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Smart city in water resources area attempts are being made by establishing an integrated urban water cycle model for a stable water supply and efficient water management in the city. Accordingly, the need for simulation and integrated management of water consumption in cities is increasing. If it is possible to predict and respond in advance to consumers' water consumption, more efficient urban water resource management will be possible based on river intake. Therefore, in this study, an integrated urban water cycle model was constructed that links river intake, water purification plants, retention tanks, water distribution, sewage pipe networks, sewage treatment plants, and river discharge of treated water. It was developed using C++, and was built by linking the modules of the water intake pump station, retention tank, water purification plant, sewage treatment plant, water supply pipe network, and the sewage pipe network. Among them, the water intake pumping station and retention tank were developed independently, and the other modules were linked with commercial software such as WaterFlow, MassFlow, EPANET, and SWMM. The model measures data such as water quality factors and flow rates for each module, displays the operation status, and enables linkage for each module, even when the measurement time interval is different. In addition, warnings and error messages were generated when a problem occurred during the operation of each module. To verify the applicability of the developed integrated model, the change in the water level of the retention tank was calculated by simulating consumer water consumption. As a result, it was confirmed that the water level change in the retention tank was proper, which meant that the operation changed from the intake pumping station. The developed model is expected to be used as an integrated urban water cycle model in the future.

The number of traffic and fatal accidents caused by road icing in winter has been increasing every year. Since traffic accidents on frozen sections of road can cause serious human and material damage, comprehensive measures are required. To reduce the damage caused by freezing sections in winter in Gangwon-do, this study developed damage prediction technology using data from past damage cases. Traffic accident data on frost and freezing road conditions from 2007 to 2018 were used, and the technology was developed mainly in Gangwon-do. A logistic regression model was implemented for predicting the presence or absence of damage. Variables were selected through the variable selection method and correlation and comparative analyses were conducted. The model developed using the variable selection method was 0.670, and the correlation was large. The model developed using variables showed 0.659. A preliminary preparation using the results of this study will be helpful in preparing for indirect damage caused by heavy snowfall and in decision-making of the relevant public officials.

In South Korea, the amount of snow depth during winter is less than 50 cm in many cities and no icecap exist. Therefore, runoff from snowpack is not a big problem in hydrology. However, still heavy snow damage is occurred sometimes and causes damage to wide area. Most damage caused by heavy snow is collapse of greenhouses or barns and traffic jam. However, sometimes people dead by the collapse of temporary buildings constructed by sandwich panel and barn. To reduce snow damage, accurate prediction of snow depth and spatial distribution are required. However, due to the lack of observation points for snow depth, it is hard to understand spatial distribution of snow. To describe more accurate spatial distribution of snow depth, two satellite images have been used to estimate snow depth using Differential Interferometric SAR (DInSAR). In this study, snow depth in a wide region in South Korea was estimated using two Sentinel images operated by the European Space Agency (ESA). As a result, observation points of snow depth could be suggested and the results will be helpful to understanding the damaged prone area. AcknowledgementThis work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. 202200610001)

Due to urban overcrowding, the population density of residential areas and water use per unit are increasing. Therefore, it is necessary to study the flow of water supplied to cities and to improve the healthy circulation of urban water. This study used Modelica, a non-causal analytical program. Using Open Modelica, the researchers constructed a model linking water distribution and sewerage, as the basis of a balanced urban water model. Using the programmer's toolkit provided by EPA-NET and EPA-SWMM, which are commonly used to simulate the existing water supply and sewage pipe networks, Open Modelica-based water distribution networks and sewage pipe networks can be connected and simulated based on the customer block. A model was built so that 90% of the hourly water consumption supplied to the water supply pipe network can be automatically introduced into the sewage pipe network. If a matching table is constructed to connect the nodes of the water supply pipe network and the sewer pipe network, the nodes will reflect in the graphical user interface (GUI) developed in Open Modelica. It was developed to enable modification of links, pumps, tanks, and valves. The 48-hour water supply was simulated using the developed model, and it was confirmed that water supply and sewage networks were successfully connected. In the future, we plan to develop a more expanded and realistic urban water circulation model by considering additional urban water circulation factors, such as sewage treatment, water reuse, rainwater use, storm runoff, and low-impact development facilities. Through this study, it was confirmed that Modelica can simulate changes in the system over time. Since it is a formula-based non-causal simulation language, it is possible to establish and reuse relationships between blocks through block-by-block development of urban water circulation elements. It is expected to contribute to the visualization and concretization of future urban water circulation models.

