• 한국농공학회논문집
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• 제56권2호
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• pp.11-23
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• 2014

The impact and adaption on agricultural water resources considering climate change is significant for reservoirs. The change in rainfall patterns and hydrologic factors due to climate change increases the uncertainty of agricultural water supply and demand. The quantitative evaluation method of uncertainty based on agricultural water resource management under future climate conditions is a major concern. Therefore, it is necessary to improve the vulnerability management technique for agricultural water supply based on a probabilistic and stochastic risk evaluation theory. The objective of this study was to analyse the uncertainty of water resources under future climate change using probability distribution function of water supply in agricultural reservoir and demand in irrigation district. The uncertainty of future water resources in agricultural reservoirs was estimated using the time-specific analysis of histograms and probability distributions parameter, for example the location and the scale parameter. According to the uncertainty analysis, the future agricultural water supply and demand in reservoir tends to increase the uncertainty by the low consistency of the results. Thus, it is recommended to prepare a resonable decision making on water supply strategies in terms of using climate change scenarios that reflect different future development conditions.

• 한국수자원학회논문집
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• 제51권spc1호
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• pp.1079-1089
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• 2018

기존 기후변화 영향평가에서 발생하는 불확실성에 대한 연구들은 전체과정에서 총 불확실성과 그 전파에 대한 것보다 각 단계별 불확실성에 초점을 맞추어 연구가 진행되었다. 따라서 본 연구에서는 first-order Taylor series expansion에 기반하여 전망의 분산을 이용하는 Uncertainty Delta Method (UDM)를 제안하였으며, 이 방법은 각 단계별 불확실성 정량화와 증감정도, 단계별 불확실성 비율, 총 불확실성의 전파 과정 제시가 가능하다. 본 연구에서는 기후변화 영향평가 과정의 단계별 불확실성 정량화와 전파과정 분석을 위해 미래 2030년부터 2059년까지를 대상으로 2개 배출 시나리오, 3개 GCM, 2개 상세화기법, 2개 수문모형을 사용하였다. 결과를 분석하면, UDM을 이용한 총 불확실성은 5.45(배출시나리오: 4.45, 상세화기법: 0.45, 상세화기법: 0.27, 수문모형: 0.28)이며, 배출 시나리오의 불확실성(4.45)이 가장 크게 나타났다. 불확실성은 각 단계를 거칠수록 증가하는 것으로 나타났다. 이러한 결과는 어떠한 배출시나리오를 선정하느냐에 따라 미래 수자원전망이 매우 달라질 수 있음을 의미한다. 다음으로 Hawkins and Sutton (2009)가 제안한 Fractional Uncertainty Method (FUM)을 이용한 기후변화 영향평가 불확실성 분석에서 가장 불확실성이 큰 요인은 배출 시나리오(FUM 불확실성: 0.52)이며, 이 결과는 UDM 결과와 동일하게 나타났다. 따라서 이 연구에서 제안한 UDM은 기후변화 영향평가에서의 불확실성 이해와 적합한 분석 및 미래 기후변화 대비 보다 나은 수자원 전망이 가능하도록 기여할 것으로 판단된다.

• 한국기후변화학회지
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• 제7권4호
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• pp.407-419
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• 2016

The low flow is the necessary and important index to establish national water planning, however there are lots of uncertainty in the low flow estimation. Therefore, the objectives of this study are to assess the climate change uncertainty and the effects of hydrological models on low flow estimation. The 5 RCMs (HadGEM3-RA, RegCM4, MM5, WRF, and RSM), 5 statistical post-processing methods and 2 hydrological models were applied for evaluation. The study area were selected as Chungju dam and Soyang river dam basin, and the 30 days minimum flow is used for the low flow evaluation. The results of the uncertainty analysis showed that the hydrological model was the largest source of uncertainty about 41.5% in the low flow projection. The uncertainty of hydrological model is higher than the other steps (RCM, statistical post-processing). Also, VIC model is more sensitive for climate change compared to SWAT model. Therefore, the hydrological model should be thoroughly reviewed for the climate change impact assessment on low flow.

