• 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).

• 대한토목학회논문집
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• 제33권3호
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• pp.937-945
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• 2013

홍수범람도의 정확성은 입력자료, 모형변수, 모델접근방법 등을 포함한 전반적인 구축과정에 포함된 모든 변수들로부터 전달되는 불확실성에 의해 결정된다. 본 연구의 목적은 미국 Missouri주 Boonville시에 위치한 Missouri 강에 대한 홍수범람도 구축과정에서 모델 변수들 가운데 주 요소 (흐름조건, 조도계수)로부터 발생하는 불확실성을 조사하는 것이다. 본 연구를 수행하기 위하여 홍수범람면적의 불확실성 구간을 정량화하기 위한 GLUE (generalized likelihood uncertainty estimation)를 이용하였다. GLUE 수행과정에서 불확실성 구간은 두 개의 우도함수를 선택함으로 산정되었는데 선택된 우도함수는 제곱오차 합의 역 (1/SSE)과 절대오차 합의 역 (1/SAE)이다. GLUE의 결과는 제곱오차 합의 역에 의한 우도측정이 절대오차 합의 역에 의한 우도측정보다 관측 자료에 더 민감하였고, 두 개의 변수에 포함된 불확실성은 관측 자료의 약 2 %에 해당하는 홍수범람면적의 불확실성 구간에 전달되었다. 이러한 결과를 토대로, 본 연구는 홍수의 특성을 알아내는데 중요한 역할을 할 것으로 기대된다.

• 한국방재학회 논문집
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• 제9권6호
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• pp.143-151
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• 2009

최근의 극한 수문사상은 홍수, 가뭄과 같은 심각한 재해를 발생시킨다. 많은 연구자들은 불확실한 미래의 확률강우량 및 유출량의 예측을 위해 많은 노력을 하고 있다. 본 연구에서는 불확실성이 낮은 확률강우량의 산정을 위하여 매개변수 추정법을 평가하였다. 인천, 강릉, 광주, 부산, 추풍령 관측소를 연구 대상 관측소로 선정하여 자료를 수집하였고, ARMA모형을 이용하여 합성강우자료를 구축하였다. 본 연구에서는 극치강우사상에 적합한 것으로 알려진 Gumbel 분포와 GEV 분포모형에 대한 매개변수를 최우도법과 베이지안 추론방법을 사용하여 추정하였으며, Bootstrap 방법을 이용하여 확률강우량의 신뢰구간 길이를 추정하였다. 매개변수 추정 방법별 산정된 확률강우량의 신뢰구간 길이를 비교함으로서 불확실성이 낮은 확률강우량을 산정할 수 있는 매개변수 추정방법을 선정하였다.

• Journal of the Korean Data and Information Science Society
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• 제24권4호
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• pp.825-833
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• 2013

온실가스 인벤토리 불확도 산정을 위해서는 인벤토리의 신뢰구간 추정이 필수적이다. 일반적으로 모수에 대한 신뢰구간 추정시에는 모집단이 정규분포를 따른다고 가정한다. 그러나 자료의 구조가 복잡해짐에 따라 정규분포가 아닌 비대칭형 자료, 즉 양의 왜도를 갖는 자료의 경우 기존의 정규분포를 가정한 신뢰구간 추정 방식은 적합하지 않다. 본 연구에서는 비대칭형 분포인 지수분포의 신뢰구간추정 방법으로 모수적인 방법과 비모수적인 방법에 대해 각각 비교분석하였다. 모의실험을 통한 신뢰구간 추정 결과를 바탕으로 범위확률, 신뢰구간 길이, 상대적 편의를 비교한 결과 모수적 방법 중에서 예상했던 대로 정확한 방법인 카이제곱방법이 신뢰계수와 유사한 범위확률을 보이고 상대적 편의도 작아 모수적 방법 중에서 신뢰구간 추정에 가장 적합한 것으로 나타났다. 마찬가지로 비모수적 방법 중에서는 표준화된 t-붓스트랩 방법이 가장 적합한 것으로 나타났다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2017년도 학술발표회
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• pp.188-188
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• 2017

Rainfall is an important input to hydrological models. The accuracy of hydrological studies for water resources and floods management depend primarily on the estimation of rainfall. Thailand is among the countries that have regularly affected by floods. Flood forecasting and warning are necessary to prevent or mitigate loss and damage. Merging near real time satellite-based precipitation estimation with relatively high spatial and temporal resolutions to ground gauged precipitation data could contribute to reducing uncertainty and increasing efficiency for flood forecasting application. This study tested the applicability of satellite-based rainfall for water resources management and flood forecasting. The objectives of the study are to assess uncertainty associated with satellite-based rainfall estimation, to perform bias correction for satellite-based rainfall products, and to evaluate the performance of the bias-corrected rainfall data for the prediction of flood events. This study was conducted using a case study of Thai catchments including the Chao Phraya, northeastern (Chi and Mun catchments), and the eastern catchments for the period of 2006-2015. Data used in the study included daily rainfall from ground gauges, telegauges, and near real time satellite-based rainfall products from TRMM, GSMaP and PERSIANN CCS. Uncertainty in satellite-based precipitation estimation was assessed using a set of indicators describing the capability to detect rainfall event and efficiency to capture rainfall pattern and amount. The results suggested that TRMM, GSMaP and PERSIANN CCS are potentially able to improve flood forecast especially after the process of bias correction. Recommendations for further study include extending the scope of the study from regional to national level, testing the model at finer spatial and temporal resolutions and assessing other bias correction methods.