Global climate change has, in recent years, increased the frequency and intensity of meteorological disasters. In particular, damage to greenhouses caused by heavy snowfall continues to occur on farms in South Korea. Because heavy snowfall occurs over a relatively long time compared to other sudden meteorological disasters, if an appropriate warning system for heavy snowfall events is in place then damage to greenhouses can be prevented. However, the existing snowfall warning system in South Korea consists only of a simple alert that is unable to anticipate future risks to an area caused by heavy snowfall. In this study, the aim was to develop a stochastic alarm model to minimise the damage to greenhouses caused by heavy snowfall events. A Markov chain was designed to construct the alarm model using snowfall data from nationwide weather stations as well as from greenhouse standards with various safety criteria. The snow depth data were divided into several sections using a cluster analysis, and the failure probabilities of the greenhouses were derived for specific time interval according to current snow depth. This method considers the weather characteristics of each region as well as various greenhouse standards because the risks of heavy snowfall vary depending on location and type of the installation. Using the alarm model developed in this study, it is possible to predict and therefore manage the negative impacts of heavy snowfall events on greenhouses.

Research shows that disasters affect women more adversely than men especially in developing countries due to differences in socio-cultural customs or physical condition. However, in developed countries, not much difference was found in the percentage of male and female victims of disaster. In South Korea, disasters cause severe damage almost every year, thus the public interest in disaster and safety management is increasing. However, due to insufficient data, it is difficult to analyze whether women suffer more severely than men or not. Therefore, in this study, we reviewed Korea’s disaster management laws and guidelines. In addition, a questionnaire survey was implemented to analyze the level of the public awareness related to disasters and safety management. A total of 489 adults participated in the survey. As a result, it was found that both men and women were not well aware of the possibility of a disaster, and needed to be educated about the locations of shelters and evacuation procedures. Gender analysis showed significant differences in male and female responses concerning some questions. For example, women found it difficult to access disaster and safety management education. Nevertheless, men and women showed similar willingness to participate in disaster and safety management education and training. Therefore, disaster and safety management education programs should be developed and implemented more actively. In addition, it was suggested that sex and age of the victims should be reported and female investigators should be included in the disaster damage investigation team.

Snow vulnerability analysis was implemented using 400 years of controlled RCP 2.6, 4.5, 6.0, and 8.5 scenarios in the following divided periods: the former period (2011-2040), middle period (2041-2070), and later period (2071-2100). Data from a total of 74 meteorological stations were used and the Thiessen polygon method was applied in the areas without stations. The indicators were classified into the Pressure-State-Response (PSR) structure, and the weight for vulnerability analysis was calculated using the entropy method. As snow vulnerability analysis was implemented for the future scenarios, it was difficult to determine social and economic factors as indicators; thus, only predicted weather data and population trends were considered. As a result, the rankings for snow vulnerable areas were determined for each period and scenario. Overall, snow vulnerability would decrease due to the decrease in long-term heavy snowfall in climate change scenarios. However, increased snow vulnerability is also expected in Sejong-si and the western coastal area due to a rise in population and snow depth in the future. Based on this, disaster prevention projects considering the characteristics of the region in the future could be implemented.

