• Title/Summary/Keyword: Water Disaster Management

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A STUDY ON NUMERICAL COUPLING BETWEEN MECHANICAL AND HYDRAULIC BEHAVIORS IN A GRANITE ROCK MASS SUBJECT TO HIGH-PRESSURE INJECTION

  • Jeong, Woo-Chang;Jai-Woo;Song, Jai-Woo
    • Water Engineering Research
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    • v.2 no.2
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    • pp.123-138
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    • 2001
  • An injection experiment was carried ut to investigate the pressure domain within which hydromechanical coupling influences considerably the hydrologic behavior of a granite rock mass. The resulting database is used for testing a numerical model dedicated to the analysis of such hydromechanical interactions. These measurements were performed in an open hole section, isolated from shallower zones by a packer set at a depth of 275 m and extending down to 840 m. They consisted in a series of flow meter injection tests, at increasing injection rates. Field results showed that conductive fractures from a dynamic and interdependent network, that individual fracture zones could not be adequately modeled as independent systems, that new fluid intakes zones appeared when pore pressure exceeded the minimum principal stress magnitude in that well, and that pore pressures much larger than this minimum stress could be further supported by the circulated fractures. These characteristics give rise to the question of the influence of the morphology of the natural fracture network in a rock mass under anisotropic stress conditions on the effects of hydromechanical couplings.

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Study on Applicability of Multi-Criteria Decision Making Technique for Malfunctioning Reservoir Selection (기능저하 저수지 선정을 위한 다기준 의사결정기법 적용성 연구)

  • Shim, Hyun Chul;Choi, Kyung Sook
    • Journal of The Korean Society of Agricultural Engineers
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    • v.59 no.3
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    • pp.11-19
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    • 2017
  • The decision-making process is the act of finding the best solution among various alternatives through comparison between various criteria based on objectives of the project, evaluation standard, and conditions. However, in practice it is not easy to simply decide the optimum decision, especially for selecting malfunctioning reservoirs because no systematic evaluation criteria or standard assessment process are available. Therefore, this study adopted AHP method, which is a MCDM (multi-criteria decision making technique) to identify the malfunctioning reservoirs for efficient management of reservoirs. Important criteria of the selection of malfunctioning reservoirs and priority weights of each criteria were determined based on results of expert's survey under a stepwise hierarchical approach. The most important factor for the decision of malfunctioning reservoirs was obtained as Reservoir efficiency among the selected criteria including Reservoir efficiency decrease, Disaster Risk, Reservoir efficiency, Available water storage, Future water demand, Resident Needs. The AHP technique was applied on 11 reservoirs in Andong region to verify its applicability. Scoring method was applied for the comparison with the results of AHP method.

A Study for Characteristics of Water that Penetrates Wood Flour due to Changes of Concentration of BDG (BDG 농도변화에 따른 용수의 목분 침투특성 연구)

  • Kong, Il-Chean;Park, Il-Gyu;Lim, Kyung-Bum;Rie, Dong-Ho
    • Journal of the Korean Society of Safety
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    • v.28 no.3
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    • pp.74-79
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    • 2013
  • As the feature of fire, it is hard for deep-seated fire to spread to the deeper site, and it also has danger for being re-ignited cause of recontacting with oxygen after being put off. Now it is ruled in the certification criteria of wetting agent used for extinguishing deep-seated fire that the criteria for surface tension is below 33[mN/m] in Korea. For figuring out how much water for fire-fighiting can permeate into combustibles, in this research, the permeating performance is analyzed by measuring the speed of permeating and transmission quantity released after that, by pouring solution whose surface tension is changed by adjusting concentration of surfactant BDG(Butyl Di Glycol) in column From this result, it is can be determined that transmission quantity becomes less and wet area goes wider as surface tension is lower, and it is also able to be analyzed as quantity of absorbed liquid and wet area is increased because fluid permeates into the core.

Establishment of monitoring system for verification of urban flooding warning criterion (도시침수 경보기준 검증을 위한 모니터링 체계 구축)

