• Journal of Korea Water Resources Association
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• v.41 no.4
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• pp.379-394
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• 2008

Recently, extreme precipitation events beyond design capacity of hydraulic system have been occurred and this is the causes of failure of hydraulic structure for flood prevention and of severe flood damage. Therefore it is very important to understand temporal and spatial characteristics of extreme precipitation events as well as expected changes in extreme precipitation events and distributional characteristics during design period under future climate change. In this paper, climate change scenarios were used to assess the impacts of future climate change on extreme precipitation. Furthermore, analysis of future extreme precipitation characteristics and I-D-F analysis were carried out. This study used SRES B2 greenhouse gas scenario and YONU CGCM to simulate climatic conditions from 2031 to 2050 and statistical downscaling method was applied to establish weather data from each of observation sites operated by the Korean Meteorological Administration. Then quantile mapping of bias correction methods was carried out by comparing the simulated data with observations for bias correction. In addition Modified Bartlett Lewis Rectangular Pulse(MBLRP) model (Onof and Wheater, 1993; Onof 2000) and adjust method were applied to transform daily precipitation time series data into hourly time series data. Finally, rainfall intensity, duration, and frequency were calculated to draw I-D-F curve. Although there are 66 observation sites in Korea, we consider here the results from only Seoul, Daegu, Jeonju, and Gwangju sites in this paper. From the results we found that the rainfall intensity will be increased and the bigger intensity will be occurred for longer rainfall duration when we compare the climate conditions of 2030s with present conditions.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.453-453
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• 2011

21세기에 들어 홍수의 규모가 대형화 되었고, 그 발생빈도 및 강도도 증가하고 있다. 최근에는 지구온난화가 지속화되면서 전 세계적으로 높은 강도의 기상이변들이 속출하고 있고, 이러한 이상기후에 따른 태풍, 집중호우 등의 대규모 호우로 인해 댐 및 제방 등의 수공구조물 붕괴와 같은 비상상황이 초래 될 수 있다. 이와 같은 피해들을 통해 홍수 침수 범위의 예측, 분석을 통한 홍수위험 및 다양한 홍수위험지도 작성의 필요성이 대두되었고, 실제로 국가 차원의 홍수위 험지도가 제작되고 있다. 특히, 홍수 위험도 분석에 있어서 홍수에 노출된 지역의 인구수, 홍수에 노출된 지역에서의 경제적 활동의 형태, 홍수가 발생했을 때 2차적 피해를 불러올 수 있는 설비 등을 나타내는 홍수 취약도(Flood Vulnerability)에 대한 정량적 평가는 홍수위험지표 및 홍수위험강도 등에 의한 Flood Risk 개념을 기반으로 한 홍수위험지도 제작을 위해 매우 중요한 사항이라 할 수 있다. 그러나 현재까지의 홍수취약도 산정방법은 방법론적인 면에 있어 다소 단순하고, 직관에 의한 위험도의 분류가 이루어지고 있는 실정이다. 또한 취약도 지표의 산정과정이 전문가의 의견에 의존하는 경우가 많아 홍수 취약도 선정과정과 가중치 결정과정에 전문가들의 주관이 개입되는 등 홍수위험지표의 정량화에 어려움을 겪는 경우가 많다. 본 연구에서는 위와 같은 문제를 극복하기 위해 Flood Risk Mapping 기술의 적용에 있어 중요한 요소인 홍수취약도를 다기준의사결정법에 의해 산정하고, 국내 낙동강 유역에 대해 행정구역별로 세분화된 홍수위험지도 제작을 위한 취약도 지표를 산정하고자 하였다. 이를 위해 다기준의사결정법중의 하나 인 PROMEETEE와 ELECTRE를 이용하여 민감도, 노출도, 저감성 지표를 낙동강 유역에 대해 정량화하여 도시하였다. 본 연구결과를 통해 홍수위험지표 및 지수들의 결합에 대한새로운 방법론을 제시하고, 그에 따른 지도화 기법을 확립할 수 있을 것으로 기대된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.16-16
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• 2011