Recently, snow disasters have been increased in South Korea due to the unexpected heavy snow in a region where winter gives little snow. For instance, 10 people were dead by the collapsed roof due to the unusual heavy snow. Many local governments do not have enough snow removal equipment because of little snow in winter season. Therefore, it has been important to estimate the amount of snow damage to prepare heavy snow disaster. There are not many researches to estimate damage of snow disaster in South Korea. In this study, historical snow damage data from 1994~2018 recorded in National Disaster Report were used to predict the future snow disaster damage using a statistical equation. However, it was not easy to predict the amount of snow damage when the heavy snow is happened in the area where no snow during the winter in history. Therefore, the relationship between the snow depth and damaged area were analyzed using the historical damage data. Principal multiple regression method was applied to develop the snow damage estimation function using the damaged area. The developed model could be applied to plan the budget for the snow removal equipment or snow damage reduction. Acknowledgement:This work was supported by Korea Environment Industry & Technology Institute (KEITI) through Intelligent Management Program for Urban Water Resources Project, funded by Korea Ministry of Environment(MOE) (2019002950002).

An analogue method (AM) is a nonparametric approach that has been applied to predict the future states of a dynamic system by following the evolution of the analogues in the historical archive. In this study, we proposed a hidden Markov model (HMM) framework for a modified analogue forecasting (MAF) approach for meteorological droughts in Korea. The unobservable (hidden) state process in the framework aims to model the underlying drought state, while the observation process was formed from the time series of the standardized precipitation index (SPI) as a drought index. Within the framework, the likelihood estimator was used as the measure of similarity between past SPI analogues and current data. The MAF approach was conducted on the selected analogues to make forecasts at lead times of one and three months. The proposed model was applied to five selected stations in Korea using the SPI data from 1973 to 2016. The forecasting performance of the proposed model was tested during the validation period (2003–2016) using several statistical criteria and it was compared to a persistence-based benchmark model. The results showed significant improvement in the forecasting capacity, and satisfactory performance for numerical SPI forecasting and categorical drought forecasting. The results also suggested that the proposed model was able to provide useful information for determining future drought categories for early drought warning with a lead time of up to three months.

Recently, domestic and external interest in regard to become underground of traffic tunnel is heightened due to the urbanization get at saturated network of roads. In addition, due to develop urban areas flood have occurred frequently, canal tunnel’s development to prevent the flood by bypassing flood discharge about flood-prone area is required. In this study, emergency response plans in the multipurpose tunnels were investigated from the related government report, websites, and previous researches. The investigated emergency response plans to cope with the natural disasters including flooding were compared to the South Korean’s cases. As a result, the problem of the water canal were explained and the disaster response policies were proposed based on the necessity of the consistency and sustainability for the disaster industry.

Due to the rapidly increased urbanization and climate change, impervious area becomes smaller and torrential rainfall is occurred frequently. These caused severe urban flood with severe property damages and human lives. To cope with the urban flood, pumping stations with retention/detention ponds have been constructed. Therefore, the pumping stations have to be included in the urban flooding system or rainfall-runoff systems for the accurate analysis, the uncertainty incurred by the rainfall-runoff models or input data and/or parameters caused difficulties. In this study, modified Pedigree matrix is proposed based on the original Pedigree matrix and input data and parameters which might cause the uncertainty in the systems are selected. The contribution is analyzed with the modified Pedigree matrix and uncertainty index. As a result, basin width and roughness of pervious and impervious areas have the highest contribution to the uncertainty and the more accurate estimation is required. The proposed results could be applied in the pumping station operations in the urban area.

Recently, global warming and climate change has been known as the main driving force of the extreme floods in urban area. Therefore, the flood and traffic problem should be solved simultaneously in the mega cities. The multi-functional tunnel with the road and stormwater bypass is suggested as one of the solutions. A single bored tunnel feasible by TBM machine has the double-deck road tunnel and stormwater bypass underneath. In the multi-functional tunnel, the shape of the stormwater bypass is usually not circular. Therefore, the friction loss in the non-circular pipe should be evaluated for the accurate design. In this study, hydraulic experiment was set and the friction loss coefficients were evaluated using 6 different Reynolds numbers. As the result, the difference between measured and computed friction loss coefficients become substantial when the Reynolds number is decreased less than 2,000 for the laminar flow. When the stormwater pipe using the non-circular shape is designed, the different friction loss coefficients should be applied for the accurate calculation.

