• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.3
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• pp.58-69
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• 2007

The vegetation area that occupies 76% in land surface of the earth can give a considerable impact on water resources, environment and ecological system by future climate change. The purpose of this study is to predict future vegetation cover information from NDVI (Normalized Difference Vegetation Index) extracted from satellite images. Current vegetation information was prepared from monthly NDVI (March to November) extracted from NOAA AVHRR (1994 - 2004) and Terra MODIS (2000 - 2004) satellite images. The NDVI values of MODIS for 5 years were 20% higher than those of NOAA. The interrelation between NDVIs and monthly averaged climate factors (daily mean, maximum and minimum temperature, rainfall, sunshine hour, wind velocity, and relative humidity) for 5 river basins of South Korea showed that the monthly NDVIs had high relationship with monthly averaged temperature. By linear regression, the future NDVIs were estimated using the future mean temperature of CCCma CGCM2 A2 and B2 climate change scenario. The future vegetation information by NOAA NDVI showed little difference in peak value of NDVI, but the peak time was shifted from July to August and maintained high NDVIs to October while the present NDVI decrease from September. The future MODIS NDVIs showed about 5% increase comparing with the present NDVIs from July to August.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.3
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• pp.48-62
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• 2018

In this study, landslide of debris flow occurred at 51 sites around Daeryounsan located in between Chuncheon-si and Hongcheon-gun during July in 2013 were investigated in field and behavior characteristics of debris flow were analyzed on the basis of records of rainfall and site investigation. According to debris flow types of channelized and hill slope, location and slope angle of initiation and deposit zone, and width and depth of erosion were investigated along entire runout of debris flow. DEM(Digital Elevation Model) of Daeryounsan was constructed with digital map of 1:5,000 scale. Land slide hazard was estimated using SINMAP(Stability INdex MAPping) and the predicted results were compared with field sites where debris flow occurred. As analyzed results, for hill slope type of debris flow, predicted sites were quite comparable to actual sites. On the other hand, for channelized type of debris flow, debris flow occurrence sites were predicted by using stability index associated with topographic wetness index. As analyzed results of 4 different conditions with the parameter T/R, Hydraulic transmissivity/Effective recharge rate, proposed by NRCS (Natual Resources Conservation Service), predicted results showed more or less different actual sites and the degree of hazard tended to increase with decrease of T/R value.

• Journal of Korean Tunnelling and Underground Space Association
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• v.18 no.1
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• pp.95-107
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• 2016

Ground water is one of important parameters in the designs of underpass structures because urban areas are characterized by soil ground which is relatively permeable than rock ground and a high level of ground water due to low elevation. Therefore, it is important properly to predict variations of the ground water when they can affect underpass structures. In this study, a series of numerical analyses are performed to predict the variations of ground water levels considering the degree of surface imperviousness and LID(Low Impact Development) application. In turn the stability of underground structure is assessed using predicted ground water level. The results show that an increase in the impervious surface area decreases the ground water level. The application of permeable pavement as a LID facility increases the ground water level, improving the infiltration capacity of rainfall into the ground. Seasonal variations of the ground water level are also verified in numerical simulation. The results of this study suggest that reasonable designs of underpass structures can be obtained with the suitable prediction and application of the ground water level considering the surface characteristics.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.3
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• pp.395-406
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• 2016

Population and development are concentrated by urbanization. Consequently, the usage of underground area and the riverside area have been increased. By increasing impermeable layer, the urban basin drainage is depending on level of sewer. Flood damage is occurred by shortage of sewer capacity and poor interior drainage at river stage. Many of researches about flood stress the unavailability of connection at the river stage with the internal inundation organically. In this study, flood calculated considering rainfall and combined inland-river. Also, using urban runoff model analyze the overflow of sewer. By using results of SWMM model, using flood inundation analysis model analyzed internal drainage efficiency of drainage system. Applying SWMM model, which results to flood inundation analysis model, analyzes internal drainage efficiency of drainage system under localized heavy rain in a basin of the city. The results of SWMM model show the smoothness of internal drainage can be impossible to achieve because of the influence of the river level and sewer overflow appearing. The main manholes were selected as the manhole of a lot of overflow volume. Overflow reduction scenarios were selected for expansion of sewer conduit and instruction retention pond. Overflow volume reduces to 45% and 33~64% by retention pond instruction and sewer conduit expansion. In addition, the results of simulating of flood inundation analysis model show the flood occurrence by road runoff moving along the road slope. Flooded area reduces to 19.6%, 60.5% in sewer conduit expansion scenarios.

