• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.506-506
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• 2022

비점오염원에서 배출되는 오염부하량(BOD, T-P)은 점오염원의 2배 이상을 차지하고 있어 비점오염원 관리에 대한 관심이 증대되고 있다. 이에 비점오염원의 효율적 관리를 위한 전략 및 추진과제 마련을 위해 제1차('04-'11), 제2차('12-'20) 비점오염원 관리 종합대책(이하 종합대책)이 수립 및 이행되었다. 이어 2016년 물환경보전법 개정에 따라 종합대책의 수립이 법제화되고 지난 2020년 말 제3차 비점종합대책('21~'25)이 수립되었다. 제3차 비점종합대책은 수질개선이 체감되는 비점오염원 관리라는 비전을 가지며 도시, 농·축산, 산림, 관리기반의 4개 분야에 총 71개의 세부 추진과제를 제시하고 있다. T-P 비점오염배출부하량 5% 감축, 불투수율 감축, 비점오염관리지역개소 확대, 고랭지 흙탕물 관리지역 구역 확장, 지역 거버넌스 구축을 대책의 목표와 각 분야별 관리지표로 제시하고 있다. 물환경보전법 제53조의5와 동법 시행령 제75조의3에 따라 환경부장관은 매년 이행사항을 점검 및 평가하여 그 결과를 비점오염원 관리 정책의 수립 및 집행에 반영해야 한다. 지난 제1·2차 대책의 경우 성과 점검 및 관리를 위한 체계가 부재하여 사업의 실효성 확보에 한계가 있었으며 이에 따라 소관별 이행사항 점검 및 평가체계의 필요성이 제기되었다. 따라서 본 연구에서는 종합대책 이행평가 전략 및 세부 추진체계를 마련하여 효율적인 소관별 이행사항 점검 및 평가를 도모하고자 하였다. 분야별 세부 추진과제는 매년, 대책의 목표와 각 분야별 관리지표는 대책 시행 후 5차년에 점검 및 평가할 수 있도록 구성하였다. 또한 종합대책의 최종 목표 달성 시뮬레이션을 통해 5차년 이후 원활한 평가가 이루어질 수 있도록 하였다. 본 연구에서 마련한 이행평가 체계를 통해 적절한 이행평가 및 효율적인 비점오염원 관리를 도모할 수 있을 것으로 사료된다.

• Journal of Korea Water Resources Association
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• v.56 no.4
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• pp.245-259
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• 2023

The agricultural reservoir is a critical water supply system in South Korea, providing approximately 60% of the agricultural water demand. However, the reservoir faces several issues that jeopardize its efficient operation and management. To address this issues, we propose a novel deep-learning-based water level recognition model that uses CCTV image data to accurately estimate water levels in agricultural reservoirs. The model consists of three main parts: (1) dataset construction, (2) image segmentation using the U-Net algorithm, and (3) CCTV-based water level recognition using either CNN or ResNet. The model has been applied to two reservoirs G-reservoir and M-reservoir with observed CCTV image and water level time series data. The results show that the performance of the image segmentation model is superior, while the performance of the water level recognition model varies from 50 to 80% depending on water level classification criteria (i.e., classification guideline) and complexity of image data (i.e., variability of the image pixels). The performance of the model can be improved if more numbers of data can be collected.

• Journal of Korea Water Resources Association
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• v.56 no.5
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• pp.325-336
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• 2023

In August 2022, even though flood damage occurred in the metropolitan area due to heavy rain, drought warnings were issued in Jeolla province, which indicates that the regional drought is intensified recent years. To cope with regarding intensified regional droughts, many studies have been conducted to identify spatial patterns of the occurrence of meteorological drought, however, case studies of spatial clustering for water shortage are not sufficient. In this study, using the estimations of water shortage in the Han River Basin in 2030 of the Master Plans for National Water Management, the spatial characteristics of water shortage were analyzed to identify the hotspot areas based on the Local Moran's I and Getis-Ord Gi^*, which are representative indicators of spatial clustering analysis. The spatial characteristics of water shortage areas were verified based on the p-value and the Moran scatter plot. The overall results of for three anayisis periods (S0(1967-1983), S1(1984-2000), S2(2001-2018)) indicated that the lower Imjin River (#1023) was the hotspot for water shortage, and there are moving patterns of water shortage from the east of lower Imjin River (#1023) to the west during S2 compared to S0 and S1. In addition, the Yangyang-namdaecheon (#1301) was the HL area that is adjacent to a high water shortage area and a low water shortage area, and had water shortage pattern in S2 compared to S0 and S1.

