• 한국수자원학회논문집
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• 제48권6호
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• pp.439-449
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• 2015

본 연구에서는 SWAT 모형을 이용해 용담댐 유역을 대상으로 k-fold cross validation 기법을 사용하여 신뢰성 있는 RCP 기반의 미래 유출량을 산정하고 이를 과거 연구와 비교하여 SWAT 모형을 이용한 기후변화 유량 전망 결과의 차이의 요인에 대해 살펴보았다. 그 결과, 총유출량은 baseline 대비 2040s, 2080s 기간에 RCP8.5 시나리오에서는 17.7%, 26.1% 증가, RCP4.5 시나리오의 경우에는 21.9%, 44.6% 증가할 것으로 전망되었다. 이를 선행 연구와 비교해 본 결과 같은 모형을 사용했음에도 불구하고 유량 전망치의 경우 연구결과 간 최저 10.3%에서 최대 53.2% 차이를 보였다. SWAT 모형에는 물리적 기반 모형으로 27개의 많은 매개변수가 존재하고 사용자마다 모형을 구축하는 과정에서 차이가 많이 발생할 수 있다. 향후 이러한 차이요인을 저감하여 표준화된 유량시나리오 생성을 위한 노력이 필요하다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2017년도 학술발표회
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• pp.30-30
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• 2017

한반도의 기후변화는 전 세계 평균보다도 빠르게 진행되고 있다. 최근 빈발하고 있는 태풍 및 극한 강우, 폭설과 한파, 온난화 현상 등이 그 예이다. 특히 북한지역은 오랜 식량난과 에너지난으로 산림생태계가 훼손되어 홍수 및 이수와 같은 기후변화 관련 자연재해에 매우 취약하다. 이렇게 예상되는 대규모 자연재해를 대비하고 기후변화에 효율적으로 대처하기 위해서는 체계적이고 과학적인 기상 및 기후 예측 정보의 활용이 매우 중요하다. 하지만 북한지역은 우리가 수문자료를 구하기가 힘들고, 직접 측정을 할 수 없으므로 수문자료의 수집에 한계가 있기 때문에 기후변화관련 수문연구에 한계점이 있다. 따라서 본 논문에서는 WMO에서 제공하고 있는 북한의 27개 기상관측소의 강수량, 기온자료와 기상청의 RCP8.5기후변화시나리오를 제공 받아 각 관측소별 미래 잠재증발산량을 산정하였다. 또한 lumped conceptual model인 WASMOD 모형을 이용하여 북한의 대표유역(금야강, 대동강, 두만강, 압록강, 예성강, 임진강, 장연남대천)에 적용하여 부족한 수문시계열자료를 산정하였다. 이렇게 산정된 북한의 미래 수문순환요소의 시계열자료를 이용하여 통계분석, 변화점분석, 유황분석등 시계열 분석 등을 통해 RCP8.5기후변화시나리오 기반의 기후변화가 북한지역의 수문순환과정에 미치는 영향을 분석하고, 이를 통해 유역규모의 수자원에 미치는 영향을 전망하였다.

• 대기
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• 제23권4호
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• pp.425-441
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• 2013

This study investigates the projections of water cycle, budget and river discharge over land in the world at the end of twenty-first century simulated by atmosphere-ocean climate model of Hadley Centre (HadGEM2-AO) and total runoff integrating pathways (TRIP) based on the RCP scenario. Firstly, to validate the HadGEM2-AO hydrology, the surface water states were evaluated for the present period using precipitation, evaporation, runoff and river discharge. Although this model underestimates the annual precipitation about 0.4 mm $mon^{-1}$, evaporation 3.7 mm $mon^{-1}$, total runoff 1.6 mm $mon^{-1}$ and river discharge 8.6% than observation and reanalysis data, it has good water balance in terms of inflow and outflow at surface. In other words, it indicates the -0.3 mm $mon^{-1}$ of water storage (P-E-R) compared with ERA40 showing -2.4 mm $mon^{-1}$ for the present hydrological climate. At the end of the twenty-first century, annual mean precipitation may decrease in heavy rainfall region, such as northern part of South America, central Africa and eastern of North America, but for increase over the Tropical Western Pacific and East Asian region. Also it can generally increase in high latitudes inland of the Northern Hemisphere. Spatial patterns of annual evaporation and runoff are similar to that of precipitation. And river discharge tends to increase over all continents except for South America including Amazon Basin, due to increased runoff. Overall, HadGEM2-AO prospects that water budget for the future will globally have negative signal (-8.0~-0.3% of change rate) in all RCP scenarios indicating drier phase than the present climate over land.

