• The Journal of Engineering Geology
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• v.32 no.1
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• pp.27-40
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• 2022

Every year landslides cause serious casualties and property damages around the world. As the accurate prediction of landslides is important to reduce the fatalities and economic losses, various approaches have been developed to predict them. Prediction methods can be divided into landslide susceptibility analysis, landslide hazard analysis and landslide risk analysis according to the type of the conditioning factors, the predicted level of the landslide dangers, and whether the expected consequence cased by landslides were considered. Landslide susceptibility analyses are mainly based on the available landslide data and consequently, they predict the likelihood of landslide occurrence by considering factors that can induce landslides and analyzing the spatial distribution of these factors. Various qualitative and quantitative analysis techniques have been applied to landslide susceptibility analysis. Recently, quantitative susceptibility analyses have predominantly employed the physically based model due to high predictive capacity. This is because the physically based approaches use physical slope model to analyze slope stability regardless of prior landslide occurrence. This approach can also reproduce the physical processes governing landslide occurrence. This review examines physically based landslide susceptibility analysis approaches.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.1
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• pp.194-204
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• 2007

The purpose of this paper was to propose a Topographic Position Index(TPI) method for predicting forest wetlands, and also to test the suitability of the predicted forest wetlands by comparing with the existing wetlands in Ulaju-gun and Gyengsangnam-do. A prediction of the spatial distribution of forest wetlands was accomplished by TPI grids from Digital Elevation Model(DEM), and the classification results of slope position and landform categories in study area using the TPI values. According to the results of predicting forest wetlands distribution by TPI method, the predicted area in case of less than $5^{\circ}$ flat slope criteria occupied 0.1%($1.38km^2$) of the total area, and 3.5%($37.1km^2$) of total area in below $10^{\circ}$ slope criteria. According to the results of the suitability analysis by comparing the predicted area with the existing forest wetlands, the suitability value (0.066) of the predicted area with less than $10^{\circ}$ flat slope criteria was the highest, but the predicted area in case of less than $20^{\circ}$ had the lowest value(0.019).

• Proceedings of the Korean Geotechical Society Conference
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• 2008.10a
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• pp.455-465
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• 2008

In this study, the load distribution and deformation of rock-socketed drilled shafts subjected to axial load are investigated based on small scale model tests. In order to analyze the effects of major influencing factors of end bearing capacity, Hoek-cell triaxial tests were performed. From the test results, it was found that the initial slope of end bearing load transfer (q-w) curve was highly dependent on rock mass modulus and pile diameter, while the ultimate unit toe resistance ($q_{max}$) was influenced by rock mass modulus and the spacing of discontinuities. End bearing load transfer function of drilled shafts socketed in rock was proposed based on the Hoek-cell triaxial test results and the field loading tests which were performed on granite and gneiss in South Korea. Through the comparison with pile load tests, it is found that the load-transfer curve by the present study is in good agreement with the general trend observed by field loading tests, and thus represents a significant improvement in the prediction of load transfer of drilled shaft.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.50 no.4
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• pp.268-275
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• 2005

Early predictions of crop yields call provide information to producers to take advantages of opportunities into market places, to assess national food security, and to provide early food shortage warning. The objectives of this study were to identify the most useful parameters for estimating yields and to compare two model selection methods for finding the 'best' model developed by multiple linear regression. This research was conducted in two 65ha corn/soybean rotation fields located in east central South Dakota. Data used to develop models were small temporal variability information (STVI: elevation, apparent electrical conductivity $(EC_a)$, slope), large temporal variability information (LTVI : inorganic N, Olsen P, soil moisture), and remote sensing information (green, red, and NIR bands and normalized difference vegetation index (NDVI), green normalized difference vegetation index (GDVI)). Second order Akaike's Information Criterion (AICc) and Stepwise multiple regression were used to develop the best-fitting equations in each system (information groups). The models with $\Delta_i\leq2$ were selected and 22 and 37 models were selected at Moody and Brookings, respectively. Based on the results, the most useful variables to estimate corn yield were different in each field. Elevation and $EC_a$ were consistently the most useful variables in both fields and most of the systems. Model selection was different in each field. Different number of variables were selected in different fields. These results might be contributed to different landscapes and management histories of the study fields. The most common variables selected by AICc and Stepwise were different. In validation, Stepwise was slightly better than AICc at Moody and at Brookings AICc was slightly better than Stepwise. Results suggest that the Alec approach can be used to identify the most useful information and select the 'best' yield models for production fields.

