• Journal of Korea Water Resources Association
• /
• v.41 no.9
• /
• pp.929-941
• /
• 2008

The objectives of this study are to propose a system for combined use of a hydrologic and a hydraulic model for urban flood forecast model and to evaluate the system on the $300km^2$ Jungrang urban watershed area, which is relatively large area as an urban watershed and consequently composed of very complex drainage pipes and streams with different land uses. In this study, SWMM for hydrologic model and HEC-RAS for hydraulic model are used and the study area is divided into 25 subbasins. The SWMM model is used for sewer drainage analysis within each subbasin, while HEC-RAS for unstready flow analysis in the channel streams. Also, this study develops a GUI system composed of mean areal precipitation input component, hydrologic runoff analysis component, stream channel routing component, and graphical representation of model output. The proposed system was calibrated for the model parameters and verified for the model applicability by using the observation data. The correlation coefficients between simulated and observed flows at the 2 important locations were ranged on 0.83-0.98, while the coefficients of model efficiency on 0.60-0.92 for the verification periods. This study also provided the possibilities of manhole overflows and channel bank inundation through the calculated water profile of longitudinal and channel sections, respectively. It can be concluded that the proposed system can be used as a surface runoff and channel routing models for urban flood forecast over the large watershed area.

• Water for future
• /
• v.29 no.4
• /
• pp.209-221
• /
• 1996

It may be difficult to make exact estimates of peak discharge or runoff depth of a flood and to establish the proper measurement for the flood protection since water stages or discharges have been rarely measured at small river basins in Korea. Three small catchments in the Su-Young river basin in Pusan were selected for the study areas. Various runoff parameters for the study areas were determined, and runoff analyses were performed using three different runoff models available in literatures; the storage function method, the discrete, linear, input-output model, and the linear reservoir model. The hydrographs calculated by three different methods showed good agreement with the observed flood hydrographs, indicating that the models selected are all capable of sucessfully modeling the flood events for small watersheds. The storage function method gave the best results in spite of its weakness that it could not be applicable to small floods, while the linear reservoir model was found to provide relatively good results with less parameters. The capabilities of simulating flood hydrographs were also evaluated based on the effective rainfall from the storage function parameters, the $\Phi$-index method, and the constant percentage method. For the On-Cheon stream watershed, the storage function parameters provided better estimates of effective rainfall for regenerating flood hydrographs than any others considered in the study. The $\Phi$-index method, however, resulted in better estimates of effective rainfall for the other two study areas.

• Korean Journal of Soil Science and Fertilizer
• /
• v.38 no.3
• /
• pp.164-171
• /
• 2005

The aim of this study was to evaluate the load of nutrient from paddy fields. Water management practices that can reduce eutrophication and meet water quality requirements will also be addressed. Continuous monitoring from May to September in 2002 and 2003 was conducted for water quantification and qualification at the intensive paddy fields in Icheon, Gyunggi province of Korea. Water balance and concentration variation of nitrogen and phosphorus in the water were independently compared for water quality assessment at each rice cultivation period. Rice land preparation and transplanting periods usually marked the highest water demand when compared to other periods of cultivation. Overall, a greater net irrigation ratio was observed during the transplanting period in 2002 (92.3%) and 2003 (87.2%). The measured total N loads of precipitation, irrigation, drainage, and percolation during the rice cultivation period were 9.9, 41.6, 22.1, and $5.5kg\;ha^{-1}$ for 2002 and 15.8, 55.4, 17.3, and $7.5kg\;ha^{-1}$ for 2003, respectively. The measured total P loads of precipitation, irrigation, drainage, and percolation during the rice cultivation period were 2.1, 13.0, 3.6, and $1.8kg\;ha^{-1}$ for 2002 and 1.6, 15.0, 5.0, and $1.2kg\;ha^{-1}$ for 2003, respectively. Daily nutrient load followed the pattern of surface drainage water, but this pattern was changed by rainfall events. The nutrient load in drainage water depends on rainfall and surface drainage water amount from the paddy fields. Interestingly, the load of total N and total P output was smaller than the input load due to the natural infiltration that Occurred during the rice cultivation period. It is concluded that the paddy fields have a beneficial effect on the ecosystem and can reduce eutrophication in the water.