• Communications for Statistical Applications and Methods
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• 제27권1호
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• pp.109-128
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• 2020

A climate-impact projection usually consists of several stages, and the uncertainty of the projection is known to be quite large. It is necessary to assess how much each stage contributed to the uncertainty. We call an uncertainty quantification method in which relative contribution of each stage can be evaluated as uncertainty decomposition. We propose a new Bayesian model for uncertainty decomposition in climate change impact assessments. The proposed Bayesian model can incorporate uncertainty of natural variability and utilize data in control period. We provide a simple and efficient Gibbs sampling algorithm using the auxiliary variable technique. We compare the proposed method with other existing uncertainty decomposition methods by analyzing streamflow data for Yongdam Dam basin located at Geum River in South Korea.

• Nuclear Engineering and Technology
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• 제33권3호
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• pp.270-282
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• 2001

A simple measure of uncertainty importance based on normalized metric distance to quantify the entire change of cumulative distribution functions (CDFs) has been developed for use in probability safety assessments (PSAs). The metric distance measure developed in this study reflects the relative impact of distributional changes of inputs on the change of an output distribution, white most of the existing uncertainty importance measures reflect the magnitude of relative contribution of input uncertainties to the output uncertainty. Normalization is made to make the metric distance measure a dimensionless quantity. The present measure has been evaluated analytically for various analytical distributions to examine its characteristics. To illustrate the applicability and strength of the present measure, two examples are provided. The first example is an application of the present measure to a typical problem of a system fault tree analysis and the second one is for a hypothetical non-linear model. Comparisons of the present result with those obtained by existing uncertainty importance measures show that the metric distance measure is a useful tool to express the measure of uncertainty importance in terms of the relative impact of distributional changes of inputs on the change of an output distribution.

• Journal of Forest and Environmental Science
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• 제33권4호
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• pp.295-304
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• 2017

This study compared and analyzed the construction of a land use change matrix for the Intergovernmental Panel on Climate Change's (IPCC) land use, land use change, and forestry area (LULUCF). We used National Forest Inventory (NFI) permanent sample plots (with a sample intensity of 4 km) and permanent sample plots with 500 m sampling intensity. The land use change matrix was formed using the point sampling method, Level-2 Land Cover Maps, and forest aerial photographs (3rd and 4th series). The land use change matrix using the land cover map indicated that the annual change in area was the highest for forests and cropland; the cropland area decreased over time. We evaluated the uncertainty of the land use change matrix. Our results indicated that the forest land use, which had the most sampling, had the lowest uncertainty, while the grassland and wetlands had the highest uncertainty and the least sampling. The uncertainty was higher for the 4 km sampling intensity than for the 500 m sampling intensity, which indicates the importance of selecting the appropriate sample size when constructing a national land use change matrix.

• 한국신뢰성학회지:신뢰성응용연구
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• 제3권1호
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• pp.83-92
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• 2003

We studied the trend change of failure rate function and uncertainty of residual life function in terms of location of their trend change points. It is shown that the trend change of uncertainty of residual life takes place before the failure rate changes its trend. Like DIFR(IDFR) does not necessary implies IDMRL(DIMRL), we find the fact that DIFR(IDFR) does not always imply IDURL(DIURL) under certain conditions, through the exponentiated-weibull distribution.

• Child Health Nursing Research
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• 제4권2호
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• pp.207-220
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• 1998

