• Journal of the Korean Society of Hazard Mitigation
• /
• v.9 no.6
• /
• pp.77-87
• /
• 2009

Potential risks of communicable disease outbreaks have significantly increased in the era of global society. However, contingency planning of local governments for communicable diseases is not prepared to the proper level in various governmental sectors of many countries. Human being has been remarkable advances in medical science and public health. However, Severe Acute Respiratory Syndrome (SARS) still remains as a very dangerous transmissible disease that has great potential to create catastrophic consequences of casualties. The SARS outbreak between November 2002 and July 2003 resulted in 8,096 known infected cases and 774 deaths with a mortality rate of 9.6% worldwide (WHO, 2004). It is regarded as one of the human health disasters. Since about sixty-six percent of total SARS cases in the world were reported in People's Republic of China, Korean tour industry was significantly affected as a neighboring country. The objective of this research is to investigate major factors of Korea entry data sets, and to analyze economic impacts of Korean tour business interruption due to the period of SARS outbreak with tourist cases of four countries: Japan, U.S.A., China, and Taiwan. Results from this research show the seasonal and long-term trends of entry data sets of four countries, and direct and indirect impacts of SARS to Korean tour industry.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2019.05a
• /
• pp.387-387
• /
• 2019

우리나라는 최근 10년간 자연재난 중 호우로 인해 인명피해 약 120명, 재산피해 약 1조 4천억원을 기록하였으며, 또한 기후변화로 인해 강한 국지성 집중호우의 발생빈도가 높아질 것으로 예상됨에 따라 호우에 의한 침수피해가 증가될 것으로 예상된다. 특히 본 연구 대상지역인 인천시의 경우 도시화로 인해 인구밀도 및 불투수지역이 증가함에 따라 침수피해가 대형화되고 있는 실정이다. 이에 본 연구에서는 인천시와 같은 도심지역에서의 침수발생을 사전에 예측하고 침수발생에 대한 대비 대응을 위해 하수관망 해석을 위한 SWMM 모델과 침수해석을 위한 2DIS 모델을 연계하여 인천시 침수심 생산체계를 구축하고자 한다. 본 연구에 적용한 침수심 생산과정은 크게 강우자료 생산, 유역 및 하수관망 해석, 침수 해석 등 총 3단계 과정으로 구성된다. 강우자료 생산과정에서는 유역 및 하수관망 해석과 침수 해석을 위한 10분 단위 유역평균 강우량자료를 생산한다. 유역 및 하수관망 해석과정에서는 지형자료 및 강우자료를 이용하여 SWMM 모델을 통해 맨홀에서의 월류량 자료를 생산한다. 마지막으로 침수해석과정에서는 지형자료와 함께 앞서 두 과정을 통해 생산된 강우 및 맨홀 월류량 자료를 입력자료로 하여 2DIS 모델을 통해 10분 단위의 시계열 침수심 정보 및 격자별 최대 침수심정보를 생산한다. 본 연구에서의 공간해상도는 도심지역의 도로단위 고해상도 침수심 정보 생산을 위해 6m 단위로 하였으며, 시간해상도는 단시간에 발생하는 도심지역의 침수특성 반영을 위해 10분으로 하였다. 또한, 침수발생 시 발생한 강우의 지표흐름 영향을 반영하기 위해 빗물받이효율 변화에 다른 침수심을 분석하였다. 본 연구를 통해 도출된 모의 침수심 결과를 실제 침수피해사례 및 풍수해저감종합계획 결과와 비교하였으며, 다수 지역에서 실제 침수발생지역과 동일하게 침수가 발생한 것으로 나타났다. 또한, 전체적인 침수 양상이 유사하게 발생함을 확인하였다. 향후 관측자료를 이용한 하수관망 및 침수해석 모델의 최적화, 하천유량 예측을 통한 하류 기점수위의 반영 등을 통해 정확도를 개선할 수 있을 것으로 판단되며, 이를 통해 인천시 침수발생을 사전에 예측하여 침수피해에 대비 및 대응과 침수피해 발생 시 정확하고 상세한 원인 분석 및 예측이 가능할 것으로 기대된다.

• Maritime Security
• /
• v.1 no.1
• /
• pp.311-343
• /
• 2020

Because of the global warming, the Arctic Ocean is expected to be ice-free by the year 2035. When the Arctic Ocean will be opened, a number of national interests will become more salient as experiencing a shortened sailing distance and decreasing navigation expense, possibility of natural resources transport by sea from Arctic Circle, and indirect-profit making by building a herb port in Asia. To secure the national interests and support the free activities of people in this region, R.O.K government is trying to make advanced policies. In order to carry out the naval tasks in the Arctic Ocean, using the operational characteristics(mobility, flexibility, sustainability, presence of capabilities, projection) is necessary. To this end, ROK Navy should analyze the operational environment (O.E.) by its capability(weakness and strength), opportunity, and threat. R.O.K. Navy should make an effort over the following issues to implement the tasks in the Arctic Ocean: first, Navy needs to map out her own plan (Roadmap) under the direction of government policies and makes crews participate in the education·training programs in home and abroad for future polar experts. Third, to develop the forces and materials for the tasks in cold, far operations area, Navy should use domestic well-experienced shipbuilding skills and techniques of the fourth industrial revolution. Next, improving the combined operations capabilities and military trust with other countries in the Arctic region to cover the large area with lack of forces' number and to resolve the ports of call issues. Lastly, preparation in advance to execute a variety of missions against military and non-traditional threats such as epidemics, HA/DR, SOLAS, in the future operation area is required.

