• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.1
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• pp.74-89
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• 2015

The objective of this study is to present countermeasures for mitigation of flood damage with inundation analysis considering the effect of inland and river flood and prediction of flood inundation area, depth and time against emergencies caused by abnormal flood and local torrential rainfall. In this study, 2-D inundation analysis was fulfilled on the basis of river flood analysis applying to HEC-HMS and FLDWAV model and inundation analysis applying to SWMM model for the area of Shineum-dong, Gimcheon-si. Also expected inundation depth and area about probable rainfall of 100 and 200 years frequency were suggested. If expected inundation depth and flooding area is presented on the basis of this inundation analysis considering the effect of inland and river flood, it would be an important preliminary data to establish structural and nonstructural countermeasures for flood prevention. Also if flood risk map is prepared based on the result of inundation analysis, it would be useful to evacuate residents in high-risk area and regulate road and vehicle.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.211-211
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• 2017

장기유출해석 모델은 수자원의 안정적인 확보와 이용, 유역단위 기초자료 조사관리 등을 위하여 수자원 장기종합계획 및 전국유역조사사업 등에 활용되고 있다. 주로 국외에서 개발된 모형이 활용되고 있어, 국내의 여건에 맞추어 편의성이 개선된 모형을 찾는 것은 매우 어려운 일이다. 또한, 유출해석을 수행하기에 앞서 지속적으로 업데이트된 모델에 대한 객관적인 평가를 수행한 사례는 드물다. 따라서, 본 연구에서는 국내에서 주로 활용되고 있는 장기유출해석모델(TANK, SWAT, SSARR, PRMS 등)에 대한 비교검토를 토대로 각종 사업과의 연계성, 계산의 효율성, 정확도 등을 고려하여 USGS에서 개발한 PRMS v.4.0.2를 기반으로 국내유역에 활용이 가능하도록 개선한 $K-BASIN^{RR}$ 및 입력자료 전처리기를 개발하였다. PRMS 모형은 융설 및 지하수 흐름 등 다양한 기능을 포함하여 강우유출 분석에 활용성 높은 모형으로 평가받고 있으나, 국내 OS환경 및 활용 단위계에서 활용성이 떨어지는 단점이 있다. 본 연구에서는 소스코드 개선 및 GUI구축을 통하여 PC 환경에서 구동이 쉽도록 재구성하였고, 사용자 편의성 확보를 위한 입력자료 전처리기를 개발함으로써 수자원단위지도 3.0, 임상도 재분류 테이블, 토양도 재분류 테이블의 DB화 및 모형의 구동을 위한 HRU분할, 입력자료 생성이 가능하도록 하였다. 매개변수 최적화를 위하여 하천 유량뿐만 아니라 기저유출량을 대상으로 Monte-Carlo 시뮬레이션 기반의 매개변수를 최적화 기능을 탑재하였다. 개발된 모형의 적용성 평가를 위하여 용담댐 시험유역을 대상으로 11년 간(2005-2015)의 강우 및 온도자료를 입력자료로 활용하여 모의한 결과 샘플의 개수에 따라 NSE(Nash-Sutcliffe Efficiency)를 0.9까지 추정이 가능함을 파악하였다. 또한, 유출량과 기저유출에 대하여 동시에 최적화를 수행하는 경우 NSE를 유출량에 대하여 0.8, 기저유출량에 대하여 0.6까지 추정이 가능하였다. 최적화된 모의 결과에 대한 검토를 위하여 계산증발산량을 측정증발산량과 비교한 결과, 유사한 패턴을 나타내는 것을 확인할 수 있었다. 본 연구에서 개발한 $K-BASIN^{RR}$을 활용하는 경우 장기유출해석 업무에 효율성 및 정확도를 향상할 수 있을 것으로 판단된다.

• Journal of Korea Water Resources Association
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• v.55 no.10
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• pp.823-833
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• 2022

This study aims to improve the runoff modeling accuracy of a basin using Hydrological Simulation Program-FORTRAN (HSPF) model by considering nonhomogeneous characteristics of a basin. By entering classified values according to the various types of land cover and soil to the parameters in HSPF-roughness coefficient (NSUR), infiltration (INFILT), and evapotranspiration (LZETP)- the heterogeneity of the Yongdam Dam basin was reflected in the model. The results were analyzed and compared with the one where the parameters were set as a single value throughout the basin. The flow rate and water quality simulation results showed improved results when classified parameters were used by land cover and soil type than when single values were used. The parameterization changed not only the flow rate, but also the composition ratio of each hydrologic components such as surface runoff, baseflow, and evapotranspiration, which shows the impact of the value set to a parameter on the entire hydrological process. This implies the importance of considering the heterogeneous characteristics of the land cover and soil of the basin when setting the parameters in a model.

