• 한국수자원학회논문집
• /
• 제47권2호
• /
• pp.135-143
• /
• 2014

본 연구에서는 기후변화에 따른 충주댐 유입량을 모의하였으며 이때 발생되는 불확실성을 분석하였다. GCM별 불확실성을 고려하기 위해 IPCC AR4 A2 시나리오에 의한 4개의 GCM 강수량 결과를 추계학적 모형인 TFN 모형에 적용하였다. TFN 모형의 불확실성을 고려하기 위하여 정규분포를 따르는 100개의 잡음항을 생성하여 앙상블 유입량 시나리오를 생성하였고, 결과적으로 400개의 미래유입량 시나리오를 제시하였다. 분석결과 과거 30년과 비교하여 미래에는 다른 변화율을 보였으며, 모든 시나리오에서 전 기간에 걸쳐 연 유입량 증가 양상을 보였고 여름철의 유입량 증가, 봄철의 유입량 감소가 전망되었다.

• 한국농공학회논문집
• /
• 제61권6호
• /
• pp.81-92
• /
• 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.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2023년도 학술발표회
• /
• pp.174-174
• /
• 2023

The impact of global warming on the south Asian summer monsoon is of critical importance for the large population of this region. This study aims to investigate the future changes of the precipitation extremes during pre-monsoon and monsoon, across this region in a more organized regional structure. The study area is divided into six major divisions based on the Köppen-Geiger's climate structure and 10 sub-divisions considering the geographical locations. The future changes of extreme precipitation indices are analyzed for each zone separately using five indices from ETCCDI (Expert Team on Climate Change Detection and Indices); R10mm, Rx1day, Rx5day, R95pTOT and PRCPTOT. 10 global climate model (GCM) outputs from the latest CMIP6 under four combinations of SSP-RCP scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) are used. The GCMs are bias corrected using nonparametric quantile transformation based on the smoothing spline method. The future period is divided into near future (2031-2065) and far future (2066-2100) and then the changes are compared based on the historical period (1980-2014). The analysis is carried out separately for pre-monsoon (March, April, May) and monsoon (June, July, August, September). The methodology used to compare the changes is probability distribution functions (PDF). Kernel density estimation is used to plot the PDFs. For this study we did not use a multi-model ensemble output and the changes in each extreme precipitation index are analyzed GCM wise. From the results it can be observed that the performance of the GCMs vary depending on the sub-zone as well as on the precipitation index. Final conclusions are made by removing the poor performing GCMs and by analyzing the overall changes in the PDFs of the remaining GCMs.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2018년도 학술발표회
• /
• pp.151-151
• /
• 2018

The present study is aimed to quantifying the uncertainty in the general circulation model (GCM) selection and its impacts on hydrology studies in the basins. For this reason, 13 GCMs was selected among the 26 GCM models of the Fifth Assessment Report (AR5) scenarios. Then, the climate data and hydrologic data with two Representative Concentration Pathways (RCPs) of the best model (INMCM4) and worst model (HadGEM2-AO) were compared to understand the uncertainty associated with GCM models. In order to project the runoff, the Precipitation-Runoff Modelling System (PRMS) was driven to simulate daily river discharge by using daily precipitation, maximum and minimum temperature as inputs of this model. For simulating the discharge, the model has been calibrated and validated for daily data. Root mean square error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were applied as evaluation criteria. Then parameters of the model were applied for the periods 2011-2040, and 2070-2099 to project the future discharge the five large basins of South Korea. Then, uncertainty caused by projected temperature, precipitation and runoff changes were compared in seasonal and annual time scale for two future periods and RCPs compared to the reference period (1976-2005). The findings of this study indicated that more caution will be needed for selecting the GCMs and using the results of the climate change analysis.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2018년도 학술발표회
• /
• pp.162-162
• /
• 2018

