• Journal of Wetlands Research
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• v.21 no.2
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• pp.157-162
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• 2019

Recently, the occurrence of unusual heavy snow and cold are increasing due to the unusual global climate change. In particular, the temperature dropped to minus 69 degrees Celsius in the United States on January 8, 2018. In Korea, on February 17, 2014, the auditorium building in Gyeongju Mauna Resort was collapsed due to the heavy snowfall. Because of the tragic accident many studies on the reduction of snow damage is being conducted, but it is difficult to predict the exact damage due to the lack of historical damage data, and uncertainty of meteorological data due to the long distance between the damaged area and the observatory. Therefore, in this study, available data were collected from factors that are thought to be corresponding to snow damage, and the amount of snow damage was estimated categorically using a random forest. At present, the prediction accuracy was not sufficient due to lack of historical damage data and changes of the design code for green houses. However, if accurate weather data are obtained in the affected areas. the accuracy of estimates would increase enough for being used for be the degree preparedness of disaster management.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.516-516
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• 2016

기후변화는 농업생산량 감소와 식량 안보 문제와 같이 농업에 심각한 영향을 미칠 수 있다. 또한 기존의 농업수리 및 관개배수 시설 운영에 영향을 줄 수 있다. 따라서 지속가능한 농업 수자원 관리를 위해서는 기후변화의 영향을 고려한 장기적인 계획 수립이 필요하다. 따라서 본 연구에서는 논벼 지역의 설계용수량의 확률론적 분석을 통한 논벼 필요수량 및 설계용수량에 대한 기후변화영향 평가를 실시하였다. 이를 위해서 본 연구에서는 23개 GCM의 36개 산출물을 활용하여 Multi-model ensemble 구축하였다. 먼저 GCM별 증발산량과 유효우량을 산정한 결과 중부지역에서는 IPSL-CM5A 모델의 기후변화자료를 활용할 경우 증발산량과 유효우량이 타 GCM 모델들과 비하여 크게 산정되었다. 남부지역에서는 CanESM2 모델을 적용할 경우 가장 많은 증발산량과 유효우량이 모의되는 것으로 나타났다. 이처럼 GCM별로 다양한 결과가 모의되기 때문에 농업시설 설계에 적용되는 설계용수량의 경우 안전성을 위하여 Multi-GCM models을 활용할 필요가 있다. Multi-model ensemble의 RCP 4.5와 RCP 8.5 시나리오를 적용한 결과, 모든 경우에서 1995s(1981-2014)에 비해 설계용수량은 점차적으로 증가하는 것으로 나타났다. 평균 증가율은 RCP 4.5에서 중부지역이 9.4%, 남부지역이 6.0% 증가하는 것으로 나타난 반면, RCP 8.5에서는 중부지역이 11.1%, 남부지역이 8.2% 증가하는 것으로 나타났다. 또한 여러 GCM 산출물간의 불확실성은 RCP 4.5보다는 RCP 8.5 시나리오가, 중부 지역보다는 남부 지역이, 논벼 증발산량 보다는 유효우량이 더 큰 것으로 분석되었다. 본 연구는 향후 미래 가뭄 위험성을 최소화하기 위한 농업 수자원관리 전략수립에 활용될 수 있을 것이다. 또한 본 연구결과는 기후변화 영향 평가에 있어서 적합한 GCM 자료를 선택하는데 있어, 불확실성을 가늠할 수 있는 유용한 척도로 이용될 수 있을 것으로 기대된다.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.309-315
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• 2021

Risks and uncertainty are unavoidable problems in management of projects. Therefore, project managers should not only prevent risks, but also have to respond and manage them. Risk management has become a critical interest subject in the construction industry for both practitioners and researchers. This paper presents critical risk factors of office building projects in the construction phase in Ho Chi Minh City, Vietnam. Data was collected through a questionnaire survey based on the likelihood and consequence level of risk factors. These factors fell into five groups: (i) financial risk factors; (ii) management risk factors; (iii) schedule risk factors; (iv) construction risk factors; and (v) environment risk factors. The research results showed that critical factors affecting office building projects are natural (i.e., prolonged rain, storms, climate effects) and human-made issues (i.e., soil instability, safety behaviors, owner's design change) and the schedule-related risk factors contributed to the most significant risks for office buildings projects in the construction phase in Ho Chi Minh City. They give construction management and project management practitioners a new perspective on risks and risk management of office buildings projects in Ho Chi Minh City and are proactive in the awareness, response, and management of risk factors comprehensively.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.5
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• pp.1-13
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• 2022