• Journal of Korea Water Resources Association
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• v.56 no.8
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• pp.509-520
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• 2023

Various drought indices are widely used for assessing drought conditions which are affected by many factors such as precipitation, soil moisture, and runoff. The values of drought indices varies depending on hydro-meteorological data and calculation formulas, and the judgment of the drought condition may also vary. This study selected four calculation components such as precipitation data length, accumulation period, probability distribution function, and parameter estimation method as the sources of uncertainty in the calculation of standardized precipitation index (SPI), and evaluated their contributions to the uncertainty using root mean square error (RMSE) and linear mixed model (LMM). The RMSE estimated the overall errors in the SPI calculation, and the LMM was used to quantify the uncertainty contribution of each factor. The results showed that as the accumulation period increased and the data period extended, the RMSEs decreased. The comparison of relative uncertainty using LMM indicated that the sample size had the greatest impact on the SPI calculation. In addition, as sample size increased, the relative uncertainty related to the sample size used for SPI calculation decreased and the relative uncertainty associated with accumulation period and parameter estimation increased. In conclusion, to reduce the uncertainty in the SPI calculation, it is essential to collect long-term data first, followed by the appropriate selection of probability distribution models and parameter estimation methods that represent well the data characteristics.

• Journal of Korea Water Resources Association
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• v.57 no.2
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• pp.87-97
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• 2024

This study analyzed the water shortage hotspot areas in South Korea using spatial clustering analysis for water shortage estimates in 2030 of the Master Plans for National Water Management. To identify the water shortage cluster areas, we used water shortage data from the past maximum drought (about 50-year return period) and performed spatial clustering analysis using Local Moran's I and Getis-Ord Gi*. The areas subject to spatial clusters of water shortage were selected using the cluster map, and the spatial characteristics of water shortage areas were verified based on the p-value and the Moran scatter plot. The results indicated that one cluster (lower Imjin River (#1023) and neighbor) in the Han River basin and two clusters (Daejeongcheon (#2403) and neighbor, Gahwacheon (#2501) and neighbor) in the Nakdong River basin were found to be the hotspot for water shortage, whereas one cluster (lower Namhan River (#1007) and neighbor) in the Han River Basin and one cluster (Byeongseongcheon (#2006) and neighbor) in the Nakdong River basin were found to be the HL area, which means the specific area have high water shortage and neighbor have low water shortage. When analyzing spatial clustering by standard watershed unit, the entire spatial clustering area satisfied 100% of the statistical criteria leading to statistically significant results. The overall results indicated that spatial clustering analysis performed using standard watersheds can resolve the variable spatial unit problem to some extent, which results in the relatively increased accuracy of spatial analysis.

• Journal of Korea Water Resources Association
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• v.57 no.5
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• pp.311-320
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• 2024

Climate change has been intensifying drought frequency and severity. Such prolonged droughts reduce reservoir levels, thereby exacerbating drought impacts. While previous studies have focused on optimizing reservoir operations using historical data to mitigate these impacts, their scope is limited to analyzing past events, highlighting the need for predictive methods for future droughts. This research introduces a novel approach for predicting minimum inflow at the Seomjingang dam which has experienced significant droughts. This study utilized the Stochastic Analysis Modeling and Simulation (SAMS) 2007 to generate inflow sequences for the same period of observed inflow. Then we simulate reservoir operations to assess firm yield and predict minimum inflow through synthetic inflow analysis. Minimum inflow is defined as the inflow where firm yield is less than 95% of the synthetic inflow in many sequences during periods matching observed inflow. The results for each case indicated the firm yield for the minimum inflow is on average 9.44 m³/s, approximately 1.07 m³/s lower than the observed inflow's firm yield of 10.51 m³/s. The minimum inflow estimation can inform reservoir operation standards, facilitate multi-reservoir system reviews, and assess supplementary capabilities. Estimating minimum inflow emerges as an effective strategy for enhancing water supply reliability and mitigating shortages.

