• 한국수자원학회논문집
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• 제56권1호
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• pp.35-43
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• 2023

미래 유량분석은 기후변화 시나리오와 수문모형의 매개변수에 영향을 받고 이에 따른 불확실성이 존재한다. 본 연구에서는 Shared Socioeconomic Pathway (SSP) 시나리오와 수문모형 매개변수에 따른 미래 유량 분석의 불확실성을 분석하고자 하였다. SSP 시나리오 중, 대표적으로 사용되는 SSP2-4.5와 SSP5-8.5시나리오를 사용하였으며, 수문모형으로는 Soil and Water Assessment Tool (SWAT) 모형을 사용하였다. SWAT 모형의 매개변수는 SWAT-CUP을 이용해 관측된 유량 데이터에 따라 총 11개의 기간에 대해 매개변수 최적화를 각각 수행하였다. 그 후 분포의 차이를 계산 할 수 있는 Jensen-Shannon Divergence (JS-D)를 이용해 과거 유량 대비 미래 추정된 유량의 불확실성 분석을 수행하였다. 분석결과 미래 유량의 불확실성은 SSP5-8.5에서 SSP2-4.5보다 더 크게 분석되었으며, 가까운 미래(2021-2060년) 보다 먼 미래(2061-2100년)에서 더 크게 분석되었다. 강우-유출 분석은 수문모형 매개변수에 따라 88.5%-108.5%까지 차이가 발생하였으며, 이에 따라 미래 유량을 추정하는데 불확실성이 발생하였다. 본 연구에서의 수문 모형의 매개변수에 따른 미래 유량 추정의 불확실성은 평년 대비 유량이 적은 연도의 관측 유량 데이터를 이용한 매개변수를 이용할 시 불확실성이 크게 분석되었다. 또한 평년 대비 유량 변화가 큰 기간의 매개 변수일수록 미래 유량 추정의 불확실성이 크게 분석되었다.

• 한국환경과학회지
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• 제24권12호
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• pp.1649-1656
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• 2015

Jeju Island is the highest rain-prone area in Korea that possesses affluent water resources, but future climate changes are predicted to further increase vulnerabilities as resultant of increasing of extreme events and creating spatial-temporal imbalance in water resources. Therefore, this study aimed to provide basic information to establish a proper water resources management plan by evaluating the effects of climate change on water resources using climate change scenario. Direct runoff ratio for 15 years (2000~2014) was analyzed to be 11~32% (average of 23%), and average direct runoff ratio for the next 86 years (2015~2100) was found as 28%, showing an increase of about 22% compared to the present average direct runoff ratio (23%). To assess the effects of climate change on long-term runoff, monthly runoff variation of future Gangjeong watershed was analyzed by dividing three time periods as follows: Present (2000~2030), Future 1 (2031~2070) and Future 2 (2071~2100). The estimated results showed that average monthly runoff increases in the future and the highest runoff is shown by Future 2. Extreme values has been expected to occur more frequently in the future as compared to the present.

• Water Engineering Research
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• 제5권3호
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• pp.111-121
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• 2004

For the long-term strategic water resources planning, forecasting the future streamflow change is important to meet the demand of a growing society. The streamflow variation to the decade-long precipitation was investigated for the two major stage gauging stations in Korea. Precipitation and runoff characteristics have been analyzed at Yongwol stream stage in the Han River as well as Sutong stream stage in the Kum River for the future water resources management strategies. Monte Carlo method has been applied to estimate the future precipitation and runoff. Based on the trend line of 10-year moving average of runoff depth for the historical runoff records, the relation between runoff and the time variation was examined in more detail using regression analysis. This study showed that the surface flows have been significantly decreased while precipitation has been stable in these basins. Decreasing in runoff reflects the regional watershed characteristics such as forest cover changes. The findings of this study could contribute to the planning and development for the efficient water resources utilization.

