• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.1
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• pp.29-41
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• 2017

Design rainfalls are one of the most important hydrologic data for river management, hydraulic structure design and risk analysis. The design rainfalls are first estimated by a point frequency analysis and the IDF (intensity-duration-frequency) curve is then constructed by a nonlinear regression to either interpolate or extrapolate the design rainfalls for other durations which are not used in the frequency analysis. It has been widely recognised that the more reliable approaches are required to better account for uncertainties associated with the model parameters under circumstances where limited hydrologic data are available for the watershed of interest. For these reasons, this study developed a hierarchical Bayesian based GLM (generalized linear model) for a regional frequency analysis in conjunction with a scaling function of the parameters in probability distribution. The proposed model provided a reliable estimation of a set of parameters for each individual station, as well as offered a regional estimate of the parameters, which allow us to have a regional IDF curve. Overall, we expected the proposed model can be used for different aspects of water resources planning at various stages and in addition for the ungaged basin.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.6
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• pp.295-306
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• 2016

The purpose of this paper is both to analyze research trends and to predict industrial flows using the meta-data from the previous studies on data quality. There have been many attempts to analyze the research trends in various fields till lately. However, analysis of previous studies on data quality has produced poor results because of its vast scope and data. Therefore, in this paper, we used a text mining, social network analysis for time series network analysis to analyze the vast scope and data of data quality collected from a Web of Science index database of papers published in the international data quality-field journals for 10 years. The analysis results are as follows: Decreases in Mathematical & Computational Biology, Chemistry, Health Care Sciences & Services, Biochemistry & Molecular Biology, Biochemistry & Molecular Biology, and Medical Information Science. Increases, on the contrary, in Environmental Sciences, Water Resources, Geology, and Instruments & Instrumentation. In addition, the social network analysis results show that the subjects which have the high centrality are analysis, algorithm, and network, and also, image, model, sensor, and optimization are increasing subjects in the data quality field. Furthermore, the industrial connection analysis result on data quality shows that there is high correlation between technique, industry, health, infrastructure, and customer service. And it predicted that the Environmental Sciences, Biotechnology, and Health Industry will be continuously developed. This paper will be useful for people, not only who are in the data quality industry field, but also the researchers who analyze research patterns and find out the industry connection on data quality.

• Journal of the Korean Institute of Gas
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• v.19 no.2
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• pp.54-65
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• 2015

China holding the world largest shale resources, has been trying to develop their domestic shale gas fields mainly with its NOCs. Chinese shale industry looks likely to have high potential to grow in the future, considering the eager support of Chinese government and the rapid development of relevant technologies by NOCs. However, there are opposite opinions as well that Chinese shale gas could not play a positive short-term results because of the complexity of structural geology, inadequacy of water resources and related infrastructure. Recently, Korean companies began to be interseted in Chinese shale gas industry, because of the special relationships with Korean industries in terms of geographic proximity and better opportunities due to the early phase of shale gas business in China. In this study, it was tried to help those companies looking out of future Chinese shale gas industry that surveying current status and problems of Chinese shale gas industry and relevant industries and investigating some trials and policies driven by China government. As a result, the various and long-term problems in Chinese shale development were reviewed and the active supports and polices of Chinese government, NOC's trials for establishments of their independent technologies and the cooperation with foreign companies or M&As were also investigated.

• Journal of Climate Change Research
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• v.4 no.1
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• pp.11-26
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• 2013

This study examined the applicability of robust decision making (RDM) over standard decision making (SDM) by comparing each result of water supply planning under climate change uncertainties for a Korean dam case. RDM determines the rank of alternatives using the regret criterion which derives less fluctuating alternatives under the risk level regardless of scenarios. RDM and SDM methods were applied to assess hypothetic scenarios of water supply planning for the Andong dam and Imha dam basins. After generating various climate change scenarios and six assumed alternatives, the rank of alternatives was estimated by RDM and SDM respectively. As a result, the average difference in the rank of alternatives between RDM and SDM methods is 0.33~1.33 even though the same scenarios and alternatives were used to be ranked by both of RDM and SDM. This study has significance in terms of an attempt to assess a new approach to decision making for responding to climate change uncertainties in Korea. The effectiveness of RDM under more various conditions should be verified in the future.

• Journal of Climate Change Research
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• v.3 no.4
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• pp.281-291
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• 2012

Forests act as carbon sinks and also improve water resources and biodiversity to climate change. Secure funding, administrative support, and sustainable management systems are essential to conserve forests and to implement international forestry related projects to climate change. Public private partnership (PPP) could be an effective way for forestry sector in developing countries. Awareness analysis should be preceded in order to encourage participation of enterprises for the diversification of funding and the enhancing quality of projects. We conducted a survey targeting more than 129 private enterprises for awareness analysis. As a result, lack of information, complexity of processes and low profit resulted in low interest on forest projects from private enterprises. Improving awareness of recipient countries on forest resources, financial and institutional supports from the public sector, information sharing, performance management and equal partnership between sectors were suggested to encourage PPP in international forestry related projects to climate change.

