• Journal of Korea Water Resources Association
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• v.54 no.7
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• pp.495-507
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• 2021

With the recent industrial development, accidental pollution in riverine environments has frequently occurred. It is thus necessary to simulate pollutant transport and dispersion using water quality models for predicting pollutant residence times. In this study, we conducted a field experiment in a meandering reach of the Sum River, South Korea, to validate the field applicability and prediction accuracy of RAMS+ (River Analysis and Modeling System+), which is a two-dimensional (2D) stream flow/water quality analysis program. As a result of the simulation, the flow analysis model HDM-2Di and the water quality analysis model CTM-2D-TX accurately simulated the 2D flow characteristics, and transport and mixing behaviors of the pollutant tracer, respectively. In particular, CTM-2D-TX adequately reproduced the elongation of the pollutant cloud, caused by the storage effect associated with local low-velocity zones. Furthermore, the transport model effectively simulated the secondary flow-driven lateral mixing at the meander bend via 2D dispersion coefficients. We calculated the residence time for the critical concentration, and it was elucidated that the calculated residence times are spatially heterogeneous, even in the channel-width direction. The findings of this study suggest that the 2D water quality model could be the accidental pollution analysis tool more efficient and accurate than one-dimensional models, which cannot produce the 2D information such as the 2D residence time distribution.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3B
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• pp.221-230
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• 2009

In Korea, many water intake plants are easily affected by effluents of sewage treatment plants because sewage treatment plants are usually located upstream or nearby the plants of the same riverine area. Furthermore, the inflow of harmful contaminants owing to pollutant spills or transportation accidents of vehicles using the roads and bridges intersecting the river causes significant impact on the management of water intake plants. Paldang lake, the main water intake plants in Korea, is especially exposed to various water pollution accidents, because the drainage basin area is significantly large compared to the water surface area of the lake. Therefore it is necessary to predict the possible pollutant spill in advance and consider measurements in case of water pollution. In this study, water quality prediction was performed in Paldang Lake in Korea durig the dry season using two-dimensional numerical models. In order to represent the cases of pollutant accidents, the difference of pollutant transport patterns with varying injection points was analyzed. Numerical simulations for hydrodynamics of water flow and water quality predictions were performed using RMA-2 and RAM4 respectively. As a result of simulation, the difference of pollutant transport with the injection points was analyzed. As a countermeasure against the pollutant accident, the augmentation of the flow rate is proposed. In comparison with the present state, the rapid dilution and flushing effects on the pollutant cloud could be expected with increase of flow rate. Thus, increase of flow rate can be used for operation of water intake plants in case of pollutant spill accidents.

• Journal of Korea Water Resources Association
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• v.37 no.12
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• pp.979-991
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• 2004

In this study, RMA2 and RMA4, the 2-D depth-averaged models, were employed to simulate the two-dimensional mixing characteristics of the pollutants in the natural streams. The velocity and depth were first calculated using RMA2, 2-D hydrodynamic model, and then the resulting flow field was inputted to RMA4, 2-D water quality model, to compute the concentration field. RMA models were verified using the velocity and concentration data measured in S-curved meandering channel. The results showed that the RMA2 model simulated well the phenomenon that the maximum velocity line is located at the Inner bank of meandering channel, and the RMA4 model was well adapted to reproduce the general mixing behavior and the separation of tracer clouds. Comparing model simulations with measured data in the field experiments, RMA2 model simulated well general flow field and tendency that the maximum velocity line skewed toward the outer bank which were found in field experiments. The simulations of RMA4 model showed that the center of the tracer cloud tends to follow the path in which the maximum velocity occurs. In this study, the dispersion coefficients are fine-tuned based on the measured coefficients calculated using field concentration data, and the results show reasonable agreement with predictive equations.

• Journal of Korean Society for Atmospheric Environment
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• v.24 no.5
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• pp.604-612
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• 2008

The ozone concentration is one of the important environmental issue for measurement of the atmospheric condition of the country. This study focuses on applying the Autoregressive Error (ARE) model for analyzing the ozone data at middle part of the Gyeonggi-Do, Anyang monitoring site in Korea. In the ARE model, eight meteorological variables and four pollution variables are used as the explanatory variables. The eight meteorological variables are daily maximum temperature, wind speed, amount of cloud, global radiation, relative humidity, rainfall, dew point temperature, and water vapor pressure. The four air pollution variables are sulfur dioxide $(SO_2)$, nitrogen dioxide $(NO_2)$, carbon monoxide (CO), and particulate matter 10 (PM10). The result shows that ARE models both overall and monthly data are suited for describing the oBone concentration. In the ARE model for overall ozone data, ozone concentration can be explained about 71% to by the PM10, global radiation and wind speed. Also the four types of ARE models for high level of ozone data (over 80 ppb) have been analyzed. In the best ARE model for high level of ozone data, ozone can be explained about 96% by the PM10, daliy maximum temperature, and cloud amount.

