• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.6
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• pp.81-92
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• 2019

The objective of this study is to evaluate hydrologic impacts of climate change according to downscaling methods using the Soil and Water Assessment Tool (SWAT) model at watershed scale. We used the APCC Integrated Modeling Solution (AIMS) for assessing various General Circulation Models (GCMs) and downscaling methods. AIMS provides three downscaling methods: 1) BCSA (Bias-Correction & Stochastic Analogue), 2) Simple Quantile Mapping (SQM), 3) SDQDM (Spatial Disaggregation and Quantile Delta Mapping). To assess future hydrologic responses of climate change, we adopted three GCMs: CESM1-BGC for flood, MIROC-ESM for drought, and HadGEM2-AO for Korea Meteorological Administration (KMA) national standard scenario. Combined nine climate change scenarios were assessed by Expert Team on Climate Change Detection and Indices (ETCCDI). SWAT model was established at the Mankyung watershed and the applicability assessment was completed by performing calibration and validation from 2008 to 2017. Historical reproducibility results from BCSA, SQM, SDQDM of three GCMs show different patterns on annual precipitation, maximum temperature, and four selected ETCCDI. BCSA and SQM showed high historical reproducibility compared with the observed data, however SDQDM was underestimated, possibly due to the uncertainty of future climate data. Future hydrologic responses presented greater variability in SQM and relatively less variability in BCSA and SDQDM. This study implies that reasonable selection of GCMs and downscaling methods considering research objective is important and necessary to minimize uncertainty of climate change scenarios.

• Korean Journal of Hydrosciences
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• v.7
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• pp.87-106
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• 1996

A precipitation change scenario in Korea due to atmospheric $ doubling has been provided with a mixed method (Rebinson and Finkelstein, 1991) based on the simulated precipitation data by three GCM(CCC, UI, and GFDL GCM) experiments. Through the analysis the precipitation change by atmospheric $ doubing can be summarized as follows : Korea may have more precipitation as much as 25mm/yr during spring season and more less 50 mm/yr during summer and autumn, respectively. In the contrary Korea may have less rainfall as much as 13 mm/yr during winter. In terms of percentage with respect to current climatological value of precipitation Korea may have more rain as much as 10%, 13% and 24%, respectively, for spring, summer and autumn than current climate. However, Korea may have less precipitation during winter than current climatological average.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.226-226
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• 2015

The complex climate system regarding human actions is well represented through global climate models (GCMs). The output from GCMs provides useful information about the rate and magnitude of future climate change. Especially, the temperature variable is most reliable among other GCM outputs. However, hydrological variables (e.g. precipitation) from GCM outputs for future climate change contain too high uncertainty to use in practice. Therefore, we propose a method that simulates temperature variable with increasing in a certain level (e.g. 0.5oC or 1.0oC increase) as a global warming scenario from observed data. In addition, a hydrometeorological variable can be simulated employing block-wise sampling technique associated with the temperature simulation. The proposed method was tested for assessing the future change of the seasonal precipitation in South Korea under global warming scenario. The results illustrate that the proposed method is a good alternative to levy the variation of hydrological variables under global warming condition.

• Journal of Korea Water Resources Association
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• v.43 no.9
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• pp.789-799
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• 2010

The objective of this study is to suggest an approach for estimating probability rainfall using climate scenario data based GCM and to analyze changes of flood characteristics like probability rainfall, flood quantile and flood water level under climate change. The study area is Namhan river basin. Probability rainfalls which is taken 1440 minutes duration and 100-year frequency are estimated by using IPCC SRES A2 climate change scenario for each time period (S0: 1971~2000; S1: 2011~2040; S2: 2041~2070; S3: 2071~2100). Flood quantiles are estimated for 17 subbasins and flood water level is analyzed in the main channel from the downstream of Chungju dam to the upstream of Paldang dam. Probability rainfalls, peak flow from flood quantile and water depth from flood water level have increase rate in the range of 13.0~15.1 % based S0 (142.1 mm), 29.1~33.5% based S0 ($20,708\;m^3/s$), 12.6~13.6% in each S1, S2 and S3 period, respectively.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.1
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• pp.205-212
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• 2019

With the rapid spread of mobile phones, users are continuously interested in using the mobile phone in connection with personal activities. Also, increasingly users want to share (transmit and receive) and save data more easily and simply in the mobile environment. This paper suggests motion recognition of mobile phone to share personal information with any people located within a certain distance using location-based service with GCM service. The suggested application is based on Google Cloud Messaging which enables asynchronous communication with the mobile applications executed in Android operating system. The requirements of light-weight mechanism can be satisfied as it is possible to access sharing of personal information easily, simply and in real time through all mobile devices anywhere.

• Journal of Korea Water Resources Association
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• v.44 no.4
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• pp.275-283
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• 2011

A local or site-specific water temperature is downscaled from the nation-wide air temperature that represents simulation by General Circulation Model (GCM). Both two-step and one-step method are tested and compared in three sites: Masan Bay, Lake Sihwa, and Nakdong River Estuary. Two-step method uses a linear regression model as the first step that converts nation-wide air temperature into local air temperature, and the corresponding coefficient of determination is in the range of 0.98~0.99. The second step that converts air temperature into water temperature uses a nonlinear curve, so called S-curve, and the corresponding root mean squared error (RMSE) is 2.07 for rising limb in Masan Bay, 1.93 for falling limb in Masan Bay, 2.59 for Lake Sihwa, and 1.58 for Nakdong River Estuary. In a similar way, one-step method is performed to directly convert nation-wade air temperature into local water temperature, and the corresponding RMSE is 2.28 for rising limb in Masan Bay, 1.89 for falling limb in Masan Bay, 2.55 for Lake Sihwa, and 1.52 for Nakdong River Estuary. Consequently both methods show a similar level of performance, and one-step method is recommendable in that it is simple and practical in relative terms.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.3
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• pp.136-149
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• 2011