The purpose of this study was to build a substantive theory about the experience of the maternal uncertainty in childhood chronic illness. The qualitative research method used was grounded theory. The interviewees were 12 mothers who have cared for a child who had chronic illness. The data were collected through in-depth interviews with audiotape recording done by the investigator over a period of nine months. The data were analyzed simutaneously by a constant comparative method in which new data were continuously coded into categories and properties according to Strauss and Corbin's methodology. The 34 concepts were identified as a result of analyzing the grounded data. Ten categories emerged from the analysis. The categories were lack of clarity, unpredictability, unfamiliarity, negative change, anxiety, devotion normalization and burn-out. Causal conditions included : lack of clarity, unpredictability, unfamiliarity and change ; central phenomena : anxiety, being perplexed ; context. seriousness of illness, support ; intervening condition : belief action/interaction strategies devotion, overprotection ; consequences : normalization, burn-out. These categories were synthesized into the core concept-anxiety. The process of experiencing uncertainty was 1) Entering the world of uncertainty, 2) Struggling in the tunnel of uncertainty, 3) Reconstruction of the situation of uncertainty. Four hypotheses were derived from the analysis : (1) The higher the lack of clarity, unpredictability, unfamiliaity, change, the higher the level of uncertainty (2) The more serious the illness and the less the support, the higher the level of uncertainty. (3) The positive believes will influence the devoted care and normalization of the family life. Through this substantive theory, pediatric nurses can understand the process of experiencing maternal uncertainty in childhood chronic illness. Further research to build substantive theories to explain other uncertainties may contribute to a formal theory of how normalization is achieved in the family with chronically ill child.

• 한국기후변화학회지
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• 제6권1호
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• pp.33-40
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• 2015

Forests are to be recognized as an important carbon sink under the UNFCCC that consist of above- and below-biomass, dead organic matter (DOM) such as dead wood and litter, and soil organic matter (SOM). In order to asses for DOM and SOM, however, it is relevant to land-use change matrices over last 20 years for each land-use category. In this study, a land-use change matrix was produced and its uncertainty was assessed using a point sampling technique with permanent sample plots in national forest inventory at Chungbuk province. With point sampling estimated areas at 2012 year for each land-use category were significantly similar to the true areas by given six land-use categories. Relative standard error in terms of uncertainty of land-use change among land-use categories ranged in 4.3~44.4%, excluding the other land. Forest and cropland covered relatively large areas showed lower uncertainty compared to the other land-use categories. This result showed that selected permanent samples in the NFI are able to support for producing land-use change matrix at a national or province level. If the $6^{th}$ NFI data are fully collected, the uncertainty of estimated area should be improved.

• 한국수자원학회논문집
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• 제49권8호
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• pp.657-671
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• 2016

전지구적으로 발생하는 기후변화로 인해 수자원의 시공간적 변화를 야기할 것으로 전망된다. 기후변화에 따른 수자원의 영향을 정량적으로 평가하고 그에 적응할 수 있는 수자원 관리 방안이 필요하다. 하지만 영향평가 시 많은 불확실성이 발생하기 때문에 평가 시 발생하는 불확실성을 정량적으로 평가할 수 있는 기술 개발이 요구된다. 본 연구에서는 기후변화에 따른 수자원 영향평가 시 발생하는 불확실성을 단계별로 평가할 수 있는 기법을 개발하였으며, 지역기후모형, 통계적 후처리기법, 수문모형에 따른 불확실성을 분석하였다. 평가를 위해 5개 지역기후모형, 5개 통계적 후처리기법과 2개 수문모형을 이용하였다. 불확실성의 요인을 분석한 결과 유출량의 경우 겨울철을 제외한 모든 계절에서 RCM의 불확실성이 29.3~8.9%로 가장 큰 비중을 차지하는 것으로 나타났으나, 겨울철은 수문모형의 불확실성이 46.5%를 차지하는 것으로 나타났다. 증발산량의 경우 가을철을 제외하고 수문모형의 불확실성이 28.5~5.1%로 가장 큰 비중을 차지하였다. 따라서 이수기는 수문모형에 더욱 영향이 큰 것으로 나타났으며, 홍수기는 기후 모델링 부분의 영향이 큰 것으로 사료된다. 이 기법을 통해 특정 RCM이나 통계적 후처리기법, 수문모형 등의 선정에 따라 전체 불확실성이 어떻게 변화될 수 있는지를 분석할 수 있으며, 이를 통해 불확실성을 저감할 수 있는 방안을 마련할 수 있을 것으로 기대된다.