• Journal of Korean Society of Transportation
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• v.29 no.6
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• pp.97-106
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• 2011

Mode choice model is an essential element for estimating- the demand of new means of transportation in the planning stage as well as in the establishment phase. In general, current demand analysis model developed for the mode choice analysis applies common parameters of utility function in each region which causes inaccuracy in forecasting mode choice behavior. Several critical problems from using common parameters are: a common parameter set can not reflect different distribution of coefficient for travel time and travel cost by different population. Consequently, the resulting model fails to accurately explain policy variables such as travel time and travel cost. In particular, the nonlinear logit model applied to aggregation data is vulnerable to the aggregation error. The purpose of this paper is to consider the regional characteristics by adopting the parameters fitted to each area, so as to reduce prediction errors and enhance accuracy of the resulting mode choice model. In order to estimate parameter of each area, this study used Household Travel Survey Data of Metropolitan Transportation Authority. For the verification of the model, the value of time by marginal rate of substitution is evaluated and statistical test for resulting coefficients is also carried out. In order to crosscheck the applicability and reliability of the model, changes in mode choice are analyzed when Seoul subway line 9 is newly opened and the results are compared with those from the existing model developed without considering the regional characteristics.

• Journal of Environmental Impact Assessment
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• v.15 no.4
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• pp.249-258
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• 2006

Impacts of global warming have been identified in many areas including natural ecosystem. A good number of studies based on climate models forecasting future climate have been conducted in many countries worldwide. Due to its global coverage, GCM, which is a most frequently used climate model, has limits to apply to Korea with such a narrower and complicated terrain. Therefore, it is necessary to perform a study impact assessment of climate changes with a climate model fully reflecting characteristics of Korean climate. In this respect, this study was designed to compare and analyze the GCM and RCM in order to determine a suitable climate model for Korea. In this study, spatial scope was Korea for 10 years from 1981 to 1990. As a research method, current climate was estimated on the basis of the data obtained from observation at the GHCN. Future climate was forecast using 4 GCMs furnished by the IPCC among SRES A2 Scenario as well as the RCM received from the NIES of Japan. Pearson correlation analysis was conducted for the purpose of comparing data obtained from observation with GCM and RCM. As a result of this study, average annual temperature of Korea between 1981 and 1990 was found to be around $12.03^{\circ}C$, with average daily rainfall being 2.72mm. Under the GCM, average annual temperature was between 10.22 and $16.86^{\circ}C$, with average daily rainfall between 2.13 and 3.35mm. Average annual temperature in the RCM was identified $12.56^{\circ}C$, with average daily rainfall of 5.01mm. In the comparison of the data obtained from observation with GCM and RCM, RCMs of both temperature and rainfall were found to well reflect characteristics of Korea's climate. This study is important mainly in that as a preliminary study to examine impact of climate changes such as global warming it chose appropriate climate model for our country. These results of the study showed that future climate produced under similar conditions with actual ones may be applied for various areas in many ways.

• 한국방재학회:학술대회논문집
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• 2011.02a
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• pp.172-172
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• 2011

The interaction between land surface and atmosphere is essentially affected by hydrometeorological variables including soil moisture. Accurate estimation of soil moisture at spatial and temporal scales is crucial to better understand its roles to the weather systems. The KLDAS(Korea Land Data Assimilation System) is a regional, specifically Korea peninsula land surface information systems. As other prior land data assimilation systems, this can provide initial soil field information which can be used in atmospheric simulations. For this study, as an enabling high-resolution tool, weather research and forecasting(WRF-ARW) model is applied to produce precipitation data using GFS(Global Forecast System) with GFS embedded and KLDAS soil moisture information as initialization data. WRF-ARW generates precipitation data for a specific region using different parameters in physics options. The produced precipitation data will be employed for simulations of Hydrological Models such as HEC(Hydrologic Engineering Center) - HMS(Hydrologic Modeling System) as predefined input data for selected regional water responses. The purpose of this study is to show the impact of a hydrometeorological variable such as soil moisture in KLDAS on hydrological consequences in Korea peninsula. The study region, Chongmi River Basin, is located in the center of Korea Peninsular. This has 60.8Km river length and 17.01% slope. This region mostly consists of farming field however the chosen study area placed in mountainous area. The length of river basin perimeter is 185Km and the average width of river is 9.53 meter with 676 meter highest elevation in this region. We have four different observation locations : Sulsung, Taepyung, Samjook, and Sangkeug observatoriesn, This watershed is selected as a tentative research location and continuously studied for getting hydrological effects from land surface information. Simulations for a real regional storm case(June 17~ June 25, 2006) are executed. WRF-ARW for this case study used WSM6 as a micro physics, Kain-Fritcsch Scheme for cumulus scheme, and YSU scheme for planetary boundary layer. The results of WRF simulations generate excellent precipitation data in terms of peak precipitation and date, and the pattern of daily precipitation for four locations. For Sankeug observatory, WRF overestimated precipitation approximately 100 mm/day on July 17, 2006. Taepyung and Samjook display that WRF produced either with KLDAS or with GFS embedded initial soil moisture data higher precipitation amounts compared to observation. Results and discussions in detail on accuracy of prediction using formerly mentioned manners are going to be presented in 2011 Annual Conference of the Korean Society of Hazard Mitigation.

