• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.274-274
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• 2020

환경부 홍수통제소의 경우는 전국단위의 강수량(지상, 레이더), 하천수위, 유사량 관측과 국부적으로 증발산량과 토양수분 관측이 이루어지고 있는 상황이며, 기상청 및 다른 공공기관도 각 목적에 맞게 수문기상관측이 이루어지나 유역(또는 지역) 단위의 물순환 과정(강우량, 유출량, 증발산량, 지하수함양량, 토양수분량 등 포함)을 규명하는 조사·연구는 매우 미비한 실정이다. 개별적인 물순환 성분별 수문조사에서 벗어난 전체적인 관점을 고려한 유역단위의 물순환 과정을 규명하는 것은 매우 중요하다. 즉 물순환 성분별 명확한 수문량 산정 결과는 수자원 개발과 물환경 보전에 중요한 정보를 제공할 수 있다. 따라서 물순환 성분별 명확한 분석을 위해서는 중·소규모 유역 단위를 대상으로 지속적이고 신뢰성 있는 자료의 획득과 축적이 중요하므로 중·소규모 유역 단위의 대표성 있는 시험유역의 운영은 매우 의미가 있다고 볼 수 있다. 본 논문에서는 한국건설기술연구원에서 운영하는 설마천 유역(유역면적 8.48㎢, 유로경사 2.15%, 경기도 파주시 적성면 소재)의 신뢰성 높은 2019년 관측자료를 이용하여 물순환 성분인 강우량, 하천유출량, 증발산량과 지하수 함양량의 자료를 산정하였으며, 물순환 성분별 균형을 이루는 자료를 생성하였다. 기본 관측자료인 강우량은 각 지점강우량의 관측자료의 비교·검토 등 품질관리를 통해 자료를 확정하고 유역평균강우량을 산정하였다. 하천수위는 기준수위표와의 검토를 통해 자료를 확정하였으며, 하천유출량은 유량측정성과와 단면검토를 통해 수위-유량관계곡선식을 개발하고, 확정된 수위자료를 적용하여 산정하였다. 그리고 증발산량은 유역내의 기상관측자료를 활용하여 잠재증발산량을 산정하였으며, 지하수함양량은 유역내에 관측된 지하수위자료를 이용하여 지하수 함양량을 산정하였다. 각 물순환 성분별로 산정된 자료는 과거년 자료와 비교·평가를 통해 균형성을 판단하였다. 각 성분별 최대치와 최소범위, 평균값을 고려하고, 강우일수, 강우의 강우강도와 지속기간, 기상자료(기온, 일조시간, 습도, 풍속 등)를 충분히 고려하였다. 각 물순환 성분별로 생성된 2019년의 설마천 유역의 총강우량은 1,024.1mm이며, 하천유출량은 608.6mm(총강우량 대비 59.4%), 실제증발산량은 385.1mm(37.6%), 지하수함양량은 30.4mm(3.0%)이다. 여기서, 실제증발산량과 지하수 함양량은 1개 지점에서 산정값이나, 물순환의 폐합 조건을 고려하여 산정된 결과이다. 향후 유역 전체를 대표하는 기법의 개발은 필요한 실정이다. 이와 같이 산정된 물순환 성분별 자료는 유역의 물순환 과정 규명을 위한 기초자료로 매우 유용하게 활용될 수 있으며, 유역 물관리를 위한 의사결정 과정에 중요한 역할을 할 수 있을 것으로 기대된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.273-273
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• 2020

