• The Journal of Engineering Geology
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• v.29 no.2
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• pp.99-112
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• 2019

Rainfall infiltration through the unsaturated zone is influenced by a range of factors including topography, geology, soil, rainfall intensity, temperature and vegetation; the actual infiltration varies largely in time and space. The infiltration capacity of soil is a critical factor in identifying groundwater recharge and leakage of surface water. It may differ depending on soil types and geological features of a particular basin or territory as well as on the usage of the land. This study was conducted in forest and farmland region of the mid-mountain area (EL. 50~300 m) of Jeju Island to test soil infiltration capacity of the area where rainfall contributes to groundwater. Results were analyzed using the four soil group classification methods presented by Jeong et al. (1995) and NAS (2007) to discover that the method offered by NAS (2007) is more reliable in the mid-mountain area of Jeju Island. The study compares and reviews the existing classification methods using the results of infiltration capacity tests executed on different soil groups throughout the whole region of the Jeju mid-mountain area. It is expected that this work will serve as a guideline for evaluating surface water recharge and hydraulic characteristics of Jeju Island.

• Journal of Korea Water Resources Association
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• v.52 no.1
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• pp.35-49
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• 2019

This study proposes a new method for categorizing the hydrological soil groups by considering the recent revision results of soil series. Also, the proposed method is evaluated by comparing the categorizing result with those based on existing three different methods. As an example, the proposed method is applied to Jeju Island to estimate the CN value, which is then compared with CN values estimated by applying the existing three different methods. Summaries of the results are as follow. (1) The revision result since 2007 shows that the soil texture has been changed in the 43 soil series, the drainage class in the 1 soil series, the permeability in the 15 soil series, and the impermeable layer in the 26 soil series. (2) The categorizing result of hydrological soil groups by applying the proposed method shows that the group B is the most dominant group covering up to 49.25%. On the other hand, one of the existing method of 1987 provides the group C as the most dominant group (46.43%). Method of 1995 defines the group B as the most dominant group (27.69%). The other method of 2007 distinguishes the group D (35.82%) to be the most dominant group. (3) Also, the CN value estimated by applying the proposed method to Jeju Island is found to be smaller than those based on existing three methods. This result indicates the possible overestimation of the CN value when applying the existing three methods.

• Journal of Korea Water Resources Association
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• v.54 no.6
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• pp.365-379
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• 2021

Hydrological model parameters are essential for model simulation and can vary over time due to topography, climatic conditions, climate change and human activity. Consequently, the use of fixed parameters can lead to inaccurate stream flow simulations. The aim of this study is to investigate an appropriate method of estimating time-varying parameters using stream flow observations, and how the simulation efficiency changes when stream flow data are assimilated into the model. The data assimilation method can be used to automatically estimate the parameters of a hydrological model by adapting to a variety of changing environments. Stream flow observations were assimilated into a two parameter monthly water balance model using a particle filter. The simulation results using the time-varying parameters by the data assimilation method were compared with the simulation results using the fixed parameters by the SCEM method. First, we conducted synthesis experiments based on various scenarios to investigate if the particle filter method can adequately track parameters that change over time. After that, it was applied to actual watersheds and compared with the predictive performance of stream flow when using parameters that change with time and fixed parameters. The conclusions obtained through this study are as follows: (1) The predictive performance of the overall monthly stream flow time series was similar between the particle filter method and the SCEM method. (2) The monthly runoff prediction performance in the period except the rainy season was better in the simulation by the periodically changing parameters using the data assimilation method. (3) Uncertainty in the observational data of stream flow used for assimilation played an important role in the predictive performance of the particle filter.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.60-66
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• 2020

Torrential rain causes landslide damage every year. In particular, the 2011 downpour caused landslides at numerous points throughout Mt. Woomyeon, which resulted in considerable damage to people and property. Because it occurred in an urban area, this case became a major social issue and received public attention. Measures were quickly implemented for multilateral investigations and recovery. Landslides caused by heavy rain are greatly affected by rainfall at the time. Landslides from the upper part erode the flow path, increasing the size, causing much damage to the lower part. This study selected a rural village area among the damaged areas of Mt. Woomyeon, and analyzed the change in terrain profile before and after a landslide using the DSM data obtained from airborne LiDAR. This area can be divided into three hydrological basins. For each basin, the analysis was performed on the average slope of each part of the flow path, as well as the erosion and deposition due to soil flow. As a result of the analysis, it was estimated that the total amount of soil from the Jeonwon village was 15,300㎥. These field data based on GIS can be used as basic information to predict damage in the case of a similar disaster, and it can be helpful in analyzing the results of various debris flow simulations.

