• Journal of Climate Change Research
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• v.4 no.4
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• pp.397-407
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• 2013

Seasons in Korea have very distinguishable features. Due to continental high pressure, spring in Korea is dry and has low precipitation. Due to climate change derived from the increase of greenhouse gases, climate variability had increased and it became harder to predict. This caused the spring drought harsher than usual. Since 1990s, numbers of chronic drought from winter to spring increased in southern regions of Korea. Such drought in the spring damages the growth and development of the crops sown in the spring and decreases its quantity. For stable agricultural production in the future, it is necessary to assess vulnerability of the relationship between spring drought and agricultural production as well as to establish appropriate measures accordingly. This research used CCGIS program to perform vulnerability assessment on spring drought based on climate change scenario SRES A1B, A1FI, A1T, A2, B1, B2 and RCP 8.5 in 232 regions in Korea. As a result, Every scenario showed that vulnerability of spring drought decreased from 2000s to 2050s. Ratio of decrease was 37% under SRES scenario but, 3% under RCP 8.5 scenario. Also, for 2050 prediction, every scenario predicted the highest vulnerability in Chungcheongnam-do. However, RCP-8.5 predicted higher vulnerability in Gyeonggi-do than SRES scenario. The reason for overall decrease in vulnerability of agriculture for future spring drought is because the increase of precipitation was predicted. The assessment of vulnerability by different regions showed that choosing suitable scenario is very important factor.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.515-530
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• 2021

This study is to estimate soil moisture (SM) using Sentinel-1A/B C-band SAR (synthetic aperture radar) images and Multiple Linear Regression Model(MLRM) in the Yongdam-Dam watershed of South Korea. Both the Sentinel-1A and -1B images (6 days interval and 10 m resolution) were collected for 5 years from 2015 to 2019. The geometric, radiometric, and noise corrections were performed using the SNAP (SentiNel Application Platform) software and converted to backscattering coefficient of VV and VH polarization. The in-situ SM data measured at 6 locations using TDR were used to validate the estimated SM results. The 5 days antecedent precipitation data were also collected to overcome the estimation difficulty for the vegetated area not reaching the ground. The MLRM modeling was performed using yearly data and seasonal data set, and correlation analysis was performed according to the number of the independent variable. The estimated SM was verified with observed SM using the coefficient of determination (R²) and the root mean square error (RMSE). As a result of SM modeling using only BSC in the grass area, R² was 0.13 and RMSE was 4.83%. When 5 days of antecedent precipitation data was used, R² was 0.37 and RMSE was 4.11%. With the use of dry days and seasonal regression equation to reflect the decrease pattern and seasonal variability of SM, the correlation increased significantly with R² of 0.69 and RMSE of 2.88%.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.22 no.4
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• pp.187-198
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• 2017

Dissolved and particulate organic carbon concentrations and fluxes were measured and estimated for the Yeongsan River during 2006~2015. The dissolved organic carbon (DOC) concentrations ranged from 2.49 to $4.39mg{\cdot}C/L$ with a variance of 30.1% (${\sigma}_x/\bar{x}$), and showed a simple correlation to algal bloom and precipitation. The particulate organic carbon (POC) concentrations had gradually decreased from 6.68 to $0.19mg{\cdot}C/L$ for 10 years, and changed definitely with weir construction in 2011. Based on the relationships between POC and suspended particulate matters and between POC and chlorophyll-a, we found out that the distinct variation of the origin and composition of POC was caused by stagnation and screening effect of the dammed river. The total organic carbon (TOC) concentrations dropped to 52.3% (from 8.26 to $3.94mg{\cdot}C/L$) as the POC concentrations diminished to more than 94.8% after weir construction, in which the DOC forms up to 90.9%. The fluxes of TOC, based on the relationship between the annual TOC concentration and the discharge of Yeongsan dike sluice, were $2.56{\sim}19.41{\times}10^9g{\cdot}C/yr$, and showed a great deal of variability in 2011. Since then the TOC flux dropped to $5.40{\times}10^9$ (2011~2015) from $14.54{\times}10^9g{\cdot}C/yr$ (2006~2010). These results suggest that the weirs trapped annually $1.83{\times}10^9g{\cdot}C$ on a river bed, but released in great levels of dissolved organic form at their exits.

