• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.156-156
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• 2022

Explicitly spatially distributed and reliable data on industrial water demand is very much important for both policy makers and researchers in order to carry a region-specific analysis of water resources management. However, such type of data remains scarce particularly in underdeveloped and developing countries. Current research is limited in using different spatially available socio-economic, climate data and geographical data from different sources in accordance to predict industrial water demand at finer resolution. This study proposes a random forest regression (RFR) model to predict the industrial water demand at 0.50× 0.50 spatial resolution by combining various features extracted from multiple data sources. The dataset used here include National Polar-orbiting Partnership (NPP)/Visible Infrared Imaging Radiometer Suite (VIIRS) night-time light (NTL), Global Power Plant database, AQUASTAT country-wise industrial water use data, Elevation data, Gross Domestic Product (GDP), Road density, Crop land, Population, Precipitation, Temperature, and Aridity. Compared with traditional regression algorithms, RF shows the advantages of high prediction accuracy, not requiring assumptions of a prior probability distribution, and the capacity to analyses variable importance. The final RF model was fitted using the parameter settings of ntree = 300 and mtry = 2. As a result, determinate coefficients value of 0.547 is achieved. The variable importance of the independent variables e.g. night light data, elevation data, GDP and population data used in the training purpose of RF model plays the major role in predicting the industrial water demand.

• Journal of Korean Society of Environmental Engineers
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• v.33 no.11
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• pp.827-833
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• 2011

In this study, fecal nonpoint pollutant sources tracking were conducted on Ansan stream. Multiple Antibiotic Resistance Analysis (MARA) method used in this study is based on the premise that fecal bacteria derived from intestine of human or animal has each different resistance for antibiotics. First of all, a database for known sources should be established to use the method and then, an unknown sample was applied on the database to find unknown sources by statistical analysis. The Ansan stream was considered with divided condition into three parts: upper (livestock farming area), mid (old section of the city), and downstream (new section of the city) to search an environmental influence of the stream basin. As results of the statistical analysis, it could be estimated that the upper stream area was influenced by animals due to the nature of influence for the livestock farms located in this area because livestock were classified as percentages of 45.8% in 3-way method divided into livestock, pet and human. In case of midstream and downstream, the human influence was remarkable as percentage of 60% and 80%, respectively. From these results, it could be judged that the MARA method is useful in source tracking the non-point pollutant sources because the MARA results correspond to which predictable non-point pollutant sources by a field study. Also, it is expected that a more effective source tracking will be possible as establishing database of each area.

• Korean Journal of Optics and Photonics
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• v.25 no.1
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• pp.1-7
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• 2014

Multiple scattering effects in cloud are important error sources of the Mie scattering Lidar inversion method, which should be measured to correct the Lidar equation in single wavelength Mie Lidar. We have calculated the multiple scattering effects in liquid water clouds by using a Monte Carlo method, and we have applied these multiple scattering effects in measuring water cloud effective size and LWC (Liquid Water Content). When cloud effective size is less than $2.5{\mu}m$, we can easily extract cloud effective size and LWC by using two wavelength Lidar such as extinction coefficients measured at 355nm and 1064nm. For a larger size cloud, we can find that saturated degree of linear polarization is strongly correlated with cloud effective size, LWC, and extinction coefficients. From these correlations we know that we can measure LWC and cloud effective size if we use single wavelength Rotational Raman Lidar and Mie scattering polarization Lidar.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.500-504
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• 2008

