• Journal of Korea Water Resources Association
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• v.47 no.1
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• pp.25-35
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• 2014

The objective of this study is to evaluate TOPLATS land surface model performance through comparison of results of water and energy balance analysis. The study area is selected Nakdong river basin and high resolution hydrometeorological components of which spatio-temporal resolution is 1 hr and 1 km are simulated during 2003 to 2013. The simulated daily and monthly depth of flows are well fitted with the observed one on Andong and Hapcheon dam basin. In results of diurnally analysis of energy components, change pattern throughout the day of net radiation, latent heat, sensible heat, and ground heat under energy balance analysis have higher accuracy than ones under water balance analysis at C3 and C4 sites. Especially, root mean square errors of net radiation and latent heat at C4 site are shown very low as 22.18 $W/m^2$ and 7.27 $W/m^2$, respectively. Mean soil moisture and evapotranspiration in summer and winter are simulated as 36.80%, 33.08% and 222.40 mm, 59.95 mm, respectively. From this result, when we need high resolution hydrometeorological components, energy balance analysis is more reasonable than water balance analysis. And this results will be used for monitor and forecast of weather disaster like flood and draught using spatial hydrometeorological information.

• Journal of Korea Water Resources Association
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• v.56 no.8
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• pp.509-520
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• 2023

Various drought indices are widely used for assessing drought conditions which are affected by many factors such as precipitation, soil moisture, and runoff. The values of drought indices varies depending on hydro-meteorological data and calculation formulas, and the judgment of the drought condition may also vary. This study selected four calculation components such as precipitation data length, accumulation period, probability distribution function, and parameter estimation method as the sources of uncertainty in the calculation of standardized precipitation index (SPI), and evaluated their contributions to the uncertainty using root mean square error (RMSE) and linear mixed model (LMM). The RMSE estimated the overall errors in the SPI calculation, and the LMM was used to quantify the uncertainty contribution of each factor. The results showed that as the accumulation period increased and the data period extended, the RMSEs decreased. The comparison of relative uncertainty using LMM indicated that the sample size had the greatest impact on the SPI calculation. In addition, as sample size increased, the relative uncertainty related to the sample size used for SPI calculation decreased and the relative uncertainty associated with accumulation period and parameter estimation increased. In conclusion, to reduce the uncertainty in the SPI calculation, it is essential to collect long-term data first, followed by the appropriate selection of probability distribution models and parameter estimation methods that represent well the data characteristics.

• Atmosphere
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• v.32 no.2
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• pp.87-101
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• 2022

In this paper, the performance improvement for the new KMA's Climate Prediction System (GloSea6), which has been built and tested in 2021, is presented by assessing the bias distribution of basic variables from 24 years of GloSea6 hindcasts. Along with the upgrade from GloSea5 to GloSea6, the performance of GloSea6 can be regarded as notable in many respects: improvements in (i) negative bias of geopotential height over the tropical and mid-latitude troposphere and over polar stratosphere in boreal summer; (ii) cold bias of tropospheric temperature; (iii) underestimation of mid-latitude jets; (iv) dry bias in the lower troposphere; (v) cold tongue bias in the equatorial SST and the warm bias of Southern Ocean, suggesting the potential of improvements to the major climate variability in GloSea6. The warm surface temperature in the northern hemisphere continent in summer is eliminated by using CDF-matched soil-moisture initials. However, the cold bias in high latitude snow-covered area in winter still needs to be improved in the future. The intensification of the westerly winds of the summer Asian monsoon and the weakening of the northwest Pacific high, which are considered to be major errors in the GloSea system, had not been significantly improved. However, both the use of increased number of ensembles and the initial conditions at the closest initial dates reveals possibility to improve these biases. It is also noted that the effect of ensemble expansion mainly contributes to the improvement of annual variability over high latitudes and polar regions.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.747-763
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• 2022