  • Bae, Changyeon;Kang, ho Seon;Choi, Changwon
    • Proceedings of the Korea Water Resources Association Conference
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    • 2018.05a
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    • pp.5-5
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    • 2018
  • 최근 기후변화로 인하여 이상기후 및 지구온난화 현상의 발생이 증가하고 있다. 2014년 한국 기후변화 평가보고서에 따르면 강우량은 1971~2000년 1,315mm에서 2001~2010년 1,412mm으로 7.4% 증가하였으며, 호우일수는 1971~2000년 20일에서 2001~2010년 28일로 8일이 증가하였다. 이러한 강우량의 증가 및 호우일수의 증가로 도심지의 침수피해는 지속적으로 발생하고 있지만 도시특성을 반영한 예 경보 체계의 부재로 그 피해는 가중되고 있다. 국립재난안전연구원에서는 2014년부터 도심지 침수피해를 예방하기 위해 한계강우량 및 도시침수 경보기준 개발 연구를 수행하고 있다. 도시침수 경보기준은 도시침수를 발생시키는 최소 강우량을 의미하는 한계강우량 개념을 도입하여 국가재난관리시스템(NDMS, National Disaster Management System)의 과거 피해이력과 강우량과의 분석을 통해 산정하였다. 2017년 까지 27개 시군구 470여개 읍면동의 경보기준을 산정하였으며, 적용성 평가를 위해 실제 피해가 발생한 지역의 CCTV자료를 수집하여 한계강우량을 추정하고 경보기준 검증을 실시하였다. CCTV를 활용한 경보기준의 검증은 영상자료 확보의 어려움과 침수시간 및 정확한 침수심의 변화를 확인하는데는 한계가 있다. 따라서 본 연구에서는 지표침수 및 우수관 수위관측 시설을 구축하여 도시침수 발생 양상을 모니터링 하고 경보기준을 검증하고자 한다. 또한 구축된 모니터링 시설은 향후 실측 기반의 예 경보체계구축을 위한 기초자료로 활용할 수 있을 것이다.

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A Machine Learning-Driven Approach for Wildfire Detection Using Hybrid-Sentinel Data: A Case Study of the 2022 Uljin Wildfire, South Korea

  • Linh Nguyen Van;Min Ho Yeon;Jin Hyeong Lee;Gi Ha Lee
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.175-175
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    • 2023
  • Detection and monitoring of wildfires are essential for limiting their harmful effects on ecosystems, human lives, and property. In this research, we propose a novel method running in the Google Earth Engine platform for identifying and characterizing burnt regions using a hybrid of Sentinel-1 (C-band synthetic aperture radar) and Sentinel-2 (multispectral photography) images. The 2022 Uljin wildfire, the severest event in South Korean history, is the primary area of our investigation. Given its documented success in remote sensing and land cover categorization applications, we select the Random Forest (RF) method as our primary classifier. Next, we evaluate the performance of our model using multiple accuracy measures, including overall accuracy (OA), Kappa coefficient, and area under the curve (AUC). The proposed method shows the accuracy and resilience of wildfire identification compared to traditional methods that depend on survey data. These results have significant implications for the development of efficient and dependable wildfire monitoring systems and add to our knowledge of how machine learning and remote sensing-based approaches may be combined to improve environmental monitoring and management applications.

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Application of Convolutional Neural Networks (CNN) for Bias Correction of Satellite Precipitation Products (SPPs) in the Amazon River Basin

  • Alena Gonzalez Bevacqua;Xuan-Hien Le;Giha Lee
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.159-159
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    • 2023
  • The Amazon River basin is one of the largest basins in the world, and its ecosystem is vital for biodiversity, hydrology, and climate regulation. Thus, understanding the hydrometeorological process is essential to the maintenance of the Amazon River basin. However, it is still tricky to monitor the Amazon River basin because of its size and the low density of the monitoring gauge network. To solve those issues, remote sensing products have been largely used. Yet, those products have some limitations. Therefore, this study aims to do bias corrections to improve the accuracy of Satellite Precipitation Products (SPPs) in the Amazon River basin. We use 331 rainfall stations for the observed data and two daily satellite precipitation gridded datasets (CHIRPS, TRMM). Due to the limitation of the observed data, the period of analysis was set from 1st January 1990 to 31st December 2010. The observed data were interpolated to have the same resolution as the SPPs data using the IDW method. For bias correction, we use convolution neural networks (CNN) combined with an autoencoder architecture (ConvAE). To evaluate the bias correction performance, we used some statistical indicators such as NSE, RMSE, and MAD. Hence, those results can increase the quality of precipitation data in the Amazon River basin, improving its monitoring and management.