Statistics of extreme rainfall play a vital role in engineering practice from the perspective of mitigation and protection of infrastructure and human life from flooding. While flood frequency assessments, based on river flood flow data are preferred, the analysis of rainfall data is often more convenient due to the finer spatial nature of rainfall recording networks, often with longer records, and potentially more easily transferable from site to site. The rainfall frequency analysis as a design tool has developed over the years in New Zealand from Seelye's daily rainfall frequency maps in 1947 to Thompson's web based tool in 2010. This paper will present a history of the development of New Zealand rainfall frequency analysis methods, and the details of the latest method, so that comparisons may in future be made with the development of Korean methods. One of the main findings in the development of methods was new knowledge on the distribution of New Zealand rainfall extremes. The High Intensity Rainfall Design System (HIRDS.V3) method (Thompson, 2011) is based upon a regional rainfall frequency analysis with the following assumptions: $\bullet$ An "index flood" rainfall regional frequency method, using the median annual maximum rainfall as the indexing variable. $\bullet$ A regional dimensionless growth curve based on the Generalised Extreme Value (GEV), and using goodness of fit test for the GEV, Gumbel (EV1), and Generalised Logistic (GLO) distributions. $\bullet$ Mapping of median annual maximum rainfall and parameters of the regional growth curves, using thin-plate smoothing splines, a $2km\times2km$ grid, L moments statistics, 10 durations from 10 minutes to 72 hours, and a maximum Average Recurrence Interval of 100 years.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.331-336
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• 1999

The optical sensors of Electro-Optical Camera (EOC) and Ocean Scanning Multi-spectral Imager (OSMI) aboard the Korea Multi-Purpose SATellite (KOMPSAT) will be placed in a sun synchronous orbit in 1999. The EOC and OSMI sensors are expected to produce the land mapping imagery of Korean territory and the ocean color imagery of world oceans, respectively. Utilization of the EOC and OSMI data would encompass the various fields of science and technology such as land mapping, land use and development, flood monitoring, biological oceanography, fishery, and environmental monitoring. Readiness of data support for user community is thus essential to the success of the KOMPSAT program. As part of testing such readiness prior to the KOMPSAT launch, we have performed the preliminary acceptance test for the KOMPSAT data processing system using the simulated EOC and OSMI data sets. The purpose of this paper is to demonstrate the readiness of the KOMPSAT data processing system, and to help data users understand how the KOMPSAT EOC and OSMI data are processed and archived. Test results demonstrate that all requirements described in the data processing specification have been met, and that the image integrity is maintained for all products. It is however noted that since the product accuracy is limited by the simulated sensor data, any quantitative assessment of image products can not be made until actual KOMPSAT images will be acquired.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.1
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• pp.84-93
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• 2011

Levee line mapping is critical to the protection of environments in river zones, the prevention of river flood and the development of river zones. Use of the remote sensing data such as LiDAR and aerial orthoimage is efficient for river mapping due to their accessibility and higher accuracy in horizontal and vertical direction. Airborne laser scanning (LiDAR) has been used for river zone mapping due to its ability to penetrate shallow water and its high vertical accuracy. Use of image source is also efficient for extraction of features by analysis of its image source. Therefore, aerial orthoimage also have been used for river zone mapping tasks due to its image source and its higher accuracy in horizontal direction. Due to these advantages, in this paper, research on three dimensional levee line mapping is implemented using LiDAR and aerial orthoimage separately. Accuracy measurement is implemented for both extracted lines generated by each data using the ground truths and statistical comparison is implemented between two measurement results. Statistical results show that the generated 3D levee line using LiDAR data has higher accuracy than the generated 3D levee line using aerial orthoimage in horizontal direction and vertical direction.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.1
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• pp.43-52
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• 2016

Due to the characteristics of microwave signals, Radar satellite image has been used for flood detection without weather and time influence. The more methods of flood detection were developed, the more detection rate of flood area has been increased. Since flood causes a lot of damages, flooded area should be distinguished from non flooded area. Also, the detection of flood area should be accurate. Therefore, not only image resolution but also the filtering process is critical to minimize resolution degradation. Although a resolution of radar images become better as technology develops, there were a limited focused on a highly suitable filtering methods for flood detection. Thus, the purpose of this study is to find out the most appropriate filtering method for flood detection by comparing three filtering methods: Lee filter, Frost filter and NL-means filter. Therefore, to compare the filters to detect floods, each filters are applied to the radar image. Comparison was drawn among filtered images. Then, the flood map, results of filtered images are compared in that order. As a result, Frost and NL-means filter are more effective in removing the speckle noise compared to Lee filter. In case of Frost filter, resolution degradation occurred severly during removal of the noise. In case of NL-means filter, shadow effect which could be one of the main reasons that causes false detection were not eliminated comparing to other filters. Nevertheless, result of NL-means filter shows the best detection rate because the number of shadow pixels is relatively low in entire image. Kappa coefficient is scored 0.81 for NL-means filtered image and 0.55, 0.64 and 0.74 follows for non filtered image, Lee filtered image and Frost filtered image respectively. Also, in the process of NL-means filter, speckle noise could be removed without resolution degradation. Accordingly, flooded area could be distinguished effectively from other area in NL-means filtered image.

