• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.325-331
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• 2016

This research developed a flood fragility curve of bridges considering the debris impacts. Damage and failures of civil infrastructure due to natural disasters can cause casualties as well as social and economic losses. Fragility analysis is an effective tool to help better understand the vulnerability of a structure to possible extreme events, such as earthquakes and floods. In particular, flood-induced failures of bridges are relatively common in Korea, because of the mountainous regions and summer concentrated rainfall. The main failure reasons during floods are reported to be debris impact and scour; however, research regarding debris impacts is considered challenging due to various uncertainties that affect the failure probability. This study introduces a fragility analysis methodology for evaluating the structural vulnerability due to debris impacts during floods. The proposed method describes how the essential components in fragility analysis are considered, including limit-state function, intensity measure of the debris impact, and finite element model. A numerical example of the proposed fragility analysis is presented using a bridge pier system under a debris impact.

• Journal of Korea Water Resources Association
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• v.37 no.10
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• pp.813-822
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• 2004

This study quantifies and compares the drought return and duration characteristics by applying the Poisson process as well as based on by analyzing the observed data directly. The drought spatial distributions derived for the Gyunggi province are also compared. The monthly rainfall data are used to construct the SPI as a drought index. Especially, this study focuses on the evaluation of the Poisson process model when applying it to various data lengths such as in the spatial analysis 'of drought. Summarizing the results are as follows. (1) The Poisson process is found to be effective for the quantification of drought, especially when the data length is short. When applying the Poisson process, two neighboring sites are found insensitive to the data length to show similar drought characteristics, so the overall drought pattern becomes smoother than that derived directly from the observed data. (2) When the data length is very different site by site, the spatial analysis of drought based on a model application seems better than that based on the direct data analysis. This study also found more obvious spatial pattern of drought occurrence and duration when applying the Poisson process.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.98-98
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• 2015

강우-유출 모형을 이용하여 직접유출량을 산정할 경우, 유역의 유효우량을 산정하기 위해 NRCS-CN(Natural Resources Conservation Service - curve number) 방법을 주로 사용한다. 그러나 NRCS-CN 방법은 초기손실량을 잠재보유수량의 20%로 가정하고 유효우량을 산정한다. 이는 초기손실량을 과대 추정하여 유효우량의 과소산정을 초래한다. 따라서 본 연구에서는 관측된 강우-유출사상을 바탕으로 초기손실량을 추정하는 방법을 보완하였다. 우리나라 홍수기 동안 강우-유출 자료를 확보한 15개의 유역에 대해 658개의 강우-유출사상에 대하여 NRCS-CN 방법을 기반으로, 초기손실량과 유효우량을 산정하고 이를 관측 직접유출량과 비교 분석하였다. 유효우량을 산정하는 방법으로는 NRCS-CN 방법(M1), NRCS-CN 방법에서 초기손실량계수를 감소시킨 방법(M2), 관측 강우-유출 관계를 바탕으로 본 연구에서 제안하는 방법(M3)을 적용하였다. 또한 USDA에서 제시하는 CN값(CNT)과 유역의 경사도를 고려하여 조정한 CN값(CNC)을 각 방법들에 적용하였다. 모형의 성과는 Root Mean Square Error (RMSE), Nash-Sutcliffe Efficiency (NSE), 그리고 Percent Bias (PBIAS) 등을 이용하여 평가되었다. 그 결과 CNT를 M1, M2, M3에 적용한 경우 각 유역에서 평균적으로 [RMSE(0.24, 18.12, and 16.04), NSE(0.54, 0.73, and 0.79), PBIAS(36.54, 20.25, and 12.00)]로 나타났으며. 이와 비슷하게 CNC를 M1, M2, M3에 적용하였을 경우의 각 유역에서 평균적으로 [RMSE(17.17, 15.88, and 13.82), NSE(0.76, 0.80, and 0.85), PBIAS(3.06, 4.47, and 0.11)]로 나타났다. 본 연구에서 제안된 M3방법을 사용하여 추정한 유효우량이 관측된 직접유출량과 통계학적으로 가장 가까운 값으로 나타났다.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.396-396
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• 2015

