• 한국습지학회지
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• 제24권1호
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• pp.25-37
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• 2022

기후변화는 예측할 수 없는 변동성이 매우 커지고 있다. 이로인해 생태계, 인류의 생활, 수문학적 순환 등 다양한 시스템에 변화를 가져오고 있다. 특히 최근 예측할 수 없는 기후변화로 인해 극한가뭄 및 집중호우가 자주 발생하며 그로 인해 1차적 재해가 아닌 침수, 퇴사로 인한 수질오염을 유발하는 복합적인 수자원재해가 발생하고 있다. 유역모델로 SWAT를 이용하여 장래 유출량 및 오염부하량을 분석하고 기후시나리오는 기상청 표준 시나리오(HadGEM3-RA)의 RCP4.5 기후시나리오를 정상성 분위사상법을 적용하여 분석하였다. 기후시나리오와 유역모델의 연계모의로 유출량 및 오염부하량 분석을 수행하였고 연계모형의 적용 및 검증과 기후변화에 따른 미래 수질 변화 분석 결과를 최종적으로 제시하였다. 본 연구에서는 인공신경망을 이용하여 기후변화 시나리오를 모의하여 저수지 수질모형인 W2모델을 통한 댐 저수지의 변화와 인공신경망에서의 수온과 탁도의 결과를 비교하였다. 본 연구의 결과로 신경망모형의 장점인 비선형성 및 간편성을 기후변화를 적용한 합천댐 저수지에서의 수온과 탁도 예측에 적용 가능성을 제시하고자 한다.

• 대한토목학회논문집
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• 제42권3호
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• pp.333-342
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• 2022

기후변화의 영향으로 집중호우가 증가하고 있으며, 이로 인한 침수피해가 매년 발생하고 있다. 본 연구는 저영향개발(LID) 시설의 우수 유출저감 효과를 분석하기 위하여, 용두빗물펌프장 유역을 대상으로, 미국 환경보호청(EPA)의 우수유출관리모형(SWMM)을 이용하여, 과거와 미래의 대표 강우사상에 대한 유출분석을 수행하였다. 그 결과 과거 강우사상과 비교하여 미래 대표 강우사상에 대한 침투량은 3.17 % 증가하였지만, 지표면 유출량 및 첨두유량은 각각 32.50 % 및 128.77 % 증가하였다. 이러한 지표면 유출량과 첨두유량의 증가를 감소시키기 위하여 투수성 포장, 옥상녹화 및 빗물정원을 선정하였다. 세 가지 LID 시설의 매개변수와 설치 면적 비율을 조정하여 LID 시설의 적용성을 평가하였다. 그 결과 첨두유량과 지표 유출량을 감소시키고 침투량과 저류량를 증가시키는 투수성 포장, 옥상 정원 그리고 빗물 정원의 적정 매개변수를 찾을 수 있었다. 또한 투수성 포장, 옥상녹화, 빗물정원의 적용 비율이 2:1:3일 때, 첨두유량 26.85 %, 침투량 12.10 %, 지표면 유출량 15.11 %, 저류량 509.47 %의 저감효과가 나타났다. 재현기간별 우수 유출저감 효과를 분석한 결과, 재현기간이 증가할수록 첨두유량과 지표면 유출량의 비중은 늘어나고 침투량과 저류량의 비중은 줄어드는 것으로 나타났다.

• 한국수자원학회논문집
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• 제56권6호
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• pp.393-402
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• 2023

최근 이상기후 현상으로 발생빈도 및 규모가 증가한 가뭄은 다양한 분야에서 극심한 문제를 유발하여 가뭄에 의한 물부족 발생 시 수생태 건강성 확보를 위한 합리적인 대응 방안을 마련하기 위해 가뭄 감시, 전망 및 대응기술 개발이 필요하다. 본 연구에서는 유역모델 HSPF와 수질모델 QUAL-MEV를 연계하여 가뭄 기간 물 부족 상태가 수문 순환을 통해 변동되는 수질을 예측하였다. SPI, RCP 4.5 시나리오를 검토하고 HSPF 및 QUAL-MEV를 활용하여 유량변동에 따른 수질변화를 모의하여 유량변동에 따른 수질 변화를 분석하였다. 갈수기 유량과 수질의 관계는 높으나 강수량과 수질의 관계는 미비한 것으로 나타났다. 유량 및 SPI6는 상이한 경향이 나타나 가뭄의 영향으로 변화되는 수질 예측시 중장기 가뭄지수와 관계는 미비한 것으로 나타났다. 가뭄에 의한 수질 영향을 평가하기 위해 단기간의 가뭄지수 활용 및 유량 변동에 따른 평가방안 마련이 필요한 것으로 사료된다.

