• Journal of Korea Water Resources Association
• /
• v.50 no.1
• /
• pp.17-28
• /
• 2017

A recent increase in extreme weather events and flash floods associated with the enhanced climate variability results in an increase in climate-related disasters. For these reasons, various studies based on a high resolution weather radar system have been carried out. The weather radar can provide estimates of precipitation in real-time over a wide area, while ground-based rain gauges only provides a point estimate in space. Weather radar is thus capable of identifying changes in rainfall structure as it moves through an ungauged basin. However, the advantage of the weather radar rainfall estimates has been limited by a variety of sources of uncertainty in the radar reflectivity process, including systematic and random errors. In this study, we developed an ensemble radar rainfall estimation scheme using the multivariate copula method. The results presented in this study confirmed that the proposed ensemble technique can effectively reproduce the rainfall statistics such as mean, variance and skewness (more importantly the extremes) as well as the spatio-temporal structure of rainfall fields.

• Journal of Applied Reliability
• /
• v.18 no.1
• /
• pp.20-32
• /
• 2018

Purpose: The purpose of this study is to set up an anomaly detection criteria for sensor data coming from a motorcycle. Methods: Five sensor values for accelerator pedal, engine rpm, transmission rpm, gear and speed are obtained every 0.02 second from a motorcycle. Exploratory data analysis is used to find any pattern in the data. Traditional process control methods such as X control chart and time series models are fitted to find any anomaly behavior in the data. Finally unsupervised learning algorithm such as k-means clustering is used to find any anomaly spot in the sensor data. Results: According to exploratory data analysis, the distribution of accelerator pedal sensor values is very much skewed to the left. The motorcycle seemed to have been driven in a city at speed less than 45 kilometers per hour. Traditional process control charts such as X control chart fail due to severe autocorrelation in each sensor data. However, ARIMA model found three abnormal points where they are beyond 2 sigma limits in the control chart. We applied a copula based Markov chain to perform statistical process control for correlated observations. Copula based Markov model found anomaly behavior in the similar places as ARIMA model. In an unsupervised learning algorithm, large sensor values get subdivided into two, three, and four disjoint regions. So extreme sensor values are the ones that need to be tracked down for any sign of anomaly behavior in the sensor values. Conclusion: Exploratory data analysis is useful to find any pattern in the sensor data. Process control chart using ARIMA and Joe's copula based Markov model also give warnings near similar places in the data. Unsupervised learning algorithm shows us that the extreme sensor values are the ones that need to be tracked down for any sign of anomaly behavior.

• International Journal of Reliability and Applications
• /
• v.12 no.1
• /
• pp.15-39
• /
• 2011

This paper deals with the reliability analysis of a complex system with three possibilities at the time of repair. The considered system consists of two subsystems A and Bin series configuration (1-out-of-2: F). Subsystem A has n units which are connected in series whereas subsystem B consists of n units in parallel configuration. The configuration of subsystem A is of 1-out-of-n: F whereas subsystem B is of k-out-of-n: D and k+1-out-of-n: F nature. System has three states: Good, degraded and failed. Supplementary variable technique has been used for mathematical formulation of the model. Laplace transform is being utilized to solve the mathematical equation. Reliability, Availability, M.T.T.F., Busy Period and Cost effectiveness of the system have been computed. The repairs from state $S_7$ to $S_0$, $S_8$ to $S_0$, $S_9$ to $S_0$ and $S_{11}$ to $S_0$ have two types namely exponential and general. Joint probability distribution of repair rate from $S_7$ to $S_0$, $S_8$ to $S_0$, $S_9$ to $S_0$ and $S_{11}$ to $S_0$ is computed by Gumbel-Hougaard family of copula. Some particular cases of the system have also been derived to see the practical importance of the model.