• Journal of Korean Society of Transportation
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• v.21 no.5
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• pp.83-95
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• 2003

This study aims to develop travel time estimation and prediction models on the freeway using measurements from vehicle detectors. In this study, we established a travel time estimation model using traffic volume which is a principle factor of traffic flow changes by reviewing existing travel time estimation techniques. As a result of goodness of fit test. in the normal traffic condition over 70km/h, RMSEP(Root Mean Square Error Proportion) from travel speed is lower than the proposed model, but the proposed model produce more reliable travel times than the other one in the congestion. Therefore in cases of congestion the model uses the method of calculating the delay time from excess link volumes from the in- and outflow and the vehicle speeds from detectors in the traffic situation at a speed of over 70km/h. We also conducted short term prediction of Kalman Filtering to forecast traffic condition and more accurate travel times using statistical model The results of evaluation showed that the lag time occurred between predicted travel time and estimated travel time but the RMSEP values of predicted travel time to observations are as 1ow as that of estimation.

• Journal of the Korean earth science society
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• v.33 no.3
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• pp.280-293
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• 2012

In order to clarify the characteristics of dispersion of volcanic tephra emitted from the Mt. Baegdu with various eruption environment, numerical analysis were performed using numerical models, Weather Research and Forecast (WRF) and FLEXPART. Synoptic conditions at 12 October 2010 was adopted because the volcanic ash of Mt. Baegdu can reach the Korean peninsula and its dispersion pattern was compared with different Volcanic Explosivity Index (VEI) and particle size. Predominant size of falling out ash flowing in the peninsular is smaller than 0.5 mm and the ash large than the size is difficult to get in the peninsular due to the its weak ability of truculent diffusion. the difference of ash distribution with various VEI scenarios is not so much but number density of ash in the air is dramatically changed. Volcanic ash tends to be deposited easily in eastern coastal area such as Gangneung and Busan, because of the inflow of ash from East Sea and barrier effect of the Taeback mountains along the east coast of the Korean Peninsula. Accumulated amount of ash deposition can be increased in short period in several urban areas.

• Atmosphere
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• v.24 no.4
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• pp.565-571
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• 2014

A long-range prediction system of tropical cyclone (TC) activity over the western North Pacific (WNP) has been operated in the National Typhoon Center of the Korea Meteorological Administration since 2012. The model forecasts the spatial distribution of TC tracks averaged over the period June~October. In this study, we separately developed TC prediction models for summer (June~August) and autumn (September~November) period based on the current operating system. To perform the three-month WNP TC activity prediction procedure readily, we modified the shell script calling in environmental variables automatically. The user can apply the model by changing these environmental variables of namelist parameter in consideration of their objective. The validations for the two seasons demonstrate the great performance of predictions showing high pattern correlations between hindcast and observed TC activity. In addition, we developed a post-processing script for deducing TC activity in the Korea emergency zone from final forecasting map and its skill is discussed.