• 한국농공학회논문집
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• 제53권6호
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• pp.75-84
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• 2011

The objective of this study is to evaluate the hydrologic impacts of climate and land use changes in a rural small watershed. HadCM3 (Hadley Centre Coupled Model, ver.3) A2 scenario and LARS-WG (Long Ashton Research Station - Weather Generator) were used to generate future climatic data. Future land use data were also generated by the CA-Markov (Cellular Automata-Markov) method. The Soil and Water Assessment Tool (SWAT) model was used to evaluate hydrologic impacts. The SWAT model was calibrated and validated with stream flow measured at the Baran watershed in Korea. The SWAT model simulation results agreed well with observed values during the calibration and validation periods. In this study, hydrologic impacts were analyzed according to three scenarios: future climate change (Scenario I), future land use change (Scenario II), and both future climate and land use changes (Scenario III). For Scenario I, the comparison results between a 30-year baseline period (1997~2004) and a future 30-year period (2011~2040) indicated that the total runoff, surface runoff, lateral subsurface runoff, groundwater discharge, and evapotranspiration increased as precipitation and temperature for the future 30-year period increased. The monthly variation analysis results showed that the monthly runoff for all months except September increased compared to the baseline period. For Scenario II, both the total and surface runoff increased as the built-up area, including the impervious surface, increased, while the groundwater discharge and evapotranspiration decreased. The monthly variation analysis results indicated that the total runoff increased in the summer season, when the precipitation was concentrated. In Scenario III, the results showed a similar trend to that of Scenario II. The monthly runoff for all months except October increased compared to the baseline period.

• 농업과학연구
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• 제48권3호
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• pp.433-446
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• 2021

In this study, the future flood inundation changes under a climate change were simulated in the Tonle Sap basin in Cambodia, one of the countries with high vulnerability to climate change. For the flood inundation simulation using the rainfall-runoff-inundation (RRI) model, globally available geological data (digital elevation model [DEM]; hydrological data and maps based on Shuttle elevation derivatives [HydroSHED]; land cover: Global land cover facility-moderate resolution imaging spectroradiometer [GLCF-MODIS]), rainfall data (Asian precipitation-highly-resolved observational data integration towards evaluation [APHRODITE]), climate change scenario (HadGEM3-RA), and observational water level (Kratie, Koh Khel, Neak Luong st.) were constructed. The future runoff from the Kratie station, the upper boundary condition of the RRI model, was constructed to be predicted using the long short-term memory (LSTM) model. Based on the results predicted by the LSTM model, a total of 4 cases were selected (representative concentration pathway [RCP] 4.5: 2035, 2075; RCP 8.5: 2051, 2072) with the largest annual average runoff by period and scenario. The results of the analysis of the future flood inundation in the Tonle Sap basin were compared with the results of previous studies. Unlike in the past, when the change in the depth of inundation changed to a range of about 1 to 10 meters during the 1997 - 2005 period, it occurred in a range of about 5 to 9 meters during the future period. The results show that in the future RCP 4.5 and 8.5 scenarios, the variability of discharge is reduced compared to the past and that climate change could change the runoff patterns of the Tonle Sap basin.

• 상하수도학회지
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• 제11권4호
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• pp.80-90
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• 1997

The ILLUDAS and SWMM models were applied to the developing area of Dongsucheon for comparisons of the total runoff, peak discharge and travel time. For this purpose, the present and future urbanization rates were assumed 70% and 90%, respectively. The runoff analysis of two models has been performed based on 10, 20, 30 and 50 return periods and Huff's 4 quantiles for time distribution pattern of design rainfalls. As results, the total runoff based on Huff's pattern had an decreasing order of 1, 4, 3 and 2 quantiles for both models. The SWMM model showed that there were 4.3% increasing of the total runoff, 4.9% increasing of peak discharge, and 6.6% decreasing of travel time. Similarly, for ILLUDAS model, there were 7.3% and 9.2% increasing of total runoff and peak discharge, respectively and 9.1% decreasing of travel time.

• 한국수자원학회논문집
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• 제53권8호
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• pp.583-595
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• 2020

본 연구에서는 청계천 효자배수분구 유역을 대상으로 RCP 시나리오를 이용하여 Historical 강수량 및 5개의 GCMs 모델로 부터 산정된 Future 강수량과의 변화를 분석하였다. 각 GCMs 모델별 Historical 대비 Future 연 평균 강수량은 최소 35.30 mm에서 최대 208.65 mm 증가하였다. 그리고 Historical 대비 Future 변화율은 1.73%~16.84% 증가하였다. SWMM 모형을 이용하여 투수성포장, 침투도랑, 옥상녹화 3가지의 LID 요소기술을 이용하였다. 그리고 LID 요소기술별 적용된 가중치 변화에 따른 유출량을 분석하였다. 그 결과 각 GCMs 모델별 차이는 있으나 최소 2.58%, 최대 28.78% 유출량이 증가하였다. 그러나 투수성포장 및 침투도랑의 단일 적용시 INM-CM4와 MRI-CGCM3 모델에서 Historical 유출량 대비 각각 3.48%와 2.74%, 8.04%와 7.16% 감소되었다. 또한 두 가지의 LID 요소기술을 조합한 경우에도 유출량이 2.74%와 2.89%, 7.16%와 7.31% 감소되었다. 이것은 기존 Historical의 유출량보다 적거나 유사한 수준인 것으로 분석되었다. LID 요소기술의 적용 결과, 옥상녹화가 도심유역 면적의 1/3정도 적용되는 것이 유출량에 대한 지체시간을 확보하는데 가장 효과적인 것으로 나타났다. 또한 구도심 지역에 LID 기법을 적용할 경우 경제적 비용, 유지관리, 도심경관의 순서로 우선순위를 고려하는 것이 바람직하다.

