Proceedings of the Korea Water Resources Association Conference
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2023.05a
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pp.248-248
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2023
In recent years, the number of landslides in Korea has been increasing due to extreme weather events such as localized heavy rainfall and typhoons. Landslides often occur with debris flows, land subsidence, and earthquakes. They cause significant damage to life and property. 64% of Korea's land area is made up of mountains, the government wanted to predict landslides to reduce damage. In response, the Korea Forest Service has established a 'Landslide Information System' to predict the likelihood of landslides. This system selects a total of 13 landslide factors based on past landslide events. Using the LR technique (Logistic Regression) to predict the possibility of a landslide occurrence and the accuracy is known to be 0.75. However, most of the data used for learning in the current system is on landslides that occurred from 2005 to 2011, and it does not reflect recent typhoons or heavy rain. Therefore, in this study, we will apply a total of six machine learning techniques (KNN, LR, SVM, XGB, RF, GNB) to predict the occurrence of landslides based on the data of Inje, Gangwon-do, which was recently produced by the National Institute of Forest. To predict the occurrence of landslides, it is necessary to process converting landslide events and factors data into a suitable form for machine learning techniques through ArcGIS and Python. In addition, there is a large difference in the number of data between areas where landslides occurred or not. Therefore, the prediction was performed after correcting the unbalanced data using Tomek Links and Near Miss techniques. Moreover, to control unbalanced data, a model that reflects soil properties will use to remove absolute safe areas.
Jung, Sungho;Oh, Sungryul;Lee, Daeeop;Le, Xuan Hien;Lee, Giha
Journal of Korea Water Resources Association
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v.54
no.7
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pp.453-462
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2021
As the frequency of localized heavy rainfall has increased during recent years, the importance of high-resolution radar data has also increased. This study aims to correct the bias of Dual Polarization radar that still has a spatial and temporal bias. In many studies, various statistical techniques have been attempted to correct the bias of radar rainfall. In this study, the bias correction of the S-band Dual Polarization radar used in flood forecasting of ME was implemented by a Convolutional Autoencoder (CAE) algorithm, which is a type of Convolutional Neural Network (CNN). The CAE model was trained based on radar data sets that have a 10-min temporal resolution for the July 2017 flood event in Cheongju. The results showed that the newly developed CAE model provided improved simulation results in time and space by reducing the bias of raw radar rainfall. Therefore, the CAE model, which learns the spatial relationship between each adjacent grid, can be used for real-time updates of grid-based climate data generated by radar and satellites.
With the occurrence of localized heavy rain while river flow has increased, both flow and rainfall cause riverside flood damages. As the degree of damage varies according to the level of social and economic impact, it is required to secure sufficient forecast lead time for flood response in areas with high population and asset density. In this study, the author established a flood risk matrix using ensemble rainfall runoff modeling and evaluated its applicability in order to increase the damage reduction effect by securing the time required for flood response. The flood risk matrix constructs the flood damage impact level (X-axis) using flood damage data and predicts the likelihood of flood occurrence (Y-axis) according to the result of ensemble rainfall runoff modeling using LENS rainfall data and as well as probabilistic forecasting. Therefore, the author introduced a method for determining the impact level of flood damage using historical flood damage data and quantitative flood damage assessment methods. It was compared with the existing flood warning data and the damage situation at the flood warning points in the Taehwa River Basin and the Hyeongsan River Basin in the Nakdong River Region. As a result, the analysis showed that it was possible to predict the time and degree of flood risk from up to three days in advance. Hence, it will be helpful for damage reduction activities by securing the lead time for flood response.