Ocean salinity affects ocean circulation on a global scale and low salinity water around coastal areas often has an impact on aquaculture and fisheries. Microwave satellite sensors (e.g., Soil Moisture Active Passive [SMAP]) have provided sea surface salinity (SSS) based on the dielectric characteristics of water associated with SSS and sea surface temperature (SST). In this study, a Light Gradient Boosting Machine (LGBM)-based model for generating high resolution SSS from Geostationary Ocean Color Imager (GOCI) data was proposed, having machine learning-based improved SMAP SSS by Jang et al. (2022) as reference data (SMAP SSS (Jang)). Three schemes with different input variables were tested, and scheme 3 with all variables including Multi-scale Ultra-high Resolution SST yielded the best performance (coefficient of determination = 0.60, root mean square error = 0.91 psu). The proposed LGBM-based GOCI SSS had a similar spatiotemporal pattern with SMAP SSS (Jang), with much higher spatial resolution even in coastal areas, where SMAP SSS (Jang) was not available. In addition, when tested for the great flood occurred in Southern China in August 2020, GOCI SSS well simulated the spatial and temporal change of Changjiang Diluted Water. This research provided a potential that optical satellite data can be used to generate high resolution SSS associated with the improved microwave-based SSS especially in coastal areas.

• Journal of Korea Water Resources Association
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• v.55 no.6
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• pp.393-404
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• 2022

Reliable terrestrial rainfall observations from satellites at finer spatial resolution are essential for urban hydrological and microscale agricultural demands. Although various traditional "top-down" approach-based satellite rainfall products were widely used, they are limited in spatial resolution. This study aims to assess the potential of a novel "bottom-up" approach for rainfall estimation, the parameterized SM2RAIN model, applied to the C-band SAR Sentinel-1 satellite data (SM2RAIN-S1), to generate high-spatial-resolution terrestrial rainfall estimates (0.01° grid/6-day) over Central South Korea. Its performance was evaluated for both spatial and temporal variability using the respective rainfall data from a conventional reanalysis product and rain gauge network for a 1-year period over two different sub-regions in Central South Korea-the mixed forest-dominated, middle sub-region and cropland-dominated, west coast sub-region. Evaluation results indicated that the SM2RAIN-S1 product can capture general rainfall patterns in Central South Korea, and hold potential for high-spatial-resolution rainfall measurement over the local scale with different land covers, while less biased rainfall estimates against rain gauge observations were provided. Moreover, the SM2RAIN-S1 rainfall product was better in mixed forests considering the Pearson's correlation coefficient (R = 0.69), implying the suitability of 6-day SM2RAIN-S1 data in capturing the temporal dynamics of soil moisture and rainfall in mixed forests. However, in terms of RMSE and Bias, better performance was obtained with the SM2RAIN-S1 rainfall product over croplands rather than mixed forests, indicating that larger errors induced by high evapotranspiration losses (especially in mixed forests) need to be included in further improvement of the SM2RAIN.

• Journal of the Korean Geographical Society
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• v.29 no.3
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• pp.233-252
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• 1994

One of major advantages of Lumped model is its ability to simulate extended flows. A further advantage is that it requires only conventional, readily available hydrological data (rainfall, evaporation and runoff). These two advantages commend the use of this type of model for the analysis of the hydrological effects of landuse change. Experimental Catchment(K11) of Kimakia site in Kenga experienced three phases of landuse change for sixteen and half years. The Institute of Hydrology offered the hydrological data from the catchment for this research. On basis of Blackie's(l972) 9-parameter model, a new model(R1131) was reorganized in consideration of the following aspects to reflect the hydrological characteristics of the catchment: 1) The evapotranspiration necessary for the landuse hydrology, 2) high permeable soils, 3) small catchment, 4) input option for initial soil moisture deficit, and 5) othel modules for water budget analysis. The new model is constructed as a 11-parameter, 3-storage, 1-input option model. Using a number of initial conditions, the model was optimized to the data of three landuse phases. The model efficiencies were 96.78%, 97.20%, 94.62% and the errors of total flow were -1.78%, -3.36%, -5.32%. The bias of the optimized models were tested by several techniques, The extended flows were simulated in the prediction mode using the optimized model and the data set of the whole series of experimental periods. They are used to analyse the change of daily high and low-flow caused by landuse change. The relative water use ratio of the clearing and seedling phase was 60.21%, but that of the next two phases were 81.23% and 83.78% respectively. The annual peak flows of second and third phase at a 1.5-year return period were decreased by 31.3% and 31.2% compared to that of the first phase. The annual peak flow at a 50-year return period in the second phase was an increase of only 4.8%, and that in the third phase was an increase of 12.9%. The annual minimum flow at a 1.5-year return period was decreased by 34.2% in the second phase, and 34.3% in the third phase. The changes in the annual minimum flows were decreased for the larger return periods; a 20.2% decrease in the second phase and 20.9% decrease in the third phase at a 50-year return period. From the results above, two aspects could be concluded. Firstly, the flow regime in Catchment K11 was changed due to the landuse conversion from the clearing and seedling phade to the intermediate stage of pine plantation. But, The flow regime was little affected after the pine trees reached a certain height. Secondly, the effects of the pine plantation on the daily high- and low-flow were reduced with the increase in flood size and the severity of drought.