• Journal of Korea Water Resources Association
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• v.41 no.9
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• pp.959-967
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• 2008

Disaggregation techniques are widely used to transform observed daily rainfall values into hourly ones, which serve as important inputs for flood forecasting purposes. However, an important limitation with most of the existing disaggregation techniques is that they treat the rainfall process as a realization of a stochastic process, thus raising questions on the lack of connection between the structure of the models on one hand and the underlying physics of the rainfall process on the other. The present study introduces a nonlinear deterministic (and specifically chaotic) framework to study the dynamic characteristics of rainfall distributions across different temporal scales (i.e. weights between scales), and thus the possibility of rainfall disaggregation. Rainfall data from the Seoul station (recorded by the Korea Meteorological Administration) are considered for the present investigation, and weights between only successively doubled resolutions (i.e., 24-hr to 12-hr, 12-hr to 6-hr, 6-hr to 3-hr) are analyzed. The correlation dimension method is employed to investigate the presence of chaotic behavior in the time series of weights, and a local approximation technique is employed for rainfall disaggregation. The results indicate the presence of chaotic behavior in the dynamics of weights between the successively doubled scales studied. The modeled (disaggregated) rainfall values are found to be in good agreement with the observed ones in their overall matching (e.g. correlation coefficient and low mean square error). While the general trend (rainfall amount and time of occurrence) is clearly captured, an underestimation of the maximum values are found.

• Journal of Korean Society of Transportation
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• v.32 no.5
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• pp.544-553
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• 2014

Activity-based models analyze individuals' various daily activities that are identified as a decision-making unit for transportation planning. In other words, it is the model that determines the types of activities according to the social, economic and situational characteristics of the groups with the same activity patterns and predicts individuals' activity time, distance, spatial movement and transportation mode. The activity-based model is a method of estimating more efficient and realistic demand in transportation forecasting because traffic is regarded as a complex decision-making process that an individual and other people participate in. In this paper, we grasp the factors affecting choice behavior of activity pattern and analyze choice behavior of activity pattern based on multi-dimensional characteristic of each person. First, we classify activity types of reviewing the trip chain and activity purpose. Next, we identified preferable activity types using complicated characteristics of main agent of activity. We concluded that choice behavior of activity pattern is dependent on complex characteristics of each agent, and further multi-dimensional characteristics of each person are affected over the whole decision process of activity schedule.

• Journal of Wetlands Research
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• v.22 no.4
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• pp.302-311
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• 2020

There are limitations to cope with flood damage by structural strategies alone because both frequency and intensity of floods are increasing due to climate change. Therefore, it is one of the necessary factors in the nonstructural countermeasures to collect and analyze historical flood damage records for the future flood damage assessments. In order to estimate flood damage costs in Gyeongsangbuk-do where severe flood damage occurs frequently due to geographical and climatic effects, this paper has performed the regression analysis on flood damage records over the past 20 years (1999-2018) by rainfall characteristics, which is one of the major causes of flood damage. This paper has then examined the relationship between the terrain features and rainfall characteristics in the regional regression functions, and also estimated the flood damage risk for 100-year rainfall by using the regional regression functions presented for the 22 administrative districts in Gyeongsangbuk-do excluding Ulleung-gun. The flood damage assessment shows that the relatively high damage risk is estimated for county areas adjacent to the eastern coast in Gyeongsangbuk-do. The regional damage estimate functions in this paper are expected to be used as one of the nonstructural countermeasures to estimate flood damage risk for the design or forecasting rainfall data.

• Journal of Korea Water Resources Association
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• v.46 no.8
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• pp.857-871
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• 2013

The interest in rainfall observation and forecasting using remote sensing method like RADAR (Radio Detection and Ranging) and satellite image is increased according to increased damage by rapid weather change like regional torrential rain and flash flood. In this study, the basin runoff was calculated using adaptive neuro-fuzzy technique, one of the data driven model and MAPLE (McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation) forecasted precipitation data as one of the input variables. The flood estimation method using neuro-fuzzy technique and RADAR forecasted precipitation data was evaluated. Six rainfall events occurred at flood season in 2010 and 2011 in Chungju Reservoir basin were used for the input data. The flood estimation results according to the rainfall data used as training, checking and testing data in the model setup process were compared. The 15 models were composed of combination of the input variables and the results according to change of clustering methods were compared and analysed. From this study was that using the relatively larger clustering radius and the biggest flood ever happened for training data showed the better flood estimation. The model using MAPLE forecasted precipitation data showed relatively better result at inflow estimation Chungju Reservoir.