• Journal of Korea Water Resources Association
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• v.57 no.9
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• pp.615-626
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• 2024

To accurately and efficiently monitor soil moisture (SM) across South Korea, this study developed a SM estimation model that integrates the cloud computing platform Google Earth Engine (GEE) and Automated Machine Learning (AutoML). Various spatial information was utilized based on Terra MODIS (Moderate Resolution Imaging Spectroradiometer) and the global precipitation observation satellite GPM (Global Precipitation Measurement) to test optimal input data combinations. The results indicated that GPM-based accumulated dry-days, 5-day antecedent average precipitation, NDVI (Normalized Difference Vegetation Index), the sum of LST (Land Surface Temperature) acquired during nighttime and daytime, soil properties (sand and clay content, bulk density), terrain data (elevation and slope), and seasonal classification had high feature importance. After setting the objective function (Determination of coefficient, R² ; Root Mean Square Error, RMSE; Mean Absolute Percent Error, MAPE) using AutoML for the combination of the aforementioned data, a comparative evaluation of machine learning techniques was conducted. The results revealed that tree-based models exhibited high performance, with Random Forest demonstrating the best performance (R² : 0.72, RMSE: 2.70 vol%, MAPE: 0.14).

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.518-518
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• 2023

자연하천에서 오염물질의 혼합 거동은 비균일한 지형학적 요인으로 인해 매우 복잡한 특성을 나타낸다. 일반적으로 오염물질 거동 모델링에서는 수체에서의 혼합을 Fick의 법칙에 따라 유속에 의한 이송과 난류에 의한 확산으로 계산하고, 국부적인 정체현상 등에 의한 non-Fickian 혼합을 야기하는 하천의 특성을 기하학적 지형 형상으로 구현하여 실제 현상에 근접한 혼합 거동을 재현한다. 하지만 계산의 효율성을 위하여 모델링의 차원을 낮추는 경우, 하천의 지형을 경계조건으로 고려할 수 없게 된다. 특히, 1차원 모델링의 경우 하천의 비균일성을 무시하고 1개의 유선으로 간주하며, 이 경우 non-Fickian 물질이동 해석을 위한 추가적인 현상학적 해석이 필요하다. 지난 50년간, non-Fickian 물질이동 해석을 위한 다양한 현상학적 모형이 제시되어 왔다. 하천을 흐름영역과 정체영역으로 구분하고 두 개의 영역 사이의 물질교환 속도를 모델링하거나, Random walk 개념으로 물질이 이동하는 경우와 이동하지 않는 경우를 확률론적으로 모델링하거나, 물질이 정체되었을 때 다시 빠져나오는 시간을 모델링하는 경우가 그 예이다. 본 연구에서는 선행연구에서 제시한 음함수 형태의 현상학적 모형을 기반으로, 수치적 반복계산 없이 상류 경계에서 임의의 형태의 농도곡선(shape-free breakthrough curve)을 갖는 오염물질운(cloud)이 일정 거리를 유하하며 발생하는 변화를 예측할 수 있는 해를 제시한다. 본 연구의 방법론은 추적법(routing procedure)을 활용한 Fickian 혼합 해석, 전달함수(transfer function) 형태의 정체시간분포 해석, 그리고 라플라스 도메인에서의 해석해 유도를 포함한다. 본 연구에서 제시된 해는 2020년 경상북도 김천시에 위치한 감천의 4.5 km 구간에서 수행한 추적자 실험의 현장 자료를 통해 정확도를 검증하여 타당성을 입증하였다.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.1
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• pp.155-163
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• 2010

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) on-board the NASA's Terra spacecraft provides along-track digital stereo image data at 15m resolution with a base-height ratio 0.6. Automated stereocorrelation procedure was implemented using the ENVI 4.1 software to derive DEMs with $15m{\times}15m$ in 43km long and 50km wide area using the ASTER stereo images. The accuracy of DEMs was analyzed in comparison with those which were obtained from digital topographic maps of 1:25,000 scale. Results indicate that RMSE in elevation between ${\pm}7$ and ${\pm}20m$ could be achieved. Excluding cloud, water and building areas as the factors which make RMSE value exceeding 10m, the accuracy of DEMs showed RMSE of ${\pm}5.789m$. Therefore for the purpose of elevating accuracy of topographic information, we intended to detect the cloud areas and shadow areas by a landcover classification method, remove those areas on the ASTER DEM and then replace with those areas detached from the cartographic DEM by band math.