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Exploring the Relationship between the Kinetic Energy and Intensity of Rainfall in Sangju, Korea

  • Van, Linh Nguyen;Le, Xuan-Hien;Yeon, Minho;Thi, Tuyet-May Do;Lee, Giha
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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    • pp.151-151
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    • 2022
  • The impact of raindrops on the soil surface causes soil detachment, which may be estimated by measuring the kinetic energy (KE) of the raindrops. Since direct measurements of rainfall force on ground surfaces are not generally available, empirical equations are an alternative option to estimate KE from rainfall intensity (I), which has the greatest influence over soil erosion and is easily accessible. Establishing the optimal formulation for the relationship between kinetic energy and rainfall intensity has proven to be difficult. Thus, this research considered thirty-seven rainfall events observed from June 2020 to December 2021 using a laster optical disdrometer erected in Kyungpook National University to examine the characteristics of KE-I relationships. We concentrated our discussion on the formation of two different expressions of the KE, including KE expenditure (KEexp) and KE content (KEcon). The following conclusions were drawn: (1) We employed statistical analysis to demonstrate that the KEexp is more suitable expression for establishing an empirical rule between KE and I than the KEcon. (2) A power-law model was used to find the best correlation between KEexp-I relationship, whereas the best match between KEcon and I were found using an exponential equation.

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Estimation of Soil Organic Carbon Stock in South Korea

  • Thi, Tuyet-May Do;Le, Xuan-Hien;Van, Linh Nguyen;Yeon, Minho;Lee, Giha
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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    • pp.159-159
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    • 2022
  • Soil represents a substantial component within the global carbon cycle and small changes in the SOC stock may result in large changes of atmospheric CO2 particularly over tens to hundreds of years. In this study, we aim to (i) evaluate the SOC stock in the topsoil 0 - 15 cm from soil physical and chemical characteristics and (ii) find the correlation of SOC and soil organic matter (SOM) for national-scale in South Korea. First of all, based on the characteristics of the soil to calculate the soil hydraulic properties, SOC stock is the SOC mass per unit area for a given depth. It depends on bulk density (BD-g/cm3), SOC content (%), the depth of topsoil (cm), and gravel content (%). Due to insufficient data on BD observation, we establish a correlation between BD and SOC content, sand content, clay content parameter. Next, we present linear and non-linear regression models of BD and the interrelationship between SOC and SOM using a linear regression model and determine the conversion factor for them, comparing with Van Bemmelen 1890's factor value for the country scale. The results obtained, helps managers come up with suitable solutions to conserve land resources.

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Analysis of bias correction performance of satellite-derived precipitation products by deep learning model

  • Le, Xuan-Hien;Nguyen, Giang V.;Jung, Sungho;Lee, Giha
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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    • pp.148-148
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    • 2022
  • Spatiotemporal precipitation data is one of the primary quantities in hydrological as well as climatological studies. Despite the fact that the estimation of these data has made considerable progress owing to advances in remote sensing, the discrepancy between satellite-derived precipitation product (SPP) data and observed data is still remarkable. This study aims to propose an effective deep learning model (DLM) for bias correction of SPPs. In which TRMM (The Tropical Rainfall Measuring Mission), CMORPH (CPC Morphing technique), and PERSIANN-CDR (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks) are three SPPs with a spatial resolution of 0.25o exploited for bias correction, and APHRODITE (Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation) data is used as a benchmark to evaluate the effectiveness of DLM. We selected the Mekong River Basin as a case study area because it is one of the largest watersheds in the world and spans many countries. The adjusted dataset has demonstrated an impressive performance of DLM in bias correction of SPPs in terms of both spatial and temporal evaluation. The findings of this study indicate that DLM can generate reliable estimates for the gridded satellite-based precipitation bias correction.

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Influences of the Construction of the Torrent Control Structure using Customized Tetrapods on the Stream Water Quality at Valley (맞춤형 테트라블록을 이용한 야계사방구조물이 계류수질에 미치는 영향)

  • Park, Jae-Hyeon;Ma, Ho-Seop;Kim, Ki-Heung;Youn, Ho-Joong
    • Journal of Korean Society of Forest Science
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    • v.100 no.1
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    • pp.105-111
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    • 2011
  • The purpose of this study was to find out the effect of a torrent control structure using customized tetrapods on the forest water quality conservation and management. The study was conducted in the Honggye valley located in Sanchung-gun, Gyungsangnam-do, and stream water quality was compared before and after construction of torrent control structure. After construction of the torrent control structure using customized tetrapods, pH of stream water didn't get out of the range of River water quality standard class I. After construction of the torrent control structure using customized tetrapods, Dissolved Oxygen concentration didn't change, and Electrical Conductivity measurements agreed well within the range of normal clean stream water quality. After construction of the torrent control structure using customized tetrapods, average of total amount of anion was 3.07/2.30~3.60 mg/L, being slightly greater than before construction. Stream water quality after construction of the torrent control structure was similar to before construction. Therefore, it was find out that the torrent control structure didn't affect stream water quality.