• Journal of Korea Water Resources Association
• /
• v.54 no.spc1
• /
• pp.1107-1118
• /
• 2021

Climate change brought on by global warming increased the frequency of flood and drought on the Korean Peninsula, along with the casualties and physical damage resulting therefrom. Preparation and response to these water disasters requires national-level planning for water resource management. In addition, watershed-level management of water resources requires flow duration curves (FDC) derived from continuous data based on long-term observations. Traditionally, in water resource studies, physical rainfall-runoff models are widely used to generate duration curves. However, a number of recent studies explored the use of data-based deep learning techniques for runoff prediction. Physical models produce hydraulically and hydrologically reliable results. However, these models require a high level of understanding and may also take longer to operate. On the other hand, data-based deep-learning techniques offer the benefit if less input data requirement and shorter operation time. However, the relationship between input and output data is processed in a black box, making it impossible to consider hydraulic and hydrological characteristics. This study chose one from each category. For the physical model, this study calculated long-term data without missing data using parameter calibration of the Soil Water Assessment Tool (SWAT), a physical model tested for its applicability in Korea and other countries. The data was used as training data for the Long Short-Term Memory (LSTM) data-based deep learning technique. An anlysis of the time-series data fond that, during the calibration period (2017-18), the Nash-Sutcliffe Efficiency (NSE) and the determinanation coefficient for fit comparison were high at 0.04 and 0.03, respectively, indicating that the SWAT results are superior to the LSTM results. In addition, the annual time-series data from the models were sorted in the descending order, and the resulting flow duration curves were compared with the duration curves based on the observed flow, and the NSE for the SWAT and the LSTM models were 0.95 and 0.91, respectively, and the determination coefficients were 0.96 and 0.92, respectively. The findings indicate that both models yield good performance. Even though the LSTM requires improved simulation accuracy in the low flow sections, the LSTM appears to be widely applicable to calculating flow duration curves for large basins that require longer time for model development and operation due to vast data input, and non-measured basins with insufficient input data.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.17 no.4
• /
• pp.200-214
• /
• 2014

Technology planning is becoming increasingly important with the rapid development and decline of technology. Technology roadmapping is a tool used to select whether the specific technique of technology planning should pursue which technology and in which time. This technology is important to secure the uncertain future since it will provide a method that is able to share the goals and strategies between organizations. Therefore, technology tree in the planning stage of the problem would be a very useful tool. In this study, both domestic and international technology tree application cases were analyzed to be able to derive a plan for ensuring that the research performed and the requirements are met for the future development and implementation of a convergence portal system. The six major systems that aim at water hazard information platform are basic information providing system, analysis information providing system, water disaster theme providing system, national disaster information system, water disaster augmented reality system and open information platform system. General standardized core technologies corresponding to the needed functions in each target system are derived through brainstorming, and classified according to the technology field to derive the technology tree.

• Journal of Korea Water Resources Association
• /
• v.54 no.3
• /
• pp.145-156
• /
• 2021

Forest fires have frequently occurred around the world, and the damages are increasing. In Korea, most forest fires are initiated by human activities, but climate factors such as temperature, humidity, and wind speed have a great impact on combustion environment of forest fires. In this study, therefore, based on statistics of forest fires in Gyeonggi-do over the past five years, meteorological and hydrological factors (i.e., temperature, humidity, wind speed, precipitation, and drought) were selected in order to quantitatively investigate causal relationships with forest fire. We applied a partial least squares structural equation model (PLS-SEM), which is suitable for analyzing causality and predicting latent variables. The overall results indicated that the measurement and structural models of the PLS-SEM were statistically significant for all evaluation criteria, and meteorological factors such as humidity, temperature, and wind speed affected by amount of -0.42, 0.23 and 0.15 of standardized path coefficient, respectively, on forest fires, whereas hydrological factor such as drought had an effect of 0.23 on forest fires. Therefore, as a practical method, the suggested model can be used for analyzing and evaluating influencing factors of forest fire and also for planning response and preparation of forest fire disasters.