• Membrane Journal
• /
• v.33 no.4
• /
• pp.181-190
• /
• 2023

Wastewater purification is one of the most important techniques for controlling environmental pollution and fulfilling the demand for freshwater supply. Various technologies, such as different types of distillations and reverse osmosis processes, need higher energy input. Capacitive deionization (CDI) is an alternative method in which power consumption is deficient and works on the supercapacitor principle. Research is going on to improve the electrode materials to improve the efficiency of the process. A reverse electrodialysis (RED) is the most commonly used desalination technology and osmotic power generator. Among many studies conducted to enhance the efficiency of RED, MXene, as an ion exchange membrane (IEM) and 2D nanofluidic channels in IEM, is rising as a promising way to improve the physical and electrochemical properties of RED. It is used alone and other polymeric materials are mixed with MXene to enhance the performance of the membrane further. The maximum desalination performances of MXene with preconditioning, Ti₃C₂T_x, Nafion, and hetero-structures were respectively measured, proving the potential of MXene for a promising material in the desalination industry. In terms of osmotic power generating via RED, adopting MXene as asymmetric nanofluidic ion channels in IEM significantly improved the maximum osmotic output power density, most of them surpassing the commercialization benchmark, 5 Wm^-2. By connecting the number of unit cells, the output voltage reaches the point where it can directly power the electronic devices without any intermediate aid. The studies around MXene have significantly increased in recent years, yet there is more to be revealed about the application of MXene in the membrane and osmotic power-generating industry. This review discusses the electrodialysis process based on MXene composite membrane.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.33 no.4
• /
• pp.1413-1424
• /
• 2013

Recently, the frequency of severe storms increases in Korea. Severe storms occurring in a short time cause huge losses of both life and property. A considerable research has been performed for the flood control system development based on an accurate stream discharge prediction. A physical model is mainly used for flood forecasting and warning. Physical rainfall-runoff models used for the conventional flood forecasting process require extensive information and data, and include uncertainties which can possibly accumulate errors during modelling processes. ANFIS, a data driven model combining neural network and fuzzy technique, can decrease the amount of physical data required for the construction of a conventional physical models and easily construct and evaluate a flood forecasting model by utilizing only rainfall and water level data. A data driven model, however, has a disadvantage that it does not provide the mathematical and physical correlations between input and output data of the model. The characteristics of a data driven model according to functional options and input data such as the change of clustering radius and training data length used in the ANFIS model were analyzed in this study. In addition, the applicability of ANFIS was evaluated through comparison with the results of HEC-HMS which is widely used for rainfall-runoff model in Korea. The neuro-fuzzy technique was applied to a Cheongmicheon Basin in the South Han River using the observed precipitation and stream level data from 2007 to 2011.

• Progress in Medical Physics
• /
• v.15 no.4
• /
• pp.186-191
• /
• 2004

The periodic Quality Assurance (QA) of each radiation treatment related equipments is important one, but quality assurance of the radiation treatment planning system (RTPS) is still not sufficient rather than other related equipments in clinics. Therefore, this study will present and test the periodic QA program to compare, evaluation the efficiency of the treatment planning systems. This QA program is divided to terms for the input, output devices and dosimetric data and categorized to the weekly, monthly, yearly and non-periodically with respect to the job time, frequency of error, priority of importance. CT images of the water equivalent solid phantom with a heterogeneity condition are input into the RTPS to proceed the test. The actual measurement data are obtained by using the ion chamber for the 6 MV, 10 MV photon beam, then compared a calculation data with a measurement data to evaluate the accuracy of the RTPS. Most of results for the accuracy of geometry and beam data are agreed within the error criteria which is recommended from the various advanced country and related societies. This result can be applied to the periodic QA program to improve the treatment outcome as a proper model in Korea and used to evaluate the accuracy of the RTPS.

• Journal of the Korean Institute of Gas
• /
• v.22 no.6
• /
• pp.90-103
• /
• 2018

This paper presents the development of two ANN models which can predict an optimum production rate by controlling choke size in oil well, and gas injection rate in gas-lift well. The input data was solution gas-oil ratio, water cut, reservoir pressure, and choke size or gas injection rate. The output data was wellhead pressure and production rate. Firstly, a range of each parameters was decided by conducting sensitive analysis of input data for onshore oil well. In addition, 1,715 sets training data for choke size decision model and 1,225 sets for gas injection rate decision model were generated by nodal analysis. From the results of comparing between the nodal analysis and the ANN on the same reservoir system showed that the correlation factors were very high(>0.99). Mean absolute error of wellhead pressure and oil production rate was 0.55%, 1.05% with the choke size model, respectively. And the gas injection rate model showed the errors of 1.23%, 2.67%. It was found that the developed models had been highly accurate.

