• Economic and Environmental Geology
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• v.45 no.6
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• pp.697-707
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• 2012

The quantitative landslide susceptibility assessment methods can be divided into statistical approaches and geomechanical approaches based on the consideration of the triggering factors and landslide models. The geomechanical approach is considered as one of the most effective approaches since this approach proposes physical slope model and considers geomorphological and geomechanical properties of slope materials. Therefore, the geomechanical approaches has been used widely in landslide susceptibility analysis using the infinite slope model as physical slope model. However, the previous studies assumed constant groundwater level for broad study area without the consideration of rainfall intensity and hydraulic properties of soil materials. Therefore, in this study, landslide susceptibility assessment was implemented using the coupled infinite slope model with hydrologic model. For the analysis, geomechanical and hydrualic properties of slope materials and rainfall intensity were measured from the soil samples which were obtained from field investigation. For the practical application, the proposed approach was applied to Jinbu area, Gangwon-Do which was experienced large amount of landslides in July 2006. In order to compare to the proposed approach, the previous approach was used to analyze the landslide susceptibility using randomly selected groundwater level. Comparison of the results shows that the accuracy of the proposed method was improved with the consideration of the hydrologic model.

• Journal of the Korean GEO-environmental Society
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• v.8 no.5
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• pp.47-55
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• 2007

The increment of impermeable land area due to widespread land development caused the adverse impact on urban disaster prevention because it could decrease the peak rate of runoff as well as increase the runoff and peak flow during rainy period. To date, little research has been conducted on the infiltration characteristics and quantitative analysis because of their highly dependence on construction method, paving material, surface permeability, and field condition. Hence, this study was performed to investigate the infiltration characteristics of runoff-reducing facilities according to the type of paving material, which were examined using experimental apparatus with varying paving material and rainfall intensity, and thus to provide fundamental research data for runoff-reducing infiltration facilities. In this study, the infiltration characteristics were examined under the rainfall intensity of 20, 30, 50, 80, 100, 200 mm/hr for a variety type of paving materials such as concrete, asphalt, sand, grassland, and permeable paving material. The infiltration rate for permeable paving material was observed to be more than 93% under the condition of less than 200 mm/hr of rainfall intensity. For the compacted earth and grassland, the ultimate infiltration rate was estimated to be about 13% to 67%. The permeable paving material was concluded to be the most appropriate one for the runoff-reducing infiltration facilities because it has more favorable advantages than others in the light of infiltration volume, disaster prevention, and river training.

• Journal of Korean Society of Disaster and Security
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• v.15 no.4
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• pp.87-98
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• 2022

In recent years, frequent localized heavy rainfalls, which have a lot of rainfall in a short period of time, have been increasingly causing flooding damages. To prevent damage caused by localized heavy rainfalls, Hydrological Quantitative Precipitation Forecast (HQPF) was developed using the Local ENsemble prediction System (LENS) provided by the Korea Meteorological Administration (KMA) and Machine Learning and Probability Matching (PM) techniques using Digital forecast data. HQPF is produced as information on the impact of heavy rainfall to prepare for flooding damage caused by localized heavy rainfalls, but there is a tendency to overestimate the low rainfall intensity. In this study, we improved HQPF by expanding the period of machine learning data, analyzing ensemble techniques, and changing the process of Probability Matching (PM) techniques to improve predictive accuracy and over-predictive propensity of HQPF. In order to evaluate the predictive performance of the improved HQPF, we performed the predictive performance verification on heavy rainfall cases caused by the Changma front from August 27, 2021 to September 3, 2021. We found that the improved HQPF showed a significantly improved prediction accuracy for rainfall below 10 mm, as well as the over-prediction tendency, such as predicting the likelihood of occurrence and rainfall area similar to observation.