The aim of this study is to develop future climate scenario by downscaling the regional climate model (RCM) from global climate model (GCM) based on IPCC A1B scenario. To this end, the study first resampled the KMA-RCM(Korea meteorological administration-regional climate model) from spatial resolution of 27km to 1km. Second, observed climatic data of temperature and rainfall through 1971-2000 were processed to reflect the temperature lapse rate with respect to the altitude of each meteorological observation station. To optimize the downscaled results, Co-kriging was used to calculate temperature lapse-rate; and IDW was used to calculate rainfall lapse rate. Fourth, to verify results of the study we performed correlation analysis between future climate change projection data and observation data through the years 2001-2010. In this study the past climate data (1971-2000), future climate change scenarios(A1B), KMA-RCM(Korea meteorological administration-regional climate model) results and the 1km DEM were used. The research area is entire South Korea and the study period is from 1971 to 2100. Monthly mean temperatures and rainfall with spatial resolution of 1km * 1km were produced as a result of research. Annual average temperature and precipitation had increased by $1.39^{\circ}C$ and 271.23mm during 1971 to 2100. The development of downscaling method using GIS and verification with observed data could reduce the uncertainty of future climate change projection.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.6
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• pp.131-142
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• 2020

The objective of this study was to evaluate future inundation risk of farmland according to the application of coupled model intercomparison project phase 5 (CMIP5) and coupled model intercomparison project phase 6 (CMIP6). In this study, future weather data based on CMIP5 and CMIP6 general circulation model (GCM) were collected, and inundation was simulated using the river modeling system for small agricultural watershed (RMS) and GATE2018 in the Tanjung district of the Moohan stream watershed. Although the average probable rainfall of CMIP5 and CMIP6 did not show significant differences as a result of calculating the probability rainfall, the difference between the minimum and maximum values was significantly larger in CMIP6. The results of the flood discharge calculation and the inundation risk assessment showed similar to trends to those of probability rainfall calculations. The risk of inundation in the future period was found to increase in all sub-watersheds, and the risk of inundation has been analyzed to increase significantly, especially if CMIP6 data are used. Therefore, it is necessary to consider climate change effects by utilizing CMIP6-based future weather data when designing and reinforcing water structures in agricultural areas in the future. The results of this study are expected to be used as basic data for utilizing CMIP6-based future weather data.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.229-229
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• 2015

Downscaling is a fundamental procedure in the assessment of the future climate change impact at regional and watershed scales. Hence, it is important to investigate the spatial variability of the climate conditions that are constructed by various downscaling methods in order to assess whether each method can model the climate conditions at various spatial scales properly. This study introduces a fundamental research from Jang and Kavvas(2015) that precipitation variability from a popular statistical downscaling method (BCSD) and a dynamical downscaling method (MM5) that is based on the NCAR/NCEP reanalysis data for a historical period and on the CCSM3 GCM A1B emission scenario simulations for a projection period, is investigated by means of some spatial characteristics: a) the normalized standard deviation (NSD), and b) the precipitation change over Northern California region. From the results of this study it is found that the BCSD method has limitations in projecting future precipitation values since the BCSD-projected precipitation, being based on the interpolated change factors from GCM projected precipitation, does not consider the interactions between GCM outputs and local geomorphological characteristics such as orographic effects and land use/cover patterns. As such, it is not clear whether the popular BCSD method is suitable for the assessment of the impact of future climate change at regional, watershed and local scales as the future climate will evolve in time and space as a nonlinear system with land-atmosphere feedbacks. However, it is noted that in this study only the BCSD procedure for the statistical downscaling method has been investigated, and the results by other statistical downscaling methods might be different.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.367-367
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• 2021

최근 기후변화로 인해 극한 강우 사상의 빈도가 잦아짐에 따라 수공 구조물의 안전성이 저해되거나 인명 및 재산 피해가 발생할 가능성이 커지고 있다. 기후변화에 따른 기상현상의 변화 추세를 파악하고 대비하기 위해 CMIP (Coupled Model Intercomparison Project Phase)의 GCM(General Circulation Model) 기상자료 산출물이 활발하게 이용되고 있다. 기후변화 시나리오는 홍수기 방재 대책 수립 등의 연구에도 적용되고 있으나, GCM에서 산출된 기상자료의 시간 간격은 24시간 혹은 3시간 정도로 시간적 해상도가 낮아 홍수 모형의 입력자료로 사용되기 어려운 형태를 가지고 있다. 따라서 기후변화 시나리오를 홍수 모의 등의 분야에 접목하기 위해서는 GCM 자료의 시간적 해상도를 1시간 이하로 낮춤으로써 시나리오 산출물이 홍수모형과 적절하게 연결될 수 있도록 해야 한다. MRC (Multiplicative Random Cascade) 모형은 국내외에서 예보강우의 시간 분해 및 일강우 데이터 분해 연구에 활용된 바 있으며 관측 강우에 대하여 분해 성능이 준수함이 확인되었다. 이에 본 연구에서는 MRC 모형을 활용하여 미래 기후변화 시나리오 산출물에 적용함으로써 MRC 모형이 일단위 및 3시간 단위 기후변화 자료의 시간 분해에 대해 적절한 성능을 수행하는지 여부를 분석하고, 기후변화 자료의 최소 시간 간격별 강우 분해 결과를 비교·분석하고자 하였다. 본 연구의 결과는 향후 기후변화 시나리오 기반 기상자료 시간 분해에 대한 MRC 모형의 적용성을 평가하는 기초 자료로 활용될 수 있을 것으로 사료된다.