• International Area Studies Review
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• v.22 no.2
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• pp.189-209
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• 2018

The purpose of this study is to identify international research trends of SDGs by analyzing the networks among the 17 goals of the SDGs. The research scope covers the World Development and the Journal of Development Studies which are the top impact journals in the field of international development. The interconnected 17 SDGs are divided into five categories of people, planet, partnership, peace and prosperity. In this study, we analyzed the abstracts of the papers of the above two journals using Atlas.ti, a qualitative analysis software, in order to identify the connections between 17 goals. The findings from the analysis of 730 abstracts published in two journals since 2015 are summarized as follows. First, issues related to gender have featured prominently in both journals. Second, China and India have been the most popular case countries in both journals. In particular south-south cooperation led by China and India has been dealt with by the World Development. Thirdly, both journals have their own biases towards to certain SDGs. For instance, the World Development have not had many articles on SDG 11, 12, 13, 14, 15, 16 and 17. The SDGs closely associated with the environment and climate change such as 6, 12, 13, 14, and 15 have also been sidelined by the Journal of Development Studies. More balanced research paying attention to all the SDGs in an integrated and balanced manner is required to provide evidence and knowledge conducive to realizing the transformative vision of the 2030 Agenda for Sustainable Development.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.1
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• pp.1-11
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• 2021

Detection of surface water features including river, wetland, reservoir from the satellite imagery can be utilized for sustainable management and survey of water resources. This research compared the water indices derived from the multispectral bands and the machine learning technique for detecting the surface water features from he Landsat-8 satellite image acquired in Daegu through the following steps. First, the NDWI(Normalized Difference Water Index) image and the MNDWI(Modified Normalized Difference Water Index) image were separately generated using the multispectral bands of the given Landsat-8 satellite image, and the two binary images were generated from these NDWI and MNDWI images, respectively. Then SVM(Support Vector Machine), the widely used machine learning techniques, were employed to generate the land cover image and the binary image was also generated from the generated land cover image. Finally the error matrices were used for measuring the accuracy of the three binary images for detecting the surface water features. The statistical results showed that the binary image generated from the MNDWI image(84%) had the relatively low accuracy than the binary image generated from the NDWI image(94%) and generated by SVM(96%). And some misclassification errors occurred in all three binary images where the land features were misclassified as the surface water features because of the shadow effects.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1277-1290
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• 2020

Water resources which is formed of surface and groundwater, are considered as one of the pivotal natural resources worldwide. Since last century, the rapid population growth as well as accelerated industrialization and explosive urbanization lead to boost demand for groundwater for domestic, industrial and agricultural use. In fact, better management of groundwater can play crucial role in sustainable development; therefore, determining accurate location of groundwater based groundwater potential mapping is indispensable. In recent years, integration of machine learning techniques, Geographical Information System (GIS) and Remote Sensing (RS) are popular and effective methods employed for groundwater potential mapping. For determining the status of the integrated approach, a systematic review of 94 directly relevant papers were carried out over the six previous years (2015-2020). According to the literature review, the number of studies published annually increased rapidly over time. The total study area spanned 15 countries, and 85.1% of studies focused on Iran, India, China, South Korea, and Iraq. 20 variables were found to be frequently involved in groundwater potential investigations, of which 9 factors are almost always present namely slope, lithology (geology), land use/land cover (LU/LC), drainage/river density, altitude (elevation), topographic wetness index (TWI), distance from river, rainfall, and aspect. The data integration was carried random forest, support vector machine and boost regression tree among the machine learning techniques. Our study shows that for optimal results, groundwater mapping must be used as a tool to complement field work, rather than a low-cost substitute. Consequently, more study should be conducted to enhance the generalization and precision of groundwater potential map.

• Journal of Wetlands Research
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• v.24 no.3
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• pp.155-160
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• 2022

The debate of South-North transboundary rivers must be expanded from the existing cooperation in water resources towards cooperation within ecosystem conservation. Regarding the Han and Imjin rivers confluence water system, the nature of the estuarine ecosystem must be conserved considering the aspect of climate change. Furthermore, the agenda of maintaining continuous inter-Korean communication and cooperation should focus on ecosystem conservation, including conserving migratory species that inhabit both Koreas. Notably, within the Han and Imjin rivers confluence, transboundary rivers are abundant legally protected species such as Grus vipio, Anser fabalis, Anser cygnoides, Platalea minor, Lutra lutra, Prionailurus bengalensis which suggests a strong need for a debate regarding habitat conservation. This study analyzed the ecosystem conditions and environmental aspects within the confluence of Han and Imjin rivers. In addition, this study provided step wise approach of ecosystem conservation that consider conditions for potential direct inter-Korean cooperation. The inter-Korean cooperation mentioned in this study will be developed into legitimate cooperation once the results from monitoring the ecosystem of transboundary rivers, awareness raising are exchanged.

• Journal of the Korea Society of Computer and Information
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• v.29 no.3
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• pp.67-74
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• 2024

In this paper, we present a study aimed at analyzing how different rainfall measurement methods affect the performance of reservoir water level predictions. This work is particularly timely given the increasing emphasis on climate change and the sustainable management of water resources. To this end, we have employed rainfall data from ASOS, AWS, and Thiessen Network-based measures provided by the KMA Weather Data Service to train our neural network models for reservoir yield predictions. Our analysis, which encompasses 34 reservoirs in Jeollabuk-do Province, examines how each method contributes to enhancing prediction accuracy. The results reveal that models using rainfall data based on the Thiessen Network's area rainfall ratio yield the highest accuracy. This can be attributed to the method's accounting for precise distances between observation stations, offering a more accurate reflection of the actual rainfall across different regions. These findings underscore the importance of precise regional rainfall data in predicting reservoir yields. Additionally, the paper underscores the significance of meticulous rainfall measurement and data analysis, and discusses the prediction model's potential applications in agriculture, urban planning, and flood management.