• Journal of Korea Water Resources Association
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• v.43 no.8
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• pp.733-745
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• 2010

Seasonality of hydrologic extreme variable is a significant element from a water resources managemental point of view. It is closely related with various fields such as dam operation, flood control, irrigation water management, and so on. Hydrological frequency analysis conjunction with partial duration series rather than block maxima, offers benefits that include data expansion, analysis of seasonality and occurrence. In this study, nonstationary frequency analysis based on the Bayesian model has been suggested which effectively linked with advantage of POT (peaks over threshold) analysis that contains seasonality information. A selected threshold that the value of upper 98% among the 24 hours duration rainfall was applied to extract POT series at Seoul station, and goodness-fit-test of selected GEV distribution has been examined through graphical representation. Seasonal variation of location and scale parameter ($\mu$ and $\sigma$) of GEV distribution were represented by Fourier series, and the posterior distributions were estimated by Bayesian Markov Chain Monte Carlo simulation. The design rainfall estimated by GEV quantile function and derived posterior distribution for the Fourier coefficients, were illustrated with a wide range of return periods. The nonstationary frequency analysis considering seasonality can reasonably reproduce underlying extreme distribution and simultaneously provide a full annual cycle of the design rainfall as well.

• Journal of Wetlands Research
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• v.20 no.3
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• pp.210-218
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• 2018

It is very important to analyze water balance in the mountain wetland for the sustainable management of the wetland. In this study, the SWAT model was used to analyze the water balance of Janggun wetland located in Geumjeong mountain of Gyungnam province, Korea. The data such as rainfall and water level measured in Janggun wetland were used for water balance analysis and from the analysis we have known that the rainfall of 10mm within 8 days is required for maintaining an appropriate water level in Janggun wetland. Also, water balance analysis in the wetland for the period of 2009 to 2017 was performed by using hydro-meteorological data obtained from Yangsan weather station which is located around Janggun wetland. From the analysis results, we have known that the amount of rainfall was relatively small in 2010, 2012 and 2015 and water shortage was occurred in the wetland. Especially, water shortage was occurred during the summer that we had intensive rainfall for very short time and faster removal of the runoff from the wetland. Therefore, we may need extend water courses from a wetland watershed to the wetland for preventing land-forming of the wetland and also store water by banking up the wetland for preventing the decrease of water level in the wetland.

• Korean Journal of Remote Sensing
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• v.17 no.1
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• pp.15-31
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• 2001

The relationship between GMS-5 IR1 brightness temperature (CTT:cloud top temperature) and AWS (automatic weather station) rainfall is investigated on a heavy rain event over the mid-western part of Korea for August 5-6, 1998. It is found that a temporal variability of the heavy rain can be described in detail y the time series of rain area and rain rates over the study area that are calculated from AWS accumulated rainfalls for 15 minutes. A time period of 0030-0430 LST 6 August 1998 is chosen in the time series as a heavy rain period which has relatively small rain area (20~25%) and very strong rain rates(6~9 mm/15 min.) with a good time continuity. In the heavy rain period, CTT of a point and AWS 15-minute rainfall beneath that point are compared. From the comparison, AWS rainfalls are shown to be not closely correlated with CTT. In the range of CTT lower than -5$0^{\circ}C$ where most AWS with rain are distributed, the probability of rain is at most about 30%. However, when the satellite images are shifted by 2~3 pixels southward and 3 pixels westward for the geometric correction of images, AWS rainfalls are shown to be statistically correlated with CTT (correlation coefficient:-0.46). Most AWS with rain are distributed in the much lower CTT range(lower than -58$^{\circ}C$), but there is still not much change in the rain probability. Even though a temporal change of CTT is taken into account, the rain probability amount to at most 50~55% in the same range.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.257-266
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• 2021

Urban areas can often suffer flood damage because of the more frequent catastrophic rainfall events from climate change. Flood mitigation measures consist of (1) structural and (2) non-structural measures. In this study, the proposed method focused on operating an urban drainage system among non-structural measures. The combined inland-river operation technique estimates the inflow of pump stations based on the water level obtained from a preselected monitoring point, and the pump station expels the stored rainwater to the riverside based on those estimates. In this study, the proposed method was applied to the Mokgam drainage watershed, where catastrophic rainfall events occurred (i.e., 2010- and 2011-years), and severe flood damage was recorded in Seoul. Using the proposed method, the efficiency of flood reduction from the two rainfall events was reduced by 34.9 % and 54.4 %, respectively, compared to the current operation method. Thus, the proposed method can minimize the flood damage in the Mokgam drainage watershed by reserving the additional storage space of a reservoir. In addition, flooding from catastrophic rainfall can be prevented, and citizens' lives and property in urban areas can be protected.

