• Atmosphere
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• v.27 no.3
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• pp.261-276
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• 2017

The main objectives of this study are to introduce Global Seasonal forecasting system version5 (GloSea5) of KMA and to evaluate the performance of ensemble prediction of system. KMA has performed an operational seasonal forecast system which is a joint system between KMA and UK Met office since 2014. GloSea5 is a fully coupled global climate model which consists of atmosphere (UM), ocean (NEMO), land surface (JULES) and sea ice (CICE) components through the coupler OASIS. The model resolution, used in GloSea5, is N216L85 (~60 km in mid-latitudes) in the atmosphere and ORCA0.25L75 ($0.25^{\circ}$ on a tri-polar grid) in the ocean. In this research, we evaluate the performance of this system using by RMSE, Correlation and MSSS for ensemble mean values. The forecast (FCST) and hindcast (HCST) are separately verified, and the operational data of GloSea5 are used from 2014 to 2015. The performance skills are similar to the past study. For example, the RMSE of h500 is increased from 22.30 gpm of 1 week forecast to 53.82 gpm of 7 week forecast but there is a similar error about 50~53 gpm after 3 week forecast. The Nino Index of SST shows a great correlation (higher than 0.9) up to 7 week forecast in Nino 3.4 area. It can be concluded that GloSea5 has a great performance for seasonal prediction.

• Journal of Korean Society of Rural Planning
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• v.11 no.4 s.29
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• pp.47-57
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• 2005

The goal of this research is to evaluate landscape-ecological characteristics of watersheds in the Nakdong River Basin by using Geogaphic Information System (GIS) and landscape indices for integation of spatio-temporal informations and multivariate statistical techniques for quantitative analysis of forest landscape. Fragmentation index and change matrix techniques using factor analysis and grid overlay method were used to efficiently analyze and manage huge amount of information for ecological-environmental assessment (land-cover and forest landscape patterns). According to the results based on the pattern analysis of land-cover changes using the change detection matrix between 1980s and 1990s, addition on 750km$^2$ became urbanized areas. The altered 442.04km$^2$ was agricultural areas which is relatively easy for shifting of land-use, and 205.1km$^2$ of forests became urbanized areas, and average elevation and slope of the whole altered areas were 75m and 4$^{\circ}$. On the other hand, 120km$^2$ of urban areas were changed into other areas (i.e., agricultural areas and green space), and fortunately, certain amount of naturalness had been recovered. But still those agricultural areas and fallow areas, which were previously urban areas, had high potential of re-development for urbanization due to their local conditions. According to the structural analysis of forest landscape using the landscape indices, the forest fragmentation of watersheds along the main stream of the Nakdong River was more severe than my other watersheds. Furthermore, the Nakdong-sangju and Nakdong-miryang watersheds had unstable forest structures as well as least amount of forest quantity. Thus, these areas need significant amount of forest through a new forest management policy considering local environmental conditions.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.3
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• pp.71-83
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• 2020

Resilience is the capacity to maintain essential services under a range of circumstances from normal to extreme. It is achieved through the ability of assets, networks, systems and management to anticipate, absorb and recover from disturbance. It requires adaptive capacity in respect of current and future risks and uncertainties as well as experience to date. The agricultural infrastructures with high resilience can not only reduce the size of the disaster relatively, but also minimize the loss by reducing the time required for recovery. This study aims to evaluate the most suitable drought countermeasures with the analysis of various resilience indices by predicting future agricultural water shortage under land use and climate change scenarios for agricultural areas in Jeju Island. The results showed that the permanent countermeasure is suitable than the temporary countermeasures as drought size and the cost required for recovery increase. Wide-area water supply system, which is a kind of water grid system, is identified as the most advantageous among countermeasures. It is recommended to evaluate the capability of agricultural infrastructure against drought with the various Resilience Indices for reliable assessment of long-term effect.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.4
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• pp.275-280
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• 2015