• Journal of Korea Water Resources Association
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• v.49 no.4
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• pp.327-333
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• 2016

Due to climate changes accelerated by global warming, South Korea has experienced regional climate variations as well as increasing severities and frequencies of extreme weather. The precipitation in South Korea during the summer season in 2013 was concentrated mainly in the central region; the maximum number of rainy days were recorded in the central region while the southern region had the minimum number of rainy days. As a result, much attention has been paid to the importance of flood control due to damage caused by spatiotemporal intensive rainfalls. In this study, forecast rainfall data was used for rapid responses to prevent disasters during flood seasons. For this purpose, the applicability of numerical weather forecast data was analyzed using the ground observation rainfall and inflow rate. Correlation coefficient, maximum rainfall intensity percent error and total rainfall percent error were used for the quantitative comparison of ground observation rainfall data. In addition, correlation coefficient, Nash-Sutcliffe efficiency coefficient, and standardized RMSE were used for the quantitative comparison of inflow rate. As a result of the simulation, the correlation coefficient up to six hours was 0.7 or higher, indicating a high correlation. Furthermore, the Nash-Sutcliffe efficiency coefficient was positive until six hours, confirming the applicability of forecast rainfall.

• Journal of Korea Water Resources Association
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• v.53 no.12
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• pp.1159-1172
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• 2020

This study applied deep convolution neural network based on U-Net and SegNet using long period weather radar data to very short-term rainfall prediction. And the results were compared and evaluated with the translation model. For training and validation of deep neural network, Mt. Gwanak and Mt. Gwangdeoksan radar data were collected from 2010 to 2016 and converted to a gray-scale image file in an HDF5 format with a 1km spatial resolution. The deep neural network model was trained to predict precipitation after 10 minutes by using the four consecutive radar image data, and the recursive method of repeating forecasts was applied to carry out lead time 60 minutes with the pretrained deep neural network model. To evaluate the performance of deep neural network prediction model, 24 rain cases in 2017 were forecast for rainfall up to 60 minutes in advance. As a result of evaluating the predicted performance by calculating the mean absolute error (MAE) and critical success index (CSI) at the threshold of 0.1, 1, and 5 mm/hr, the deep neural network model showed better performance in the case of rainfall threshold of 0.1, 1 mm/hr in terms of MAE, and showed better performance than the translation model for lead time 50 minutes in terms of CSI. In particular, although the deep neural network prediction model performed generally better than the translation model for weak rainfall of 5 mm/hr or less, the deep neural network prediction model had limitations in predicting distinct precipitation characteristics of high intensity as a result of the evaluation of threshold of 5 mm/hr. The longer lead time, the spatial smoothness increase with lead time thereby reducing the accuracy of rainfall prediction The translation model turned out to be superior in predicting the exceedance of higher intensity thresholds (> 5 mm/hr) because it preserves distinct precipitation characteristics, but the rainfall position tends to shift incorrectly. This study are expected to be helpful for the improvement of radar rainfall prediction model using deep neural networks in the future. In addition, the massive weather radar data established in this study will be provided through open repositories for future use in subsequent studies.

• The Journal of Engineering Geology
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• v.28 no.3
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• pp.489-499
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• 2018

A flume experiments was used to study the characteristics of the surface displacements and volumetric water contents (VWC) during torrential rain. The surface displacement and VWC of the granite weathered soil were measured for rainfall intensity (100, 200 mm/hr) and initial ground condition (VWC 7, 14, 26%). The test processes were also recorded by video cameras. According to the test results, The shallow failure is classified into three types: retrogressive failure, progressive failure and defined failure. In the case of retrogressive failure and progressive failure, relatively large damage could occur due to the feature that soil is deposited to the bottom of the slope. the shallow failure occurred when the VWC reached a certain value regardless of the initial soil condition. It was found that the shallow failure can be predicted through the increase patton of the VWC under the condition of the ground dry condition (VWC 7%) and the natural condition (VWC 14%). For high rainfall intensity, progressive failure predominated, and rainfall intensity above a certain level did not affect wetting front transition.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.5
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• pp.791-803
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• 2016