환경부 홍수통제소의 경우는 전국단위의 강수량(지상, 레이더), 하천수위, 유사량 관측과 국부적으로 증발산량과 토양수분 관측이 이루어지고 있는 상황이며, 기상청 및 다른 공공기관도 각 목적에 맞게 수문기상관측이 이루어지나 유역(또는 지역) 단위의 물순환 과정(강우량, 유출량, 증발산량, 지하수함양량, 토양수분량 등 포함)을 규명하는 조사·연구는 매우 미비한 실정이다. 개별적인 물순환 성분별 수문조사에서 벗어난 전체적인 관점을 고려한 유역단위의 물순환 과정을 규명하는 것은 매우 중요하다. 즉 물순환 성분별 명확한 수문량 산정 결과는 수자원 개발과 물환경 보전에 중요한 정보를 제공할 수 있다. 따라서 물순환 성분별 명확한 분석을 위해서는 중·소규모 유역 단위를 대상으로 지속적이고 신뢰성 있는 자료의 획득과 축적이 중요하므로 중·소규모 유역단위의 대표성 있는 시험유역의 운영은 매우 의미가 있다고 볼 수 있다. 본 논문에서는 한국건설기술연구원에서 운영하는 차탄천 유역(유역면적 190.64㎢, 유로경사 0.96%, 경기도 연천군 소재)의 신뢰성 높은 2019년 관측자료를 이용하여 물순환 성분인 강우량, 하천유출량, 증발산량의 자료를 산정하였으며, 물순환 성분별 균형을 이루는 자료를 생성하였다. 기본 관측자료인 강우량은 각 지점강우량의 관측자료의 비교·검토 등 품질관리를 통해 자료를 확정하고 유역평균강우량을 산정하였다. 하천수위는 기준수위표와의 검토, 상·하류 검토를 통해 자료를 확정하였으며, 하천유출량은 유량측정성과와 단면검토를 통해 수위-유량관계곡선식을 개발하고, 확정된 수위자료를 적용하여 산정하였다. 그리고 증발산량은 유역내의 기상관측자료를 활용하여 잠재증발산량을 산정하였다. 각 물순환 성분별로 산정된 자료는 과거년 자료와 비교·평가를 통해 균형성을 판단하였다. 각 성분별 최대치와 최소범위, 평균값을 고려하고, 강우일수, 강우의 강우강도와 지속기간, 기상자료(기온, 일조시간, 습도, 풍속 등)를 충분히 고려하였다. 각 물순환 성분별로 생성된 2019년의 차탄천 유역의 총강우량은 975.9mm이며, 하천유출량은 507.9mm(총강우량 대비 52.0%), 실제증발산량은 366.4mm(37.5%), 지하수함양량은 101.6mm(10.4%)이다. 여기서, 실제증발산량은 유역내 1개 지점의 잠재증발산량을 산정하여 추정한 값이며, 지하수 함양량을 산정을 위한 지하수위 관측정이 부재한 상황이나 물순환의 폐합 조건을 고려하여 산정하였다. 이와 같이 산정된 물순환 성분별 자료는 유역의 물순환 과정 규명을 위한 기초자료로 매우 유용하게 활용될 수 있으며, 유역 물관리를 위한 의사결정 과정에 중요한 역할을 할 수 있을 것으로 기대된다.

• Journal of the Korean Geotechnical Society
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• v.40 no.4
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• pp.49-60
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• 2024

Ground-penetrating radar (GPR) enables rapid data acquisition over extensive areas, but interpreting the obtained data requires specialized knowledge. Numerous studies have utilized numerical analysis methods to examine GPR signal characteristics under various conditions. To develop more realistic numerical models, the heterogeneous nature of the ground, which causes clutter, must be considered. Clutter refers to signals reflected by objects other than the target. The Peplinski material model and fractal techniques can simulate these heterogeneous characteristics, yet there is a shortage of research on the necessary input parameters. Moreover, methods for quantitatively evaluating the similarity between field and analytical data are not well established. In this study, we calculated the autocorrelation coefficient of field data and determined the correlation length using the autocorrelation function. The correlation length represented the temporal or spatial distance over which data exhibited similarity. By comparing the correlation length of field data with that of the numerical model incorporating fractal weights, we quantitatively evaluated a numerical model for heterogeneous ground. Consequently, the results of this study demonstrated a numerical modeling technique that reflected the clutter characteristics of the field through correlation length.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.181-193
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• 2024