In order to figure out the future drought characteristics of the Jeonju plains, the major crop production area in Korea, daily agricultural drought indexes based on soil water balance were calculated for the relevant 12.5 km by 12.5 km grid cell using the weather data generated by the RCP8.5 climate scenario during 1951-2100. The calculations were grouped into five climatological normal years, the past (1951-1980), the present (1981-2010), and the three futures (2011-2040, 2041-2070, and 2071-2100). Results showed that the soil moisture conditions in early spring, worst for both the past and present normal years, will ameliorate gradually in the future and the crop water stress in spring season was projected to become negligible by the end of this century. Furthermore, the drought frequency in early spring was projected to diminish, resulting in rare occurrence of spring drought by that time. However, the result also showed that the soil moisture conditions during the summer season (when most crops grow in Jeonju plain) will deteriorate and the drought incidence will be more frequent than in the past or present period.

• The Journal of the Korea Contents Association
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• v.17 no.8
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• pp.619-630
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• 2017

With the growing popularity of smart devices, various location based services have been providing to users. Recently, some location based social applications that combine social services and location based services have been emerged. The demands of a k-nearest neighbors(k-NN) query which finds k closest locations from a user location are increased in the location based social network services. In this paper, we propose an approximate k-NN query processing method for fast response time in a large number of users environments. The proposed method performs efficient stream processing using big data distributed processing technologies. In this paper, we also propose a modified grid index method for indexing a large amount of location data. The proposed query processing method first retrieves the related cells by considering a user movement. By doing so, it can make an approximate k results set. In order to show the superiority of the proposed method, we conduct various performance evaluations with the existing method.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.42 no.1
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• pp.35-40
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• 2005

Recently, the location based service for moving customers is becoming one of the most important service in mobile communication area and for moving object applications, there are lots of update operations and such update loads are concentrated on some particular area unevenly. The primary processing of LBS application is spatio-temporal range queries and to improve the throughput of spatio-temporal range queries, the time of disk I/O in query processing should be reduced. In this paper, we adopt non-uniform two-level grid index structure, which are designed to minimize update operations. We propose query scheduling technique using spatial relationship and time relationship and a combined spatio-temporal query processing method using time zone concepts to improve the throughput of query processing. Some experimental results are shown for range queries with different query range to show the performance tradeoffs of the proposed methods.

• Atmosphere
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• v.27 no.2
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• pp.189-197
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• 2017

Progressing from weather forecasts and warnings to multi-hazard impact-based forecast and warning services represents a paradigm shift in service delivery. Urban flooding is a typical meteorological disaster. This study proposes support plan for urban flooding impact-based forecast by providing inundation risk matrix. To achieve this goal, we first configured storm sewer management model (SWMM) to analyze 1D pipe networks and then grid based inundation analysis model (GIAM) to analyze 2D inundation depth over the Gangnam drainage area with $7.4km^2$. The accuracy of the simulated inundation results for heavy rainfall in 2010 and 2011 are 0.61 and 0.57 in POD index, respectively. 20 inundation scenarios responding on rainfall scenarios with 10~200 mm interval are produced for 60 and 120 minutes of rainfall duration. When the inundation damage thresholds are defined as pre-occurrence stage, occurrence stage to $0.01km^2$, 0.01 to $0.1km^2$, and $0.1km^2$ or more in area with a depth of 0.5 m or more, rainfall thresholds responding on each inundation damage threshold results in: 0 to 20 mm, 20 to 50 mm, 50 to 80 mm, and 80 mm or more in the rainfall duration 60 minutes and 0 to 30 mm, 30 to 70 mm, 70 to 110 mm, and 110 mm or more in the rainfall duration 120 minutes. Rainfall thresholds as a trigger of urban inundation damage can be used to form an inundation risk matrix. It is expected to be used for urban flood impact forecasting.

