• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.2
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• pp.121-132
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• 2018

Along with climate change, it is reported that the extreme climate events such as severe drought could cause difficulties of agricultural water supply. To minimize such damages, it is necessary to secure the agricultural water resources by using or saving the amount of irrigation water efficiently. The objectives of this study were to develop paddy water management scenarios and to evaluate their effectiveness on water saving. Three water management scenarios (a) deep irrigation with ponding depth of 20~80 mm (control, CT), (b) no/intermittent irrigation until paddy cracks (water management A, WM-A), and (c) intermittent irrigation with ponding depth under 20 mm (water management B, WM-B) were developed. Water saving effects were analyzed using monitored data from experimental paddy fields, and agricultural water supply was analyzed on a reservoir-scale using MASA model. The observed irrigation amounts were reduced by 21 % and 17 % for WM-A and WM-B compared to CT, respectively, and mainly occurred by the increase of effective rainfall. The simulation results showed that water management scenarios could reduce irrigation by 21~51 % and total inflow by 10~24 % compared to CT. The long-term simulated water level change of agricultural reservoir resulted in the decrease of dead level occurrence for WM-A and WM-B. The study results showed that WT-A and WT-B have more benefit than CT in the aspect of agricultural reservoir water supply.

• KCID journal
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• v.18 no.2
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• pp.33-42
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• 2011

Climate change has impacts on not only the average temperature rise but also the intensity and frequency of extreme events such as flood and drought. It is also expected that the damages on agricultural infrastructure will be increased resulting from increased rainfall intensity and frequency caused by climate change. To strengthen the climate change adaptation capacity, it is necessary to identify the vulnerability of a given society's physical infrastructures and to develop appropriate adaptation strategies with infrastructure management because generally facilities related to human settlements are vulnerable to climate changes and establishing an adaptive public infrastructure would reduce the damages and the repair cost. Therefore, development of mitigation strategies for agricultural infrastructure against climatic hazard is very important, but there are few studies on agricultural infrastructure vulnerability assessment and adaptation strategies. The concept of vulnerability, however, is difficult to functionally define due to the fact that vulnerability itself includes many aspects (biological, socioeconomic, etc.) in various sectors. As such, much research on vulnerability has used indicators which are useful for standardization and aggregation. In this study, for the vulnerability assessment for agricultural infrastructure, 3 categories of climate exposure, sensitivity, and adaptation capacity were defined which are composed of 16 sub-categories and 49 proxy variables. Database for each proxy variables was established based on local administrative province. Future studies are required to define the weighting factor and standardization method to calculate the vulnerability indicator for agricultural infrastructure against climate change.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.6
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• pp.1919-1924
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• 2014

Recently, due to the climate change, the frequency and intensity of extreme rainfall events have been continuously increased in regions of South Korea. As a consequence, safety issues have been raised especially in the hydrologic safety of old dams designed and constructed by the old standards. In general, for improving hydrologic safety of existing dams, two options are considered: 1) raising dam crest; and 2) constructing or expanding an emergency spillway. In this process, the main criteria of alternative selection are overtopping possibility and cost efficiency of each alternative. This approach is easy to implement but it is subject to major limitation for the proper evaluation of alternatives, overlooking downstream flood damages by any controlled flow of water that is intentionally released from dams to eliminate the possibility of overtopping. Therefore, this study suggests a framework for evaluating the dam safety strengthening alternatives in terms of a comprehensive flood control by applying the concept of resilience. The case study shows that the resilience-based evaluation framework which considering downstream flood damages is effective in the selection of dam safety strengthening alternatives.

• 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.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.203-203
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• 2016

The linkage between climate change and water security, i.e., the response of water resource to the future climate change, have been of great concern to both scientific community and policy makers. In this study, the impact of future climate on water resources in Yellow River Basin in North of China has been investigated using the Coupled Land surface and Hydrology Model System (CLHMS) and IPCC AR5 projected future climate change in the basin. Firstly, the performances of 14 IPCC AR5 models in reproducing the observed precipitation and temperature in China, especially in North of China, have been evaluated, and it's suggested most climate models do show systematic bias compared with the observation, however, CNRM-CM5、HadCM5 and IPSL-CM5 model are generally the best models among those 14 models. Taking the daily projection results from the CNRM-CM5, along with the bias-correction technique, the response of water resources in Yellow river basin to the future climate change in different emission scenarios have been investigated. All the simulation results indicate a reduction in water resources. The current situation of water shortage since 1980s will keep continue, the water resources reduction varies between 28 and 23% for RCP 2.6 and 4.5 scenarios. RCP 8.5 scenario simulation shows a decrease of water resources in the early and mid 21th century, but after 2080, with the increase of rainfall, the extreme flood events tends to increase.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.154-154
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• 2018

To interpret the climate projections for the future as well as present, recognition of the consequences of the climate internal variability and quantification its uncertainty play a vital role. The Korean Peninsula belongs to the Far East Asian Monsoon region and its rainfall characteristics are very complex from time and space perspective. Its internal variability is expected to be large, but this variability has not been completely investigated to date especially using models of high temporal resolutions. Due to coarse spatial and temporal resolutions of General Circulation Models (GCM) projections, several studies adopted dynamic and statistical downscaling approaches to infer meterological forcing from climate change projections at local spatial scales and fine temporal resolutions. In this study, stochastic downscaling methodology was adopted to downscale daily GCM resolutions to hourly time scale using an hourly weather generator, the Advanced WEather GENerator (AWE-GEN). After extracting factors of change from the GCM realizations, these were applied to the climatic statistics inferred from historical observations to re-evaluate parameters of the weather generator. The re-parameterized generator yields hourly time series which can be considered to be representative of future climate conditions. Further, 30 ensemble members of hourly precipitation were generated for each selected station to quantify uncertainty. Spatial map was generated to visualize as separated zones formed through K-means cluster algorithm which region is more inconsistent as compared to the climatological norm or in which region the probability of occurrence of the extremes event is high. The results showed that the stations located near the coastal regions are more uncertain as compared to inland regions. Such information will be ultimately helpful for planning future adaptation and mitigation measures against extreme events.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.287-294
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• 2021