Localized unprecedented torrential rain and heavy rainfall cause repeated damages and make it difficult to detect and predict the landslide caused by heavy rainfall. To analyze the landslide characteristics of Inje area this study used satellite images photographed after the occurrence of landslide caused by the typhoon Ewiniar occurred in July, 2006, and for GIS analysis purpose, interpreted the satellite images (SPOT5) visually to digitize into developing parts, water traveling parts and sediment parts. For analysis of spatial characteristics, landslide areas obtained from visual interpretation of digital map, 3rd & 4th forest vegetation maps and detailed soil map and grids were overlaid and analyzed. As a result, in regard to topographic features, landslide occurred at places, of which average slope is $26.34^{\circ}$, had south, south-east, south-west aspects and average altitude of 627m. From hydrological analysis, it was found out that water traveling area rapidly spread approaching water traveling area and sediment area. From forest type analysis, it was found out that landslide occurrence was high in pine woods, and in terms of girth class attribute, landslide occurred in small-sized woods, in which the crown occupancy of trees that have the diameter at breast height, 6~16cm, was greater than 50%. From the analysis of soil series, landslide areas constitute 37.85% of OdF and 37.35% of SmF, which had sandy loam soil and excellent drainage capacity. Through this study, landslides in Inje area were characterized and SPOT5 images of 2.5m resolution could be used. But there was a difficulty in determining water traveling parts adjacent to urban area.
Kim, Sung-Wook;Choi, Eun-Kyeong;Park, Dug-Keun;Yoon, Yeo-Jin;Lee, Kyu-Hwan
Journal of the Korean Geotechnical Society
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v.28
no.7
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pp.41-53
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2012
During rainfall period, to identify the characteristics of the infiltration of moisture, electrical resistivity monitering survey was carried out to weathered zone. Four regions of geophysical exploration areas with different rock types, four regions were selected. An area consists of mafic granite and three areas are composed of sedimentary rocks (Sandstone, Shale, Unconsolidated Mudstone). Survey was conducted from June (rainy season) to November (dry season), and during the period the change in resistivity was observed. According to the result of monitoring exploration on Geumjeong and Jinju areas, for the estimation of the standard rainfall, it is necessary to estimate the effects of the antecedent rainfall during the rainy season based on the overall rainfall from June till October and also necessary to consider this for the estimation of the half period. Also, the vertical distribution of the low resistivity anomaly zone does not show that the infiltration of moisture does not occur uniformly from the surface of the ground to the lower ground but shows that it occurs along the relaxed gap of the crack or soil stratum of the weathering zone. In Pohang area, the type of moisture infiltration is different from that of the granite or sedimentary rock. Since, after the rainfall, the rate of infiltration to the lower ground is high and the period of cultivation to the lower bedrock aquifer is short, it has similar effect to that of the antecedent rainfall applied for the estimation of the standard rainfall being presently used. In Danyang, due to the degree of water content of the ground, the duration period of the low resistivity anomaly zone observed in the lower ground of the place where clastic sedimentary rock is distributed is similar to that in Pohang area. The degree of lateral water diffusion at the time of localized heavy rain is the same as that of the sedimentary rock in Jinju. According to the above analysis results, in Danyang area, the period when the antecedent rainfall has its influence is estimated as three weeks or so.
Journal of the Korean Society of Hazard Mitigation
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v.10
no.4
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pp.105-117
/
2010
The topographical depressions in urban areas, the lack in drainage capability, sewage backward flow, road drainage, etc. cause internal inundation, and the increase in rainfall resulting from recent climate change, the rapid urbanization accompanied by economic development and population growth, and the increase in an impervious area in urban areas deteriorate the risk of internal inundation in the urban areas. In this study, the vulnerability of internal inundation in urban areas is analyzed and SWMM model is applied into Oncheoncheon watershed, which represents urban river of Busan, as a target basin. Based on the results, the representative storm sewers in individual sub-catchments is selected and the risk of vulnerability to internal inundation due to rainfall in urban streams is analyzed. In order to analyze the risk and vulnerability of internal inundation, capacity is applied as an index indicating the volume of a storm sewer in the SWMM model, and the risk of internal inundation is into 4 steps. For the analysis on the risk of internal inundation, simulation results by using a SMMM model are compared with the actual inundation areas resulting from localized heavy rain on July 7, 2009 at Busan and comparison results are analyzed to prove the validity of the designed model. Accordingly, probabilistic rainfall at Busan was input to the model for each frequency (10, 20, 50, 100 years) and duration (6, 12, 18, 24hr) at Busan. In this study, it suggests that the findings can be used to preliminarily alarm the possibility of internal inundation and selecting the vulnerable zones in urban areas.
