• 한국방재학회:학술대회논문집
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• 2010.02a
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• pp.103.1-103.1
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• 2010

기후변화가 가속됨에 따라 이에 따른 수문환경의 변화 예측이 중요한 문제로 부각되고 있다. 본 연구에서는 기후변화 시나리오에 따른 경안천 유역의 부유사량 변화를 모의하였다. SRES A1B 시나리오를 채택하고 이 시나리오에서의 강수량 변화를 10개 GCM을 이용해 모의하였다. 샘플링 오차를 줄이기 위해 BMA(Bayesian model averaging)기법을 사용해 10개 GCM의 결과를 앙상블했다. 부유사량의 모의를 위해 SWAT 모형이 이용되었다. 모의 결과, 경안천 유역의 경우 강수량과 부유사량 모두 상당히 증가하는 것으로 나타났다. 안정하도를 위한 구조물 설계시, 이러한 변화를 고려하는 것이 적절할 것으로 판단된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.847-850
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• 2010

최근 많은 수문학자들은 전지구적 기후변화로 인한 피해 예방과 저감을 위해 기후변화가 수문학적으로 어떤 영향을 미치고 있는지 알기 위해 많은 연구를 진행하고 있으며, 기후변화시나리오를 작성하고자 이산화탄소 배출농도를 가정하여 다양한 시나리오를 생성하고 있다. 본 연구에서는 효율적인 수자원 관리를 위해 저해상도의 GCM(General Circulation Models) 모형에서 생성되는 모의결과를 유역 규모의 단위로 스케일 상세화 기법(downscaling)을 적용 시켜 보고자 한다. 이를 위해 2007년 IPCC AR4와 함께 제시된 SRES A1B 시나리오를 채택하여 우리나라 기상청이 연구에 참여 제공하고 있는 EHCO-G 모델의 모의결과를 이용하여 소양강 유역에 적용하였다. 상세화 기법으로는 현재와 과거의 입력값들과 이에 대응된 출력값들을 알고 있는 경우에 미래의 새로운 입력값들에 대한 예측값들을 추출하는데 유용하며, 비선형적 비연속적인 특성이 강한 모델에 강점을 가지고 있는 인공신경망(Artificial Neural Network) 모델을 사용하고자 한다.

• Journal of Korea Water Resources Association
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• v.40 no.12
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• pp.921-930
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• 2007

The objective of this study is to present temporal-spatial variation of water resources on climate change impacts using the IPCC SRES A2 scenario and dynamical downscaling of the results (using the MM5 model with a resolution of 27km by 27km) at 139 sub-basins in Korea. The variation of runoff shows differences in the change of rate according to the each sub-basins and analysis durations. It has increased in the sub-basins located in Han river basin and east part of it, the other basins have decreased. In seasonal analysis, runoff in autumn and winter have increased, while in spring and summer have decreased. The results of frequency analyzing classified runoff(Low flow(Q$\leq$5mm), Normal flow(5$\geq$100mm)) show that low flow increase in most of the sub-basins for 2031-2060 and 2061-2090. In the case of high flow, it have higher frequency ranging from -100% to 500% than low flow. Regardless of the variation of mean runoff, maximum discharge appeared to be increase in process of time. The regression method is used to figure out the relationship between the rate of runoff change and mean temperature, mean precipitation under A2 scenario. The mean actual evapotranspirations from the regression equations increased by 3.4$\sim$5.3% for the change of $1^{\circ}C$. Also, for the precipitation change of $\pm$10%, runoff variety range is -18.2$\sim$+12.4% in Han River, -21.6$\sim$+14.6% in Nakdong River, -17.5$\sim$+11.5% in Gum River, -18.4$\sim$+10.6% in Sumjin River, -19.9$\sim$+12.7% Youngsan River basin.

• Korean journal of applied entomology
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• v.52 no.4
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• pp.427-430
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• 2013

Recently, climate change scenarios were substituted by the Special Report on Emission Scenarios (SRES) for Representative Concentration Pathway (RCP). Using the RCP scenario, the World Meteorological Organization (WMO) produced new climate change scenarios. Further, the National Institute of Meteorological Research (NIMR) of Korea produced new climate change scenarios for the Korean Peninsula. In this study, emergence time of small brown planthopper (SBPH), Laodelphax striatellus and the number of generations a year were estimated during climatic normal year (1981-2010) with previous studies and they were predicted during 2050s (2045-2054) and 2090s (2085-2094) by means of RCP8.5 climate change scenario. In comparison with $176.0{\pm}0.97$ Julian data in the climatic normal year, the emergence time of overwintering SBPH was predicted to be $13.2{\pm}0.18$ days ($162.8{\pm}0.91$ Julian date) earlier in 2050s and $32.1{\pm}0.61$ days ($143.9{\pm}1.08$ Julian date) earlier in 2090s. The SBPH was expected to produce an additional $2.0{\pm}0.02$ generations in 2050s and $5.2{\pm}0.06$ generations in 2090s.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.3
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• pp.160-174
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• 2014

