• Water for future
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• v.49 no.10
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• pp.62-66
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• 2016

• Water for future
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• v.53 no.9
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• pp.52-57
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• 2020

• Journal of Korean Society of Disaster and Security
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• v.13 no.2
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• pp.1-9
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• 2020

Vietnamese cities have a high risk of flooding under climate change due to their geographical characteristics. In this situation, the urban area is expanding with rapid growth of urban population. However, the risk of flooding is increasing due to the increase in impermeable areas and insufficient infrastructure. This study analyzed the urban expansion trend at the national level in Vietnam for the past 10 years (2007-2017) by using the Urban Expansion Intensity Index. Also, this study selected Hue City as a region with a large impact of climate change and a rapid expansion and found the possibility of flooding in the urban expansion area. The result showed that cities have been expanded around major cities in the Red River Delta, Mekong Delta, and coastal areas. In the case of Hue City, the area with fast expansion rate has a higher expected flood area. It implies that the risk of flood disasters may increase if the urabn expansion is carried out without disaster prevention measures. It is expected that Korean urban disaster prevention policies such as urban climate change disaster vulnerability analysis system will be helpful in establishing urban plans considering climate change in the fast growing regions such as Vietnam.

• The Journal of Engineering Geology
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• v.26 no.2
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• pp.197-205
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• 2016

Rainfall-induced landslide disaster case histories are typically required to establish critical lines based on the decrease coefficient for judging the likelihood of slope collapse or failure; however, reliably setting critical lines is difficult because the number of nationwide disaster case histories is insufficient and not well distributed across the region. In this study, we propose a method for setting the critical area to judge the risk of slope collapse without disaster case history information. Past 10 years rainfall data based on decrease coefficient are plotted as points, and a reference line is established by connecting the outermost points. When realtime working rainfall cross the reference line, warning system is operating and this system can be utilized nationwide through setting of reference line for each AWS (Automatic Weather Station). Warnings were effectively predicted at 10 of the sites, and warnings could have been issued 30 min prior to the landslide movement at eight of the sites. These results indicate a reliability of about 67%. To more fully utilize this model, it is necessary to establish nationwide rainfall databases and conduct further studies to develop regional critical areas for landslide disaster prevention.

• Journal of Korea Water Resources Association
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• v.54 no.6
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• pp.395-405
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• 2021

When issuing forecasts and alerts for agricultural drought, the relevant ministries only rely on the observation data from the reservoirs managed by the Korea Rural Community Corporation, which creates gaps between the drought analysis results at the local (si/gun) governments and the droughts actually experienced by local residents. Closing these gaps requires detailed local geoinformation on reservoirs, which in turn requires the information on reservoirs managed by local governments across Korea. However, installing water level and flow measurement equipment at all of the reservoirs would not be reasonable in terms of operation and cost effectiveness, and an alternate approach is required to efficiently generate information. In light of the above, this study validates and calibrates the parameters of the TANK model for reservoir basins, divided them into groups based on the characteristics of different basins, and applies the grouped parameters to unmeasured local government reservoirs to estimate and assess inflow. The findings show that the average determinant coefficient and the NSE of the group using rice paddies and inclinations are 0.63 and 0.62, respectively, indicating better results compared with the basin area and effective storage factors (determinant coefficient: 0.49, NSE: 0.47). The findings indicate the possibility of utilizing the information regarding unmeasured reservoirs managed by local governments.

• Journal of Korean Society of Forest Science
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• v.101 no.4
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• pp.656-662
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• 2012

This study has been undertaken to research the characteristics of growth of Pinus thunbergii Parl., which were planted in Uljin-gun, Gyeongbuk, Coast Disaster Prevention Forest. The total amount of 3600 trees of 9 sand dune stabilizing hedges were monitored in the past 4 years. The relationship between tree growth with environmental factors such as wind speed, soil conditions and sand-accumulation fences has been compared and investigated. To increase the growth increment of coastal disaster prevention forests, the development of sand-accumulating fences is the most important factor in controlling wind speed effectively. The monitoring for the maximizing wind-break effect of the sand-accumulating fences should be investigated when building coastal disaster prevention forests.

• The Journal of Society for e-Business Studies
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• v.22 no.4
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• pp.103-115
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• 2017

Globally, frequency and scale of natural disasters are growing, also the damage is increasing. In view of the damage by natural disasters for several years, it is true that Korea is not free from such damages. In this paper, we propose a process to efficiently manage recovery resources in case of disaster damage. We utilize the IoT technology to detect the resource status in real time, and configure the process so that the state and movement of the recovery resource can be grasped in real time through the resource activity recognition module. In addition, we designed the database that is necessary to actualize it, and developed and experimented resource activity recognition module using smart-phone sensors. This will contribute to building a quick and efficient disaster response system.

• Journal of Korean Society of Forest Science
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• v.101 no.1
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• pp.1-6
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• 2012

To achieve the forest fire management goals such as early detection and quick suppression, fire resources should be allocated at high probability area where forest fires occur. The objective of this study was to develop and validate models to estimate spatially distributed probabilities of occurrence of forest fire. The models were builded by exploring relationships between fire ignition location and forest, terrain and anthropogenic factors using logistic regression. Distance to forest, cemetery, fire history, forest type, elevation, slope were chosen as the significant factors to the model. The model constructed had a good fit and classification accuracy of the model was 63%. This model and map can support the allocation optimization of forest fire resources and increase effectiveness in fire prevention and planning.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.188-188
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• 2016

The Mekong which is one of the world's most significant rivers plays an extremely important role to South East Asia. Lying across six riparian countries including China, Myanmar, Thailand, Laos, Cambodia and Vietnam and being a greatly biological and ecological diversity of fishes, the river supports a huge population who living along Mekong Basin River. Therefore, much attention has been focused on the giant Mekong Basin River, particularly, the soil erosion and sedimentation problems which rise critical impacts on irrigation, agriculture, navigation, fisheries and aquatic ecosystem. In fact, there have been many methods to calculate these problems; however, in the case of Mekong, the available data have significant limitations because of large area (about 795 00 km2) and a failure by management agencies to analyze and publish of developing countries in Mekong Basin River. As a result, the Universal Soil Loss Equation (USLE) model in a GIS (Geographic Information System) framework was applied in this study. The USLE factors contain the rainfall erosivity, soil erodibility, slope length, steepness, crop management and conservation practices which are represented by raster layers in GIS environment. In the final step, these factors were multiplied together to estimate the soil erosion rate in the study area by using spatial analyst tool in the ArcGIS 10.2 software. The spatial distribution of soil loss result will be used to support river basin management to find the subtainable management practices by showing the position and amount of soil erosion and sediment load in the dangerous areas during the selected 56- year period from 1952 to 2007.

• Journal of Korea Water Resources Association
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• v.54 no.1
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• pp.61-69
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• 2021

In this study, in order to efficiently perform smart city river management, we developed an integrated platform that connects flood analysis models on the web and provides information by converting input and output data into a database. In the integrated platform, a watershed analysis model, a river flow analysis model and an urban runoff analysis model were applied to perform flood analysis in smart city. This platform is able to obtain more reliable results by step-by-step approach to urban runoff that may occur in smart city through the applied model. In addition, since all analysis processes such as data collection, input data generation and result storage are performed on the web, anyone in an environment that can access the web without special equipment or tools can perform analysis and view results. Through this, it is expected that smart city managers can efficiently manage urban runoff and nearby rivers, and can also be used as educational materials for urban outflows.