• Journal of Korea Water Resources Association
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• v.57 no.7
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• pp.471-479
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• 2024

Flood damage is becoming more serious due to the heavy rainfall caused by climate change. Physically based hydrological models have been utilized to predict stream water level variability and provide flood forecasting. Recently, hydrological simulations using machine learning and deep learning algorithms based on nonlinear relationships between hydrological data have been getting attention. In this study, the Long Short-Term Memory (LSTM) algorithm is used to predict the water level of the Seomjin River watershed. In addition, Climate Prediction Center morphing method (CMORPH)-based gridded precipitation data is applied as input data for the algorithm to overcome for the limitations of ground data. The water level prediction results of the LSTM algorithm coupling with the CMORPH data showed that the mean CC was 0.98, RMSE was 0.07 m, and NSE was 0.97. It is expected that deep learning and remote data can be used together to overcome for the shortcomings of ground observation data and to obtain reliable prediction results.

• Journal of Environmental Science International
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• v.26 no.12
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• pp.1321-1331
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• 2017

This study reviewed the applicability of the existing flood discharge calculation method on Jeju Island Han Stream and compared this method with observation results by improving the mediating variables for the Han Stream. The results were as follows. First, when the rain-discharge status of the Han Stream was analyzed using the flood discharge calculation method of the existing design (2012), the result was smaller than the observed flood discharge and the flood hydrograph differed. The result of the flood discharge calculation corrected for the curve number based on the terrain gradient showed an improvement of 1.47 - 6.47% from the existing flood discharge, and flood discharge was improved by 4.39 - 16.67% after applying the new reached time. In addition, the sub-basin was set separately to calculate the flood discharge, which yielded an improvement of 9.92 - 32.96% from the existing method. In particular, the steepness and rainfall-discharge characteristics of Han Stream were considered in the reaching time, and the sub-basin was separated to calculate the flood discharge, which resulted in an error rate of -8.77 to 8.71%, showing a large improvement of 7.31 - 28.79% from the existing method. The flood hydrograph also showed a similar tendency.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.3
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• pp.773-784
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• 2014

This study evaluated the applicability of the Modified Bartlett-Lewis Rectangular Pulse (MBLRP) rainfall generation model for modeling extreme rainfalls and floods in Korean Peninsula. Firstly, using the ISPSO (Isolated Species Particle Swarm Optimization) method, the parameters of the MBLRP model were estimated at the 61 ASOS (Automatic Surface Observation System) rain gauges located across Korean Peninsula. Then, the synthetic rainfall time series with the length of 100 years were generated using the MBLRP model for each of the rain gauges. Finally, design rainfalls and design floods with various recurrence intervals were estimated based on the generated synthetic rainfall time series, which were compared to the values based on the observed rainfall time series. The results of the comparison indicate that the design rainfalls based on the synthetic rainfall time series were smaller than the ones based on the observation by 20% to 42%. The amount of underestimation increased with the increase of return period. In case of the design floods, the degree of underestimation was 31% to 50%, which increases along with the return period of flood and the curve number of basin.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.3
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• pp.29-39
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• 2017

In this study, the GPM (Global Precipitation Mission) IMERG (Integrated Multi-satellitE retrievals for GPM) rainfall data was verified and evaluated using ground AWS (Automated Weather Station) and radar in order to investigate the availability of GPM IMERG rainfall data. The SPI (Standardized Precipitation Index) was calculated based on the GPM IMERG data and also compared with the results obtained from the ground observation data for the Hoengseong Dam and Yongdam Dam areas. For the radar data, 1.5 km CAPPI rainfall data with a resolution of 10 km and 30 minutes was generated by applying the Z-R relationship ($Z=200R^{1.6}$) and used for accuracy verification. In order to calculate the SPI, PERSIANN_CDR and TRMM 3B42 were used for the period prior to the GPM IMERG data availability range. As a result of latency verification, it was confirmed that the performance is relatively higher than that of the early run mode in the late run mode. The GPM IMERG rainfall data has a high accuracy for 20 mm/h or more rainfall as a result of the comparison with the ground rainfall data. The analysis of the time scale of the SPI based on GPM IMERG and changes in normal annual precipitation adequately showed the effect of short term rainfall cases on local drought relief. In addition, the correlation coefficient and the determination coefficient were 0.83, 0.914, 0.689 and 0.835, respectively, between the SPI based GPM IMERG and the ground observation data. Therefore, it can be used as a predictive factor through the time series prediction model. We confirmed the hydrological utilization and the possibility of real time drought monitoring using SPI based on GPM IMERG rainfall, even though results presented in this study were limited to some rainfall cases.

• Journal of Korea Water Resources Association
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• v.46 no.5
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• pp.465-476
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• 2013

The outgoing longwave radiation (Rlu) for estimation of evapotranspiration is essential to understand energy balance of earth. However, the ground measurement based Rlu has a limitation that the observation can just stand for the exact site, not for an area. In this study, remote sensing technique is adopted to compensate the limitation of ground observation using the geostationary satellite. We calculated Rlu using Communication, Ocean and Meteorological Satellite (COMS). We validated Rlu from COMS with Cheongmicheon (CFK) and Sulmacheon (SMK) flux tower observations controlled by Hydrological Survey Center. The results showed that Rlu from COMS represented reasonable correlation with ground based measurement. Based on the results in this study, COMS will be able to be used for estimation of evapotranspiration.