• Journal of Korean Society of societal Security
• /
• v.4 no.2
• /
• pp.73-78
• /
• 2011

In order to resolve the problem of change in global climate which is worsening as days go by and to preemptively cope with strengthened restriction on carbon emission, the government enacted 'Framework Act on Low Carbon Green Growth' in 2010 and selected green technology and green industry as new national growth engines. For this reason, the necessity to use the un-utilized waste heat across the whole industrial system has become an issue, and studies on and applications of recycling in the agricultural and fishery fields such as cultivation of tropical crops and flatfishes by utilizing the waste heat and thermal effluent generated by large industrial complexes including power plants are being actively carried out. In this study, we looked into the domestic and overseas examples of having utilized waste heat abandoned in the form of power plant thermal effluent, and carried out economic efficiency evaluation of sturgeon aquaculture utilizing thermal effluent of Yeongwol LNG Combined Cycle Power Plant in Gangwon-do. In this analysis, we analyzed the economic efficiency of a model business plan divided into three steps, starting from a small scale in order to minimize the investment risk and financial burden, which is then gradually expanded. The business operation period was assumed to be 10 years (2012~2021), and the NVP (Net Present Value) and economic efficiency (B/C) for the operation period (10 years) were estimated for different loan size by dividing the size of external loan by stage into 80% and 40% based on the basic statistics secured through a site survey. Through the result of analysis, we can see that reducing the size of the external loan is an important factor in securing greater economic efficiency as, while the B/C is 1.79 in the case the external loan is 80% of the total investment, it is presumed to be improved to 1.81 when the loan is 40%. As the findings of this study showed that the economic efficiency of sturgeon aquaculture utilizing thermal effluent of power plant can be secured, it is presumed that regional development project items with high added value can be derived though this, and, in addition, this study will greatly contribute to reinforcement of the capability of local governments to cope with climate change.

• Journal of Korea Water Resources Association
• /
• v.54 no.spc1
• /
• pp.1095-1105
• /
• 2021

The advancement of dam operation is further required due to the upcoming rainy season, typhoons, or torrential rains. Besides, physical models based on specific rules may sometimes have limitations in controlling the release discharge of dam due to inherent uncertainty and complex factors. This study aims to forecast the water level of the nearest station to the dam multi-timestep-ahead and evaluate the availability when it makes a decision for a release discharge of dam based on LSTM (Long Short-Term Memory) of deep learning. The LSTM model was trained and tested on eight data sets with a 1-hour temporal resolution, including primary data used in the dam operation and downstream water level station data about 13 years (2009~2021). The trained model forecasted the water level time series divided by the six lead times: 1, 3, 6, 9, 12, 18-hours, and compared and analyzed with the observed data. As a result, the prediction results of the 1-hour ahead exhibited the best performance for all cases with an average accuracy of MAE of 0.01m, RMSE of 0.015 m, and NSE of 0.99, respectively. In addition, as the lead time increases, the predictive performance of the model tends to decrease slightly. The model may similarly estimate and reliably predicts the temporal pattern of the observed water level. Thus, it is judged that the LSTM model could produce predictive data by extracting the characteristics of complex hydrological non-linear data and can be used to determine the amount of release discharge from the dam when simulating the operation of the dam.

• Journal of Korea Water Resources Association
• /
• v.56 no.2
• /
• pp.75-89
• /
• 2023

As the Mekong River basin is a nationally shared river, it is difficult to collect precipitation data, and the quantitative and qualitative quality of the data sets differs from country to country, which may increase the uncertainty of hydrological analysis results. Recently, with the development of remote sensing technology, it has become easier to obtain grid-based precipitation products(GPPs), and various hydrological analysis studies have been conducted in unmeasured or large watersheds using GPPs. In this study, rainfall-runoff simulation in the Mekong River basin was conducted using the SWAT model, which is a quasi-distribution model with three satellite GPPs (TRMM, GSMaP, PERSIANN-CDR) and two GPPs (APHRODITE, GPCC). Four water level stations, Luang Prabang, Pakse, Stung Treng, and Kratie, which are major outlets of the main Mekong River, were selected, and the parameters of the SWAT model were calibrated using APHRODITE as an observation value for the period from 2001 to 2011 and runoff simulations were verified for the period form 2012 to 2013. In addition, using the ConvAE, a convolutional neural network model, spatio-temporal correction of original satellite precipitation products was performed, and rainfall-runoff performances were compared before and after correction of satellite precipitation products. The original satellite precipitation products and GPCC showed a quantitatively under- or over-estimated or spatially very different pattern compared to APHPRODITE, whereas, in the case of satellite precipitation prodcuts corrected using ConvAE, spatial correlation was dramatically improved. In the case of runoff simulation, the runoff simulation results using the satellite precipitation products corrected by ConvAE for all the outlets have significantly improved accuracy than the runoff results using original satellite precipitation products. Therefore, the bias correction technique using the ConvAE technique presented in this study can be applied in various hydrological analysis for large watersheds where rain guage network is not dense.