• 물과 미래
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• 제29권6호
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• pp.131-139
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• 1996

본 연구의 목적은 분포형 강우-유출 모형에 의한 유출량을 해석하는 것이다. 본 모형은 두개의 부모형으로 구성되어 있다. 하나는 수계망(drainage network) 을 통하여 운동파 모형(kinematic wave model)을 이용하여 분포적으로 추적되는 직접 유출 부모형이며, 다른 하나는 기저유출 부모형으로서 집중형으로 취급되어 유역 출구에서만 계산하도록 하였다. 본 연구에서 개발된 모형에 의하여 청미천 유역에 대한 유출량의 시간적, 공간적인 분포를 고려할 수 있었다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2015년도 학술발표회
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• pp.439-439
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• 2015

The temporal and spatial relationship of the weather elements such as rainfall and temperature is closely linked to the streamflow simulation, especially, to the flood forecasting problems. For the study area, Imjin river basin, which has the specific characteristics in geography with river cross operation between North and South Korea, the meteorological information in the northern area is totally deficiency, lead to the inaccuracy of streamflow estimation. In the paper, this problem is solved by using the combination of global (such as soil moisture content, land use) and local hydrologic components data such as weather data (precipitation, evapotranspiration, humidity, etc.) for the model-driven runoff (surface flow, lateral flow and groundwater flow) data in each subbasin. To compute the streamflow in Imjin river basin, this study is applied the hydrologic model SURR (Sejong Univ. Rainfall-Runoff) which is the continuous rainfall-runoff model used physical foundations, originally based on Storage Function Model (SFM) to simulate the intercourse of the soil properties, weather factors and flow value. The result indicates the spatial variation in the runoff response of the different subbasins influenced by the input data. The dependancy of runoff simulation accuracy depending on the qualities of input data and model parameters is suggested in this study. The southern region with the dense of gauges and the adequate data shows the good results of the simulated discharge. Eventually, the application of SURR model in Imjin riverbasin gives the accurate consequence in simulation, and become the subsequent runoff for prediction in the future process.

• Membrane and Water Treatment
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• 제10권1호
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• pp.1-11
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• 2019

The Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) predicted that recent extreme hydrological events would affect water quality and aggravate various forms of water pollution. To analyze changes in water quality due to future climate change, input data (precipitation, average temperature, relative humidity, average wind speed and sunlight) were established using the Representative Concentration Pathways (RCP) 8.5 climate change scenario suggested by the AR5 and calculated the future runoff for each target period (Reference:1989-2015; I: 2016-2040; II: 2041-2070; and III: 2071-2099) using the semi-distributed land use-based runoff processes (SLURP) model. Meteorological factors that affect water quality (precipitation, temperature and runoff) were inputted into the multiple linear regression analysis (MLRA) and artificial neural network (ANN) models to analyze water quality data, dissolved oxygen (DO), biological oxygen demand (BOD), chemical oxygen demand (COD), suspended solids (SS), total nitrogen (T-N) and total phosphorus (T-P). Future water quality prediction of the Anseongcheon River basin shows that DO at Gongdo station in the river will drop by 35% in autumn by the end of the $21^{st}$ century and that BOD, COD and SS will increase by 36%, 20% and 42%, respectively. Analysis revealed that the oxygen demand at Dongyeongyo station will decrease by 17% in summer and BOD, COD and SS will increase by 30%, 12% and 17%, respectively. This study suggests that there is a need to continuously monitor the water quality of the Anseongcheon River basin for long-term management. A more reliable prediction of future water quality will be achieved if various social scenarios and climate data are taken into consideration.