• Journal of Korea Water Resources Association
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• v.52 no.3
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• pp.195-206
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• 2019

In this study, the vulnerable period assessment method for weekly groundwater resources management was developed considering correlation between data of groundwater level, river level, precipitation applying critical infiltration concept. The vulnerable periods of 3 case study were assessed using data of groundwater, precipitation, river level, and results were compared. The weights for between observation stations were calculated using correlation of groundwater, precipitation, river level data, and weights that could be considered recently trend of data for each observation station. The vulnerable period was assessed using final calculated weights and multi criteria decision method, compared result for each case study. The developed method can be a quantitative basis for the establishment of efficient groundwater resources management and the decision of specific countermeasure applyment.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.17 no.1
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• pp.1-13
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• 2019

The accident at the Fukushima Dai-ichi Nuclear Power Plant (FDNPP) resulted in the deposition of large quantities of radionuclides over parts of eastern Japan. Radioactive contaminants have been observed over a large area including forests, cities, rivers and lakes. Due to the strong adsorption of radioactive cesium by soil particles, radioactive cesium migrates with the eroded soil, follows the surface flow paths, and is delivered downstream of population-rich regions and eventually to coastal areas. In this study, we developed a model to simulate the transport of contaminated sediment in a watershed hydrological system and this model was compared with observation data from eroded soil observation instruments located at the Korea Atomic Energy Research Institute. Two methods were applied to analyze the soil particle size distribution of the collected soil samples, including standardized sieve analysis and image analysis methods. Numerical models were developed to simulate the movement of soil along with actual rainfall considering initial saturation, rainfall infiltration, multilayer and rain splash. In the 2019 study, a numerical model will be used to add rainfall shield effect by trees, evaporation effect and shield effects of surface water. An eroded soil observation instrument has been installed near the Wolsong nuclear power plant since 2018 and observation data are being continuously collected. Based on these observations data, we will develop the numerical model to analyze long-term behavior of radionuclides on land as they move from land to rivers, lakes and coastal areas.

• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.1105-1114
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• 2022

A study on a method to overcome the limitations of the topographical and hydrological observation environment for estimating the QPE with high consistency with the ground rainfall by utilizing the spatiotemporal observation advantages of the rainfall radar for use in flood forecasting, and quantitative observations of localized rainfall due to these limiting conditions Uncertainty should be identified in terms of flood analysis. Against this background, in this study, 22 major heavy rain events in 2016 were analyzed for each of Mt. Biseul (BSL), Mt. Sobaek (SBS), Mt. Gari (GRS), Mt. Mohu (MHS), and Mt. Seodae (SDS) to determine the observation distance and altitude. The uncertainty of observation was quantified and an error map was derived. As a result of the analysis, it was found that, on average, the rainfall radar exceeded 10% up to 100 km and 30% over 150 km. Based on the average radar operating altitude angle, it was found that the error for the altitude was approximately 10% or less up to the second altitude angle, 20% at the third or higher altitude angle, and more than 50% at the fourth altitude angle or higher.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.224-227
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• 2008

Land cover and its changes, affecting multiple aspects of the environmental system such as energy balance, biogeochemical cycles, hydrological cycles and the climate system, are regarded as critical elements in global change studies. Especially in arid and semiarid regions, the observation of ecosystem that is sensitive to climate change can improve an understanding of the relationships between climate and ecosystem dynamics. The purpose of this research is analyzing the ecosystem surrounding the Gobi desert in North Asia quantitatively as well as qualitatively more concretely. We used Normalized Difference Vegetation Index (NDVI) derived from SPOT-VEGETATION (VGT) sensor during 1999${\sim}$2007. Ecosystem monitoring of this area is necessary because it is a hot spot in global environment change. This study will allow predicting areas, which are prone to the rapid environmental change. Eight classes were classified and compare with MODerate resolution Imaging Spectrometer (MODIS) global land cover. The time-series analysis was carried out for these 8 classes. Class-1 and -2 have least amplitude variation with low NDVI as barren areas, while other vegetated classes increase in May and decrease in October (maximum value occurs in July and August). Although the several classes have the similar features of NDVI time-series, we detected a slight difference of inter-annual variation among these classes.

• Journal of The Korean Society of Agricultural Engineers
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• v.51 no.1
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• pp.1-9
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• 2009

The objective of this paper was to evaluate the auto-calibration with multi-objective optimization method to calibrate the parameters of the Soil and Water Assessment Tool (SWAT) model. The model was calibrated and validated by using nine years (1996-2004) of measured data for the 384-ha Baran reservoir subwatershed located in central Korea. Multi-objective optimization was performed for sixteen parameters related to runoff. The parameters were modified by the replacement or addition of an absolute change. The root mean square error (RMSE), relative mean absolute error (RMAE), Nash-Sutcliffe efficiency index (EI), determination coefficient ($R^2$) were used to evaluate the results of calibration and validation. The statistics of RMSE, RMAE, EI, and $R^2$ were 4.66 mm/day, 0.53 mm/day 0.86, and 0.89 for the calibration period and 3.98 mm/day, 0.51 mm/day, 0.83, and 0.84 for the validation period respectively. The statistical parameters indicated that the model provided a reasonable estimation of the runoff at the study watershed. This result was illustrated with a multi-objective optimization for the flow at an observation site within the Baran reservoir watershed.