• Journal of Korea Water Resources Association
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• v.55 no.5
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• pp.345-356
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• 2022

A severe flooding occured at a small urban catchment in Daejeon-si South Korea on July 30, 2020 causing significant loss of property (inundated 78 vehicles and two apartments) and life (one casualty and 56 victims). In this study, a retrospective analysis of the inundation event was implemented using a physically-based urban flood model, H12 with high-resolution data. H12 is an integrated 1-dimensional sewer network and 2-dimensional surface flow model supported by hybrid parallel techniques to efficiently deal with high-resolution data. In addition, we evaluated the impact of the flooding barriers which were installed after the flood disaster. As a result, it was found that the inundation was affected by a combination of multiple components including the shape of the basin, the low terrain of the inundation area located in the downstream part of the basin, and lack of pipe capacity to drain discharge from the upstream during heavy rain. The impact of the flooding barriers was analyzed by modeling with and without barriers on the high-resolution terrain input data. It was evaluated that the flood barriers effectively lower the water depth in the apartment complex. This study demonstrates capability of high-resolution physically-based urban modeling to quantitatively assess the past inundation event and the impact of the reduction measures.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.246-246
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• 2021

본 연구는 강우 발생시 유량을 추정하는 것에 목적이 있다. 이를 위해 본 연구는 선행연구의 모형 개발방법론에서 벗어나 딥러닝 알고리즘 중 하나인 합성곱 신경망 (convolution neural network)과 수문학적 이미지 (hydrological image)를 이용하여 강우 발생시 유량을 추정하였다. 합성곱 신경망은 일반적으로 분류 문제 (classification)을 해결하기 위한 목적으로 개발되었기 때문에 불특정 연속변수인 유량을 모의하기에는 적합하지 않다. 이를 위해 본 연구에서는 합성곱 신경망의 완전 연결층 (Fully connected layer)를 개선하여 연속변수를 모의할 수 있도록 개선하였다. 대부분 합성곱 신경망은 RGB (red, green, blue) 사진 (photograph)을 이용하여 해당 사진이 나타내는 것을 예측하는 목적으로 사용하지만, 본 연구의 경우 일반 RGB 사진을 이용하여 유출량을 예측하는 것은 경험적 모형의 전제(독립변수와 종속변수의 관계)를 무너뜨리는 결과를 초래할 수 있다. 이를 위해 본 연구에서는 임의의 유역에 대해 2차원 공간에서 무차원의 수문학적 속성을 갖는 grid의 집합으로 정의되는 수문학적 이미지는 입력자료로 활용했다. 합성곱 신경망의 구조는 Convolution Layer와 Pulling Layer가 5회 반복하는 구조로 설정하고, 이후 Flatten Layer, 2개의 Dense Layer, 1개의 Batch Normalization Layer를 배열하고, 다시 1개의 Dense Layer가 이어지는 구조로 설계하였다. 마지막 Dense Layer의 활성화 함수는 분류모형에 이용되는 softmax 또는 sigmoid 함수를 대신하여 회귀모형에서 자주 사용되는 Linear 함수로 설정하였다. 이와 함께 각 층의 활성화 함수는 정규화 선형함수 (ReLu)를 이용하였으며, 모형의 학습 평가 및 검정을 판단하기 위해 MSE 및 MAE를 사용했다. 또한, 모형평가는 NSE와 RMSE를 이용하였다. 그 결과, 모형의 학습 평가에 대한 MSE는 11.629.8 m3/s에서 118.6 m3/s로, MAE는 25.4 m3/s에서 4.7 m3/s로 감소하였으며, 모형의 검정에 대한 MSE는 1,997.9 m3/s에서 527.9 m3/s로, MAE는 21.5 m3/s에서 9.4 m3/s로 감소한 것으로 나타났다. 또한, 모형평가를 위한 NSE는 0.7, RMSE는 27.0 m3/s로 나타나, 본 연구의 모형은 양호(moderate)한 것으로 판단하였다. 이에, 본 연구를 통해 제시된 방법론에 기반을 두어 CNN 모형 구조의 확장과 수문학적 이미지의 개선 또는 새로운 이미지 개발 등을 추진할 경우 모형의 예측 성능이 향상될 수 있는 여지가 있으며, 원격탐사 분야나, 위성 영상을 이용한 전 지구적 또는 광역 단위의 실시간 유량 모의 분야 등으로의 응용이 가능할 것으로 기대된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.340-340
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• 2021