• Journal of Korean Society on Water Environment
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• v.29 no.3
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• pp.383-392
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• 2013

In this research, mixing behavior of the floating pollutant such as oil spill accidents was analyzed by studying the advection-diffusion of GPS floaters at water surface. The LPT (Lagrangian Particle Tracking) model of EFDC (Environmental Fluid Dynamics Computer Code) was used to simulate the motion of the GPS floater tracer. In the field experiment, 35 GPS floaters were injected at the Samun Bridge of Nakdong River. GPS floaters traveled to downstream about 700 m for 90 minutes. The field data by the GPS floater experiments were compared with the simulation in order to calibrate the parameter of LPT model. The turbulent diffusion coefficient of LPT model was determined as $K_H/hu^*$ = 0.17 from the scatter diagram. The arrival time of peak concentration and transverse diffusion from the simulation results were similar with the experiments from the concentration curves. Numerical experiments for anticipation of damage from floating pollutant were conducted in the same reach of the Nakdong River and the results show that the pollutant cloud transported to the left bank where the Hwawon pumping station is located. For this reason, it is suggested that the proper action should be needed to maintain the safety of the water withdrawal at the Hwawon pumping station.

• Korean Journal of Remote Sensing
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• v.9 no.2
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• pp.51-69
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• 1993

Precipitable Water(PW) are retrieved over the tropical and subtropical Pacific Ocean from TOVS infrared and microwave channel brightness temperature and OLR observations by means of stepwise linear regression. The retrieved TOVS PW fields generated by PW$_{sfc}$(71.1 % of the variance and 0.62 g cm$^{-2}$ standard error over the surface) and PW$_{700500}$(71.7 % and 0.17 g cm$^{-2}$ over the 700 - 500 hPa layer) revealed more evolving synoptic signals over the tropical and subtropical Pacific Ocean. The PW$_{sfc}$ dose not show significantly the TP feature because of the representation of the lower PW for high-level clouds not associated with deep convection. There exists some elusion to trace the TP on the PW$_{sfc}$ field if any supplementary information does not provide. But ECMWF analysis has a general tendency of drying the subtropics and moistening the ITCZ (InterTropical Convergence Zone) and SPCZ(South Pacific Convergence Zone). However, although ECMWF analysis is fairly successful in capturing mean patterms, it is unsuccessful in following active synoptic signal like a tropical plume. Similarly, SMMR-PW does not represent the TP well which consists of the highand middle-level clouds, but PW$_{sfc}$ shows underestimated moistness of TP and does not depict significant signal of TP. In the PW field derived from microwave observations, the TP can not be recognized well. Furthermore, the signature of PW$_{sfc}$ was different from OLR for the TP, which implies the presence of high- and middle-layer thin clouds, but in a closer agreement for deep and active convection areas which contain thick middle- and lower-layer clouds; though OLR represented the cloudiness in the tropics well. In synoptically active regions, it differed from OLR analysis, primarily bacause of actual differences in water vapor and cloud features. The signature of PW$_{sfc}$ was different from OLR for the TP.

• Journal of the Society of Naval Architects of Korea
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• v.61 no.2
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• pp.98-105
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• 2024

Due to the low accuracy of measured data obtained from low-cost GNSS and IMU devices, it was hard to secure the required accuracy of the measured position and heading angle for autonomous navigation which was conducted by a model-scale marine mobility. In this paper, a localization technique using the Extended Kalman Filter (EKF) is proposed for coping with the issue. First of all, a position and heading angle estimator is developed using EKF with the assumption of a point mass model. Second, the measured data from GNSS and IMU, including position, heading angle, and velocity are used for the estimator. In addition, the heading angle is additionally obtained by comparing the LiDAR point cloud with map information for a temporal water tank. The newly acquired heading angle is integrated into the estimator as an additional measurement to correct the inaccuracy in the heading angle measured from the IMU. The effectiveness of the proposed approach is investigated using data acquired from preliminary tests of the model-scale autonomous marine mobility.