The objective of this paper is to evaluate the feasibility of using an optimization model as a effective way to search conjunctive operation scheme to meet two conditions; one is to minimize the electric cost for pumping and another is to meet the water demand for satisfying customers. The feasibility is confirmed as comparing the best combinations of pumps between multi-regional water supply networks from multiple sources which are obtained through an optimization modeling and EPAnet modeling. KModsim model, a network optimization model, was used to determine conjunctive operation scheme in the pipe system. KModsim, based on Lagrangian Relaxation algorithm, is useful for modeling network system and obtaining simultaneously pump combination and water allocation with given input option such as energy unit cost supplying from a source into a consumer, operating pumping combination. This study develops the procedure of determining optimal conjunctive operation scheme with using KModsim model. As a study region, the water supplying systems of the Geojae-city in the Geongsang Namdo Province was selected and investigated. The EPAnet hydraulic simulation result(Ryu et al, 2007, KSWW) gave input data for optimization model; energy unit price(won/$m^3$), water service available area etc.. It was assured that the combination of pump operation through optimum conjunctive operation is to be optimum scheme to obtain the best economic water allocation with comparison to the hydraulic simulation result such as electric cost and pump combination cases. The results obtained through the study are as follows. First, It was found that a well-allocated water supply scheme, the best combination of pump operation through optimum joint operation, promises to save the electric cost and satisfy all operational goals such as stability and revenues during the period. Second, an application of KModSim, a network model, gave the amount of water allocation from each source to a consumer with consideration of economic supply. Finally, in a service area available to supply through conjunctive operation of existing inter-regional water supply networks within short distance, a conjunctive operation is useful for determining each transmission pipeline's service area and maximizing the effectiveness of optimizations in pumping operation time.

• Journal of the korean society of oceanography
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• v.37 no.3
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• pp.187-195
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• 2002

The characteristics of surface circulation in the Yellow Sea and the East China Sea are discussed by analyzing a great deal of current data observed by 142 sets of mooring buoy and 58 sets of drifters trajectories collected in the Yellow Sea and the East China Sea through domestic and abroad measurements. Some major features are demonstrated as bellow: 1) Tsushima Warm Current flows away from the Kuroshio and has multiple sources in warm half year and comes only from Kuroshio surface water in cold half year. 2) Taiwan Warm Current comes mainly from the Taiwan Strait Water in warm half year and comes from the intruded Kuroshio surface water and branches near 27N in cold half year. 3) The Changjiang Diluted Water turns towards Cheju Island in summer and flows southward along the coastal line in winter. 4) The study sea area is an eddy developing area, especially in the southern area of Cheju Island and northern area of Taiwan.

• Journal of Environmental Health Sciences
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• v.42 no.4
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• pp.280-292
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• 2016

Objectives: The objective of this study was to build COD regression models for the Han River and evaluate water quality. Methods: Water quality data sets for the dry season (as of January) during a four-year period (2012-2015) were collected from the database of the Han River automatic water quality monitoring stations. Statistical techniques, including combined genetic algorithm-multiple linear regression (GA-MLR) were used to build five-descriptor COD models. Multivariate statistical techniques such as principal component analysis (PCA) and cluster analysis (CA) are useful tools for extracting meaningful information. Results: The $r^2$ of the best COD models provided significant high values (> 0.8) between 2012 and 2015. Total organic carbon (TOC) was a surrogate indicator for COD (as COD/TOC) with high reliability ($r^2=0.63$ in 2012, $r^2=0.75$ for 2013, $r^2=0.79$ for 2014 and $r^2=0.85$ for 2015). The ratios of COD/TOC were calculated as 2.08 in 2012, 1.79 in 2013, 1.52 and 1.45 in 2015, indicating that biodegradability in the water body of the Han River was being sustained, thereby further improving water quality. The BOD/COD ratio supported these findings. The cluster analysis revealed higher annual levels of microorganisms and phosphorous at stations along the Hangang-Seoul and Hantangang areas. Nevertheless, the overall water quality over the last four years showed an observable trend toward continuous improvement. These findings also suggest that non-point pollution control strategies should consider the influence of upstreams and downstreams to protect water quality in the Han River. Conclusion: This data analysis procedure provided an efficient and comprehensive tool to interpret complex water quality data matrices. Results from a trend analysis provided much important information about sources and parameters for Han River water quality management.