Frequent urban floods affect the human safety and economic properties due to a lack of the capacity of drainage system and the increased frequency of torrential rainfall. The drainage system has played an important role in flooding control, so it is necessary to establish the effective countermeasures considering the connection between drainage system and surface flow. To consider the connection, we selected SWMM5 model for analyzing transportation capacity of drainage system and FLUMEN model for calculating inundation depth and time variation of inundation area. First, Thiessen method is used to delineate the sub-catchments effectively base on drainage network data in SWMM5. Then, the output data of SWMM5, hydrograph of each manhole, were used to simulate FLUMEN to obtain inundation depth and time variation of inundation area. The proposed method is applied to Sadang area for the event occurred in $27^{th}$ of July, 2011. A total of 11 manholes, we could check the overflow from the manholes during that event as a result of the SWMM5 simulation. After that, FLUMEN was utilized to simulate overland flow using the overflow discharge to calculate inundation depth and area on ground surface. The simulated results showed reasonable agreements with observed data. Through the simulations, we confirmed that the main reason of the inundation was the insufficient transportation capacities of drainage system. Therefore cooperation of both models can be used for not only estimating inundation damages in urban areas but also for providing the theoretical supports of the urban network reconstruction. As a future works, it is recommended to decide optimized pipe diameters for efficient urban inundation simulations.

• Journal of the Korean Society of Hazard Mitigation
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• v.11 no.3
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• pp.157-163
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• 2011

In this study, after the target basin was divided into both overland and channel grids, the travel time from center of each grid cell to watershed's outlet was calculated based on the manning equation. Through this process, volumetric discharge was calculated according to the isochrones and finally, the direct runoff hydrograph was estimated considering watershed's hydrodynamic characteristics. Sanseong subwatershed located in main stream of Bocheong basin was selected as a target basin. The model parameters are only two: area threshold and channel velocity correction factor; the optimized values were estimated at 3,800 and 3.3, respectively. The developed model based on the tuned parameters led to well-matching results between observed and calculated hydrographs (mean of absolute error of peak discharge: 3.41%, mean of absolute error of peak time: 0.67 hr). Moreover, the analysis results regarding histogram of travel time-contribution area demonstrates that the proposed model characterizes relatively well hydrodynamic characteristics of the catchment due to effective rainfall.

• Journal of the Korean Geosynthetics Society
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• v.17 no.4
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• pp.157-168
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• 2018

Recently, the occurrence of typhoons and heavy rainfall is increasing due to climate change. This causes increase in possibility of landslide damages in rural areas. However, in reality, the precise engineering stability assessment studies are still insufficient. Therefore, in order to reduce the landslide damages and effectively manage mountainous areas, the development of disaster prevention techniques is needed. In this study, to analyze the shock absorbing effect of the buffer-spring during application of dynamic impact load in the debris flow protection system, numerical analysis is carried out for each free field of the buffer-spring and the load sharing ratio of the buffer-spring is also examined. In addition, the field applicability is verified by comparison of the tensile strength of the conventional buffer-spring and the wedge type buffer-spring on various magnitudes of dynamic impact load. As a result of the study, it is found that the net-type debris protection system is effective to mitigate loss of properties and human lifes during landslide.

• Korean Journal of Agricultural Science
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• v.48 no.1
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• pp.103-117
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• 2021

The severe effects of climate change, such as global warming and the El Niño phenomenon, have become more prevalent. In recent years, natural disasters such as drought, heavy rain, and typhoons have taken place, resulting in noticeable damage. Korea is affected by droughts that cause damage to rice fields and crops. Societal interest in droughts is growing, and measures are urgently needed to address their impacts. As the demand for high-quality agricultural products expands, farmers have become more interested in water management, and the demand for field irrigation is increasing. Therefore, we investigated water demand in the irrigation of drought-vulnerable crops. Specifically, we determined the water requirements for crops including cabbage, red pepper, apple, and bean in four regions by calculating the consumptive water use (evapotranspiration), effective rainfall, and irrigation capacity. The total consumptive water use (crop evapotranspiration) estimates for Dangjin-si (cabbage), Yesan-gun (apple), Cheongyang-gun (pepper) in Chungnam, and Goesan-gun (bean) in Chungbuk were 33.5, 206.4, 86.1, and 204.5 mm, respectively. The volumes of groundwater available in the four regions were determined to be the following: Dangjin-si, 4,968,000 m³; Yesan-gun, 4,300,000 m³; Cheongyang-gun, 1,114,000 m³, and Goesan-gun, 3,794,000 m³. The annual amounts available for the representative crops, compared to the amount of evapotranspiration, were 313.9% in Dangjin-si, 29.5% in Yesan-gun, 56.1% in Cheongyang-gun, and 20.1% in Goesan-gun.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.3
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• pp.33-43
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• 2022