The increasing atmospheric imbalance caused by climate change leads to an elevation in precipitation, resulting in a heightened frequency of flooding. Consequently, there is a growing need for technology to detect and monitor these occurrences, especially as the frequency of flooding events rises. To minimize flood damage, continuous monitoring is essential, and flood areas can be detected by the Synthetic Aperture Radar (SAR) imagery, which is not affected by climate conditions. The observed data undergoes a preprocessing step, utilizing a median filter to reduce noise. Classification techniques were employed to classify water bodies and non-water bodies, with the aim of evaluating the effectiveness of each method in flood detection. In this study, the Otsu method and Support Vector Machine (SVM) technique were utilized for the classification of water bodies and non-water bodies. The overall performance of the models was assessed using a Confusion Matrix. The suitability of flood detection was evaluated by comparing the Otsu method, an optimal threshold-based classifier, with SVM, a machine learning technique that minimizes misclassifications through training. The Otsu method demonstrated suitability in delineating boundaries between water and non-water bodies but exhibited a higher rate of misclassifications due to the influence of mixed substances. Conversely, the use of SVM resulted in a lower false positive rate and proved less sensitive to mixed substances. Consequently, SVM exhibited higher accuracy under conditions excluding flooding. While the Otsu method showed slightly higher accuracy in flood conditions compared to SVM, the difference in accuracy was less than 5% (Otsu: 0.93, SVM: 0.90). However, in pre-flooding and post-flooding conditions, the accuracy difference was more than 15%, indicating that SVM is more suitable for water body and flood detection (Otsu: 0.77, SVM: 0.92). Based on the findings of this study, it is anticipated that more accurate detection of water bodies and floods could contribute to minimizing flood-related damages and losses.

• Atmosphere
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• v.20 no.4
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• pp.467-482
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• 2010

In this study, characteristics of various stability indexes (SI) and environmental parameters (EP) for the lightning are analysed by using 5 upper air observatories (Osan, Gwangju, Jeju, Pohang, and Baengnyeongdo) for the years 2002-2006 over South Korea. The analysed SI and EP are the lifted index, K-index, Showalter stability index, total precipitable water, mixing ratio, wind shear and temperature of lifting condensation level. The lightning data occurred on the range of -2 hr~+1 hr and within 100 km based on the launch time of rawinsonde and observing location are selected. In general, summer averaged temperature and mixing ratio of lower troposphere for the lightning cases are higher about 1 K and $1{\sim}2gkg^{-1}$ than no lightning cases, respectively. The Box-Whisker plot shows that the range of various SI and EP values for lightning and no lightning cases are well separated but overlapping of SI and EP values between lightning and no lightning are not a little. The optimized threshold values for the detection of lightning are determined objectively based on the highest Heidke skill socre (HSS), which is the most favorable validation parameter for the rare event, such as lightning, by using the simulation of SI and EP threshold values. Although the HSS is not high (0.15~0.30) and the number and values of selected SI and EP are dependent on geographic location, the new threshold values can be used as a supplementary tool for the detection or forecast of lightning over South Korea.

• Korean Journal of Remote Sensing
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• v.23 no.6
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• pp.559-566
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• 2007

The generation of precise digital elevation model (DEM) is very important in coastal area where time series are especially required. Although a LIDAR system is useful in coastal regions, it is not yet popular in Korea mainly because of its high surveying cost and national security reasons. Recently, precise DEM has been made using radar interferometry and waterline methods. One of these methods, spaceborne imaging radar interferometry has been widely used to measure the topography and deformation of the Earth. We acquired ALOS PALSAR FBD mode (Fine Beam Dual) data for evaluating the quality of interferograms and their coherency. We attempted to construct DEM using ALOS PALSAR pairs - One pair is 2007/05/22 and 2007/08/22, another pair is 2007/08/22 and 2007/10/22 with respective perpendicular baseline of 820 m, 312m and respective height sensitivity of 75 m and 185m at southern of Ganghwa tidal flat, Siwha- and Hwaong-lake over west coastal of Korea peninsula. Ganghwa tidal flat has low coherence between 0.3 and 0.5 of 2007/05/22 and 2007/08/22 pair. However, Siwha-lake and Hwaong-lake areas have a higher coherence value (From 0.7 and 0.9) than Ganghwa tidal area. The reason of difference coherence value is tidal condition between tidal flat area (Ganghwa) and reclaimed zone (Siwha-lake and Hwaong-lake). Therefore, DEM was constructed by ALOS PALSAR pair over Siwha-lake and Hwaong-lake. If the temporal baseline is enough short to maintain the coherent phases and height sensitivity is enough small, we will be able to successfully construct a precise DEM over coastal area. From now on, more ALOS PALSAR data will be needed to construct precise DEM of West Coast of Korea peninsular.