• Journal of Korea Water Resources Association
• /
• v.49 no.3
• /
• pp.217-225
• /
• 2016

The drought is generally characterized by duration and severity, thus it is required to conduct the bivariate frequency analysis simultaneously considering the drought duration and severity. However, since a bivariate joint probability distribution function (JPDF) has a 3-dimensional space, it is difficult to interpret the results in practice. In order to suggest the technical solution, this study employed copula functions to estimate an JPDF, then developed conditional JPDFs on various drought durations and estimated the critical severity corresponding to non-exceedance probability. Based on the historical severe drought events, the hydrologic risks were investigated for various extreme droughts with 95% non-exceedance probability. For the drought events with 10-month duration, the most hazardous areas were decided to Gwangju, Inje, and Uljin, which have 1.3-2.0 times higher drought occurrence probabilities compared with the national average. In addition, it was observed that southern regions were much higher drought prone areas than northern and central areas.

• Journal of Korea Water Resources Association
• /
• v.48 no.12
• /
• pp.969-979
• /
• 2015

This study applied a probabilistic-based hidden Markov model (HMM) to better characterize drought patterns. In addition, a copula-based bivariate drought frequency analysis was employed to further investigate return periods of the current drought condition in year 2015. The obtained results revealed that western Kangwon area was generally more vulnerable to drought risk than eastern Kangwon area using the 40-year data. Imjin-river watershed including Cheorwon area was the most vulnerable area in terms of severe drought events. Four stations in Han-river watershed showed a joint return period exceeding 1,000 years associated with the drought duration and severity in 2014-2015. Especially, current drought status in Northern Han-river and Imjin-river watershed is most severe drought exceeding 100-year return period.

• Korean Journal of Remote Sensing
• /
• v.38 no.5_3
• /
• pp.887-899
• /
• 2022

Drought caused by meteorological factors negatively affects vegetation in terrestrial ecosystems. In this study, the state in which meteorological drought affects vegetation was defined as the ecological drought of vegetation, and the ecological drought condition index of vegetation (EDCI-veg) was proposed to quantitatively monitor the degree of impact. EDCI-veg is derived from a copula-based bi-variate joint probability model between vegetation and meteorological drought information, and can be expressed numerically how affected the current vegetation condition was by the drought when the drought occurred. Comparing past meteorological drought events with their corresponding vegetation condition, the proposed index was examined, and it was confirmed that EDCI-veg could properly monitor the ecological drought of vegetation. In addition, it was possible to spatially identify ecological drought conditions by creating a high-resolution drought map using remote sensing data.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2021.06a
• /
• pp.343-343
• /
• 2021

최근 국내외적으로 발생되는 대규모의 가뭄에 대하여 여러 과학자들은 자연적인 현상의 가뭄이 아니라 인간의 영향으로 변형된 유역 상황으로 증발산과 토양수분량 그리고 하천유량 등이 자연적인 상태와 다르게 변화되면서 지속된 가뭄으로 평가하고 있다. 우리나라는 대부분의 지역에서 댐과 저류지를 중심으로 수자원 관리가 이루어지고 있으며, 자연적인 수문과정에 의한 유출에 따른 수문학적 가뭄과는 차이가 존재한다. 사회경제적 인자(인구밀도, 농업 및 산업 경제규모 등)는 댐 및 저수지의 용수사용에 큰 영향을 미치며, 저류지의 저류량을 활용하여 판단한 인위적 용수사용이 고려된 수문학적 가뭄(인위적 수문학적 가뭄)과 자연 상태로의 수문학적 가뭄의 특성은 크게 다를 수 있다. 하지만, 사회경제적 인자들이 수문학적 가뭄에 미치는 영향에 대하여 비교한 연구는 상관성 분석을 토대로한 연구가 대부분이다. 본 연구에서는 인자들이 인위적 수문학적 가뭄에 미치는 정도를 정량적으로 비교하기 위하여 베이지안 네크워크 모형을 활용하여 사회경제적 인자와 인위적 수문학적 가뭄과의 관계를 분석하였다. 해당 관계를 바탕으로 코플라 함수를 활용함으로써 베이지안 네트워크 내의 결합확률을 산정하였다. 다양한 사회경제적 인자들에 중에서 인과지도를 바탕으로 활용 가능한 인자로 농업용수 사용량, 생공용수 사용량 자료를 구축하였으며, 기상학적 가뭄지수를 추가적으로 고려하여 한강유역 충주댐 유역에 적용하였다. 그 결과 기상학적 가뭄과 농업용수 사용량과 생공용수 사용량은 값이 증가함에 따라 인위적 수문학적 가뭄의 발생확률이 증가하였다. 사회경제적 인자 중에서는 생공용수 사용량(0.39~0.49)이 전반적으로 농업용수 사용량(0.36~0.48)보다 인위적 수문학적 가뭄에 보다 큰 영향을 미치고 있으며, 값이 적을수록 생공용수 사용량의 영향이 보다 더 크다는 것이 확인되었다. 이를 바탕으로 인위적 수문학적 가뭄의 대응을 위해서는 농업용수 사용량보다 생공용수 사용량의 감축이 우선적으로 이루어져야 그 효과가 클 것으로 판단된다. 본 연구에서 제시한 모형은 베이지안 네트워크를 기반으로 하므로, 둘 이상의 인자에 대하여 복합적으로 가뭄에 영향을 미치는 영향에 대한 추가적인 연구가 가능하다.