• Korean Journal of Ecology and Environment
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• v.43 no.3
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• pp.385-399
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• 2010

The objective of this study was to analyze long term temporal trends of water chemistry and spatial heterogeneity for 83 sampling sites of Geum-River watershed using water quality dataset during 2003~2007 (obtained from the Ministry of Environment, Korea). The water quality, based on multi-parameters of temperature, dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), suspended solids (SS), total nitrogen (TN), total phosphorus (TP), and electric conductivity (EC), largely varied depending on the landuse patterns, years and seasons. The watershed was classified into three different landuse types: forest stream (Fo), agricultural stream (Ag), and urban stream (Ur). Largest seasonal variabilities in most parameters occurred during the two months of July to August and these were closely associated with large spate of summer monsoon rain. Conductivity, used as a key indicator for an ionic dilution during rainy season, and nutrients of TN and TP had inverse functions of precipitation. BOD, COD decrease during the rainy season. Minimum values in the conductivity, TN, and TP were observed during the summer monsoon, indicating an ionic and nutrient dilution of river water by the rainwater. In contrast, major inputs of suspended solids (SS) occurred during the period of summer monsoon. The landuse patterns analyses, based on the variables of BOD, COD, TN, TP and SS, showed that the values were greater in the agricultural stream (Ag) than in the forest stream (Fo) and urban stream (Ur) and that water quality was worst in the urban stream (Ur). The overall dataset suggest that efficient water quality management, especially in Gap-Stream and Miho-Stream, which showed worst water quality is required along with some of urban stream (Ur), based on the analysis of landuse patterns.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.8 no.3
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• pp.251-261
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• 2003

As a part of an on-going project investigating flux of materials in Gomso Tidal Flat, we have monitored temporal and spatial distribution of nitrogen components(TN, PON, DON, DIN) and have sought the relationships with the freshwater input(tidal range, salinity), the biological activities(chlorophyll-${\alpha}$, TP, DIP, silicate) and the resuspended bottom sediment in seawater(SPM) from 1999 to 2000. TN in seawater was 39.05 $\mu\textrm{m}$ol 1$\^$-1/ (31.03∼42.93 $\mu\textrm{m}$ol 1$\^$-1/) without any statistical difference(p<0.05) between the studied periods. Organic nitrogen (DON and PON) occupied 75％, 95％, 73％, and 75％ in April, August, September and November, respectively. DON and PON have been found within the narrow concentration ranges of 11.30∼16.38 $\mu\textrm{m}$ol 1$\^$-1/ and 13.16∼20.04 $\mu\textrm{m}$ol 1$\^$-1/ in spite of severe environmental differences through the studied periods. Dissolved fractions of nitrogen(DON and DIN) occupied 53∼65％ of TN. Only DIN varied with an evident temporal variability: low concentrations(1.325∼1.616 $\mu\textrm{m}$ol 1$\^$-1/) in August and high enrichment(8.377∼14.65 $\mu\textrm{m}$ol 1$\^$-1/) in September. High consumption rate of DIN by phytoplankton and a long-lasted drought probably induced such low concentration of DIN in August. Eventually heavy precipitation probably introduced plenty of new nitrogen sources into Gomso Bay in September. The portion of PON, DON and DIN in the total nitrogen was 40％, 38％ and 22％, respectively. Their contents were in the order of DON>PON>DIN for the year round except PON>DON>DIN only in September. The highest DON portion in August probably due to the active microbial decomposition of organic material in summer. Only in April, some evident negative correlations have been found between chlorophyll-${\alpha}$ and DIN mostly nitrate(-0.64, p<0.01), phosphate(-0.46, p<0.01) and silicate(-0.55, p<0.01). The Si(OH)$_4$/DIN/DIP ratios in the water column suggests the limitation of DIN for the growth of phytoplankton during the dry summer in Gomso Bay, which was the case of August in this work. Even with some difference between the studied periods, the primary factors on the distribution of nitrogen components in seawater overlying the Gomso Tidal Flat have been the tidal range and the freshwater input, but the additional variations were due to the biological activities.