A Python-based LSTM model was constructed using a Tensorflow backend to estimate the amount of outflow during floods in the Gokgyo-cheon basin flowing into the Sapgyo Lake. To understand the effects of the length of input data used for learning, i.e., the sequence length, on the performance of the model, the model was implemented by increasing the sequence length to three, five, and seven hours. Consequently, when the sequence length was three hours, the prediction performance was excellent over the entire period. As a result of predicting three extreme rainfall events in the model verification, it was confirmed that an average NSE of 0.96 or higher was obtained for one hour in the leading time, and the accuracy decreased gradually for more than two hours in the leading time. In conclusion, the flood level at the Gangcheong station of Gokgyo-cheon can be predicted with high accuracy if the prediction is performed for one hour of leading time with a sequence length of three hours.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.3
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• pp.101-112
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• 2019

This study developed selection criteria of small-scales reservoirs, having under $300,000m^3$ storage capacity, for the Emergency Action Plan(EAP) establishment in order to reduce the disaster risks of the reservoir's failures. Those reservoirs are out of ranges of Korean EAP establishment standard, but have potential risk of disasters as they have often failed by the recent extreme rainfall events and earthquakes, causing economical and life losses. The problem of reservoir aging is also one of the reasons of them. In this study, the developed selection criteria of small reservoirs for EAP establishment are storage capacity, embankment height, reservoir age, heavy rain factor and earthquake factor. These criteria were selected based on the review of the existing EAP establishment guidelines, analysis of the past dam failure cases, and the previous related studies. The quantification of these criteria were conducted for the practical applications in the fields, and applied to 67 previous failures in order to investigate the relation of each criteria with these failures. The earthquake factor found to be the highest relations followed by heavy rain factors, combination of earthquake and heavy rain factors, and reservoir age. The classification was made as observation and review groups for EAP establishments based on overlapping numbers of each criteria. This classifications applied to 354 reservoirs designated as having the potential disaster risk by MOIS, and showed 38.4% of observation and 11.9% of review groups. Anticipatory monitoring and regular inspection should be made by professional facility managers for the observation group, and necessity of EAP establishment should be assessed for the review group based on the downstream status and financial budget.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.294-294
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• 2022

In 2013, the Asian Development Bank classified the Philippines among the countries facing high food security risks. Evidence has suggested that climate change has affected agricultural productivity, and the effect of extreme climatic events notably drought has worsened each year. This had resulted in serious hydrological repercussions by limiting the timely water availability for the agriculture sector. Laguna is the 3^rd most populated province in the country, and it serves as one of the food baskets that feed the region and nearby provinces. In addition to climate change, population growth, rapid industrialization, and urban encroachment are also straining the delicate balance between water demand and supply. Studies have projected that the province will experience less rainfall and an increase in temperature, which could simultaneously affect water availability and crop yield. Hence, understanding the composite threat of climate change for crop yield and water consumption is imperative to devise mitigation plans and judicious use of water resources. The water footprint concept elaborates the water used per unit of crop yield production and it can approximate the dual impacts of climate change on water and agricultural production. In this study, the water footprint (WF) of six main crops produced in Laguna were estimated during 2010-2020 by following the methodology proposed by the Water Footprint Network. The result of this work gives importance to WF studies in a local setting which can be used as a comparison between different provinces as well as a piece of vital information to guide policy makers to adopt plans for crop-related use of water and food security in the Philippines.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.334-334
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• 2022

Improvement of old-fashioned rain gauge systems for automatic, timely, continuous, and accurate precipitation observation is highly essential for weather/climate prediction and natural hazards early warning, since the occurrence frequency and intensity of heavy and extreme precipitation events (especially floods) are recently getting more increase and severe worldwide due to climate change. Although rain gauge accuracy of 0.1 mm is recommended by the World Meteorological Organization (WMO), the traditional rain gauges in both weighting and tipping bucket types are often unable to meet that demand due to several existing technical limitations together with higher production and maintenance costs. Therefore, we aim to introduce a newly developed and cost-effective hybrid rain gauge system at 0.1 mm accuracy that combines advantages of weighting and tipping bucket types for continuous, automatic, and accurate precipitation observation, where the errors from long-term load cells and external environmental sources (e.g., winds) can be removed via an automatic drainage system and artificial intelligence-based data quality control procedure. Our rain gauge system consists of an instrument unit for measuring precipitation, a communication unit for transmitting and receiving measured precipitation signals, and a database unit for storing, processing, and analyzing precipitation data. This newly developed rain gauge was designed according to the weather instrument criteria, where precipitation amounts filled into the tipping bucket are measured considering the receiver's diameter, the maximum measurement of precipitation, drainage time, and the conductivity marking. Moreover, it is also designed to transmit the measured precipitation data stored in the PCB through RS232, RS485, and TCP/IP, together with connecting to the data logger to enable data collection and analysis based on user needs. Preliminary results from a comparison with an existing 1.0-mm tipping bucket rain gauge indicated that our developed rain gauge has an excellent performance in continuous precipitation observation with higher measurement accuracy, more correct precipitation days observed (120 days), and a lower error of roughly 27 mm occurred during the measurement period.