• Knowledge Management Research
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• v.22 no.4
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• pp.71-85
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• 2021

The purpose of this study is to find out which artificial intelligence methodology is most suitable for creating a foreign exchange rate prediction model using the indicators of bond market and interest rate market. KTBs and MSBs, which are representative products of the Korea bond market, are sold on a large scale when a risk aversion occurs, and in such cases, the USD/KRW exchange rate often rises. When USD liquidity problems occur in the onshore Korean market, the KRW Cross-Currency Swap price in the interest rate market falls, then it plays as a signal to buy USD/KRW in the foreign exchange market. Considering that the price and movement of products traded in the bond market and interest rate market directly or indirectly affect the foreign exchange market, it may be regarded that there is a close and complementary relationship among the three markets. There have been studies that reveal the relationship and correlation between the bond market, interest rate market, and foreign exchange market, but many exchange rate prediction studies in the past have mainly focused on studies based on macroeconomic indicators such as GDP, current account surplus/deficit, and inflation while active research to predict the exchange rate of the foreign exchange market using artificial intelligence based on the bond market and interest rate market indicators has not been conducted yet. This study uses the bond market and interest rate market indicator, runs artificial neural network suitable for nonlinear data analysis, logistic regression suitable for linear data analysis, and decision tree suitable for nonlinear & linear data analysis, and proves that the artificial neural network is the most suitable methodology for predicting the foreign exchange rates which are nonlinear and times series data. Beyond revealing the simple correlation between the bond market, interest rate market, and foreign exchange market, capturing the trading signals between the three markets to reveal the active correlation and prove the mutual organic movement is not only to provide foreign exchange market traders with a new trading model but also to be expected to contribute to increasing the efficiency and the knowledge management of the entire financial market.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.497-510
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• 2022

Agricultural reservoirs are essential structures for water supplies during dry period in the Korean peninsula, where water resources are temporally unequally distributed. For efficient water management, systematic and effective monitoring of medium-small reservoirs is required. Synthetic Aperture Radar (SAR) provides a way for continuous monitoring of those, with its capability of all-weather observation. This study aims to evaluate the applicability of SAR in monitoring medium-small reservoirs using Sentinel-1 (10 m resolution) and Capella X-SAR (1 m resolution), at Chari (CR), Galjeon (GJ), Dwitgol (DG) reservoirs located in Ulsan, Korea. Water detected results applying Z fuzzy function-based threshold (Z-thresh) and Chan-vese (CV), an object detection-based segmentation algorithm, are quantitatively evaluated using UAV-detected water boundary (UWB). Accuracy metrics from Z-thresh were 0.87, 0.89, 0.77 (at CR, GJ, DG, respectively) using Sentinel-1 and 0.78, 0.72, 0.81 using Capella, and improvements were observed when CV was applied (Sentinel-1: 0.94, 0.89, 0.84, Capella: 0.92, 0.89, 0.93). Boundaries of the waterbody detected from Capella agreed relatively well with UWB; however, false- and un-detections occurred from speckle noises, due to its high resolution. When masked with optical sensor-based supplementary images, improvements up to 13% were observed. More effective water resource management is expected to be possible with continuous monitoring of available water quantity, when more accurate and precise SAR-based water detection technique is developed.