http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Markov-Chain Monte Carlo 기법을 이용한 준 분포형 수문모형의 매개변수 및 모형 불확실성 분석
최정현 ( Choi Jeonghyeon ),장수형 ( Jang Suhyung ),김상단 ( Kim Sangdan ) 한국물환경학회(구 한국수질보전학회) 2020 한국물환경학회지 Vol.36 No.5
Hydrological models are based on a combination of parameters that describe the hydrological characteristics and processes within a watershed. For this reason, the model performance and accuracy are highly dependent on the parameters. However, model uncertainties caused by parameters with stochastic characteristics need to be considered. As a follow-up to the study conducted by Choi et al (2020), who developed a relatively simple semi-distributed hydrological model, we propose a tool to estimate the posterior distribution of model parameters using the Metropolis-Hastings algorithm, a type of Markov-Chain Monte Carlo technique, and analyze the uncertainty of model parameters and simulated stream flow. In addition, the uncertainty caused by the parameters of each version is investigated using the lumped and semi-distributed versions of the applied model to the Hapcheon Dam watershed. The results suggest that the uncertainty of the semi-distributed model parameters was relatively higher than that of the lumped model parameters because the spatial variability of input data such as geomorphological and hydrometeorological parameters was inherent to the posterior distribution of the semi-distributed model parameters. Meanwhile, no significant difference existed between the two models in terms of uncertainty of the simulation outputs. The statistical goodness of fit of the simulated stream flows against the observed stream flows showed satisfactory reliability in both the semi-distributed and the lumped models, but the seasonality of the stream flow was reproduced relatively better by the distributed model.
Choi, Jeonghyeon,Lee, Okjeong,Jang, Juhyoung,Jang, Suhyung,Kim, Sangdan John Wiley Sons, Ltd 2019 International journal of climatology Vol.39 No.2
<P>Many Global Climate Models (GCMs) or Regional Climate Models (RCMs) are being developed around the world and are being used in future climate change adaptation planning. However, in Korea, future rainfall data as a national standard scenario are provided on a daily basis, so it is difficult to apply directly to the design of hydraulic structures considering the impact of climate change. In this study, a method for estimating future intensity–depth–frequency (IDF) curves in Korea is proposed using a simple scale‐invariance assumption associated with trend analysis of future extreme rainfall data. First, the scale characteristics of hourly rainfall data observed at 60 meteorological stations operated by Korea Meteorological Administration (KMA) are examined, and scale parameters of IDF curves are estimated from observed scale‐invariance characteristics. Second, the future daily annual maximum rainfall data provided by KMA‐RCM is bias‐corrected. Various methods are used for the correction of biases of rainfall depths. The third is trend analysis, which is used to determine the mean and the coefficient of variance of future daily annual maximum rainfall time series in future years. Finally, future IDF curves are estimated by combining scale‐invariance method and trend analysis.</P>
최정현(Choi Jeonghyeon),이옥정(Lee Okjeong),장수형(Jang Suhyung),조덕준(Jo Deok Jun),김상단(Kim Sangdan) 한국방재학회 2018 한국방재학회논문집 Vol.18 No.6
본 연구에서는 태풍 매미를 대상으로 WRF (Weather Research and Forecast) 모형을 이용하여 초기 및 경계조건의 해수면온도 및 상대습도의 변경을 통해 태풍 강우량을 최대화하고, 해수면온도가 태풍 강우량의 최대화에 미치는 영향을 분석하고자 하였다. 사전연구를 통해 수치적으로 재현된 태풍 매미를 기반으로, 태풍으로 유입되는 수증기량을 증가시켜 태풍강우를 최대화하고자 하였다. 이를 위하여 모형의 초기 및 경계조건 중 상대습도를 100 %로 고정하고 해수면온도를 0.0 ℃에서 5.0 ℃까지 증가시켜가며 태풍 강수량이 모의되었다. 모의된 태풍의 강우를 살펴본 결과, 해수면온도의 증가에 따라 모의된 총 강우량의 공간적인 분포가 매우 다양하게 나타났으며, 특히 해수면온도의 변화는 육지에 떨어지는 강우량에 많은 영향을 미치는 것을 살펴볼 수 있었다. 또한, 해수면온도의 증가와 육지에 떨어지는 강우량은 선형적인 관계를 나타내지 않는 것으로 나타났다. 따라서 태풍강우 최대화를 위해서는 무조건적으로 해수면온도를 증가시켜 WRF를 구동하기 보다는 다양한 조건에 대한 수치실험을 반복하여 모의하고자 하는 태풍에 가장 적합한 최적 해수면온도 증가량을 탐색할 필요가 있을 것으로 판단된다. In this study, the WRF (Weather Research and Forecast) model was used to maximize typhoon rainfall depth by changing the sea surface temperature (SST) and relative humidity in the initial and boundary conditions. The effects of SST on maximizing typhoon rainfall depth were analyzed. Typhoon MAEMI’s rainfall depth, which was numerically reproduced by pre-study, was maximized by increasing the amount of water vapor entering the typhoon. For this, the relative humidity of the initial and boundary conditions of the model was fixed at 100 %, and the typhoon rainfall was simulated by increasing SST from 0.0 °C to 5.0 °C. The simulation of typhoon rainfall under various SSTs indicates that the spatial distribution of the simulated total rainfall depth varies with increasing SST. In particular, it can be seen that the change in SST greatly affects the rain falling on the land. In addition, it is found that the total rainfall depth on land and changes in SST do not exhibit a linear relationship. Therefore, it is necessary to investigate the optimal increase in SST in accordance with the target typhoon by carrying out repeated numerical experiments using various SST conditions, rather than unconditionally increasing SST to maximizing typhoon rainfall depth.