Recently, frequency of extreme rainfall events in South Korea has been substantially increased due to the enhanced climate variability. Korea is prone to flooding due to being surrounded by mountains, along with high rainfall intensity during a short period. In the past three decades, an increase in the frequency of heavy rainfall events has been observed due to enhanced climate variability and climate change. This study aimed to analyze extreme rainfalls informed by their frequency of occurrences using a long-term rainfall data. In this respect, we developed a Poisson-Generalized Pareto Distribution (Poisson-GPD) based rainfall frequency method which allows us to simultaneously explore changes in the amount and exceedance probability of the extreme rainfall events defined by different thresholds. Additionally, this study utilized a Bayesian approach to better estimate both parameters and their uncertainties. We also investigated the synoptic patterns associated with the extreme events considered in this study. The results showed that the Poisson-GPD based design rainfalls were rather larger than those of based on the Gumbel distribution. It seems that the Poisson-GPD model offers a more reasonable explanation in the context of flood safety issue, by explicitly considering the changes in the frequency. Also, this study confirmed that low and high pressure system in the East China Sea and the central North Pacific, respectively, plays crucial roles in the development of the extreme rainfall in South Korea.

• Journal of Korea Water Resources Association
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• v.47 no.1
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• pp.83-93
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• 2014

This research was carried out for suggesting design criteria and procedure for maximizing flood control capacity by building flood control facilities like flood retention basin built in connection with existing facilities in order to cope with increased uncertainty due to factors such as urbanization and climate change. We suggested the procedure for the analysis under the various scenarios applicable for the cases of determining retention basin capacity as provision for the flood water level increase in main river channel or estimating flood water level reduction effect when retention basin capacity is given. Procedure for estimating design flood hydrograph at any duration using Intensity-Duration-Quantity (IDQ) originated from the existing IDF, and its application example were provided. Based on rainfall estimated by the IDQ analysis, it is possible to calculate an equivalent peak hydrographs under various scenarios, e.g. lower frequency hydrograph under same rainfall duration with water level higher than existing hydrograph, hydrograph with same peak and higher volume due to increased rainfall duration, hydrograph with higher peak and volume than existing hydrograph, etc.

• Economic and Environmental Geology
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• v.47 no.1
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• pp.49-59
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• 2014

Rainfall-induced landslides are caused by reduction of effective stress and shear strength due to rainfall infiltration. In order to analyze the susceptibility of landslides, the statistical analysis approach has been used widely but this approach has the limitation which cannot take into account of landslide triggering mechanism. Therefore, the physically based model which can consider the process of landslide occurrence was proposed and commonly used. However, the most previous physically based model analyses evaluate and consider the strength characteristics for saturated soil only in the susceptibility analysis. But the strength parameters for unsaturated soil such as matric suction should be considered with the strength parameters for saturated soil since the shear strength in unsaturated soil also plays important role in the stability of slope. Consequently this study suggested the modified physically based slope model which can evaluate strength characteristics for both of saturated and unsaturated soils. In addition, this study evaluated the thickness of saturated part in slope with rainfall intensity and hydraulic characteristics of slope on the basis of physically based model. In order to evaluate the feasibility, the proposed model was applied to practical example in Jinbu area, Gangwon-do, which was experienced large amount of landslides in July 2006. The ROC graph analysis was used to evaluate the validation of the model, and the analysis results were compared with the results of the previous analysis approach.

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.3
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• pp.29-36
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• 2008

The purpose of this study is to examine the characteristics of disaster associated with typhoon passed through the sea areas excluding the South Sea around the Korean Peninsula. First, Korean peninsula-affecting typhoons were divided into their track patterns of passing through the Korean West Sea and East Sea based on typhoon data from 1951 to 2006 provided by Regional Specialized Meteorological Center(RSMC)-Tokyo. Then, annual and monthly frequency and intensity of typhoon in each pattern was examined. In particular, typhoon related damages during the period of 1973 to 2006 were analyzed in each case. Results showed that since early 1970, in the West Sea case, typhoon becomes weaker without significant change in frequency, while in the East Sea case, it becomes stronger with an increasing trend. It is also found that the high amount of typhoon damage results from the submergence of houses and farmlands in the East Sea case, while it is due to the breakdown of houses, ships, roads and bridges in the West Sea case. In addition, it is revealed from the analysis of rainfall and maximum wind speed data associated with typhoon disasters that the main cause of occurring typhoon disasters seem to be qualitatively related to strong wind in the West Sea case and heavy rainfall in the East Sea case.