Kang, Keon Kuk;Lee, Dong Seop;Hwang, Seok Hwan;Kim, Byung Sik
Journal of Korea Water Resources Association
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v.47
no.12
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pp.1107-1119
/
2014
Interesting in abnormal climate is currently growing because of climate change. With this, an increasing number of people continue to show concern over the negative effects of such changes. In Korea, the annual average rainfall amount increased to about 19% from 1,155 mm in the 1910s to 1,375 mm in the 2000s. By the end of the 21st century, it has been projected that rainfall will further increase to about 17%. In particular, the 10-year frequency of localized heavy rain of more than 100-mm rainfall per day reached 385 days in the last 10 years. As such, it increased 1.7 times from 222 in the 1970s-80s. The extreme events caused by climate change is thus reported as having exacerbated over the years. Gangwon-province will suffer more from climate change than any other region in Korea because of its mostly mountainous terrain. It is a special region with both mountainous and oceanic climates divided alongside the eastern and western regions of the Taebaek Mountain Range. As such, this paper try to quantify using ETCCDI (Expert Team on Climate Change Detection and Indices) the recent climate changes in this region.
Urban flooding caused by localized heavy rainfall with unstable climate is constantly occurring, but a system that can predict spatial flood information with weather forecast has not been prepared yet. The worst flood situation in urban area can be occurred with difficulties of structural measures such as river levees, discharge capacity of urban sewage, storage basin of storm water, and pump facilities. However, identifying in advance the spatial flood information can have a decisive effect on minimizing flood damage. Therefore, this study presents a methodology that can predict the urban flood map in real-time by using rainfall data of the Korea Meteorological Administration (KMA), the results of two-dimensional flood analysis and random forest (RF) regression model. The Ujeong district in Ulsan metropolitan city, which the flood is frequently occurred, was selected for the study area. The RF regression model predicted the flood map corresponding to the 50 mm, 80 mm, and 110 mm rainfall events with 6-hours duration. And, the predicted results showed 63%, 80%, and 67% goodness of fit compared to the results of two-dimensional flood analysis model. It is judged that the suggested results of this study can be utilized as basic data for evacuation and response to urban flooding that occurs suddenly.
Water disasters such as flash floods and inundation caused by localized heavy rainfall in urban areas have a large impact on climate change but are also closely related to the increase in impervious areas as pointed out in domestic and international studies. It is difficult to secure natural green areas in urban areas that have already been developed. So, urban regeneration can be expected using water management optimized with technologies to secure infiltration and storage capacity such as Low-Impact Development technology. In this study, the water cycle improvement ability was confirmed by applying the LID technology within the district unit plan of the environmentally friendly village, and the economic feasibility of LID application was analyzed by estimating the costs and benefits of installing the facilities. The site was planned to conserve sufficient green and plans for securing the watershed infiltration and storage capacity were formulated with the application of additional LID technology, such as infiltration trenches, rain barrels and permeable pavements. The LID design method applicable to the site was established, and the water balance of the watershed was analyzed through simulations of the SWMM model. The water circulation improvement effect was confirmed through the water balance analysis, and the cost-benefits were determined according to the estimation method, and the economic analysis was conducted. This study confirms that the investment of LID technology is economically feasible for the hydrological improvement effect of the housing complex.
Journal of Korean Society of Disaster and Security
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v.12
no.3
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pp.51-57
/
2019
In recent years, the occurrence of localized torrential rain has increased due to the increase in heavy rainfall and massive typhoons caused by abnormal weather. As a result, the flow rate of small and medium-sized rivers in Korea is rapidly increasing, affecting the safety of bridges and increasing the risk of scour. However, the domestic bridge construction technology does not reflect the watershed characteristics of domestic rivers because the bridge scour depth calculation formula developed overseas is used to calculate the bridge scour depth. Therefore, this study is a basic study for prevention of bridge damage according to scouring phenomenon, and a comparative analysis was performed between the experimental data measured through hydraulic model test and the scour depth formulas applied in Korea. In addition, the statistical analysis between experimental data and scour depth formula shows that Coleman's (1971) formula estimates the best scour depth. The results of this study are expected to be used to calculate more accurate bridge scour depth in river design and bridge design.
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