• Journal of Korea Water Resources Association
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• v.32 no.6
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• pp.721-730
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• 1999

A Grid-based daily evapotranspiration(ET) prediction model which calculates temporal and spatial ET with a complementary relationship of Morton(1983) was developed. The model was programmed by C-language and uses ASCII formatted map data of DEM(Digital Elevation Model) and land use. Daily ET within the watershed is calculated and the results of temporal variations and spatial distributions of ET are presented by using GRASS(Geographic Resources Analysis Support System). To verify the applicability of the model, it was applied to the part of Bocheong stream basin (76.5$\textrm{km}^2$) located in the upstream of Dacheong Dam watershed. The result shows that the estimated evapotranspiration in 1995 was 766.1mm and 22% increased after correction radiation for slope and area.

• The Journal of Engineering Geology
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• v.18 no.4
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• pp.447-457
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• 2008

Laboratory tests for single plane sliding were conducted using the model rock slope to investigate the cut slope deformability and failure mechanism due to combined effect of engineering characteristics such as angle of sliding plane, water force, joint roughness and infillings. Also the possibility of prediction of slope failure through displacement monitoring was explored. The joint roughness was prepared in forms of saw-tooth type having different roughness specifications. The infillings was maintained between upper and lower roughness plane from zero to 1.2 times of the amplitude of the surface projections. Water force was expressed as the percent filling of tension crack from dry (0%) to full (100%), and constantly increased from 0% at the rate of 0.5%/min and 1%/min upto failure. Total of 50 tests were performed at sliding angles of $30^{\circ}$ and $35^{\circ}$ based on different combinations of joint roughness, infilling thickness and water force increment conditions. For smooth sliding plane, it was found that the linear type of deformability exhibited irrespective of the infilling thickness and water force conditions. For sliding planes having roughness, stepping or exponential types of deformability were predominant under condition that the infilling thickness is lower or higher than asperity height, respectively. These arise from the fact that, once the infilling thickness exceeds asperities, strength and deformability of the sliding plane is controlled by the engineering characteristics of the infilling materials. The results obtained in this study clearly show that the water force at failure was found to increase with increasing joint roughness, and to decrease with increasing filling thickness. It seems possible to estimate failure time using the inverse velocity method for sliding plane having exponential type of deformability. However, it is necessary to estimate failure time by trial and error basis to predict failure of the slope accurately.

• Journal of Korean Society on Water Environment
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• v.23 no.6
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• pp.897-905
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• 2007

Approximately 70% of Korea is composed of forest areas. Especially 48% of agricultural field is practiced at highland areas over 400 m in elevation in Kangwon province. Over 90% of highland agricultural farming is located at Kangwon province. Runoff characteristics at the mountainous area such as Kangwon province are largely affected by steep slopes, thus runoff estimation considering field slopes needs to be utilized for accurate estimation of direct runoff. Although many methods for runoff estimation are available, the Soil Conservation Service (SCS), now Natural Resource Conservation Service (NRCS), Curve Number (CN)-based method is used in this study. The CN values were obtained from many plot-years dataset obtained from mid-west areas of the United States, where most of the areas have less than 5% in slopes. Thus, the CN method is not suitable for accurate runoff estimation where significant areas are over 5% in slopes. Therefore, the CN values were adjusted based on the average slopes (25.8% at Doam-dam watershed) depending on the 5-day Antecedent Moisture Condition (AMC). In this study, the CN-based Long-Term Hydrologic Impact Assessment (L-THIA) direct runoff estimation model used and the Web-based Hydrograph Analysis Tool (WHAT) was used for direct runoff separation from the stream flow data. The $R^2$ value was 0.65 and the Nash-Sutcliffe coefficient value was 0.60 when no slope adjustment was made in CN method. However, the $R^2$ value was 0.69 and the Nash-Sutcliffe value was 0.69 with slope adjustment. As shown in this study, it is strongly recommended the slope adjustment in the CN direct runoff estimation should be made for accurate direct runoff prediction using the CN-based L-THIA model when applied to steep mountainous areas.