• Journal of the Korean Society of Hazard Mitigation
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• v.4 no.4 s.15
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• pp.55-61
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• 2004

Rapid developments in sensor technologies now allow the generation of multi-source topographical data. For many applications, however, the geospatial information provided by individual sensors is not complete, precise, and consistent. To solve these inherent problems, additional diverse sources of complementary data can be used and fused. In this paper, the experiment was done for generation of 3D orthoimage data using LIDAR data and digital camera image. And the results show that 3D orthoimage can be used for the flood monitoring.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.1
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• pp.47-57
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• 2015

Along with climate change, the occurrence and severity of natural disasters have been increased globally. In particular, the increase of localized heavy rainfalls have caused severe flood damage. Thus, it is needed to consider climate change into the estimation of design flood, a principal design factor. The main objective of this study was to estimate design floods for an agricultural reservoir watershed based on the RCP (Representative Concentration Pathways) scenarios. Gyeryong Reservoir located in the Geum River watershed was selected as the study area. Precipitation data of the past 30 years (1981~2010; 1995s) were collected from the Daejeon meteorological station. Future precipitation data based on RCP2.6, 4.5, 6.0, 8.5 scenarios were also obtained and corrected their bias using the quantile mapping method. Probability rainfalls of 200-year frequency and PMPs were calculated for three different future spans, i.e. 2011~2040; 2025s, 2041~2070; 2055s, 2071~2100; 2085s. Design floods for different probability rainfalls were calculated using HEC-HMS. As the result, future probability rainfalls increased by 9.5 %, 7.8 % and 22.0 %, also design floods increased by 20.7 %, 5.0 % and 26.9 %, respectively, as compared to the past 1995s and tend to increase over those of 1995s. RCP4.5 scenario, especially, resulted in the greatest increase in design floods, 37.3 %, 36.5 % and 47.1 %, respectively, as compared to the past 1995s. The study findings are expected to be used as a basis to reduce damage caused by climate change and to establish adaptation policies in the future.

• Journal of Korea Water Resources Association
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• v.46 no.8
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• pp.833-842
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• 2013

The quantile mapping is utilized to reproduce reliable GCM(Global Climate Model) data by correct systematic biases included in the original data set. This scheme, in general, projects the Cumulative Distribution Function (CDF) of the underlying data set into the target CDF assuming that parameters of target distribution function is stationary. Therefore, the application of stationary quantile mapping for nonstationary long-term time series data of future precipitation scenario computed by GCM can show biased projection. In this research the Nonstationary Quantile Mapping (NSQM) scheme was suggested for bias correction of nonstationary long-term time series data. The proposed scheme uses the statistical parameters with nonstationary long-term trends. The Gamma distribution was assumed for the object and target probability distribution. As the climate change scenario, the 20C3M(baseline scenario) and SRES A2 scenario (projection scenario) of CGCM3.1/T63 model from CCCma (Canadian Centre for Climate modeling and analysis) were utilized. The precipitation data were collected from 10 rain gauge stations in the Han-river basin. In order to consider seasonal characteristics, the study was performed separately for the flood (June~October) and nonflood (November~May) seasons. The periods for baseline and projection scenario were set as 1973~2000 and 2011~2100, respectively. This study evaluated the performance of NSQM by experimenting various ways of setting parameters of target distribution. The projection scenarios were shown for 3 different periods of FF scenario (Foreseeable Future Scenario, 2011~2040 yr), MF scenario (Mid-term Future Scenario, 2041~2070 yr), LF scenario (Long-term Future Scenario, 2071~2100 yr). The trend test for the annual precipitation projection using NSQM shows 330.1 mm (25.2%), 564.5 mm (43.1%), and 634.3 mm (48.5%) increase for FF, MF, and LF scenarios, respectively. The application of stationary scheme shows overestimated projection for FF scenario and underestimated projection for LF scenario. This problem could be improved by applying nonstationary quantile mapping.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.15 no.2
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• pp.237-244
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• 1997

The goal of this research is to evaluate methodology that uses satellite data for the analysis of flood and drought damaged area. Land cover classification were performed using satellite data that were acquired at disaster periods and comparatively normal times. Damaged area was extracted by use of overlay analysis in land cover change and compared with the field survey results. The results show analysis of flood damaged area could be carried out with single scene acquired at adequate day, and are corresponded with field survey data very well. And also, some areas that had been missed in field survey were found. The suggested method proved to be more accurate and effective way for mapping inundated areas of floodplains than field survey that would be held a few month later. The results on the analysis of drought damaged area show that drained water could be detected just only in small area, and crop damaged area could not be verified in objective validity. Drought analysis by remote sensing was proved not to be adequate for practical use in this study.