• Journal of Korea Water Resources Association
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• v.48 no.7
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• pp.581-593
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• 2015

This study constructs the drought outlook system using ESP(Ensemble Streamflow Prediction) method and evaluates its utilization for drought prediction. Historical Runoff(HR) was estimated by employing LSM(Land Surface Model) and the observed meteorological, hydrological and topographical data in South Korea. Also Predicted Runoff(PR) was produced for different lead times(i.e. 1-, 2-, 3-month) using 30-year past meteorological data and the initial soil moisture condition. The HR accuracy was higher during MAM, DJF than JJA, SON, and the prediction accuracy was highly decreased after 1 month outlook. SRI(Standardized Runoff Index) verified for the feasibility of domestic drought analysis was used for drought outlook, and PR_SRI was evaluated. The accuracy of PR_SRI with lead times of 1- and 2-month was highly increased as it considered the accumulated 1- and 2-month HR, respectively. The Correlation Coefficient(CC) was 0.71, 0.48, 0.00, and Root Mean Square Error(RMSE) was 0.46, 0.76, 1.01 for 1-, 2- and 3-month lead times, respectively, and the accuracy was higher in arid season. It is concluded that ESP method is applicable to domestic drought prediction up to 1- and 2-month lead times.

• Journal of Korean Society on Water Environment
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• v.23 no.6
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• pp.897-905
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• 2007

Approximately 70% of Korea is composed of forest areas. Especially 48% of agricultural field is practiced at highland areas over 400 m in elevation in Kangwon province. Over 90% of highland agricultural farming is located at Kangwon province. Runoff characteristics at the mountainous area such as Kangwon province are largely affected by steep slopes, thus runoff estimation considering field slopes needs to be utilized for accurate estimation of direct runoff. Although many methods for runoff estimation are available, the Soil Conservation Service (SCS), now Natural Resource Conservation Service (NRCS), Curve Number (CN)-based method is used in this study. The CN values were obtained from many plot-years dataset obtained from mid-west areas of the United States, where most of the areas have less than 5% in slopes. Thus, the CN method is not suitable for accurate runoff estimation where significant areas are over 5% in slopes. Therefore, the CN values were adjusted based on the average slopes (25.8% at Doam-dam watershed) depending on the 5-day Antecedent Moisture Condition (AMC). In this study, the CN-based Long-Term Hydrologic Impact Assessment (L-THIA) direct runoff estimation model used and the Web-based Hydrograph Analysis Tool (WHAT) was used for direct runoff separation from the stream flow data. The $R^2$ value was 0.65 and the Nash-Sutcliffe coefficient value was 0.60 when no slope adjustment was made in CN method. However, the $R^2$ value was 0.69 and the Nash-Sutcliffe value was 0.69 with slope adjustment. As shown in this study, it is strongly recommended the slope adjustment in the CN direct runoff estimation should be made for accurate direct runoff prediction using the CN-based L-THIA model when applied to steep mountainous areas.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.8-9
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• 2017