• Journal of Preventive Medicine and Public Health
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• v.22 no.4 s.28
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• pp.454-465
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• 1989

In a small island community with a population of less than 100 residents, nine persons died and five experienced severe illnesses during the period from November 1986 to May 1988. Their initial symptoms were sore throat and fever. Renal failure and hepatitis developed within one week after the onset. Oral mucosal ulcer developed in some cases. After one week, progressive respiratory failure and dyspnea developed evidently and severe respiratory distress and hypoxia preceded those fatal cases. Chest X-ray findings revealed bilateral diffuse multiple cystic lesion with occasional multiple large emphysematous bullae. Based on these features paraquat poisoning was diagnosed and route of poisoning was investigated. In three sources of drinking water, trace amount of paraquat was detected in November 1988, six months after the incidence of recent fatal case. In November 1988, soybean sauces and soybean pastes from 12 households were found contaminated with high concentration of paraquat, the cause could not be identified. The possibility of the contamination of drinking water as the cause of this mass poisoning has been suggested.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.143-143
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• 2022

Precipitation plays an essential role in water resources management and disaster prevention. Therefore, the understanding related to spatiotemporal characteristics of rainfall is necessary. Nowadays, highly accurate precipitation is mainly obtained from gauge observation systems. However, the density of gauge stations is a sparse and uneven distribution in mountainous areas. With the proliferation of technology, satellite-based precipitation sources are becoming increasingly common and can provide rainfall information in regions with complex topography. Nevertheless, satellite-based data is that it still remains uncertain. To overcome the above limitation, this study aims to take the strengthens of machine learning to generate a new reanalysis of precipitation data by fusion of multiple satellite precipitation products (SPPs) with gauge observation data. Several machine learning algorithms (i.e., Random Forest, Support Vector Regression, and Artificial Neural Network) have been adopted. To investigate the robustness of the new reanalysis product, observed data were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the machine learning model showed higher accuracy than original satellite rainfall products, and its spatiotemporal variability was better reflected than others. Thus, reanalysis of satellite precipitation product based on machine learning can be useful source input data for hydrological simulations in ungauged river basins.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.2
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• pp.42.2-43
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• 2015

Massive stars play a major role in the interstellar energy budget and the shaping of the galactic environment. The water molecule is thought to be a sensitive tracer of physical conditions and dynamics in star-forming regions because of its large abundance variations between hot and cold regions. Herschel/HIFI allows us to observe the multiple rotational transitions of H2O including the ground-state levels, and its isotopologues toward high-mass star-forming regions in different evolutionary stages. Photodissociation regions (PDRs) are also targeted to investigate the distribution of water and its chemistry. We present line profiles and maps of H2O using data from two guaranteed-time key programs "Water In Star-forming regions with Herschel" and "Herschel observations of EXtra-Ordinary Sources". We analyze the temperature and density structures using LTE and non-LTE methods. We also estimate turbulent and expansion velocities, and abundance of water in the inner and outer envelopes using the 1D radiative transfer code. Around high-mass protostars we find H2O abundances of ~10-8-10-9 for the outer envelope and ~10-4-10-5 for the inner envelope, and expansion and turbulent velocities range from 1.0 km s-1 to 2.0 km s-1. The abundances and kinematic parameters of the sources do not show clear trends with evolutionary indicators. The Herschel/HIFI mapping observations of H2O toward the Orion Bar PDR show that H2O emission peaks between the shielded dense gas and the radicals position, in agreement with the theoretical and the observational PDR structure. The derived H2O abundance is ~10-7 and peaks at the depth of AV ~8 mag from the ionization front. Together with the low ortho-to-para ratio of H2O (~1) presented by Choi et al. (2014), our results show that the chemistry of water in the Orion Bar is dominated by photodesorption and photodissociation.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.151-151
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• 2021

The alarming climate change impacts are demanding the use of renewable energy sources like never before. Hydropower is one of the most cost-effective and environmental friendly energy technology recognized in the world. Big hydropower projects come up with the requirements of huge investment costs along with environmental impacts, whereas small hydropower(SHP) are considered a best solution for the economical source of energy. SHP, basically Run-of-River (RoR) type plants can be sustainable renewable energy sources and given the nature of perennial rivers flowing from steep gradient and rugged topography, feasibility of such plants is equally high in Nepal. The objective of this study is to determine the primary potential sites for the development of RoR type SHP sites using Geo-spatial Information System(GSIS). The use of GSIS enables precise survey of large area within a short period of time. This study has focused on the determination of locations by establishing defined criterions and methodologies and hence have located multiple locations rather than selecting one best location. The approach is applicable for the rapid initial screening of potential locations and results can facilitate detail feasibility study for the technical and economic analysis of SHP in the basin.