• Journal of Climate Change Research
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• v.8 no.4
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• pp.287-295
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• 2017

This paper provides a mathematical approach for estimating flood risks due to the effects of climate change by developing a one dimensional (1D) hydraulic model for the mountainous river reaches located close to the Yeongwol thermal power plant. Input data for the model, including topographical data and river discharges measured every 10 minutes from July $1^{st}$ to September $30^{th}$, 2013, were imported to a 1D hydraulic model. Climate change scenarios were estimated by referencing the climate change adaptation strategies of the government and historical information about the extreme flood event in 2006. The down stream boundary was determined as the friction slope, which is 0.001. The roughness coefficient of the main channels was determined to be 0.036. The results show the effectiveness of the riverbed widening strategy through the six flooding scenarios to reduce flood depth and flow velocity that impact on the power plant. In addition, the impact of upper Namhan River flow is more significant than Dong River.

• Spatial Information Research
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• v.15 no.2
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• pp.135-146
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• 2007

The purpose of this study was to ascertain and analyze environmental factors of subgenus Lycoctonum in Korea for conservation and management of rare high land plant species by GIS. We derived the habitat model of Lycoctonum from GPS coordination, habitat factors and digital topology maps. Suitable altitude fur the subgenus Lycoctonum is from 470m to 1320m, and northern slopes(between 15.5 and 36 degrees) are ideal for the Lycoctonum populations. In addition to altitude, slope and aspect, deciduous forest and approximation to water source were found as important factor. Using GIS and the Lycoctonum habitat model, we overlaid elevation, aspect, slope and land cover layers and analyzed buffer from the water source on two topology maps, Yang-Soo and Mock-Dong. After making prediction map for Lycoctonum habitat, we verified the existence of Lycoctonum populations on the predicted sites through field survey. Through this research, we're convinced that GIS software is powerful tool for plants conservation, such as finding unknown habitat or selecting alternative habitat.

• Geomechanics and Engineering
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• v.34 no.3
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• pp.267-284
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• 2023

Landslides are one of the most dangerous phenomena and natural disasters. Landslides cause many human and financial losses in most parts of the world, especially in mountainous areas. Due to the climatic conditions and topography, people in the northern and western regions of Iran live with the risk of landslides. One of the measures that can effectively reduce the possible risks of landslides and their crisis management is to identify potential areas prone to landslides through multi-criteria modeling approach. This research aims to model landslide potential area in the Oshvand watershed using a support vector machine algorithm. For this purpose, evidence maps of seven effective factors in the occurrence of landslides namely slope, slope direction, height, distance from the fault, the density of waterways, rainfall, and geology, were prepared. The maps were generated and weighted using the continuous fuzzification method and logistic functions, resulting values in zero and one range as weights. The weighted maps were then combined using the support vector machine algorithm. For the training and testing of the machine, 81 slippery ground points and 81 non-sliding points were used. Modeling procedure was done using four linear, polynomial, Gaussian, and sigmoid kernels. The efficiency of each model was compared using the area under the receiver operating characteristic curve; the root means square error, and the correlation coefficient . Finally, the landslide potential model that was obtained using Gaussian's kernel was selected as the best one for susceptibility of landslides in the Oshvand watershed.