가뭄의 특성상 시점과 종점을 명확하게 정의하기 어렵기 때문에 기준수문량을 설정하고 부족량과 지속기간을 정의하는 것이 일반적이다. 대상 수문량은 강우나 유출량을 사용할 수 있지만, 두 성분간 지체와 감쇄효과로 인하여 빈도해석의 결과는 차이를 보일 수 밖에 없어, 사용 목적에 따라 선별적으로 적용해야 한다. 가뭄빈도해석은 강우를 기반으로 지속기간과 심도를 정의하여 빈도를 해석하는 연구가 선행되어왔지만, 기본적으로 강우의 간헐적 발생특성과 체감도의 한계가 문제로 지적되고 있다. 본 연구에서는 댐 유입량의 Run 시계열 특성을 이용하여 다양한 유황을 기준유량으로 활용하여 가뭄의 시점과 종점에 대한 가뭄사상을 추출하고 지속기간과 누적부족량을 계산하여 가뭄빈도해석의 변수로 설정하였다. 두 변수간의 복잡한 상호 관계를 해석하기 위해 Copula 함수를 이용한 이변량 가뭄빈도해석을 진행하였다. 먼저 소양강댐('74-'19) 유입량, 충주댐('86-'19) 유입량을 연구대상지역으로 설정하여, 두 유역의 유입량의 추세분석을 통해 시간의존성을 파악하였다. 유황분석에 사용되는 분위량중 평수량을 기준값으로 사용하여 각 년별 최대 지속기간과 누적부족량을 추출하였다. Copula 가뭄빈도해석을 수행하기 전에 지속기간에는 GEV, 누적 부족량에는 Log-normal 분포를 적용해 단변량 누적확률분포를 계산하여 재현기간을 도출하였다. 이변량 빈도해석에 Clayton Copula 함수를 적용하여 가뭄빈도해석을 진행하였고, Copula 이변량 재현기간과 SDF곡선을 도출하였다. Clayton Copula를 이용한 이변량 가뭄빈도해석의 결과로 소양강댐의 가장 극심한 가뭄은 1996년으로 단변량 재현기간은 지속기간 기준 9.11년, 누적부족량 기준 17.26년, Copula 재현기간은 141.19년 이며 충주댐의 가장 극심한 가뭄은 2014년으로 단변량 재현기간은 지속기간 기준 17.76년, 누적부족량 기준 18.72년, Copula 재현기간은 184.19년으로 단변량 가뭄빈도해석을 통한 재현기간보다 Copula 재현기간이 높은 결과가 도출되었다. Run 시계열을 바탕으로 한 기준유량의 임계값 기준 Event 산정과 Copula를 이용한 빈도해석은 가뭄분석에 이용되는 자료의 상관관계와 분포특성을 재현하는데 효과적인 특징이 있다. 이를 미루어 보아 Copula 함수를 이용한 가뭄빈도해석의 재현기간은 보다 현실적인 재현기간을 도출할 수 있는 것으로 판단된다. 임계값의 조정을 통해 가뭄빈도해석의 변수의 양이 늘어나면, 보다 정확도 높은 재현기간을 도출하여 수문학적 가뭄을 정의할 수 있을 것이라고 사료된다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4B
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• pp.345-354
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• 2006