• 한국화재소방학회논문지
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• 제30권1호
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• pp.57-62
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• 2016

본 연구에서는 한국환경정책평가연구원에서 가장 최근에 배포한 기후변화 취약성 평가 프로그램인 VESTAP을 활용하여 RCP 8.5 시나리오를 기반으로 2000년대에서 2040년대까지 제주시 및 서귀포시에 대한 산불 취약성을 평가하였다. 평가된 취약성 지수는 표준화 작업을 통해 제주시 및 서귀포시를 종합한 제주도 전체 읍면동의 산불 취약성 평가에 활용하였는데, 취약성이 높은 상위 10개 읍면동으로 제주시는 도서지역인 추자면과 우도면 그리고 2개의 동지역이, 서귀포시는 대정읍과 5개의 동지역이 산불에 대한 취약성이 상대적으로 높게 평가되었다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2016년도 학술발표회
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• pp.203-203
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• 2016

The linkage between climate change and water security, i.e., the response of water resource to the future climate change, have been of great concern to both scientific community and policy makers. In this study, the impact of future climate on water resources in Yellow River Basin in North of China has been investigated using the Coupled Land surface and Hydrology Model System (CLHMS) and IPCC AR5 projected future climate change in the basin. Firstly, the performances of 14 IPCC AR5 models in reproducing the observed precipitation and temperature in China, especially in North of China, have been evaluated, and it's suggested most climate models do show systematic bias compared with the observation, however, CNRM-CM5、HadCM5 and IPSL-CM5 model are generally the best models among those 14 models. Taking the daily projection results from the CNRM-CM5, along with the bias-correction technique, the response of water resources in Yellow river basin to the future climate change in different emission scenarios have been investigated. All the simulation results indicate a reduction in water resources. The current situation of water shortage since 1980s will keep continue, the water resources reduction varies between 28 and 23% for RCP 2.6 and 4.5 scenarios. RCP 8.5 scenario simulation shows a decrease of water resources in the early and mid 21th century, but after 2080, with the increase of rainfall, the extreme flood events tends to increase.

• 한국농림기상학회지
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• 제15권4호
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• pp.219-233
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• 2013

본 연구는 산림에서 나타나는 수종의 분포 패턴을 해석하고 예측하기 위한 목적으로 수행되었다. 국내에서 처음으로 시도된 전국 규모의 체계적 산림조사라 할 수 있는 NFI (National Forest Inventory)의 수종별 출현 정보와 출현지점별 풍부도를 기반으로 소나무의 현존분포도를 작성하였다. 생태적 지위 모형의 하나인 GARP (Genetic Algorithm for Ruleset Production)를 이용하여 소나무 현존분포와 연관성이 높은 환경요인변수들을 선정하였고, 선정된 변수들을 설명변수로 하는 소나무 잠재분포 모형을 작성한 후 기후변화 시나리오를 적용하여 미래의 잠재분포를 예측하였다. 기후, 지리 지형, 토양 지질, 토지이용 및 식생현황 등 27개 환경요인변수를 각각 설명변수로 하여 모형을 구동함으로써 소나무 현존분포와의 연관성을 평가한 결과 1월 평균기온이 최상위를 차지하였고 연평균기온, 8월평균기온, 연교차 등도 영향을 미치는 것으로 분석되었다. NFI 정보로부터 추출하여 소스개체군으로 선정된 조사지점들을 소나무의 최종출현정보로, 환경요인변수 간의 연관성 분석을 통해 최종적으로 선정된 변수 세트를 설명변수로 하여 모형을 구동함으로써 최적의 모형을 선정한 후 잠재분포도를 작성하였다. 현재 시점의 환경요인변수들에 의해 트레이닝 된 잠재분포 모형에서 기후관련변수들을 RCP 8.5 기후변화시나리오에서 산출한 변수들로 대체하여 2020년대, 2050년대, 2090년대의 소나무의 예측 잠재분포도를 작성하였다. 최종적으로 작성된 소나무 잠재분포모형의 평가 통계량인 AUC (Area Under Curve)는 0.67로 다소 미흡하였으나 향후 기후변화 환경 하에서 소나무림의 보전 및 관리를 위한 최소한의 실마리를 제공할 수 있을 것으로 판단되었다.