• Journal of the Korean Geotechnical Society
• /
• v.31 no.8
• /
• pp.51-62
• /
• 2015

It is not possible to provide resonable evidence for embankment (or dam) overtopping in geotechnical engineering, and conventional analysis by hydrologic design has not provided the evidence for the overflow. However, hydrologic design analysis using Copula function demonstrates the possibility that dam overflow occurs when estimating rainfall probability with rainfall data for 40 years based on fluctuating water level of a dam. Hydrologic dam risk analysis depends on complex hydrologic analyses in that probabilistic relationship needs to be established to quantify various uncertainties associated with modeling process and inputs. The systematic approaches to uncertainty analysis for hydrologic risk analysis have not been addressed yet. In this paper, the initial level of a dam for stability of a dam is generally determined by normal pool level or limiting the level of the flood, but overflow of probability and instability of a dam depend on the sensitivity analysis of the initial level of a dam. In order to estimate the initial level, Copula function and HEC-5 rainfall-runoff model are used to estimate posterior distributions of the model parameters. For geotechnical engineering, slope stability analysis was performed to investigate the difference between rapid drawdown and overtopping of a dam. As a result, the slope instability in overtopping of a dam was more dangerous than that of rapid drawdown condition.

• Economic Analysis
• /
• v.27 no.1
• /
• pp.67-90
• /
• 2021

This study found an interesting fact that the nonlinear relationship structure between volatility and trading volume changed before and after the COVID-19 pandemic according to empirical analysis using Bitcoin (BTC) market data that sensitively reflects investors' trading behavior. That is, their relationship appeared positive (+) in a stable market state before COVID-19 pandemic, as in theory based on the information flow paradigm. In a state under severe market stress due to COVID-19 pandemic, however, their dependence structure changed and even negative (-). This can be seen as a consequence of increased market stress caused by COVID-19 pandemics from a behavioral economics perspective, resulting in structural changes in the asset market and a significant impact on the nonlinear dependence of volatility and trading volume (in particular, their dependence at extreme quantiles). Hence, it should be recognized that in addition to information flows, psychological phenomena such as behavioral biases or herd behavior, which are closely related to market stress, can be a key in changing their dependence structure. For empirical analysis, this study performs a test of Ross (2015) for detecting a structural change, and proposes a Copula Regression Quantiles (CRQ) approach that can identify their nonlinear relationship structure and the asymmetric dependence in their distribution tails without the assumption of i.i.d. random variable. In addition, it was confirmed that when the relationship between their extreme values was analyzed by linear models, incorrect results could be derived due to model specification errors.

• Communications for Statistical Applications and Methods
• /
• v.19 no.1
• /
• pp.85-95
• /
• 2012

In this paper we define extended negative quadrant dependence which is weaker negative quadrant dependence and show conditions for having extended negative quadrant dependence property. We also derive generalized Farlie-Gumbel-Morgenstern uniform distributions that possess the extended quadrant dependence property.