In mega cities such as Seoul in South Korea, it is very important to protect the city from the flooding even for the short time of period due to the enormous amount of economic damage. In impervious area of the city, stormwater pipe network is commonly applied to discharge rainfall to the outside of catchment. Therefore, the stormwater pipe network in urban catchment should be carefully designed to discharge the runoff quickly and efficiently. In this study, different types of structures in stormwater pipe network were evaluated using the relationship between the peaks rainfall and runoff in urban catchments in South Korea. More than 400 historical rainfall events were applied in five urban catchments to estimate peak runoff from different type of network structures. Linear regression analysis was implemented to estimate peak runoffs. The coefficient of determination of the regressions were higher than 0.9 which means the regression model represent very well the relationship between the two peaks. However, the variation of the prediction becomes large as the peak rainfall increases and the variation become even larger when the network structure is branched. Therefore, it depends on the structure of stormwater pipe network. When the water paths in the pipe network is unique (branched network), the increased amount of rainfall is congested around the rainwater inlets and the uncertainty of peak runoff prediction is increased. If there are many possible water paths depending on the amount of discharge (looped network), the increased rainfall is discharged more quickly through the many water paths. This can be a way to represent the reliability of the stormwater pipe network. The structures of stormwater pipe network is evaluated using drainage density which is the length of pipes over the unit catchment area and 95% confidence interval. As a result, the 95% confidence interval is increased as the drainage density is increased because the accuracy of peak runoff prediction is decreased. As mentioned earlier, because the looped networks have many alternative water flowing paths, elimination time of rainfall from the catchments become short, the 95% confidence interval become narrow, and the reliability of peak runoff prediction become high. Therefore, it is beneficial to install looped stormwater pipe network within the affordable budget. It is important factor to determine the amount of complexity in stormwater pipe network to decrease the risk of urban flooding.

Due to the climate change, the natural disasters have been occurred more frequently and the amount of damage has been increased as well. In South Korea, the number of snow disaster has been increased recently. In last 20 years, from 1994 to 2013, total snow damage was 1.3 billion dollars. In this study, the snow damage was estimated using historical damage data to response the possible heavy snow and mitigate the damage. The historical snow damage data from Annual Natural Disaster Report for the last 22 years were used to develop a multiple linear regression model. Input data for the model were daily maximum snow depth (or daily maximum fresh snow depth), daily highest temperature, daily lowest temperature, daily average temperature, relative humidity as meteorological factors, and also regional area, greenhouse area, number of farmers, number of farmers over age 60 were considered as socioeconomic factors. The developed model was applied in Jeolla-do, Chungcheong-do, and Kangwon-do which have the largest snow damage in the history. As the results, the model showed over 70% of accuracy in all of three cities.

Due to the rapid industrialization and urbanization, many studies on nonpoint source load reduction by SWMM. In this study, Sensitivity and uncertainty analysis for the SWMM Water Quality parameters, Max.Buildup, Rate Constant, EMC Coefficient and Cleaning Efficient, were conducted. Exponential and EMC functions were selected in the Buildup and Washoff function, respectively. As a results of sensitivity analysis, Rate Constant has the highest sensitivity and Max.Buildup, Cleaning Efficient and EMC Coefficient in the order. Rate Constant has the highest uncertainty as well. Max.buildup uncertainty index depended on simulation time and simulation time in accordance with time of concentration was more carefully determined in urban area than in forest and agricultural area. This result will be able to take advantage of sewer design in urban area.