• Journal of Korea Water Resources Association
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• v.51 no.6
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• pp.503-514
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• 2018

In recent, the hydrological regime of the Mekong river is changing drastically due to climate change and haphazard watershed development including dam construction. Information of hydrologic feature like streamflow of the Mekong river are required for water disaster prevention and sustainable water resources development in the river sharing countries. In this study, runoff simulations at the Kratie station of the lower Mekong river are performed using SWAT (Soil and Water Assessment Tool), a physics-based hydrologic model, and LSTM (Long Short-Term Memory), a data-driven deep learning algorithm. The SWAT model was set up based on globally-available database (topography: HydroSHED, landuse: GLCF-MODIS, soil: FAO-Soil map, rainfall: APHRODITE, etc) and then simulated daily discharge from 2003 to 2007. The LSTM was built using deep learning open-source library TensorFlow and the deep-layer neural networks of the LSTM were trained based merely on daily water level data of 10 upper stations of the Kratie during two periods: 2000~2002 and 2008~2014. Then, LSTM simulated daily discharge for 2003~2007 as in SWAT model. The simulation results show that Nash-Sutcliffe Efficiency (NSE) of each model were calculated at 0.9(SWAT) and 0.99(LSTM), respectively. In order to simply simulate hydrological time series of ungauged large watersheds, data-driven model like the LSTM method is more applicable than the physics-based hydrological model having complexity due to various database pressure because it is able to memorize the preceding time series sequences and reflect them to prediction.

• Journal of Korea Water Resources Association
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• v.51 no.11
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• pp.1021-1029
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• 2018

A primary objective of this study is to develop a drought forecasting technique based on groundwater which can be exploit for water supply under drought stress. For this purpose, we explored the lagged relationships between regionalized SGI (standardized groundwater level index) and SPI (standardized precipitation index) in view of the drought propagation. A regional prediction model was constructed using a NARX (nonlinear autoregressive exogenous) artificial neural network model which can effectively capture nonlinear relationships with the lagged independent variable. During the training phase, model performance in terms of correlation coefficient was found to be satisfactory with the correlation coefficient over 0.7. Moreover, the model performance was described by root mean squared error (RMSE). It can be concluded that the proposed approach is able to provide a reliable SGI forecasts along with rainfall forecasts provided by the Korea Meteorological Administration.

• Journal of Korea Water Resources Association
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• v.49 no.1
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• pp.1-9
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• 2016

A correlation analysis between raw water turbidity at two wide-area water treatment plants and hydrological data was conducted for efficient water supply, design and management of water treatment plant. Both correlation analysis and principal component analysis were conducted using hydrological time series data such as inflow discharge, outflow discharge, and rainfall at dam basin of intake station of wide-area water treatment plants. And, forecasting of change in turbidity was conducted using regression equation for turbidity prediction. The raw water turbidity of two water treatment plants was strongly related to time series of discharge. The raw water turbidity of Chungju water treatment plant is strongly related to outflow discharge at Chungju dam (0.708). Whereas, the raw water turbidity of Wabu water treatment plant is strongly related to inflow discharge at Paldang dam (0.805). Similar trends between turbidity forecasting result using regression equation and calculation result using estimation equation on Korea water supply facilities standard were obtained. The result of this study can provide basic data for construction and management of water treatment plant.

• Atmosphere
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• v.20 no.3
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• pp.239-246
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• 2010

In this study, the climatological characteristics of the landfall typhoons on North Korea are surveyed to estimate the frequency, the intensity, the track, and their damage. The data for the period of 1951-2008 are used from both RSMC (Regional Specialized Meteorological Center) Tokyo Typhoon Center and NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research), EM-DAT (Emergency Events Database). There are the ten highest frequencies from 1961 to 1965 and is one frequency for the period of both 1966-1979 and 1976-1980 respectively. Even if a clear trend on the frequency of typhoon is not defined, it is noticeable the intensity has been weak since the frequency of TS (Tropical Storm) decreased. In order to figure out both the characteristic of intensity and the relation between the typhoon track and the expansion of North Pacific High (NPH), Typhoon's tracks are classified into three types as follows: (I) landing on the west coast of North Korea through the mainland of China, (II) landing on the west coast of North Korea, (III) landing on a central/eastern part of the Korean peninsula through South Korea. More often than not, the characteristic of Type (I) is the case of a landfall after it becomes extratropical cyclone. Type(II) and Type(III) show a landfall as TS grade, by comparision. On the relation between the typhoon's track and the expansion of NPH analyzed, Type (I) shows the westward expansion while both Type (II) and Type (III) show the northward expansion and development of NPH. This means the intensity of a typhoon landfall on North Korea is variable depending on the development of NPH. Finally, only two cases are found among total five cases in EM-DAT, reportedly that North Korea was damaged. And therefore, the damage by the wind of Prapiroon (the $12^{th}$ typhoon, 2000) and heavy rainfall with Rusa (the $15^{th}$ typhoon, 2002) landing on North Korea was analyzed. Moreover, it is estimated both Prapiroon and Rusa have done badly damaged to North Korea as the economical losses of as much as six billion and five hundred-thousand US dollar, respectively.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.6
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• pp.533-538
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• 2013