The damages caused by landslides are increasing worldwide due to climate change. In Korea, damages from landslides occur frequently, making it necessary to develop the effective response strategies. In particular, there is a lack of countermeasures against landslides in cultural heritage areas. The purpose of this study was to spatially analyze the relationship between Buyeo-gun's cultural heritage and landslide susceptible areas in Buyeo-gun, Chungcheongnam-do, which has a long history. Nine spatial distribution models were used to evaluate the landslide susceptibility, and the ensemble method was applied to reduce the uncertainty of individual model. There were 17 cultural heritages belonging to the landslide susceptible area. As a result of calculating the area ratio of the landslide susceptible area for cultural heritages, the cultural heritages with 100% of the area included in the landslide susceptible area were "Standing statue of Maae in Hongsan Sangcheon-ri" and "Statue of King Seonjo." More than 35% of "Jeungsanseong", "Garimseong", and "Standing stone statue of Maitreya Bodhisattva in Daejosa Temple" belonged to landslide susceptible areas. In order to effectively prevent landslide damage, the application of landslide prevention measures should be prioritized according to the proportion belonging to the landslide susceptible area. Since it is very difficult to restore cultural properties once destroyed, preventive measures are required before landslide damage occurs. The approach and results of this study provide basic data and guidelines for disaster response plans to prevent landslides in Buyeo-gun.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.1
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• pp.33-41
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• 2023

Recently, global warming has accelerated climate change, increased extreme weather phenomena, and increased the frequency and intensity of weather disasters, leading to increasing uncertainty about the power production of new and renewable energy that is sensitive to weather. In fact, it has been reported that a number of damage to hydroelectric power generation have occurred due to weather disasters. Therefore, using the hydroelectric power generation performance data of Chungju Dam, meteorological data of Chungju Meteorological Observatory, and operation data of Chungju Dam, this study investigated the effect of meteorological disasters on hydroelectric power generation through structural equation modeling considering the number and intensity of meteorological disasters per month. The results indicated that the increased drought occurrence affected the decreased hydroelectric power generation by about 38.3 %, however the increased hydroelectric power generation could not explained by the increased flood occurrence. In conclusion, an increased drought occurrence in future may significantly influence hydroelectric power generation.

• Journal of Korea Water Resources Association
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• v.45 no.5
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• pp.505-516
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• 2012

The study applies a hydrologic simulation model, HEC-1 developed by Hydrologic Engineering Center to Daecheong dam watershed for modeling hourly inflows of Daecheong dam. Although the HEC-1 model provides an automatic optimization technique for some of the parameters, the built-in optimization model is not sufficient in estimating reliable parameters. In particular, the optimization model often fails to estimate the parameters when a large number of parameters exist. In this regard, a main objective of this study is to develop Bayesian Markov Chain Monte Carlo simulation based HEC-1 model (BHEC-1). The Clark IUH method for transformation of precipitation excess to runoff and the soil conservation service runoff curve method for abstractions were used in Bayesian Monte Carlo simulation. Simulations of runoff at the Daecheong station in the HEC-1 model under Bayesian optimization scheme allow the posterior probability distributions of the hydrograph thus providing uncertainties in rainfall-runoff process. The proposed model showed a powerful performance in terms of estimating model parameters and deriving full uncertainties so that the model can be applied to various hydrologic problems such as frequency curve derivation, dam risk analysis and climate change study.