• 한국농공학회논문집
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• 제57권3호
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• pp.65-76
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• 2015

Estimating water requirements for upland crops are characterized by standing soil moisture condition during the entire crop growth period. However, scarce rainfall and intermittent dry spells often cause soil moisture depletion resulting in unsaturated condition in the fields. Changes in rainfall patterns due to climate change have significant influence on the increasing the occurrence of extreme soil moisture depletion. Therefore, it is necessary to evaluate agricultural drought for upland crop water planning and management in the context of climate change. The objective of this study is to predict the impacts of climate change on agricultural drought for upland crops and changes in the temporal trends of drought characteristics. First, the changes in crop evapotranspiration and soil moisture in the six upland crops, such as Soybeans, Maize, Potatoes, Red Peppers, Chinese Cabbage (spring and fall) were analyzed by applying the soil moisture model from commonly available crop and soil characteristics and climate data, and were analyzed for the past 30 years (1981-2010), and Representative Concentration Pathways (RCP) climate change scenarios (2011-2100). Second, the changes on the temporal trends of drought characteristics were performed using run theory, which was used to compare drought duration, severity, and magnitude to allow for quantitative evaluations under past and future climate conditions.

• Journal of Ecology and Environment
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• 제41권11호
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• pp.310-317
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• 2017

Background: Many studies about climate-related range shift of plants have focused on understanding the relationship between climatic factors and plant distributions. However, consideration of adaptation factors, such as dispersal and plant physiological processes, is necessary for a more accurate prediction. This study predicted the future distribution of marlberry (Ardisia japonica), a warm-adapted evergreen broadleaved shrub, under climate change in relation to the dispersal ability that is determined by elapsed time for the first seed production. Results: We introduced climate change data under four representative concentration pathway (RCP 2.6, 4.5, 6.0, and 8.5) scenarios from five different global circulation models (GCMs) to simulate the future distributions (2041~2060) of marlberry. Using these 20 different climate data, ensemble forecasts were produced by averaging the future distributions of marlberry in order to minimize the model uncertainties. Then, a dispersal-limited function was applied to the ensemble forecast in order to exam the impact of dispersal capacity on future marlberry distributions. In the dispersal-limited function, elapsed time for the first seed production and possible dispersal distances define the dispersal capacity. The results showed that the current suitable habitats of marlberry expanded toward central coast and southern inland area from the current southern and mid-eastern coast area in Korea. However, given the dispersal-limited function, this experiment showed lower expansions to the central coast area and southern inland area. Conclusions: This study well explains the importance of dispersal capacity in the prediction of future marlberry distribution and can be used as basic information in understanding the climate change effects on the future distributions of Ardisia japonica.

• Asian Journal of Atmospheric Environment
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• 제11권4호
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• pp.330-343
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• 2017

Climate change is an important issue, with many researches examining not only future climatic conditions, but also the interaction of climate and air quality. In this study, a new version of the emissions processing software tool - Python-based PRocessing Operator for Climate and Emission Scenarios (PROCES) - was developed to support climate and atmospheric chemistry modeling studies. PROCES was designed to cover global and regional scale modeling domains, which correspond to GEOS-Chem and CMAQ/CAMx models, respectively. This tool comprises of one main system and two units of external software. One of the external software units for this processing system was developed using the GIS commercial program, which was used to create spatial allocation profiles as an auxiliary database. The SMOKE-Asia emissions modeling system was linked to the main system as an external software, to create model-ready emissions for regional scale air quality modeling. The main system was coded in Python version 2.7, which includes several functions allowing general emissions processing steps, such as emissions interpolation, spatial allocation and chemical speciation, to create model-ready emissions and auxiliary inputs of SMOKE-Asia, as well as user-friendly functions related to emissions analysis, such as verification and visualization. Due to its flexible software architecture, PROCES can be applied to any pregridded emission data, as well as regional inventories. The application results of our new tool for global and regional (East Asia) scale modeling domain under RCP scenario for the years 1995-2006, 2015-2025, and 2040-2055 was quantitatively in good agreement with the reference data of RCPs.