• Korean Journal of Remote Sensing
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• v.34 no.3
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• pp.519-533
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• 2018

The sensible heat flux (SHF)and latent heat flux (LHF) over Korean Peninsula ocean during recent 4 years were calculated using Coupled Ocean-Atmosphere Response Experiment (COARE) 3.5 bulk algorithm and satellite-based atmospheric-ocean variables. Among the four input variables (10-m wind speed; U, sea surface temperature; $T_s$, air temperature; $T_a$, and air humidity; $Q_a$) required for heat flux calculation, Ta and $Q_a$, which are not observed directly by satellites, were estimated from empirical relations developed using satellite-based columnar atmospheric water vapor (W) and $T_s$. The estimated satellite-based $T_a$ and $Q_a$ show high correlation coefficients above 0.96 with the buoy observations. The temporal and spatial variability of monthly ocean heat fluxes were analyzed for the Korean Peninsula ocean. The SHF showed low values of $20W/m^2$ over the entire areas from March to August. Particularly, in July, SHF from the atmosphere to the ocean, which is less than $0W/m^2$, has been shown in some areas. The SHF gradually increased from September and reached the maximum value in December. Similarly, The LHF showed low values of $40W/m^2$ from April to July, but it increased rapidly from autumn and was highest in December. The analysis of monthly characteristics of the meteorological variables affecting the heat fluxes revealed that the variation in differences of temperature and humidity between air and sea modulate the SHF and LHF, respectively. In addition, as the sensitivity of SHF and LHF to U increase in winter, it contributed to the highest values of ocean heat fluxes in this season.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.5
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• pp.779-789
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• 2016

The effective rainfall is calculated considering the soil moisture. It utilizes observed data directly in order to incorporate the soil moisture into the rainfall-runoff model, or it calculates indirectly within the model. The rainfall-runoff model, IHACRES, used in this study computes the catchment wetness index (CWI) first varying with temperature and utilize it for estimating precipitation loss. The nonlinear relationship between the CWI and the effective rainfall in the Hapcheondam watershed was derived and utilized for the long-term runoff calculation. The effects of variable and constant CWI during calibration and validation were suggested by flow regime. The results show the variable CWI is generally more effective than the constant CWI. The $R^2$ during high flow period shows relatively higher than the ones during normal or low flow period, but the difference between cases of the variable and constant CWI was insignificant. The results indicates that the high flow is relatively less sensitive to the evaporation and soil moisture associated with temperature. On the other hand, the variable CWI gives more desirable results during normal and low flow periods which means that it is crucial to incorporate evaporation and soil moisture depending on temperature into long-term continuous runoff simulation. The NSE tends to decrease during high flow period with high variability which could be natural because NSE index is largely influenced by outliers of underlying variable. Nevertheless overall NSE shows satisfactory range higher than 0.9. The utilization of variable CWI during normal and low flow period would improve the computation of long-term rainfall-runoff simulation.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.61 no.3
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• pp.171-183
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• 2016

The effects of weather variations on winter hulless barley were analyzed using data obtained from winter crop situation test at Iksan from 1985 to 2015. The wintering stage in the 16 years from 2000 to 2015 has become colder and shorter than that in the previous 15 years from 1985 to 1999. This has resulted in an early sequence of regrowth date, heading date, and ripening date. Heading date of hulless barley was mostly influenced by regrowth date and period of stem elongation. Futher, the regrowth date and period of stem elongation were strongly negatively correlated with the average air temperature in February and the maximum air temperature in March, respectively. The number of spikes per $m^2$ and 1000-grain weight of Saechalssal cultivated from 2003 to 2015 showed strong positive correlations with yield. In early heading years, yield increased with extended ripening period and with increased 1000-grain weight. There was a strong negative correlation between 1000-grain weight and the average temperature during the ripening period. In the 15 years from 1985 to 1999, warm winters contributed to yield increase with increase in the number of spikes per $m^2$ and a long ripening period. In contrast, in the recent 16 years from 2000 to 2015, the large variability in air temperature during the wintering stage, the decreasing number of spikes per $m^2$ and the steadily increasing air temperature and decreasing precipitation during the ripening stage have caused high temperature stress and yield loss in late heading years.

