• Journal of the Korean earth science society
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• v.34 no.1
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• pp.41-50
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• 2013

To analyze the distribution pattern of flood sediment deposits near the mouth of Chucheoncheon (river), side scan sonar images and seafloor sediment properties were investigated in the offshore area within about 50 m deep in water. Based on the analysis result of the sonar images, the seafloor of the study area is divided into three areas of basement, sandy-mud, and dispersed flood sediment. The colors of sonar images in each area are represented by dark black, light grey, and greyish black, respectively. The sediment composition in the grey black area shows 33.73% of gravel, 62.88% of sand, 3.37% of silt, and 0.02% of clay. On the other hand, the composition of the light grey area is 10.31% of sand, 56.42% of silt, and 33.27% of clay. Especially the sediment of the grey black area contains the considerable amount of burned plant fragments in black color, which could distinctly be differentiated from those in the offshore. The distribution pattern of the flood sediment deposits suggests that the land-originated detrital sediments seem to be transported from the Chucheon river into offshore along the shore rather than transversely. In conclusion, the longshore current of the study area is probably dominant to affect the spatial distribution of bottom features.

• Journal of Environmental Impact Assessment
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• v.24 no.2
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• pp.175-189
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• 2015

The objective of this study was to analyze characteristics of distribution of amphibian species and the affecting ecological factors. For the study, habitat environment factors were determined and applied to a habitat suitability model for the data collected from the Seom River in Hoengseong County and Wonju City, Gangwon Province, Korea between March 2013 to October 2013. The analyzed amphibian species were Rana nigromaculata, Hyla japonica, Rana dybowski, and Rana rugosa Temminck and Schlegel, and a logistic regression model was used with the pseudo-absence data. The result of the model analysis suggests that the major factors for Rana nigromaculata are distance to vegetation and rock and that for Hyla japonica is waterway. Rana dybowski and Rana rugosa Temminck and Schlegel have similar habitat characteristics, but the latter is shown to be dominant due to its wider habitat preference. According to the species richness model, the analyzed amphibian species are shown to have tendency to move between valleys or streams. This study quantitatively analyzed habitat environment characteristics using species distribution model, however, there is a limitation in terms of analysis on food factor and connectivity with other species. Combined with additional density or habitat analysis on birds or fish, this study can lead to more comprehensive analysis on biological environment factors.

• Journal of Korea Water Resources Association
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• v.50 no.3
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• pp.139-153
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• 2017

The variation in runoff due to global climate change and urbanization should be identified quantitatively because these two factors have been significantly accelerated during the last three decades in South Korea. However, only a few research to analyze the impacts due to two factors over different time scales can be found. Therefore, in this study, the hydrological model based approach and the hydrological sensitivity approach were used to separate relative impacts by two factors on monthly, seasonal, and annual time scales at the Soyang River upper basin and the Seom River basin in South Korea. The 3 techniques such as the double mass curve method, the Pettitt's test, and the BCP analysis were performed to detect change point occurred by abrupt change in the collected observed runoff. After detection of change ponts, SWAT models calibrated on the natural periods were used to calculate the changes due to human activities. Also, 6 Budyko based methods were auxiliary to verify the results from hydrological based approach.

• Korean Journal of Ecology and Environment
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• v.44 no.3
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• pp.303-313
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• 2011

Field observations and culture experiments have been carried out during the rainy season (on the 6th, 8th and 27th July 2009) to examine changes in the primary productivity and associated plant pigments in the estuary of the Seom-jin River. Primary productivity was determined at four sampling stations along the salinity gradient. On 6th July (before heavy rain) primary productivity ranged from 689~1,169 mgC $m^{-2}$ $d^{-1}$. On the 8th, just after more than 216.5 mm of precipitation, euphotic layers at all stations were reduced to very shallow water because of the high concentration of suspended solids in the water. This resulted in dramatically decreased primary productivity down to as low as 12~32 mg C $m^{-2}$ $d^{-1}$. However, after the rain, primary productivity on the 27th ranged from 266~999 mgC $m^{-2}$ $d^{-1}$, demonstrating a fast recovery in the upper stream water to similar productivity levels to those before the rainy season. Concentration of fucoxanthin in the water was highest on the 6th July. Before the rain, concentration of the zeaxanthin, increased as the salinity decreased. Immediately after the heavy rain, the Chl b (Chlorophytes) concentration was higher at all sites than before the rainy season. The concentration of fucoxanthin decreased after the heavy rain. At the downstream site, peridinin (Dinoflagellates) were found. During the rainy season, the diatoms contributed to the primary productivity at all sites. However, after the rainy season, Chl b (Chlorophytes) and Peridinin (Dinoflagellates) increased, demonstrating the enhanced contribution of those species in addition to diatoms.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.901-912
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• 2022

The frequency of disasters is increasing due to global climate change, and unusual heavy rains and rainy seasons are occurring in Korea. Periodic monitoring and rapid detection are important because these weather conditions can lead to drought and flooding, causing secondary damage. Although research using optical images is continuously being conducted to determine the waterbody, there is a limitation in that it is difficult to detect due to the influence of clouds in order to detect floods that accompany heavy rain. Therefore, there is a need for research using synthetic aperture radar (SAR) that can be observed regardless of day or night in all weather. In this study, using Sentinel-1 SAR images that can be collected in near-real time as open data, the UNet model among deep learning algorithms that have recently been used in various fields was applied. In previous studies, waterbody detection studies using SAR images and deep learning algorithms are being conducted, but only a small number of studies have been conducted in Korea. In this study, to determine the applicability of deep learning of SAR images, UNet and the existing algorithm thresholding method were compared, and five indices and Sentinel-2 normalized difference water index (NDWI) were evaluated. As a result of evaluating the accuracy with intersect of union (IoU), it was confirmed that UNet has high accuracy with 0.894 for UNet and 0.699 for threshold method. Through this study, the applicability of deep learning-based SAR images was confirmed, and if high-resolution SAR images and deep learning algorithms are applied, it is expected that periodic and accurate waterbody change detection will be possible in Korea.