• 한국환경복원기술학회지
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• 제18권1호
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• pp.103-113
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• 2015

Korean pines(Pinus koraiensis) are one of the major plantation species in the Republic of Korea and their natural habitats range from Japan and China to Siberia. The seed of Korean pines, pine nuts, are well know for good food reserves. Due to the global changes which drive the Korean peninsula into the semi-tropical climate, current plantations and natural habitats of Korean pines are faced with the change in the environmental conditions to some extent. To anticipate suitable sites for Korean pines in the future, the location of Korean pines were extracted from the 'Map of suitable trees on a site' that provides the map of suitable trees on a site considering tree species for timber and special uses, and then MaxEnt modelling was used for generating a prediction map on the basis of statistical analysis. As a result, the order of predicted suitable sites were Kangwon-do, Kyungsangbuk-do and Chungcheongbuk-do provinces and sites with high elevation within those provinces were considered most suitable in common. The prediction map of suitable sites for Korean pines presented that suitable sites in the future decreased by 72.2% by 2050's and almost disappeared with a decrease of 92.1% by 2070's on a nationwide scale. In relation to the major production regions of pine nuts in South Korea - Gapyung gun and Yangpyung gun, Kyunggi province and Hongcheon gun, Kangwon province, suitable sites within their areas were predicted to increase by 2050's but become extinct in South Korea by 2070's. To establish a long-term countermeasures against the improvement on forest productivity quality in terms of managing national food security, the result from this study can be considered as a firm basis of predicting plantation suitability. Also, it can be used to predict the changes in supply of forest products and thereby market values in accordance with climate change scenarios.

• Journal of Ecology and Environment
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• 제43권4호
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• pp.427-437
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• 2019

Background: Climate change is believed to be continuously affecting ticks by influencing their habitat suitability. However, we attempted to model the climate change-induced impacts on future genus Rhipicephalus distribution considering the major environmental factors that would influence the tick. Therefore, 50 tick occuance points were taken to model the potential distribution using maximum entropy (MaxEnt) software and 19 climatic variables, taking into account the ability for future climatic change under representative concentration pathways (RCPs) 4.5 and 8.5, were used. Results: MaxEnt model performance was tested and found with the AUC value of 0.99 which indicates excellent goodness-of-fit and predictive accuracy. Current models predict increased temperatures, both in the mid and end terms together with possible changes of other climatic factors like precipitation which may lead to higher tick-borne disease risks associated with expansion of the range of the targeted tick distribution. Distribution maps were constructed for the current, 2050, and 2070 for the two greenhouse gas scenarios and the most dramatic scenario; RCP 8.5 produced the highest increase probable distribution range. Conclusions: The future potential distribution of the genus Rhipicephalus show potential expansion to the new areas due to the future climatic suitability increase. These results indicate that the genus population of the targeted tick could emerge in areas in which they are currently lacking; increased incidence of tick-borne diseases poses further risk which can affect cattle production and productivity, thereby affecting the livelihood of smallholding farmers. Therefore, it is recommended to implement climate change adaptation practices to minimize the impacts.

• 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.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2018년도 학술발표회
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• pp.195-195
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• 2018

기상청에서는 영국 전지구기후모델인 HadGEM2-AO 기반의 영국 지역기후모델 HadGEM3-RA로부터 생산된 기후변화 시나리오를 기후변화예측을 위한 국가표준시나리오 자료로 제공하고 있다. 하지만, 기후모델의 특성상, 관측자료와 모의자료 간에는 통계적인 차이가 존재하며, 이러한 차이를 무시하고 원자료를 그대로 분석에 사용하는 것은 무의미 하다. 따라서 이러한 보정하기 위해서 주로 Quantile Mapping, Quantile Delta Mapping, Detrended Quantile Mapping 방법이 주로 사용된다. 하지만 어떠한 편의보정 방법이든 극값이 다수 존재하는 미래기간 모의자료를 보정할 때에는 외삽법(extrapolation)의 적용이 필요하다. 외삽법의 경우 constant correction 방법이 주로 적용된다. 본 연구에서는 기상청의 국가표준시나리오를 대상으로 이러한 편의보정 방법의 적용에 따른 미래 극한강우량의 차이를 분석하고자 하였다. 우선, 모의자료에서 우리나라 주요 기상관측지점에 해당하는 격자로부터 강우량자료를 추출하고 연최대강우시계열을 산정하였다. 그 후, 위의 세 가지 편의보정 방법을 이용하여 강우자료의 편의보정을 수행하였으며, constant correction 방법을 적용하여 이상치를 보정하였다. 그 후, 보정된 미래기간 모의자료의 추세를 분석하고, 이를 미래 확률강우량 산정방법인 scale-invariance 기법에 적용하여 미래 확률강우량을 산정하였다. 그 결과, 외삽법의 적용에 따라 편의보정 방법에 따라 미래 자료의 추세 또는 확률강우량의 변화패턴은 큰 차이를 나타내지 않았지만, 그 값 자체는 다소 차이가 있는 것으로 나타났다. 이러한 차이는 사용된 GCM과 RCM 조합으로 인한 오차와 더해져, 미래 예측결과의 불확실성으로 나타나기에 미래 극한강우량 예측을 위해서는 다수의 GCM, RCM 조합뿐만 아니라 다수의 편의보정 방법에 따른 결과도 함께 고려(ensemble)하여 결과를 나타내는 것이 필요할 것으로 판단된다.