Drought brings on long term damage in contrast to flood, on economic loss in the region, and on ecologic and environmental disruptions. Drought is one of major natural disasters and gives a painful hardship to human beings. So we have tried to quantify the droughts for reducing drought damage and developed the drought indices for drought monitoring and management. The Palmer's drought severity index (PDSI) is widely used for the drought monitoring but it has the disadvanges and limitations in that the PDSI is estimated by considering just climate conditions as pointed out by many researchers. Thus this study uses the SWAT model which can consider soil conditions like soil type and land use in addition to climate conditions. We estimate soil water (SW) and soil moisture index (SMI) by SWAT which is a long term runoff simulation model. We apply the SWAT model to Soyang dam watershed for SMI estimation and compare SMI with PDSI for drought analysis. Say, we calibrate and validate the SWAT model by daily inflows of Soyang dam site and we estimate long term daily soil water. The estimated soil water is used for the computation of SMI based on the soil moisture deficit and we compare SMI with PDSI. As the results, we obtained the determination coefficient of 0.651 which means the SWAT model is applicable for drought monitoring and we can monitor drought in more high resolution by using GIS. So, we suggest that SMI based on the soil moisture deficit can be used for the drought monitoring and management.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.5B
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• pp.487-495
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• 2010

Soil moisture is a crucial factor in hydrological system which influences runoff, energy balance, evaporation, and atmosphere. United States National Aeronautic and Space Administration (NASA) and Department of Agriculture (USDA) have established Soil Moisture Experiment (SMEX) since 2002 for the global observations. SMEX provides useful data for the hydrological science including soil moisture and hydrometeorological variables. The purpose of this study is to investigate the relationship between remotely sensed soil moisture data from aircraft and satellite and ground based experiment. C-band of Polarimetric Scanning Radiometer (PSR) that observed the brightness temperature provides soil moisture data using a retrieval algorithm. It was compared with the In-situ data for 2-30 cm depth at four sites. The most significant depth is 2-10 cm from the correlation analysis. Most of the sites, two data are similar to the mean of data at 10 cm and the median at 7 cm and 10 cm at the 10% significant level using the Rank Sum test and t-test. In general, soil moisture data using the C-band of the PSR was established to fit the Normal, Log-normal and Gumbel distribution. Soil moisture data using the aircraft and satellites will be used in hydrological science as fundamental data. Especially, the C-band of PSR will be used to prove soil moisture at 7-10 cm depths.

• Journal of the Korean Society for Marine Environment & Energy
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• v.16 no.2
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• pp.102-114
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• 2013

The basin of Lake Shihwa is one of highly industrialized region of Korea and a current environmental issue of study area is the operation of tidal power plant (TPP) to improve water quality. The application of water quality index (WQI) which integrates five physiochemical parameters (transparency, DO, DIN, DIP and chlorophyll-a) of water quality in Lake Shihwa and outer sea during 2011~2012 were performed not only to evaluate the spatial and temporal distribution of the water quality but also to assess the effect of water quality improvement by the operation of tidal power plant. The higher WQI values were observed in monitored sites near the industrial complexes in Lake Shihwa and the outfall of wastewater treatment plants (WWTPs) in outer sea. This indicates that the quality of seawater is influenced by diffuse non-point sources from industrial, municipal and agricultural areas in Lake Shihwa and by point sources from the effluence of municipal and industrial wastewater throughout WWTPs in outer sea. Mean WQI value decreased from 53.0 in 2011 to 42.8 in 2012 of Lake Shihwa. Water quality has improved significantly after TPP operation because enhancement of seawater exchange between Lake Shihwa and outer sea leads to improve a hypoxic condition which is primarily a problem in Lake Shihwa. Mean WQI of outer sea showed similar values between 2011 and 2012. However, the results of hierarchical cluster analysis and the deterioration of water quality in summer season indicate that the operation of tidal power plant was not improved the water quality in the upper most area of Lake Shihwa. To successfully improve overall water quality of Lake Shihwa, it is urgently necessary to manage and reduce of non-point pollution sources of the basin of Lake Shihwa.