• Journal of Korea Water Resources Association
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• v.54 no.12
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• pp.1339-1348
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• 2021

In accordance with the River Law, the basic river maintenance plan is established every 5-10 years with a considerable national budget for domestic rivers, and various river surveys such as the river section required for HEC-RAS simulation for flood level calculation are being conducted. However, river survey data are provided only in the form of a pdf report to the River Management Geographic Information System (RIMGIS), and the original data are distributedly owned by designers who performed the river maintenance plan in CAD format. It is a situation that the usability for other purposes is considerably lowered. In addition, when using surveyed CAD-type cross-sectional data for HEC-RAS, tools such as 'Dream' are used, but the reality is that time and cost are almost as close as manual work. In this study, RAUT (River Information Auto Upload Tool), a tool that can solve these problems, was developed. First, the RAUT tool attempted to automate the complicated steps of manually inputting CAD survey data and simulating the input data of the HEC-RAS one-dimensional model used in establishing the basic river plan in practice. Second, it is possible to directly read CAD survey data, which is river spatial information, and automatically upload it to the river spatial information DB based on the standard data model (ArcRiver), enabling the management of river survey data in the river maintenance plan at the national level. In other words, if RIMGIS uses a tool such as RAUT, it will be able to systematically manage national river survey data such as river section. The developed RAUT reads the river spatial information CAD data of the river maintenance master plan targeting the Jeju-do agar basin, builds it into a mySQL-based spatial DB, and automatically generates topographic data for HEC-RAS one-dimensional simulation from the built DB. A pilot process was implemented.

• Journal of Distribution Science
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• v.10 no.7
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• pp.33-41
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• 2012

The purpose of this study is to analyse the state of the energy industry and to determine the efficiency of its functioning on the basis of energy conservation principle and application of innovative technologies aimed at improving the ecological modernisation of agricultural sectors of Kazakhstan. The research methodology is based on an integrated approach of financial and economic evaluation of the effectiveness of the investment project, based on calculation of elasticity, total costs and profitability, as well as on comparative, graphical and system analysis. The current stage is characterised by widely spread restructuring processes of electric power industry in many countries through introduction of new technical installations of energy facilities and increased government regulation in order to enhance the competitive advantage of electricity market. Electric power industry features a considerable value of creating areas. For example, by providing scientific and technical progress, it crucially affects not only the development but also the territorial organisation of productive forces, first of all the industry. In modern life, more than 90% of electricity and heat is obtained by Kazakhstan's economy by consuming non-renewable energy resources: different types of coal, oil shale, oil, natural gas and peat. Therefore, it is significant to ensure energy security, as the country faces a rapid fall back to mono-gas structure of fuel and energy balance. However, energy resources in Kazakhstan are spread very unevenly. Its main supplies are concentrated in northern and central parts of the republic, and the majority of consumers of electrical power live in the southern and western areas of the country. However, energy plays an important role in the economy of industrial production and to a large extent determines the level of competitive advantage, which is a promising condition for implementation of energy-saving and environmentally friendly technologies. In these circumstances, issues of modernisation and reforms of this sector in Kazakhstan gain more and more importance, which can be seen in the example of economically sustainable solutions of a large local monopoly company, significant savings in capital investment and efficiency of implementation of an investment project. A major disadvantage of development of electricity distribution companies is the prevalence of very high moral and physical amortisation of equipment, reaching almost 70-80%, which significantly increases the operating costs. For example, while an investment of 12 billion tenge was planned in 2009 in this branch, in 2012 it is planned to invest more than 17 billion. Obviously, despite the absolute increase, the rate of investment is still quite low, as the total demand in this area is at least more than 250 billion tenge. In addition, industrial infrastructure, including the objects of Kazakhstan electric power industry, have a tangible adverse impact on the environment. Thus, since there is a large number of various power projects that are sources of electromagnetic radiation, the environment is deteriorated. Hence, there is a need to optimise the efficiency of the organisation and management of production activities of energy companies, to create and implement new technologies, to ensure safe production and provide solutions to various environmental aspects. These are key strategic factors to ensure success of the modern energy sector of Kazakhstan. The contribution of authors in developing the scope of this subject is explained by the fact that there was not enough research in the energy sector, especially in the view of ecological modernisation. This work differs from similar works in Kazakhstan in the way that the proposed method of investment project calculation takes into account the time factor, which compares the current and future value of profit from the implementation of innovative equipment that helps to bring it to actual practise. The feasibility of writing this article lies in the need of forming a public policy in the industrial sector, including optimising the structure of energy disbursing rate, which complies with the terms of future modernised development of the domestic energy sector.