• 제어로봇시스템학회논문지
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• 제12권2호
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• pp.93-100
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• 2006

In this paper, a new-type Extended Kalman Filter (EKF) is proposed as a robust nonlinear filter for a stochastic nonlinear system. The original EKF is widely used for various nonlinear system applications. But it is fragile to its estimation errors because they give rise to linearization errors that affect the system mode1 as the modeling errors. The linearization errors are nonlinear functions of the estimation errors therefore it is very difficult to obtain the accurate error covariance of the EKF using the linear form. The inaccurately estimated error covariance hinders the EKF from being a sub-optimal estimator. The proposed filter tries to obtain the upper bound of the error covariance tolerating the uncertainty of the error covariance instead of trying to obtain the accurate one. It treats the linearization errors as uncertain modeling errors that can be handled by the robust linear filtering. In order to be more robust to the estimation errors than the original EKF, the proposed filter minimizes the upper bound like the robust linear filter that is applied to the linear model with uncertainty. The in-flight alignment problem of the inertial navigation system with GPS position measurements is a good example that the proposed robust filter is applicable to. The simulation results show the efficiency of the proposed filter in the robustness to initial estimation errors of the filter.

• 대한교통학회지
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• 제32권6호
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• pp.694-702
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• 2014

국가 온실가스를 산정, 보고, 검정을 관장하는 온실가스종합정보센터가 2010년에 출범된 후, 주요 업무의 집합체인 국가 온실가스 인벤토리 보고서가 2012년부터 해마다 발간되었다. 보고서에는 부문별 온실가스 배출량 및 불확도가 보고되고 있지만, 대부분의 부문에서 불확도의 기입은 단순히 IPCC 가이드라인의 기본값으로 대체되고 있는 실정이다. IPCC 가이드라인은 부문별 온실가스 배출량을 산정함에 있어 Tier 수준에 따른 구체적인 산정식을 제시하고 있지만, 불확도의 경우 확률밀도함수 추정 또는 몬테카를로 방법 등을 적용한 국가고유 방법론의 개발을 권고하고 있다. 도로교통부문도 배출량이 Tier 1수준으로 산정되고 있지만 불확도는 보고되지 못하고 있는 실정이다. 본 연구는 도로교통부문에서 일반자가용자동차대형을 대상으로 활동자료인 연간 주행거리, 연비 그리고 배출계수를 이용하여 연간 배출량을 산정하는데 국한하지 않고 불확도 산정에 적용되는 여러 통계적 기법 중에 한 가지인 붓스트랩 및 몬테카를로 방법을 소개하는데 있다.

• International Journal of Control, Automation, and Systems
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• 제1권4호
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• pp.520-526
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• 2003

In the case of a strapdown inertial navigation system (SDINS) with sizeable attitude errors, the uncertainty caused by linearization of the system degrades the performance of the filter. In this paper, a robust filter and various error models for the uncertainty are presented. The analytical characteristics of the proposed filter are also investigated. The results show that the filter does not require the statistical property of the system disturbance and that the region of the estimation error depends on a freedom parameter in the worst case. Then, the uncertainty of the SDINS is derived. Depending on the choice of the reference frame and the attitude error state, several error models are presented. Finally, various in-flight alignment methods are proposed by combining the robust filter with the error models. Simulation results demonstrate that the proposed filter effectively improves the performance.

• 한국자동차공학회논문집
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• 제23권4호
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• pp.361-370
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• 2015

There will inevitably be errors and uncertainties in tire yaw mark related critical speed formula, which is derived merely from the relationship between the centrifugal force and the friction force acting on the point-mass vehicle. Constructing and measuring yaw marks through appropriate simulation works have made it possible to perform uncertainty analysis in calculation of critical speeds under variation of variety of conditions and parameters while existing yaw mark experimental tests have not performed properly. This paper does not present only the critical speed analysis results for parametric sensitivity and uncertainty of chord and middle ordinate, coefficient of friction and road grade, but also modeling uncertainty such as variation of braking level during turning and vehicle size. The yaw mark analysis methods and results may be now applied in practice of traffic accident investigation.

• 대한안전경영과학회지
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• 제13권2호
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• pp.267-273
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• 2011

Since 'The Act on Private Investment of The Infrastructure' was established in 1994, private investment as well as government's investment in transport infrastructure has been active. However investment in transport infrastructure has more risks than others' due to uncertainty both in traffic volume and in construction cost. In the current appraisal procedure of deciding transportation infrastructure investment, instead of risk management, the sensitivity analysis considering only the changes of benefit, cost and social discount rate which are main factor affecting economic feasibility is carried out. Therefore the uncertainty of various factors affecting demand, cost and benefit are not considered in feasibility study. In this study the problems in current investment appraisal system were reviewed. Using Delphi technique the major factors which have high uncertainty in feasibility study were surveyed and then improvement plan was suggested in the respective of classic 4 step demand forecasting method. The range estimation technique was also mentioned to deal with the uncertainty of the future.