The damage caused by Recent frequently occurring locality torrential rains is increasing rapidly. In case of densely populated metropolitan area, casualties and property damage is a serious due to landslides and debris flows and floods. Therefore, the importance of predictions about the torrential is increasing. Precipitation characteristic of the bad weather in Korea is divided into typhoons and torrential rains. This seems to vary depending on the duration and area. Rainfall is difficult to predict because regional precipitation is large volatility and nonlinear. In this paper, Very short-term precipitation forecasting pattern model is implemented using KLAPS data used by Korea Meteorological Administration. we designed very short term precipitation forecasting pattern model using GA-based RBFNNs. the structural and parametric values such as the number of Inputs, polynomial type,number of fcm cluster, and fuzzification coefficient are optimized by GA optimization algorithm.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.291-295
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• 2007

강수진단모형을 이용하여 저수지 이수운영을 위한 실시간 유량예측기법을 개발하였다. 강수진단모형은 현재 기상청 현업에서 수행중인 강우수치예보를 기반으로 상세 지역의 지형 효과에 의한 강수를 예측하는 정량강수예측모형(QPM; Quantitative Precipitation Model)으로서 부경대학교 환경대기과학과에서 개발된 모형이다. QPM은 중규모 예측 모형으로부터 계산된 수평 바람, 고도, 기온, 강우 강도, 그리고 상대습도 등의 예측 자료를 이용하고, 소규모 상세지형 효과를 고려함으로써 중규모 예측 모형에서 생산된 강수량 예측 값을 상세 지역의 지형을 고려한 강수량 예측 값으로 재구성하여 결과적으로 3km 간격의 상세지역 강우산출과 지형에 따른 강수량의 분포 파악이 용이할 뿐만 아니라 계산 효율성을 개선된 모형이다. QPM 검증을 위하여 기상학적 평가와 수문학적 평가를 수행하였다. 호우 사례별 일강수량의 시공간 분포로 부터, QPM을 활용한 시스템에 의한 예측결과가 원시자료 RDAPS 보다 고해상도의 예측 및 지형효과의 반영도가 높았으며, AWS의 관측자료와 비교하여 보다 높은 예측성을 보여 주었다. 대상기간인 2006년 1월 1일부터 6월 20일까지 관측강우는 총 391.5mm 였으며 RQPM은 실적강우에 비하여 119.5mm 정도 과소산정하고 있으나 분위사상과정을 거치게 되면 351.7mm로서 실적강우에 불과 10.2% 못미치고 있다. 이는 고무적인 결과로 볼 수 있으며 현업에서의 활용성이 기대되는 수준이라 볼 수 있다. 강우-유출모의를 위한 QPM신뢰도를 높이기 위하여 분위사상법(Quantile Mapping)을 이용하여 QPM모의에 존재할 수 있는 계통오차에 대한 추가적인 보정을 수행하였다. 수문학적 평가를 위하여는 장기연속유출모형인 SSARR모형을 기반으로 개발된 RRFS(Rainfall-Runoff Forecast System)을 이용하여 2006년 1월${\sim}$9월까지의 용담댐 유입량에 대하여 모의예측결과와 관측유입량 비교를 통한 검증을 수행하였다. 위 기간중 예측유입량의 RMSE(Root Mean Squared Error), COE(Sutcliffe Coefficient of Efficiency), MAE(Mean Absolute Error), $R^2$값은 각각 7.50, 0.68, 2.59, 0.69 값을 보이고 있다. 본 연구에서는 QPM에 의한 예측성의 향상 및 구축된 시스템에 의한 일강수량의 장기예측 가능성을 확인하였고, 향후 시스템을 현업에 활용하기 위해서 생산된 예측자료의 보다 장기적인 검증을 통한 시스템의 안정화가 필요할 것으로 사료된다.