the chargeability was derived from the model. Parametric study has been performed on the variables to figure out the most influential factors affecting the chargeability. The results of the parametric study show that the size of narrow pores ($r_1$) and the salinity of pore water are the most influential factors on chargeability. Laboratory tests were conducted on various types of ground condition by changing the salinity of pore water, the thickness of the fracture zone and the existence of gouge (weathered granite) within the joints of the fractured zone to figure out the effect of the ground characteristics on the IP phenomenon. Test results show that the chargeability of the fractured zone saturated by seawater increases if the joints in the fractured zone are filled with gouge since the infilled gouge will decrease the size of narrow pores ($r_1$).

• Journal of Korea Water Resources Association
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• v.40 no.9
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• pp.723-734
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• 2007

This study was to investigate the settling velocity which is an important factor for the prediction of cohesive deposition under the various densities of particle and dissolved ion addition$(Na^+,\;Cl^-,\;OH^-,\;H^+)$ in rivers, ports, reservoirs and lakes. Settling velocity of suspended fine particles in still water was measured with a pressure sensor (maximum 10 mbar). At the initial concentration of 20g/l of alumina and quartz the average settling velocities were high due to the aggregation behaviour of particles. At this point it was 0.185 mm/s (alumina) and 0.022 mm/s (quartz). Above this initial concentration it was on the decrease owing to the hindered settling. The higher the salinity is, the faster the settling velocity of alumina and quartz is. Furthermore, in an acid condition the average settling velocity of alumina was on the decrease. In an alkaline water, which causes strong flocculation, the average settling velocity of alumina it was observed on the increase. However, in an alkaline medium the low average settling velocity of quartz powder was measured.

• Korean Journal of Remote Sensing
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• v.36 no.1
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• pp.41-53
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• 2020

The production of near- and off-shore fisheries in South Korea is decreasing due to rapid changes in the fishing environment, particularly including higher sea temperature in recent years. To improve the competitiveness of the fisheries, it is necessary to provide fish catch information that changes spatiotemporally according to the sea state. In this study, artificial intelligence models that predict the CPUE (catch per unit effort) of mackerel, anchovies, and squid (Todarodes pacificus), which are three major fish species in the near- and off-shore areas of South Korea, on a 15-km grid and daily basis were developed. The models were trained and validated using the sea surface temperature, rainfall, relative humidity, pressure,sea surface wind velocity, significant wave height, and salinity as input data, and the fish catch statistics of Suhyup (National Federation of Fisheries Cooperatives) as observed data. The 10-fold blind test results showed that the developed artificial intelligence models exhibited accuracy with a corresponding correlation coefficient of 0.86. It is expected that the fish catch models can be actually operated with high accuracy under various sea conditions if high-quality large-volume data are available.

• Applied Biological Chemistry
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• v.35 no.4
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• pp.281-285
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• 1992

Composite seasioning was stored at different temperature with PE/Al/PE/PET packaging. $Q_{10}$ value due to temperature was 2.54 and shelf-lie of composite seasoning was predicted 29, 73 and 185 weeks at $35^{\circ}C$, $25^{\circ}C$ and $15^{\circ}C$, respectively. L value was decreased during storage but a and b value had little change. Correlation coefficient between sensory score and cole. value was low. Browning development and carbonyl value were increased with storage temperature and correlation coefficient between sensory score and those was comparatively high. Moisture content, salinity and total sugar content were within KS-standard during 18 weeks storage.