Spatial and time variation of the precipitation in Korea is high, therefore, more than 2/3 of the annual precipitation is concentrated during the rainy season. Climate change also causes the intensive rainfall in the area of dense population, thus the occurrence frequency of the heavy flood in the impervious area has been increased. Therefore, the structural food mitigation measures such as the construction of the higher design frequency stormwater pipes, pumping stations, and/or detention ponds. The flood bypass tunnel or retention storage is also one of the efficient structures to mitigate flood damage in the urban area. However, the economic feasibility has been controversial because the flood bypass tunnel might be used once or twice a year. To solve the problem, the multi-functional tunnel for the urban traffic and flooding bypass has been considered. In this study, the design criteria of the road and water tunnel has been analysed and the composite design criteria is proposed for the multi-functional tunnel which is expected to be constructed.

Watershed-scale modeling can be useful in identifying the main environmental factors and the physical mechanisms responsible for acid mine drainage (AMD) formation, attenuation, and impacts. Since flow rates and water quality of the AMD and receiving streams are related to the rainfall-runoff relationship and associated contaminant dissolution, we thought that hydrologic analysis of the mined area and surrounding drainage basin should be the starting point in documenting the source and fate of AMD contaminants. Further modeling of AMD pollutants could then be performed in terms of metal concentrations and loading at the watershed scale. In this study, monitoring was conducted in the Geopung mine watershed; the watershed analysis risk management framework (WARMF) model was used to evaluate the effect of AMD contributions to downstream metal concentrations. The hydrologic model of the basin was calibrated and verified with rainfall and streamflow data, and the water quality model was calibrated for the dissolved concentrations of metals (Cd, Cu, Zn, and Pb), using discharge data gathered in 2009. There was a strong correlation (r = 0.93) between the observed and simulated runoff values plus high Nash–Sutcliffe model efficiency (NSE = 0.89) and low average percent difference between predicted and measured values (%Diff = 0.46). Subsequent model validation using data gathered in 2010 also showed good agreement (%Diff = 9.76; NSE = 0.77; r = 0.91) between the observed and simulated values. For the metals, the model was calibrated using data from 2010; the correlation between the observed and simulated values was quite good (r = 0.80–0.41).

In the case of rapidly developed urban and industrial complex, the most area becomes impervious, which causes the increasing runoff and high probability of flooding. SWMM model has been widely used to calculate stormwater runoff in urban areas, however, the model is limited to interpreting the actual natural phenomenon. It has the uncertainty in the model structure, so it is difficult to calculate the accurate runoff from the urban basin. In this study, the model parameters were investigated and uncertainty was quantified using Uncertainty Quantification Index (UQI). As a result, pipe roughness coefficient has the largest total uncertainty and largest effect on the total runoff. Therefore, when the stormwater pipe network is designed, pipe roughness coefficient has to be calibrated accurately. The quantified uncertainty should be considered in the runoff calculation. It is recommended to understand the characteristics of each parameter for the prevention and mitigation of urban flood.

In this study, optimal water quality sensor placement is performed based on the sensitivity of flow direction under different water demands for detecting accidental water quality contamination. First, Betweenness Centrality (BC), a network analysis method, is used for determining optimal locations considering a network’s connectivity. Second, sensor locations are optimized for minimizing the contaminant intrusion detection time using the travel time matrix and the Multi-Objective Genetic Algorithm (MOGA). These methods were applied to two water distribution networks. It was found that the BC method generates optimal locations close to the water sources and the water main, whereas the MOGA-based method generates optimal sensor locations far away from the sources. These results support the following conclusions. First, the installation priority of gauges can be determined with a more objective standard using the aforementioned two methods. Second, given specific objectives, the two models can be used as alternative decision-making tools for sensor installation.