• Journal of Korea Water Resources Association
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• v.42 no.7
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• pp.547-558
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• 2009

General reliability assessment of levees embankment is performed with safety factors for rainfall characteristics and hydrologic and hydraulic parameters, based on the results of deterministic analysis. The safety factors are widely employed in the field of engineering handling model parameters and the diversity of material properties, but cannot explain every natural phenomenon. Uncertainty of flood analysis and related parameters by introducing stochastic method rather than deterministic scheme will be required to deal with extreme weather and unprecedented flood due to recent climate change. As a consequence, stochastic-method-based measures considering parameter uncertainty and related factors are being established. In this study, a variety of dimensionless cumulative rainfall curve for typhoon and monsoon season of July to September with generation method of stochastic temporal variation is generated by introducing Monte Carlo method and applied to the risk assessment of levee embankment using reliability index. The result of this study reflecting temporal and regional characteristics of a rainfall can be used for the establishment of flood defence measures, hydraulic structure design and analysis on a watershed.

• Journal of Korea Water Resources Association
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• v.41 no.3
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• pp.341-351
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• 2008

Since the damage from the torrential rain increases recently due to climate change and global warming, the significance of flood forecasting and warning becomes important in medium and small streams as well as large river. Through the preprocess and main processes for estimating runoff, diverse errors occur and are accumulated, so that the outcome contains the errors in the existing flood forecasting and warning method. And estimating the parameters needed for runoff models requires a lot of data and the processes contain various uncertainty. In order to overcome the difficulties of the existing flood forecasting and warning system and the uncertainty problem, ANFIS(Adaptive Neuro-Fuzzy Inference System) technique has been presented in this study. ANFIS, a data driven model using the fuzzy inference theory with neural network, can forecast stream level only by using the precipitation and stream level data in catchment without using a lot of physical data that are necessary in existing physical model. Time series data for precipitation and stream level are used as input, and stream levels for t+1, t+2, and t+3 are forecasted with this model. The applicability and the appropriateness of the model is examined by actual rainfall and stream level data from 2003 to 2005 in the Tancheon catchment area. The results of applying ANFIS to the Tancheon catchment area for the actual data show that the stream level can be simulated without large error.

• Journal of Korea Water Resources Association
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• v.47 no.1
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• pp.83-93
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• 2014

This research was carried out for suggesting design criteria and procedure for maximizing flood control capacity by building flood control facilities like flood retention basin built in connection with existing facilities in order to cope with increased uncertainty due to factors such as urbanization and climate change. We suggested the procedure for the analysis under the various scenarios applicable for the cases of determining retention basin capacity as provision for the flood water level increase in main river channel or estimating flood water level reduction effect when retention basin capacity is given. Procedure for estimating design flood hydrograph at any duration using Intensity-Duration-Quantity (IDQ) originated from the existing IDF, and its application example were provided. Based on rainfall estimated by the IDQ analysis, it is possible to calculate an equivalent peak hydrographs under various scenarios, e.g. lower frequency hydrograph under same rainfall duration with water level higher than existing hydrograph, hydrograph with same peak and higher volume due to increased rainfall duration, hydrograph with higher peak and volume than existing hydrograph, etc.

• Journal of Korea Water Resources Association
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• v.54 no.6
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• pp.365-379
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• 2021

Hydrological model parameters are essential for model simulation and can vary over time due to topography, climatic conditions, climate change and human activity. Consequently, the use of fixed parameters can lead to inaccurate stream flow simulations. The aim of this study is to investigate an appropriate method of estimating time-varying parameters using stream flow observations, and how the simulation efficiency changes when stream flow data are assimilated into the model. The data assimilation method can be used to automatically estimate the parameters of a hydrological model by adapting to a variety of changing environments. Stream flow observations were assimilated into a two parameter monthly water balance model using a particle filter. The simulation results using the time-varying parameters by the data assimilation method were compared with the simulation results using the fixed parameters by the SCEM method. First, we conducted synthesis experiments based on various scenarios to investigate if the particle filter method can adequately track parameters that change over time. After that, it was applied to actual watersheds and compared with the predictive performance of stream flow when using parameters that change with time and fixed parameters. The conclusions obtained through this study are as follows: (1) The predictive performance of the overall monthly stream flow time series was similar between the particle filter method and the SCEM method. (2) The monthly runoff prediction performance in the period except the rainy season was better in the simulation by the periodically changing parameters using the data assimilation method. (3) Uncertainty in the observational data of stream flow used for assimilation played an important role in the predictive performance of the particle filter.