• Journal of Environmental Science International
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• v.15 no.2
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• pp.141-155
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• 2006

This study is aimed at the development of a runoff forecasting model to solve the uncertainties occurring in the process of rainfall-runoff modeling and improve the modeling accuracy of the stream runoff forecasting, The study area is the downstream of Naeseung-chun. Therefore, time-dependent data was obtained from the Wolpo water level gauging station. 11 and 2 out of total 13 flood events were selected for the training and testing set of model. The model performance was improved as the measuring time interval$(T_m)$ was smaller than the sampling time interval$(T_s)$. The Neuro-Fuzzy(NF) and TANK models can give more accurate runoff forecasts up to 4 hours ahead than the Feed Forward Multilayer Neural Network(FFNN) model in standard above the Determination coefficient$(R^2)$ 0.7.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1998.10a
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• pp.92-98
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• 1998

Among several indices that have been proposed and adopted in different disciplines of sciences, standardized precipitation index, SPI by McKee et al. (1993) was applied to evaluate drought severity for historical rainfall records. Monthly SPI in Seoul station was reviewed in this study, in an effort to characterize the drought intensities during 1994. The SPI drought frequency decreases inversely with monthly time scales of different spans, while the drought duration increases. March, 1994 was found to be the most severe for the three month period, and was recognized as the beginning month of the historical drought spans. Drought intensities became less severe during May and June. SPI becomes greater from July to September particularly in eastern parts of the country.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2002.10a
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• pp.41-44
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• 2002

It is unreasonable to calculate the amount of agricultural water use by applying unit demand method, because it is different from other water use due to the return flow and reuse in the recycle of watershed. Data from irrigation pumping station and reservoir were analysed. Factors for water balance are precipitation, evapotranspiration, percolation, runoff, and management loss, etc. Here in the study, the amount of agricultural water was defined in the way of three different categories. First one is "Gross water" including evapotranspiration, percolation, and management loss. Second one is "Agricultural water" including Gross water and effective rainfall. Third one is "Broad water" which is abstracting the return flow from Agricultural water.

• Magazine of the Korean Society of Agricultural Engineers
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• v.33 no.4
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• pp.61-72
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• 1991

A lumped deterministic model(DAWAST model) was developed to predict the daily streamflow. Since the streamflow is dominantly determined by the soil water storage in the watershed, the model takes the soil water accounting procedures which are based on three linear reservoirs representing the surface, unsaturated, and saturated soil layers. The variation of soil water storage in the unsaturated zone is traced from the soil water balance on a daily basis. DAWAST model consists of 5 parameters for water balance and 3 parameters for routing. A optimization technique of unconstrained nonlinear Simplex method was applied for the determination of the optimal parameters for water balance. Model verification was carried out to the 7 hydrologic watersheds with areas of 5.89-7,126km$^2$ and the results were generally satisfactory. The daily streamflow can be arbitrarily simulated with the input data of daily rainfall and pan evaporation by the DAWAST model at the station where the observed streamflow data of short periods are available to calibrate the model parameters.

• Journal of the Korean Society of Hazard Mitigation
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• v.4 no.2 s.13
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• pp.53-59
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• 2004

The mechanism of manhole bursting which occurs at excess rainfall events Is studied by using both the physical model and the numerical model (SWMM ; Storm Water Management Model). The result of numerical simulation to steep pressure rising agrees well with that of the physical model at the sewer system under surcharged flow. A cause of manhole bursting is an expansion and spout of the condensed all at manhole that results from the surcharged flow and press wave propagation caused by gate operation or closure of conduit at pumping station.

• Magazine of the Korean Society of Agricultural Engineers
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• v.44 no.3
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• pp.146-156
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• 2002

The objective of this study was to develop a modified CREAMS model for paddy field conditions. The model simulates daily balance of water and nutrient from irrigated paddies using meteorological, irrigation, and agricultural management data. The model simulates daily evapotranspiration of paddy using Penman equation and determines daily flooding depth changes. Total nitrogen and phosphorus concentrations within flooding water, surface runoff, and leaching water from a paddy field also can be simulated. Parameters of the model were calibrated using observed data of the Agricultural Experiment Station of the Seoul National University in Suwon Korea. The model was applied for the irrigation period of paddy field in Gicheon area when 1,234 mm annual rainfall was occurred. The simulated losses of the total nitrogen and total phosphorous were 11.27 kg/ha and 0.98 kg/ha, respectively. There was a good agreement between observed and simulated data. It was found that CREAMS-PADDY model was capable of predicting runoff and nutrient losses from irrigated paddy fields.