Rainfall data is measured by rain gauge and the effects of wind speed on the data have not been considered when the data is dis-tributed. The calculated runoff using there rainfall data could be underestimated or overestimated. In this study, therefore, the rainfalldata was calibrated using the wind speed, and the runoff was analayzed in the Geum Cheon catchment which has impervious areamore than 90% of the catchment. SWMM model was used to calculate the runoff. Runoff characteristics were analyzed in dry, wet,and entire period. In wet period, the peak discharge has increased about 1.3 times than the runoff in dry period. The amount of totaldischarge in wet period has increased upto 1.3 times as well. The amount of rainfall and runoff has increased as the wind speedincrease. Therefore, when stormwater pipes are designed, the wind speed should be considered to avoid underestimated runoff cal-culation which could cause urban flood.Key words : Effect of wind speed, Urban runoff calculation, Calibration of runoff, Stormwater pipe design

재난의 대형화 복잡화가 진행되어 막대한 피해를 야기하는 대형재난의 발생하는 빈도가 높 아짐에 따라 재난대비 및 대응을 위한 재난 및 안전교육이나 훈련의 중요성이 강조되고 있 다. 본 연구에서는 재난안전교육이 재난의 위험도에 미치는 영향을 분석하였다. 위험도를 계산하기 위한 발생가능성과 재난의 결과에 재난안전교육이 미치는 저감효과를 전문가 설 문조사를 이용하여 계산하였다. 교육대상을 세분화하여 저감효과가 달라짐을 확인하였으 며, 이는 재난관련 업무 종사 공무원부터 초·중·고 학생들의 의무교육까지 전국민을 대상으 로 적극적인 교육과 훈련을 실시할 경우, 최대 약48% 정도까지 재난위험도가 감소할 수 있을 것으로 조사되었다. 이에 대한 검증을 위해 실제 자료조사 및 분석과정이 수행되어야 할 것이지만, 이는 적극적인 재난안전교육을 실시해야만 하는 정당한 이유가 될 수 있을 것이다. 재난 및 안전교육 재난위험도 재난 발생가능성 재난 및 안전훈련 c 2014 Koea Society of Diaster Information All rights reserved 재난 위험도 평가 과정에 재난안전교육이 미치는 영향 평가 Effect of Disaster and Safety Education on Disaster Risk Assessment Gunhui Chung a Department of Civil Engineering, Hoseo University, 20, Hoseo-ro 79th Road, Baebang-eup, Asan-si, Chungcheongnam-do, 336-795, Republic of Korea * Corresponding author. Tel. 82-41-540-5794. Fax. 82-41-540-5798. Email. gunhui@hoseo.edu ARTICLE HISTORY Recieved May. 20, 2014 Revised Jun. 02, 2014 Accepted Jul. 07, 2014 Journal of the Korea Society of Disaster Information Vol.10 No.3 ❙ pp. 366 372 Available online at www.kosdi.or.kr 1976-2208 c 2014 Korea Society of Disaster Information All rights reserved. http://dx.doi.org/10.15683/kosdi.2014.10.3.366 G.H. Chung Journal of Korea Society of Diaster Information Vol.10, No.3, pp. 366 372, 2014

Climate change is one of the most important factors increasing a system’s vulnerability. Therefore, various methods have been applied to evaluate the vulnerability to develop an appropriate adaptation policy to minimize theeffects of climate change. On the other hand, it has barely been used to examine the suitability of the selected proxyvariables to calculate the vulnerability. In this study, it was shown that the degree of disaster and safety educationshould be considered as one of the proxy variables in non-structural measures when the vulnerability is calculatedusing an expert survey. As a result, the degree of the contribution on the climate change vulnerability can be differentaccording to the education target and the characteristics of various systems. The results might be useful for developinga climate change adaptation policy in a specific area. Key Words : Climate change vulnerability, Disaster and safety education, Contribution analysis 이 논문은 2013년 방재청 재난안전기술개발기반구축사업단의 “재난안전교육 컨텐츠 개발 국제공동연구 및 정보공유 네트워크 구축방안 연구(2013-NEMA15-008-01010000-2013)” 재원으로 수행된 연구결과이며, 이에 감사드립니다.