Soybean yield has been low and unstable in Japan and other areas in East Asia, despite long history of cultivation. This is contrasting with consistent increase of yield in North and South America. This presentation tries to describe perspective of breaking stagnation of soybean yield in East Asia, considering the factors of the different yields between regions. Large amount of rainfall with occasional dry-spell in the summer is a nature of monsoon climate and as frequently stated excess water is the factor of low and unstable soybean yield. For example, there exists a great deal of field-to-field variation in yield of 'Tanbaguro' soybean, which is reputed for high market value and thus cultivated intensively and this results in low average yield. According to our field survey, a major portion of yield variation occurs in early growth period. Soybean production on drained paddy fields is also vulnerable to drought stress after flowering. An analysis at the above study site demonstrated a substantial field-to-field variation of canopy transpiration activity in the mid-summer, but the variation of pod-set was not as large as that of early growth. As frequently mentioned by the contest winners of good practice farming, avoidance of excess water problem in the early growth period is of greatest importance. A series of technological development took place in Japan in crop management for stable crop establishment and growth, that includes seed-bed preparation with ridge and/or chisel ploughing, adjustment of seed moisture content, seed treatment with mancozeb+metalaxyl and the water table control system, FOEAS. A unique success is seen in the tidal swamp area in South Sumatra with the Saturated Soil Culture (SSC), which is for managing acidity problem of pyrite soils. In 2016, an average yield of $2.4tha^{-1}$ was recorded for a 450 ha area with SSC (Ghulamahdi 2017, personal communication). This is a sort of raised bed culture and thus the moisture condition is kept markedly stable during growth period. For genetic control, too, many attempts are on-going for better emergence and plant growth after emergence under excess water. There seems to exist two aspects of excess water resistance, one related to phytophthora resistance and the other with better growth under excess water. The improvement for the latter is particularly challenging and genomic approach is expected to be effectively utilized. The crop model simulation would estimate/evaluate the impact of environmental and genetic factors. But comprehensive crop models for soybean are mainly for cultivations on upland fields and crop response to excess water is not fully accounted for. A soybean model for production on drained paddy fields under monsoon climate is demanded to coordinate technological development under changing climate. We recently recognized that the yield potential of recent US cultivars is greater than that of Japanese cultivars and this also may be responsible for different yield trends. Cultivar comparisons proved that higher yields are associated with greater biomass production specifically during early seed filling, in which high and well sustained activity of leaf gas exchange is related. In fact, the leaf stomatal conductance is considered to have been improved during last a couple of decades in the USA through selections for high yield in several crop species. It is suspected that priority to product quality of soybean as food crop, especially large seed size in Japan, did not allow efficient improvement of productivity. We also recently found a substantial variation of yielding performance under an environment of Indonesia among divergent cultivars from tropical and temperate regions through in a part biomass productivity. Gas exchange activity again seems to be involved. Unlike in North America where transpiration adjustment is considered necessary to avoid terminal drought, under the monsoon climate with wet summer plants with higher activity of gas exchange than current level might be advantageous. In order to explore higher or better-adjusted canopy function, the methodological development is demanded for canopy-level evaluation of transpiration activity. The stagnation of soybean yield would be broken through controlling variable water environment and breeding efforts to improve the quality-oriented cultivars for stable and high yield.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.2
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• pp.82-96
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• 2019

This study evaluated the status of watershed health in Geum River Basin by SWAT (Soil and Water Assessment Tool) hydrology and water quality. The watershed healthiness from watershed hydrology and stream water quality was calculated using multivariate normal distribution from 0(poor) to 1(good). Before evaluation of watershed healthiness, the SWAT calibration for 11 years(2005~2015) of streamflow(Q) at 5 locations with 0.50~0.77 average Nash-Sutcliffe model efficiency and suspended solid (SS), total nitrogen(T-N), and total phosphorus(T-P) at 3 locations with 0.67~0.94, 0.59~0.79, and 0.61~0.79 determination coefficient($R^2$) respectively. For 24 years (1985~2008) the spatiotemporal change of watershed healthiness was analyzed with calibarted SWAT and 5 land use data of 1985, 1990, 1995, 2000, and 2008. The 2008 SWAT results showed that the surface runoff increased by 40.6%, soil moisture and baseflow decreased by 6.8% and 3.0% respectively compared to 1985 reference year. The stream water quality of SS, T-N, and T-P increased by 29.2%, 9.3%, and 16.7% respectively by land development and agricultural activity. Based on the 1985 year land use condition. the 2008 watershed healthiness of hydrology and stream water quality decreased from 1 to 0.94 and 0.69 respectively. The results of this study be able to detect changes in watershed environment due to human activity compared to past natural conditions.