• 한국농공학회논문집
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• 제60권5호
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• pp.149-162
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• 2018

It is necessary to select the appropriate global climate model (GCM) to take into account the impacts of climate change on integrated water management. The objective of this study was to develop the selection technique of representative GCMs for uncertainty in climate change scenario. The selection technique which set priorities of GCMs consisted of two steps. First step was evaluating original GCMs by comparing with grid-based observational data for the past period. Second step was evaluating whether the statistical downscaled data reflect characteristics for the historical period. Spatial Disaggregation Quantile Delta Mapping (SDQDM), one of the statistical downscaling methods, was used for the downscaled data. The way of evaluating was using explanatory power, the stepwise ratio of the entire GCMs by Expert Team on Climate Change Detection and Indices (ETCCDI) basis. We used 26 GCMs based on CMIP5 data. The Representative Concentration Pathways (RCP) 4.5 and 8.5 scenarios were selected for this study. The period for evaluating reproducibility of historical period was 30 years from 1976 to 2005. Precipitation, maximum temperature, and minimum temperature were used as collected climate variables. As a result, we suggested representative 13 GCMs among 26 GCMs by using the selection technique developed in this research. Furthermore, this result can be utilized as a basic data for integrated water management.

• 한국물환경학회지
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• 제30권5호
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• pp.549-558
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• 2014

Occurrence frequency of flood and drought tends to increase in last a few decades, leading to social and economic damage since the abnormality of climate changes is one of the causes for hydrologic facilities by exceedance its designed tolerance. Soil and Water Assessment Tool (SWAT) model was used in the study to estimate temporal variance of groundwater recharge and baseflow. It was limited to consider recession curve coefficients in SWAT model calibration process, thus the recession curve coefficient was estimated by the Baseflow Filter Program (BFLOW) before SWAT model calibration. Precipitation data were estimated for 2014 to 2100 using three models which are GFDL-ESM2G, IPSL-CM5A-LR, and MIROC-ESM with Representative Concentration Pathways (RCP) scenario. SWAT model was calibrated for the Soyang watershed with NSE of 0.83, and $R^2$ of 0.89. The percentage to precipitation of groundwater recharge and baseflow were 27.6% and 17.1% respectively in 2009. Streamflow, groundwater recharge, and baseflow were estimated to be increased with the estimated precipitation data. GFDL-ESM2g model provided the most large precipitation data in the 2025s, and IPSL-CM5A-LR provided the most large precipitation data in the 2055s and 2085s. Overall, groundwater recharge and baseflow displayed similar trend to the estimated precipitation data.

• 한국농공학회논문집
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• 제57권1호
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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.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2016년도 학술발표회
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• pp.197-197
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• 2016

Forecasting future drought events in a region plays a major role in water management and risk assessment of drought occurrences. The creeping characteristics of drought make it possible to mitigate drought's effects with accurate forecasting models. Drought forecasts are inevitably plagued by uncertainties, making it necessary to derive forecasts in a probabilistic framework. In this study, a new probabilistic scheme is proposed to forecast droughts, in which a discrete-time finite state-space hidden Markov model (HMM) is used aggregated with the Representative Concentration Pathway 8.5 (RCP) precipitation projection (HMM-RCP). The 3-month standardized precipitation index (SPI) is employed to assess the drought severity over the selected five stations in South Kore. A reversible jump Markov chain Monte Carlo algorithm is used for inference on the model parameters which includes several hidden states and the state specific parameters. We perform an RCP precipitation projection transformed SPI (RCP-SPI) weight-corrected post-processing for the HMM-based drought forecasting to derive a probabilistic forecast that considers uncertainties. Results showed that the HMM-RCP forecast mean values, as measured by forecasting skill scores, are much more accurate than those from conventional models and a climatology reference model at various lead times over the study sites. In addition, the probabilistic forecast verification technique, which includes the ranked probability skill score and the relative operating characteristic, is performed on the proposed model to check the performance. It is found that the HMM-RCP provides a probabilistic forecast with satisfactory evaluation for different drought severity categories, even with a long lead time. The overall results indicate that the proposed HMM-RCP shows a powerful skill for probabilistic drought forecasting.