• Water Engineering Research
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• 제7권1호
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• pp.9-20
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• 2006

The watersheds are functional geographical areas that integrate a variety of environmental and ecological processes and human impacts on landscapes. Geographical assessments using GIS recognize the relationship between interdependence of resources and ecological/environmental components in watersheds. They are useful methodology for viable long term natural resource management. This paper performs through the using hydrological analyses, landscape ecological analyses, remote sensing, and GIS. Indicators are items or measures that represent key components of the small watersheds, and they are developed to be evaluated. Some indicators are described that they represent watershed condition and trend as well as focus on physical, biological and chemical properties of small watershed. Also, ecological functions such as stability, resilience, and sensitivity are inferred from them. The model implemented in GIS allows to reflect the ecological and hydrological functioning of watershed. Methodology from image analysis, landscape ecological analysis, spatial interpolation, and numerical process modeling are integrated within GIS to provide assessment for eco-logical/environmental condition. Results are described from the small watershed of Gwynns Falls in Baltimore County and Baltimore City, Maryland, an area of about 66.5 square miles. The small watershed within Gwynns Falls watershed are subject to a number of land-use. But it is predominantly urban, with significantly lesser amounts of forest and agriculture. The increasing urbanization is ass-coiated with ecological/environmental impacts and citizen conflicts.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2019년도 학술발표회
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• pp.327-327
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• 2019

The study will quantify the total uncertainties in streamflow and precipitation projections for Upper Awash River Basin located in central Ethiopia. Three hydrological models (GR4J, CAT, and HBV) will be used to simulate the streamflow considering two emission scenarios, six high-resolution GCMs, and two downscaling methods. The readily available hydrometeorological data will be applied as an input to the three hydrological models and the potential evapotranspiration will be estimated using the Penman-Monteith Method. The SCE-UA algorithm implemented in PEST will be used to calibrate the three hydrological models. The total uncertainty including the incremental uncertainty at each stage (emission scenarios and model) will be presented after assessing a total of 24 (=$2{\times}6{\times}2$) high-resolution precipitation projections and 72 (=$2{\times}6{\times}2{\times}3$) streamflow projections for the study basin. Finally, the primary causes that generate uncertainties in future climate change impact assessments will be identified and a conclusion will be made based on the finding of the study.

• 한국농공학회논문집
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• 제47권3호
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• pp.3-13
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• 2005

The conceptual rainfall-runoff models are used to predict complex hydrological effects of a basin. However, to obtain reliable results, there are some difficulties and problems in choosing optimum model, calibrating, and verifying the chosen model suitable for hydrological characteristics of the basin. In this study, Genetic Algorithm and SCE-UA method as global optimization methods were applied to compare the each optimization technique and to analyze the application for the rainfall-runoff models. Modified TANK model that is used to calculate outflow for watershed management and reservoir operation etc. was optimized as a long term rainfall-runoff model. And storage-function model that is used to predict real-time flood using historical data was optimized as a short term rainfall-runoff model. The optimized models were applied to simulate runoff on Pyeongchang-river watershed and Bocheong-stream watershed in 2001 and 2002. In the historical data study, the Genetic Algorithm and the SCE-UA method showed consistently good results considering statistical values compared with observed data.

• Journal of Ecology and Environment
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• 제33권1호
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• pp.47-57
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• 2010

To understand day-to-day fluctuations in soil moisture content in Seoul, I simulated daily soil moisture content from 1908 to 2009 using long-term climatic precipitation and temperature data collected at the Surface Synoptic Meteorological Station in Seoul for the last 98 years with a hydrological simulation model, BROOK. The output data set from the BROOK model allowed me to examine day-to-day fluctuations and the severity and duration of droughts in the Seoul area. Although the soil moisture content is highly dependent on the occurrence of precipitation, the pattern of changes in daily soil moisture content was clearly quite different from that of precipitation. Generally, there were several phases in the dynamics of daily soil moisture content. The period from mid-May to late June can be categorized as the initial period of decreasing soil moisture content. With the initiation of the monsoon season in late June, soil moisture content sharply increases until mid-July. From the termination of the rainy season in mid-July, daily soil moisture content decreases again. Highly stochastic events of typhoons from late June to October bring large amount of rain to the Korean peninsula, culminating in late August, and increase the soil moisture content again from late August to early September. From early September until early October, another sharp decrease in soil moisture content was observed. The period from early October to mid-May of the next year can be categorized as a recharging period when soil moisture content shows an increasing trend. It is interesting to note that no statistically significant increase in mean annual soil moisture content in Seoul, Korea was observed over the last 98 years. By simulating daily soil moisture content, I was also able to reconstruct drought phenomena to understand the severity and duration of droughts in Seoul area. During the period from 1908 to 2009, droughts in the years 1913, 1979, 1939, and 2006 were categorized as 'severe' and those in 1988 and 1982 were categorized as 'extreme'. This information provides ecologists with further potential to interpret natural phenomenon, including tree growth and the decline of tree species in Korea.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2018년도 학술발표회
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• pp.155-155
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• 2018