• Journal of Korea Water Resources Association
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• v.56 no.3
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• pp.211-224
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• 2023

In this study, a soil moisture estimation was performed using the Water Cloud Model (WCM), a backscatter model that considers vegetation based on SAR (Synthetic Aperture Radar). Sentinel-1 SAR and Sentinel-2 MSI (Multi-Spectral Instrument) images of a 40 × 50 km² area including the Yongdam Dam watershed of the Geum River were collected for this study. As vegetation descriptor of WCM, Sentinel-1 based vegetation index RVI (Radar Vegetation Index), depolarization ratio (DR), and Sentinel-2 based NDVI (Normalized Difference Vegetation Index) were used, respectively. Forward modeling of WCM was performed by 3 groups, which were divided by the characteristics between backscattering coefficient and soil moisture. The clearer the linear relationship between soil moisture and the backscattering coefficient, the higher the simulation performance. To estimate the soil moisture, the simulated backscattering coefficient was inverted. The simulation performance was proportional to the forward modeling result. The WCM simulation error showed an increasing pattern from about -12dB based on the observed backscattering coefficient.

• Korean Journal of Remote Sensing
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• v.40 no.2
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• pp.229-241
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• 2024

With the advancement of big data processing technology using cloud platforms, access, processing, and analysis of large-volume data such as satellite imagery have recently been significantly improved. In this study, the Change Detection Method, a relatively simple technique for retrieving soil moisture, was applied to the backscattering coefficient values of pre-processed Sentinel-1 synthetic aperture radar (SAR) satellite imagery product based on Google Earth Engine (GEE), one of those platforms, to estimate the surface soil moisture for six observatories within the Yongdam Dam watershed in South Korea for the period of 2015 to 2023, as well as the watershed average. Subsequently, a correlation analysis was conducted between the estimated values and actual measurements, along with an examination of the applicability of GEE. The results revealed that the surface soil moisture estimated for small areas within the soil moisture observatories of the watershed exhibited low correlations ranging from 0.1 to 0.3 for both VH and VV polarizations, likely due to the inherent measurement accuracy of the SAR satellite imagery and variations in data characteristics. However, the surface soil moisture average, which was derived by extracting the average SAR backscattering coefficient values for the entire watershed area and applying moving averages to mitigate data uncertainties and variability, exhibited significantly improved results at the level of 0.5. The results obtained from estimating soil moisture using GEE demonstrate its utility despite limitations in directly conducting desired analyses due to preprocessed SAR data. However, the efficient processing of extensive satellite imagery data allows for the estimation and evaluation of soil moisture over broad ranges, such as long-term watershed averages. This highlights the effectiveness of GEE in handling vast satellite imagery datasets to assess soil moisture. Based on this, it is anticipated that GEE can be effectively utilized to assess long-term variations of soil moisture average in major dam watersheds, in conjunction with soil moisture observation data from various locations across the country in the future.

• 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%.

• Journal of Korean Society of Disaster and Security
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• v.15 no.1
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• pp.1-12
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• 2022

An automatic optimization technique is used to estimate the optimal parameters of the hydrologic model, and different hydrologic response results can be provided depending on objective functions. In this study, the parameters of the event-based rainfall-runoff model were estimated using various objective functions, the reproducibility of the hydrograph according to the objective functions was evaluated, and appropriate objective functions were proposed. As the rainfall-runoff model, the storage function model(SFM), which is a lumped hydrologic model used for runoff simulation in the current Korean flood forecasting system, was selected. In order to evaluate the reproducibility of the hydrograph for each objective function, 9 rainfall events were selected for the Cheoncheon basin, which is the upstream basin of Yongdam Dam, and widely-used 7 objective functions were selected for parameter estimation of the SFM for each rainfall event. Then, the reproducibility of the simulated hydrograph using the optimal parameter sets based on the different objective functions was analyzed. As a result, RMSE, NSE, and RSR, which include the error square term in the objective function, showed the highest accuracy for all rainfall events except for Event 7. In addition, in the case of PBIAS and VE, which include an error term compared to the observed flow, it also showed relatively stable reproducibility of the hydrograph. However, in the case of MIA, which adjusts parameters sensitive to high flow and low flow simultaneously, the hydrograph reproducibility performance was found to be very low.