South Korea's agricultural nitrogen balance and phosphorus balance rank first and second, respectively, among OECD countries, and proper nutrient management is required to preserve the water quality of rivers and lakes. This study evaluates the effects of furrow mulching on the reduction of non-point source pollution (NPS) load from a sloped upland. The study site was Wanju-gun, Jeollabuk-do, and the survey period was from 2018 to 2019. The slope of the testbed was 13%, and the soil type was sandy loam. The cropping system consisted of maize-autumn Chinese cabbage rotation. The testbed was composed of bare soil (bare), control (Cont.), furrow vegetation mulching (FVM), and furrow nonwoven fabric mulching (FFM) plots. Runoff was collected for each rainfall event with a 1/100 sampler, and the NPS load was calculated by measuring the concentrations of SS, T-N, and T-P. The NPS load was then analyzed for the entire monitoring and crop cultivation periods. During the monitoring period, the effect of reducing the NPS load was 1.5%~44.5% for FVM and 13.1%~55.2% for FFM. During the crop cultivation period, it was 1.2%~80.5% for FVM and 27.0%~65.1% for FFM, indicating that FFM was more effective than FVM. As the NPS load was fairly high during the crop conversion period, an appropriate management method needs to be implemented during this period.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.133-152
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• 2022

Rice is a fundamental staple food commodity all around the world. Globally, it is grown over 167 million hectares and occupies almost 1/5^th of total cultivated land under cereals. With a total production of 782 million metric tons in 2018. In Pakistan, it is the 2^nd largest crop being produced and 3^rd largest food commodity after sugarcane and rice. The stem borers a type of pest in rice and other crops, Scirpophaga incertulas or the yellow stem borer is very serious pest and a major cause of yield loss, more than 90% damage is recorded in Pakistan on rice crop. Yellow stem borer population of rice could be stimulated with various environmental factors which includes relative humidity, light, and environmental temperature. Focus of this study is to find the environmental factors changes i.e., temperature, relative humidity and rainfall that can lead to cause outbreaks of yellow stem borers. this study helps to find out the hot spots of insect pest in rice field with a control of farmer's palm. Proposed system uses temperature, relative humidity, and rain sensor along with artificial neural network to predict yellow stem borer attack and generate warning to take necessary precautions. result shows 85.6% accuracy and accuracy gradually increased after repeating several training rounds. This system can be good IoT based solution for pest attack prediction which is cost effective and accurate.

• ETRI Journal
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• v.44 no.4
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• pp.573-587
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• 2022

The agricultural sector is completely different from other sectors since it completely relies on various natural and climatic factors. Climate changes have many effects, including lack of annual rainfall and pests, heat waves, changes in sea level, and global ozone/atmospheric CO₂ fluctuation, on land and agriculture in similar ways. Climate change also affects the environment. Based on these factors, farmers chose their crops to increase productivity in their fields. Many existing agricultural ontologies are either domain-specific or have been created with minimal vocabulary and no proper evaluation framework has been implemented. A new agricultural ontology focused on subdomains is designed to assist farmers using Jaccard relative extractor (JRE) and Naïve Bayes algorithm. The JRE is used to find the similarity between two sentences and words in the agricultural documents and the relationship between two terms is identified via the Naïve Bayes algorithm. In the proposed method, the preprocessing of data is carried out through natural language processing techniques and the tags whose dimensions are reduced are subjected to rule-based formal concept analysis and mapping. The subdomain ontologies of weather, pest, and soil are built separately, and the overall agricultural ontology are built around them. The gold standard for the lexical layer is used to evaluate the proposed technique, and its performance is analyzed by comparing it with different state-of-the-art systems. Precision, recall, F-measure, Matthews correlation coefficient, receiver operating characteristic curve area, and precision-recall curve area are the performance metrics used to analyze the performance. The proposed methodology gives a precision score of 94.40% when compared with the decision tree(83.94%) and K-nearest neighbor algorithm(86.89%) for agricultural ontology construction.