Uncertainty in flood forecasting using a coupled meteorological and hydrological model is arisen from various sources, especially the uncertainty comes from the inaccuracy of Quantitative Precipitation Forecasts (QPFs). In order to improve the capability of flood forecast, the uncertainty estimation and mitigation are required to perform. This study is conducted to investigate and reduce such uncertainty. First, ensemble QPFs are generated by using Monte - Carlo simulation, then each ensemble member is forced as input for a hydrological model to obtain ensemble streamflow prediction. Likelihood measures are evaluated to identify feasible member. These members are retained to define upper and lower limits of the uncertainty interval and assess the uncertainty. To mitigate the uncertainty for very short lead time, a blending method, which merges the ensemble QPFs with radar-based rainfall prediction considering both qualitative and quantitative skills, is proposed. Finally, blending bias ratios, which are estimated from previous time step, are used to update the members over total lead time. The proposed method is verified for the two flood events in 2013 and 2016 in the Yeonguol and Soyang watersheds that are located in the Han River basin, South Korea. The uncertainty in flood forecasting using a coupled Local Data Assimilation and Prediction System (LDAPS) and Sejong University Rainfall - Runoff (SURR) model is investigated and then mitigated by blending the generated ensemble LDAPS members with radar-based rainfall prediction that uses McGill algorithm for precipitation nowcasting by Lagrangian extrapolation (MAPLE). The results show that the uncertainty of flood forecasting using the coupled model increases when the lead time is longer. The mitigation method indicates its effectiveness for mitigating the uncertainty with the increases of the percentage of feasible member (POFM) and the ratio of the number of observations that fall into the uncertainty interval (p-factor).

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2007년도 학술발표회 논문집
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• pp.253-257
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• 2007

Channel-aquifer interaction is one of the key hydrological processes that determine water flows in the stream/river channel. Field measurements of channel-aquifer interaction, however, is very difficult and costly, particularly when one intends to understand its variations across a catchment for a long period. Hydrological simulations using a catchment model are a relatively easier and cheaper alternative provided the model structure is appropriate for describing channel-aquifer interaction. In this study, a catchment model called CAMEL (Chemicals from Agricultural Management and Erosion Losses) is used for estimating channel-aquifer interaction over time and space. CAMEL is a distributed catchment model to simulate transformation and transport processes of sediment and pollutants as well as water flows at the catchment scale. In the model, a catchment is represented using a network of square columns each of which is comprised of various storages of water. CAMEL explicitly simulates both surface and subsurface processes including channel-aquifer interaction. This paper presents an application study results of CAMEL for the Tarland Burn Catchment, a small (catchment area $52\;km^2$) rural catchment in Scotland, UK, demonstrating some of the channel-aquifer interaction dynamics across the catchment during a 2-year period.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2009년도 학술발표회 초록집
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• pp.149-153
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• 2009

Physics-based distributed rainfall-runoff models are now commonly used in a variety of hydrologic applications such as to estimate flooding, water pollutant transport, sedimentation yield and so on. Moreover, it is not surprising that GIS has become an integral part of hydrologic research since this technology offers abundant information about spatial heterogeneity for both model parameters and input data that control hydrological processes. This study presents the development of a distributed rainfall-runoff prediction system for the Guem river basin ($9,835km^2$) using an Object-oriented Hydrological Modeling System (OHyMoS). We developed three types of element modules: Slope Runoff Module (SRM), Channel Routing Module (CRM), and Dam Reservoir Module (DRM) and then incorporated them systemically into a catchment modeling system under the OHyMoS. The study basin delineated by the 250m DEM (resampled from SRTM90) was divided into 14 midsize catchments and 80 sub-catchments where correspond to the WAMIS digital map. Each sub-catchment was represented by rectangular slope and channel components; water flows among these components were simulated by both SRM and CRM. In addition, outflows of two multi-purpose dams: Yongdam and Daechung dams were calculated by DRM reflecting decision makers' opinions. Therefore, the Guem river basin rainfall-runoff modeling system can provide not only each sub-catchment outflow but also dam inand outflow at one hour (or less) time step such that users can obtain comprehensive hydrological information readily for the effective and efficient flood control during a flood season.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2017년도 학술발표회
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• pp.462-462
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• 2017