일 강수량자료의 시간적 다운스케일링을 위한 추계학적 점강우모형의 적용
이옥정(Lee, Okjeong),최정현(Choi, Jeonghyeon),장수형(Jang, Suhyung),김상단(Kim, Sangdan) 한국방재학회 2017 한국방재학회논문집 Vol.17 No.1
In this study, a stochastic point rainfall model which uses the 3-parameter mixed exponential probability density function for rain cell intensities is applied to downscale daily rainfall data into sub-daily rainfall data. Cluster characteristics of rainfall events are simulated by using the Neyman–Scott cluster point process. The model performance in producing sub-daily rainfall time series from daily rainfall time series is evaluated with rainfall data at Gangreung, Busan, Mokpo, and Incheon situated on coastal regions of the Korean peninsula. Results from generating long time rainfall events show that the model reproduces well the statistical characteristics of the historical rainfall time series and has better ability than original Neyman-Scott rectangular pulse model in reproducing statistics related to dry period and extreme rainfall events. 본 연구에서는 일 강수량 자료를 시간 강수량 자료로 다운스케일링하기 위하여 강우세포의 강도를 3-변수 지수분포로 모의하는 추계학적 점 강우모형이 적용된다. 강우사상의 군집특성은 Neyman-Scott 군집 점 과정을 이용하여 모의된다. 연안지역에 위치한 강릉, 부산, 목포, 인천 지점의 일 강우자료를 이용하여 모형의 성능을 평가하였다. 장기간의 여름철 강우사상들을 모의 발생한 결과, 모형은 관측된 강우 시계열의 통계학적 특성을 적절히 재현하고 있으며, 특히 무 강우 및 극한강우와 관련된 통계특성의 재현에 있어서 기존의 Neyman-Scott 구형 펄스 모형보다는 더 우수한 성능을 나타내고 있음을 확인할수 있었다.
홍승록(Seungrok Hong),최진욱(Jinwook Choi),유충식(Chungsik Yoo),이대영(Daeyoung Lee),이수형(Suhyung Lee),유인균(Inkyoon Yoo) 한국지반신소재학회 2013 한국지반신소재학회 논문집 Vol.12 No.3
본 논문에서는 투수성 포장 하부구조의 지반에 지오셀 보강에 따른 거동특성을 다루었다. 지오셀을 이용한 포장구조체의 하중지지력 증가효과를 고찰하기 위하여 지오셀 결합부의 유형, 벽 두께, 직경을 변화시켜가며 총 9가지의 실험 케이스의 실내 축소모형실험을 진행하여 무보강 투수성 포장에 비해 지오셀로 보강된 포장 하부구조에서 더 큰 지지력이 발현 되는 것으로 나타났고 지오셀의 단면 형태의 관계 없이 거의 일정한 하중 지지력을 보이는 것으로 나타났다. 또한 지오셀 속채움시 지오셀의 형상은 직경 30cm, 두께 1.8mm에서 가장 지지 효과가 크게 나타나는 것을 알 수 있었다. This paper presents the results of a laboratory investigation of the porous pavement substructure effect when reinforced with geocell. In order to analyze load carrying capacity of Geocell, a series of 9 reduced-scale laboratory tests was performed, changing the type, thickness, diameter of Geocell. The results of the analyses indicated that the bearing capacity of the reinforced Geocell increases much more than the non-reinforced Geocell and load carrying capacity was considered to be insignificant according to the type of Geocell. It was also found that the most supportive effects appeared as 30 cm in diameter and 1.8mm in thickness.