• Korean Journal of Plant Resources
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• v.34 no.4
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• pp.311-338
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• 2021

This study was investigated to find out the distribution of vascular flora and remarkable plants and its factors and management plan in the forest genetic resource reserve of Mt. Munsu, located in the DMZ and DMZ border area in Gimpo, Gyeonggi-do province. The survey was carried out 17 times from April 2019 to October 2020. First of all, in the forest genetic resource reserve of the Mt. Munsu, a total of 444 taxa in 95 families, 276 genera, 395 species, 13 subspecies, 33 varieties and 3 forms. This result was found to be about 9.09% of the total 4,881 taxa of vascular plants in Korea. In addition, endemic plants were classified as 6 taxa. Floristic special and rare plants were identified as 39 taxa and 3 taxa, respectively. Lastly, the invasive alien plants that appeared in Mt. Munsu of the forest genetic resource reserve were observed in 58 taxa. Moreover, the naturalization rate was 13.1% and the urbanization index was calculated to be 18.0%. As a result of comparing the vascular flora at the forest genetic resource reserve on Mt. Munsu identified in this study with previous studies, it was found the number of taxa was decreased compared to the previous studies, despite the fact that the recent survey section was wider and more varies routes were investigated. In particular, it was confirmed that the number of rare and endemic plants decreased significantly, and the number of invasive plants greatly spread to forest roads and hiking trails. Therefore, it is considered that the forest rest year system should be introduced for the conservation and management of native plants in the forest genetic resource reserve.

• Journal of Korea Water Resources Association
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• v.56 no.11
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• pp.751-764
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• 2023

Gangwon State is centered on the Taebaek Mountains with very different climate characteristics depending on the region, and localized heavy rainfall is a frequent occurrence. Heavy rain disasters have a short duration and high spatial and temporal variability, causing many casualties and property damage. In the last 10 years (2012~2021), the number of heavy rain disasters in Gangwon State was 28, with an average cost of 45.6 billion won. To reduce heavy rain disasters, it is necessary to establish a disaster management plan at the local level. In particular, the current criteria for heavy rain warnings are uniform and do not consider local characteristics. Therefore, this study aims to propose a heavy rainfall warning criteria that considers the threshold rainfall for the advisory areas located in Gangwon State. As a result of analyzing the representative value of threshold rainfall by advisory area, the Mean value was similar to the criteria for issuing a heavy rain warning, and it was selected as the criteria for a heavy rain warning in this study. The rainfall events of Typhoon Mitag in 2019, Typhoons Maysak and Haishen in 2020, and Typhoon Khanun in 2023 were applied as rainfall events to review the criteria for heavy rainfall warnings, as a result of Hit Rate accuracy verification, this study reflects the actual warning well with 72% in Gangneung Plain and 98% in Wonju. The criteria for heavy rain warnings in this study are the same as the crisis warning stages (Attention, Caution, Alert, and Danger), which are considered to be possible for preemptive rain disaster response. The results of this study are expected to complement the uniform decision-making system for responding to heavy rain disasters in the future and can be used as a basis for heavy rain warnings that consider disaster risk by region.