유량은 기후적 요인과 인간활동 요인에 의하여 변동된다. 특히 우리나라는 지난 30년 동안 전지구적인 기후변화와 특정지역에서의 인간활동의 변화가 급격하게 진행된 바 있으므로, 합리적인 수자원 계획을 수립하기 위해서는 두 가지 요소들로 인한 유량의 변동량을 정량적으로 분리하여 분석할 필요가 있다. 또한 우리나라와 같이 연강수량의 대부분이 특정 계절에 집중되는 국가나 유역에서는 월별, 계절별 및 년별로 구분된 수문분석을 시행하여야 보다 실질적인 수자원 관리계획을 수립할 수 있다. 그러나 유량의 변동량을 특정 원인별로 구분하여 분석하고자 하는 연구는 기존의 홍수나 가뭄 자체에 관한 연구에 비해 미미한 형편이며, 다양한 시간단위를 이용한 원인별 유량 변동량의 산정에 관한 연구는 더욱 찾아보기 힘들다. 따라서 본 연구에서는 기후변화로 및 인간활동으로 인한 유량 변동량을 정량적으로 분리하기 위하여 수문모형(hydrological model)을 이용한 방법과 수문학적 민감도 (hydrological sensitivity) 분석 방법을 소양강 상류유역 및 섬강 유역에 대해 적용하고 유량 변동량의 결과를 월별, 분기별 및 년별로 구분하여 제시하였다. 먼저 두 유역에 대한 기후변화 및 인간활동의 양상을 강수, 온도, 유량, 인구변화, 불투수층 변화의 추세를 통해 파악하였으며, 인간활동으로 인해 발생되는 급진적인 변동점을 탐색하기 위해 이중누가곡선, Pettitt 검정 및 베이지안 변동점 (Bayesian change point) 분석을 시행하였다. 탐색된 변동점을 활용하여 수문모형에 의한 유량 변동량을 정량화하기 위하여 변동점 이전 구간에 대해 보정 및 검증된 SWAT모형을 사용하였으며, 6가지의 Budyko 곡선 함수들로부터 각각 유량 변동량을 산정하여 수문모형에 의한 유량 변동량을 검증하였다. 최종적으로 수문모형을 이용한 방법을 통해 두 유역에 대한 기후변화 및 인간활동으로 인한 유량 변동량을 정량화하였다. 소양강 상류유역은 기후변화로 인한 유량 변동량이 인간활동으로 인한 유량변동량보다 상대적으로 크게 산정되었으며, 섬강 유역은 소양강 유역과 반대의 결과를 보이는 것으로 분석되었다. 특히 본 연구에서는 해당 분석결과를 월별 및 분기별로 구분하여 제시함으로써, 향후 특정 지역 및 시기에서의 합리적인 수자원 관리계획의 수립에 활용될 수 있는 기초적인 자료를 제공하였다.

• 대한토목학회논문집
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• 제2권2호
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• pp.29-38
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• 1982

유효강우량(有效降雨量), 섬체시간(暹滯時間) 및 유출(流出)의 비선형(非線型)을 포함하는 비선형(非線型) 수문학적(水文學的) 모형(模型)이 기술(記述)된다. 모형(模型)의 입력자료(入力資料)를 구성하는 유효강우량(有效降雨量)의 산정(算定)은 polynomial fitting 방법(方法)이 이용되었으며 섬체시간(暹滯時間)의 비선형성(非線型性)이 고려된 비선형섬체모형(非線型暹滯模型)을 남한강(南漢江) 상류(上流)에 위치한 섬강유역(蟾江流域)에 적용하여 상수(常數)값을 산정하고 종래의 방법인 fitting 방법(方法) 및 저류함수모형(貯溜凾數模型)에 변형(變型)을 가한 상관모형(相關模型)의 상수(常數)값들과 비교하였다. 각 모형(模型)에서 구한 상수(常數)값의 결과로부터 본연구(本硏究)의 수학적(數學的) 해법(解法)인 연속근사해법(連續近似解法)과 수치해법(數値解法)인 Newton-Rhapson 방법(方法)이 비선형(非線型) 유출과정해석(流出過程解析)에서 종전의 계산도해법(計算圖解法) 등에 비해 우수함이 밝혀졌다.

• 한국측량학회지
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• 제15권2호
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• pp.221-230
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• 1997

수문해석에서 지형의 경사분석결과는 수질예측이나 수량예측에 매우 중요한 영향을 미친다. 최근의 경사분석은 기존의 종이지도를 이용하기 보다는 수치표고모형을 이용하는 추세이다. 그러나 수치표고모형에 의한 지형 경사분석은 수치표고모형의 격자크기에 영향을 받는다. 따라서 격자크기에 따른 경사분석결과의 영향은 중요한 요소가 될 수 있다. 이 연구에서는 수질과 수문을 시뮬레이션하기 위해서 요구되는 수문매개변수와 지형매개변수를 결정하기 위해 소양호 유역의 면적이 $640\;km^2$인 내린천 유역과 삼척오십천의 $33\;km^2$ 인 무릉천 유역에 적용하였다. 격자의 크기가 유역의 경사분석에 미치는 영향을 분석하기 위해 내린천유역에 대해서는 1,000 m에서 100 m까지 100 m 격자간격으로 그리고 무릉천유역에 대해서 300 m에서 20 m까지 10 rn간격으로 각각의 격자를 만들어 변화시키면서 적용하였다.