• Journal of Soil and Groundwater Environment
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• v.12 no.5
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• pp.19-32
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• 2007

In Korea, there have been various methods of estimating groundwater recharge which generally can be subdivided into three types: baseflow separation method by means of groundwater recession curve, water budget analysis based on lumped conceptual model in watershed, and water table fluctuation method (WTF) by using the data from groundwater monitoring wells. However, groundwater recharge rate shows the spatial-temporal variability due to climatic condition, land use and hydrogeological heterogeneity, so these methods have various limits to deal with these characteristics. To overcome these limitations, we present a new method of estimating recharge based on water balance components from the SWAT-MODFLOW which is an integrated surface-ground water model. Groundwater levels in the interest area close to the stream have dynamics similar to stream flow, whereas levels further upslope respond to precipitation with a delay. As these behaviours are related to the physical process of recharge, it is needed to account for the time delay in aquifer recharge once the water exits the soil profile to represent these features. In SWAT, a single linear reservoir storage module with an exponential decay weighting function is used to compute the recharge from soil to aquifer on a given day. However, this module has some limitations expressing recharge variation when the delay time is too long and transient recharge trend does not match to the groundwater table time series, the multi-reservoir storage routing module which represents more realistic time delay through vadose zone is newly suggested in this study. In this module, the parameter related to the delay time should be optimized by checking the correlation between simulated recharge and observed groundwater levels. The final step of this procedure is to compare simulated groundwater table with observed one as well as to compare simulated watershed runoff with observed one. This method is applied to Mihocheon watershed in Korea for the purpose of testing the procedure of proper estimation of spatio-temporal groundwater recharge distribution. As the newly suggested method of estimating recharge has the advantages of effectiveness of watershed model as well as the accuracy of WTF method, the estimated daily recharge rate would be an advanced quantity reflecting the heterogeneity of hydrogeology, climatic condition, land use as well as physical behaviour of water in soil layers and aquifers.

• Journal of Wetlands Research
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• v.16 no.4
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• pp.303-318
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• 2014

Baseflow gives a significant contribution to stream function in the regions where climatic characteristics are seasonally distinct. In this regard, variable baseflow can make it difficult to maintain a stable water supply, as well as causing disruption to the stream ecosystem. Changes in land use can affect both the direct flow and baseflow of a stream, and consequently, most other components of the hydrologic cycle. Baseflow estimation depends on the observed streamflow in gauge watersheds, but accurate predictions of streamflow through modeling can be useful in determining baseflow data for ungauged watersheds. Accordingly, the objectives of this study are to 1) improve predictions of SWAT by applying the alpha factor estimated using RECESS for calibration; 2) estimate baseflow in an ungauged watershed using the WHAT system; and 3) evaluate the effects of changes in land use on baseflow characteristics. These objectives were implemented in the Gapcheon watershed, as an ungauged watershed in South Korea. The results show that the alpha factor estimated using RECESS in SWAT calibration improves the prediction for streamflow, and, in particular, recessions in the baseflow. Also, the changes in land use in the Gapcheon watershed leads to no significant difference in annual baseflow between comparable periods, regardless of precipitation, but does lead to differences in the seasonal characteristics observed for the temporal distribution of baseflow. Therefore, the Guem River, into which the stream from the Gapcheon watershed flows, requires strategic seasonal variability predictions of baseflow due to changes in land use within the region.