지난 100년간(1996~2005년)의 전지구 평균 온도는 $0.74^{\circ}C$ 상승하였고 이러한 온도 상승은 온실효과의 영향으로 파악되고 있으며, 장래에는 이러한 상승 경향이 가속화되어 진행될 것으로 예측되고 있다(IPCC 2014; Baek et al 2011). 전지구 기온 상승은 극한 해수면 증가 및 호우 빈도와 평균 강수량 증가로 나타나며, 이로 인한 상당한 홍수 및 침수피해 가능성이 나타나고 있어 이에 대한 선제적 대응책 마련이 필요한 실정이다. 본 연구에서는 GCMs 모델별 연 최대 일 강수량을 추출하여 정상성 및 비정상성 빈도분석을 수행하고 빈도별 확률강수량을 산정하였다. 정상성 및 비정상성 분석을 위해 모델별 연최대치 일강우 자료를 산정하고, 모델별 경향성 검정을 수행하였다. 또한 각 모델별로 2021년부터 30년을 기준으로 1개년씩 자료이동을 통해 30세트를 구성하고, 각 세트별 80mm 이상의 강우의 평균 발생횟수 및 여름철(6월~9월) 평균 강우 총량의 산정을 통해 순위 도출에 적용하였다. 경향성 검정 및 순위도출 결과를 토대로 8개 GCMs 자료 중에서 4개의 GCMs를 선정하였고, 시나리오별 세트구성에 따른 연 최대 일 강우량의 평균 및 Gumbel 분포형의 위치 및 축척매개변수를 산정하였으며, 이를 토대로 서울지역을 대상으로 위치 및 축척 매개변수 추정에 따른 비정상성 빈도분석을 수행하였다.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2018년도 학술발표회
• /
• pp.35-35
• /
• 2018

본 연구의 목적은 한강유역을 대상으로 다중 GCMs (General Circulation Models)을 이용하여 장기유출량을 분석하는 데 있다. 기후변화 전망을 분석하기 위해 총 13개의 GCMs을 선정하여 사용하였다. SDQDM (Spatial Disaggregation-Quantile Delta Mapping) 방법을 이용하여 GCMs을 60개 종관기상관측장비 (Automated Synoptic Observing System, ASOS)에 대해 상세화하였다. GCMs은 총 6개의 변수(강수, 최고 기온, 최저기온, 풍속, 상대습도, 일사량)를 제공하였다. 장기유출량 분석은 투수지역과 불투수지역을 모두 고려할 수 있는 HSPF 모형을 선정하여 수행하였다. 장기유출량의 공간적인 범위는 한강유역의 16개 중권역을 기준으로 선정하였고, 시간적인 범위는 과거 기준 기간 (Reference period: 1976-2005), 미래 3개 기간 (Near future period: 2011-2040, Mid-century period: 2041-2070, Distance future period: 2071-2099)으로 30년 단위로 구분하여 선정하였다. 본 연구는 13개의 GCM을 사용하여 추정된 장기유출량의 연간 및 계절적 평균과 변동성을 분석하였다. 본 연구에서 HSPF 모형을 활용하여 분석한 결과는 복잡한 한강유역의 특성을 적절히 반영하여, 기후변화에 따른 수자원 계획 및 통합 유역 관리를 수립하기 위한 기초 자료로 활용될 수 있을 것이라 사료된다.

• 한국기후변화학회지
• /
• 제9권2호
• /
• pp.133-142
• /
• 2018

Climate change will affect not only the crop productivity but also the pattern of rice disease epidemics in Korea. Impact assessments for the climate change are conducted using various climate change scenarios from many global climate models (GCM), such as a scenario from a best GCM or scenarios from multiple GCMs, or a combination of both. Here, we evaluated the feasibility of using a climate change scenario from the best GCM for the impact assessment on the potential epidemics of a rice leaf blast disease in Korea, in comparison to a multi?model ensemble (MME) scenario from multiple GCMs. For this, this study involves analyses of disease simulation using an epidemiological model, EPIRICE?LB, which was validated for Korean rice paddy fields. We then assessed likely changes in disease epidemics using the best GCM selected for individual agro?climatic zones and MME scenarios constructed by running 11 GCMs. As a result, the simulated incidence of leaf blast epidemics gradually decreased over the future periods both from the best GCM and MME. The results from this study emphasized that the best GCM selection approach resulted in comparable performance to the MME approach for the climate change impact assessment on rice leaf blast epidemic in Korea.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2015년도 학술발표회
• /
• pp.226-226
• /
• 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.

• 국제학술발표논문집
• /
• The 6th International Conference on Construction Engineering and Project Management
• /
• pp.738-739
• /
• 2015

The main objective of this study, "Spatial Downscaling of Precipitation from GCMs for Assessing Climate Change over Han River and Imjin River Watersheds", is to carry out over Han River and Imjin River watersheds. To this end, a statistical regression method with MOS (Model Output Statistics) corrections at every downscaling step was developed and applied for downscaling the spatially-coarse Global Climate Model Projections (GCMPs) from CCSM3 and CSIRO with respect to precipitation into 0.1 degree (about 11 km) spatial grid over study regions. The spatially archived hydro-climate data sets such as Willmott, GsMap and APHRODITE datasets were used for MOS corrections by means of monthly climatology between observations and downscaled values. Precipitation values downscaled in this study were validated against ground observations and then future climate simulation results on precipitation were evaluated for the projections.

• 한국관개배수논문집
• /
• 제16권2호
• /
• pp.10-22
• /
• 2009