• Korean Journal of Soil Science and Fertilizer
• /
• v.42 no.6
• /
• pp.439-446
• /
• 2009

Nitrogen balance in the regional scale which was calculated the difference between nitrogen input and output was estimated to assess the impact of rice cultivation on water environment. Nitrogen balances in Gyeonggi province, where nitrogen concentration in irrigation water was high and in Chungnam province, where nitrogen absorbtion by rice was high, were -5.4 and -8.3 kg $-8.3kg\;ha^{-1}\;yr^{-1}$, respectively. Nitrogen balances of paddy field in Gangwon province, where nitrogen output was small and irrigation water was clean, and in Gyeongnam province, where organic matter content of soil was high and rice yield was low, were 4.9 and $14.0kg\;ha^{-1}\;yr^{-1}$, respectively. Average nitrogen balance and total nitrogen absorption of paddy field in Korea were estimated to $-0.3kg\;ha^{-1}\;yr^{-1}$ and $-3,315Mg\;yr^{-1}$, respectively. When the nitrogen concentration in irrigation water was increased by $1mg \;L^{-1}$, nitrogen balance of rice paddy changed by $-2.91kg\;ha^{-1}\;yr^{-1}$. Also, when nitrogen fertilizer applied was decreased from 110 to $90kg\;ha^{-1}$ and the same harvest was maintained, the nitrogen absorption by rice paddy from irrigation water was estimated to increase by 10,600 Mg per year in Korea. However, in cases, the harvest was reduced to either 90% or 85%, nitrogen balances were changed from -11.7 to -2.3 and $2.4kg\;ha^{-1}$, respectively. These results suggest that the reduction of nitrogen fertilizer use may not always lead to a negative nitrogen balance and sustainable agriculture can achieve by not cutting down the use of fertilizer only but by reduction of fertilizer application concurrently by maintenance of harvest and by utilization of environmental characteristics such as nutrient contents in irrigation water and soils.

• Economic and Environmental Geology
• /
• v.48 no.6
• /
• pp.509-523
• /
• 2015

This study introduces newly implemented geological well logs database for Jeju public water wells, built for a research project focusing on integrated hydrogeology database of Jeju Island. A detailed analysis of the existing 1,200 Jeju Island geological logs for the public wells developed since 1970 revealed six major indications to be improved for their use in Jeju geological logs DB construction: (1) lack of uniformity in rock name classification, (2) poor definitions of pyroclastic deposits and sand and gravel layers, (3) lack of well borehole aquifer information, (4) lack of information on well screen installation in many water wells, (5) differences by person in geological logging descriptions. A new Jeju geological logs DB enabling standardized input and output formats has been implemented to overcome the above indications by reestablishing the names of Jeju volcanic and sedimentary rocks and utilizing a commercial, database-based input structured, geological log program. The newly designed database structure in geological log program enables users to store a large number of geology, well drilling, and test data at the standardized DB input structure. Also, well borehole groundwater and aquifer test data can be easily added without modifying the existing database structure. Thus, the newly implemented geological logs DB could be a standardized DB for a large number of Jeju existing public wells and new wells to be developed in the future at Jeju Island. Also, the new geological logs DB will be a basis for ongoing project 'Developing GIS-based integrated interpretation system for Jeju Island hydrogeology'.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2002.05a
• /
• pp.43-50
• /
• 2002

Accurate quantitative forecasting of rainfall for basins with a short response time is essential to predict streamflow and flash floods. Previously, neural networks were used to develop a Quantitative Precipitation Forecasting (QPF) model that highly improved forecasting skill at specific locations in Pennsylvania, using both Numerical Weather Prediction (NWP) output and rainfall and radiosonde data. The objective of this study was to improve an existing artificial neural network model and incorporate the evolving structure and frequency of intense weather systems in the mid-Atlantic region of the United States for improved flood forecasting. Besides using radiosonde and rainfall data, the model also used the satellite-derived characteristics of storm systems such as tropical cyclones, mesoscale convective complex systems and convective cloud clusters as input. The convective classification and tracking system (CCATS) was used to identify and quantify storm properties such as life time, area, eccentricity, and track. As in standard expert prediction systems, the fundamental structure of the neural network model was learned from the hydroclimatology of the relationships between weather system, rainfall production and streamflow response in the study area. The new Quantitative Flood Forecasting (QFF) model was applied to predict streamflow peaks with lead-times of 18 and 24 hours over a five year period in 4 watersheds on the leeward side of the Appalachian mountains in the mid-Atlantic region. Threat scores consistently above .6 and close to 0.8 ∼ 0.9 were obtained fur 18 hour lead-time forecasts, and skill scores of at least 4％ and up to 6％ were attained for the 24 hour lead-time forecasts. This work demonstrates that multisensor data cast into an expert information system such as neural networks, if built upon scientific understanding of regional hydrometeorology, can lead to significant gains in the forecast skill of extreme rainfall and associated floods. In particular, this study validates our hypothesis that accurate and extended flood forecast lead-times can be attained by taking into consideration the synoptic evolution of atmospheric conditions extracted from the analysis of large-area remotely sensed imagery While physically-based numerical weather prediction and river routing models cannot accurately depict complex natural non-linear processes, and thus have difficulty in simulating extreme events such as heavy rainfall and floods, data-driven approaches should be viewed as a strong alternative in operational hydrology. This is especially more pertinent at a time when the diversity of sensors in satellites and ground-based operational weather monitoring systems provide large volumes of data on a real-time basis.