The purpose of this paper is to develop a meso-scale grid-based continuous hydrological model and apply to assess the future watershed hydrology by climate change. The model divides the watershed into rectangular cells, and the cell profile is divided into three layered flow components: a surface layer, a subsurface unsaturated layer, and a saturated layer. Soil water balance is calculated for each grid cell of the watershed, and updated daily time step. Evapotranspiration(ET) is calculated by Penman-Monteith method and the surface and subsurface flow adopts lag coefficients for multiple days contribution and recession curve slope for stream discharge. The model was calibrated and verified using 9 years(2001-2009) dam inflow data of two watersheds(Chungju Dam and Soyanggang Dam) with 1km spatial resolution. The average Nash-Sutcliffe model efficiency was 0.57 and 0.71, and the average determination coefficient was 0.65 and 0.72 respectively. For the whole Han river basin, the model was applied to assess the future climate change impact on the river bsain. Five IPCC SRES A1B scenarios of CSIRO MK3, GFDL CM2_1, CONS ECHO-G, MRI CGCM2_3_2, UKMO HADGEMI) showed the results of 7.0%~27.1 increase of runoff and the increase of evapotranspiration with both integrated and distributed model outputs.

• 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.

• 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.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.9
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• pp.4335-4340
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• 2016

Background: Bone metastasis is a single condition but presents with various patterns and severities. Skeletal-related events (SREs) deteriorate overall performance status and reduce quality of life. However, guidelines for early detection and management are limited. This study includes a survey of the prevalence of bone metastasis in cases with common cancers in Thailand as well as a focus on survival patterns and SREs. Materials and Methods: A retrospective cohort analysis was conducted using a database of the Chiang Mai Cancer Registry and the Musculoskeletal Tumor Registry of the OLARN Center, Chiang Mai University. The prevalence of bone metastasis from each type of primary cancer was noted and time-to-event analysis was performed to estimate cancer survival rates after bone metastasis. Results: There were 29,447 cases of the ten most common cancers in Thailand, accounting for 82.2% of the entire cancer registry entries during the study period. Among those cases, there were 2,263 with bone metastases, accounting for 7.68% of entries. Bone metastasis from lung, liver, breast, cervix and prostate are common in the Thai population, accounting for 83.4% of all positive cases. The median survival time of all was 6 months. Of the bone metastases, 48.9% required therapeutic intervention, including treatment of spinal cord and nerve root compression, pathological fractures, and bone pain. Conclusions: The frequency of the top five types of bone metastasis in Thailand were different from the frequencies in other countries, but corresponded to the relative prevalence of the cancers in Thailand and osteophilic properties of each cancer. The results of this study support the establishment of country specific guidelines for primary cancer identification with skeletal lesions of unknown origin. In addition, further clinical studies of the top five bone metastases should be performed to develop guidelines for optimal patient management during palliative care.

• Journal of Korea Water Resources Association
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• v.40 no.3
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• pp.205-214
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• 2007

The objective of this study is to generate the regional scale runoff scenarios by using IPCC SRES A2 climate change scenario for analyzing the spatial variation of water resources in Korea. The PRMS model was adopted to simulate long-term stream discharge. To estimate the PRMS model parameters on each sub-basin, the streamflow data at 6 dam sites and Rosenbrock's scheme are used for model parameter calibration and those parameters are translated to ungauged catchments by regionalization method. The other 3 dam sites are selected for the verification of the adequateness of regionalized model parameters in ungagued catchments. The statistical results show that the simulated flows by using regionalized parameters well agree with observed ones. The generated runoff scenarios by climate change are compared with observed data on 4 dam sites for the reference period. The consequences show that the selection of climate station for generating climate scenario affects the reliability of climate scenario at sub-basin. The comparison results of the stream flows between the 30-year baseline period (1971-2000) and future 90-year (2001-2030, 2031-2060, 2061-2090) show that the long-term mean annual runoff in the Han River has increasing trend, while the Nakdong, the Gum, the Youngsan and the Sumjin Rivers have decreasing trend.

• Journal of Korea Water Resources Association
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• v.44 no.3
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• pp.169-177
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• 2011

The impacts of climate change on paddy irrigation water demands in Korea have been analyzed. High-resolution ($27{\times}27\;km$) climate data for the SRES A2 scenario produced by the Korean Meteorological Research Institute (METRI) and the observed baseline climatology dataset were used. The outputs from the ECHO-G GCM model were dynamically downscaled using the MM5 regional model by the METRI. The Geographic information system (GIS) was used to produce maps showing the spatial changes in irrigation water requirements for rice paddies. The results showed that the growing season mean temperature for future scenarios was projected to increase by $1.5^{\circ}C$ (2020s), $3.3^{\circ}C$ (2050s) and $5.3^{\circ}C$ (2080s) as compared with the baseline value (1971~2000). The growing season rainfall for future scenarios was projected to increase by 0.1% (2020s), 4.9% (2050s) and 19.3% (2080s). Assuming cropping area and farming practices remain unchanged, the total volumetric irrigation demand was projected to increase by 2.8% (2020s), 4.9% (2050s) and 4.5% (2080s). These projections are contrary to the previous study that used HadCM3 outputs and projected decreasing irrigation demand. The main reason for this discrepancy is the difference with the projected climate of the GCMs used. The temporal and spatial variations were large and should be considered in the irrigation water resource planning and management in the future.