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.6
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• pp.19-30
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• 2013

This study is to evaluate the use of dual-polarization radar data for storm runoff modeling in Namgang dam (2,293 $km^2$) watershed using KIMSTORM (Grid-based KIneMatic wave STOrm Runoff Model). The Bisl dual-polarization radar data for 3 typhoons (Khanun, Bolaven, Sanba) and 1 heavy rain event in 2012 were obtained from Han River Flood Control Office. Even the radar data were overall less than the ground data in areal average, the spatio-temporal pattern between the two data was good showing the coefficient of determination ($R^2$) and bias with 0.97 and 0.84 respectively. For the case of heavy rain, the radar data caught the rain passing through the ground stations. The KIMSTORM was set to $500{\times}500$ m resolution and a total of 21,372 cells (156 rows${\times}$137 columns) for the watershed. Using 28 ground rainfall data, the model was calibrated using discharge data at 5 stations with $R^2$, Nash and Sutcliffe Model Efficiency (ME) and Volume Conservation Index (VCI) with 0.85, 0.78 and 1.09 respectively. The calibration results by radar rainfall showed $R^2$, ME and VCI were 0.85, 0.79, and 1.04 respectively. The VCI by radar data was enhanced by 5 %.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.16-16
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• 2011

Statistics of extreme rainfall play a vital role in engineering practice from the perspective of mitigation and protection of infrastructure and human life from flooding. While flood frequency assessments, based on river flood flow data are preferred, the analysis of rainfall data is often more convenient due to the finer spatial nature of rainfall recording networks, often with longer records, and potentially more easily transferable from site to site. The rainfall frequency analysis as a design tool has developed over the years in New Zealand from Seelye's daily rainfall frequency maps in 1947 to Thompson's web based tool in 2010. This paper will present a history of the development of New Zealand rainfall frequency analysis methods, and the details of the latest method, so that comparisons may in future be made with the development of Korean methods. One of the main findings in the development of methods was new knowledge on the distribution of New Zealand rainfall extremes. The High Intensity Rainfall Design System (HIRDS.V3) method (Thompson, 2011) is based upon a regional rainfall frequency analysis with the following assumptions: $\bullet$ An "index flood" rainfall regional frequency method, using the median annual maximum rainfall as the indexing variable. $\bullet$ A regional dimensionless growth curve based on the Generalised Extreme Value (GEV), and using goodness of fit test for the GEV, Gumbel (EV1), and Generalised Logistic (GLO) distributions. $\bullet$ Mapping of median annual maximum rainfall and parameters of the regional growth curves, using thin-plate smoothing splines, a $2km\times2km$ grid, L moments statistics, 10 durations from 10 minutes to 72 hours, and a maximum Average Recurrence Interval of 100 years.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.260-260
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• 2017

This study aims to compare the performance of TRIGRS (Transient Rainfall Infiltration and Grid-based Regional Slope-stability model) and TiVaSS (Time-variant Slope Stability model) in the prediction of rainfall-induced shallow landslides. TRIGRS employs one-dimensional (1-D) subsurface flow to simulate the infiltration rate, whereas a three-dimensional (3-D) model is utilized in TiVaSS. The former has been widely used in landslide modeling, while the latter was developed only recently. Both programs are used for the spatiotemporal prediction of shallow landslides caused by rainfall. The present study uses the July 2011 landslide event that occurred in Mt. Umyeon, Seoul, Korea, for validation. The performance of the two programs is evaluated by comparison with data of the actual landslides in both location and timing by using a landslide ratio for each factor of safety class ( index), which was developed for addressing point-like landslide locations. In addition, the influence of surface flow on landslide initiation is assessed. The results show that the shallow landslides predicted by the two models have characteristics that are highly consistent with those of the observed sliding sites, although the performance of TiVaSS is slightly better. Overland flow affects the buildup of the pressure head and reduces the slope stability, although this influence was not significant in this case. A slight increase in the predicted unstable area from 19.30% to 19.93% was recorded when the overland flow was considered. It is concluded that both models are suitable for application in the study area. However, although it is a well-established model requiring less input data and shorter run times, TRIGRS produces less accurate results.