• Journal of Korea Water Resources Association
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• v.38 no.12 s.161
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• pp.1061-1072
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• 2005

A hydrological grey model is developed to forecast short-term river runoff from the Naju watershed located at upstream of the Youngsan estuary dam in Korea. The runoff of the Naju watershed is measured in real time at the Naju streamflow gauge station, which is a key station for forecasting the upstream inflow and operating the gates of the estuary dam in flood period. The model's governing equation is formulated on the basis of the grey system theory. The model parameters are reparameterized in combination with the grey system parameters and estimated with the annealing-simplex method In conjunction with an objective function, HMLE. To forecast accurately runoff, the fifth order differential equation was adopted as the governing equation of the model in consideration of the statistic values between the observed and forecast runoff. In calibration, RMSE values between the observed and simulated runoff of two and six Hours ahead using the model range from 3.1 to 290.5 $m^{3}/s,\;R^2$ values range from 0.909 to 0.999. In verification, RMSE values range from 26.4 to 147.4 $m^{3}/s,\;R^2$ values range from 0.940 to 0.998, compared to the observed data. In forecasting runoff in real time, the relative error values with lead-time and river stage range from -23.4 to $14.3\%$ and increase as the lead time increases. The results in this study demonstrate that the proposed model can reasonably and efficiently forecast runoff for one to six Hours ahead.

• Journal of Korea Water Resources Association
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• v.36 no.4
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• pp.609-621
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• 2003

The purpose of this study is to evaluate the hydrological impact due to temporal land cover change by gradual urbanization of upstream watershed of Pyeongtaek gauging station of Anseong -cheon. WMS HEC-1 was adopted, and DEM with 200$\times$200m resolution and hydrologic soil group from 1:50,000 soil map were prepared. Land covers of 1986, 1990, 1994 and 1999 Landsat TM images were classified by maximum likelihood method. The watershed showed a trend that forest ＆ paddy areas decreased and urban/residential area gradually increased for the period of 14 years. The model was calibrated at 2 locations (Pyeongtaek and Gongdo) by comparing observed with simulated discharge results for 5 summer storm events from 1998 to 2001. The watershed average CN values varied from 61.7 to 62.3 for the 4 selected years. To identify the impact of streamflow by temporal area change of a target land use, a simple evaluation method that the CN values of areas except the target land use are unified as one representative CN value was suggested. By applying the method, watershed average CN value was affected in the order of paddy, forest and urban/residential, respectively.

• Journal of Korea Water Resources Association
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• v.36 no.4
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• pp.647-659
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• 2003

The purpose of this study is to evaluate hydrological applicability of spatially observed rainfall distribution data by the TRMM/PR (Tropical Rainfall Measuring Mission / Precipitation Radar). For this study, firstly, TRMM/PR data (Y) of the Yongdam-Dam Watershed (930.38$km^2$) was extracted and secondly, TRMM/PR data and the rainfall data (X) by AWS (Automatic Weather Station) were compared by executing a correlation analysis. As a result, the regression equations were deduced as two parts (under 60mm/day : Y = 18.55X-0.53, over 60mm/day : Y = 3.11X+51.16). SCS runoff analysis was conducted using 7 rainfall events in 1999 for Yongdam-Dam watershed and the Cheon-Cheon subwatershed for the revised TRMM/PR data. TRMM/PR data showed relative errors ranging from 19.6％ ti 45.6％, and from 11.3％ to 38.9％ for Cheon-Cheon subwatershed and Yongdam-Dam watershed, respectively, AWS data showed relative errors ranging from 0.5％ to 12.8％, and from -1.6％ to -10.3％, for Cheon-Cheon subwatershed and Yongdam-Dam watershed, respectively. Futher researches are necessary to evaluate the relationship between TRMM/PR data and AWS data for practical hydrological applications.

• Economic and Environmental Geology
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• v.55 no.1
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• pp.45-51
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• 2022

Whether Dokdo can sustain human habitation or economic life of their own plays an important role to the legal status of the island in the international maritime law. This study reports the hydrological survey results regarding the water resource of the island occurred at Moolgol in Seodo. The amount of underground discharge at Moolgol was estimated at least 1.1 m³/d, conforming the results of previous studies. Based on the oxygen and hydrogen isotope ratios of water, the discharge appeared to originate from precipitation, and about 36% of the daily precipitation moves fast to the Moolgol through the joints developed in the volcanic bedrocks. Quality of the discharged water shows relatively higher concentrations in Cl and NO₃ to be used for drinking and domestic purposes, probably affected by the sea spray and waves from surrounding sea and the birds' excretion such as black-tailed gulls.

• Journal of Korea Water Resources Association
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• v.51 no.6
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• pp.503-514
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• 2018

In recent, the hydrological regime of the Mekong river is changing drastically due to climate change and haphazard watershed development including dam construction. Information of hydrologic feature like streamflow of the Mekong river are required for water disaster prevention and sustainable water resources development in the river sharing countries. In this study, runoff simulations at the Kratie station of the lower Mekong river are performed using SWAT (Soil and Water Assessment Tool), a physics-based hydrologic model, and LSTM (Long Short-Term Memory), a data-driven deep learning algorithm. The SWAT model was set up based on globally-available database (topography: HydroSHED, landuse: GLCF-MODIS, soil: FAO-Soil map, rainfall: APHRODITE, etc) and then simulated daily discharge from 2003 to 2007. The LSTM was built using deep learning open-source library TensorFlow and the deep-layer neural networks of the LSTM were trained based merely on daily water level data of 10 upper stations of the Kratie during two periods: 2000~2002 and 2008~2014. Then, LSTM simulated daily discharge for 2003~2007 as in SWAT model. The simulation results show that Nash-Sutcliffe Efficiency (NSE) of each model were calculated at 0.9(SWAT) and 0.99(LSTM), respectively. In order to simply simulate hydrological time series of ungauged large watersheds, data-driven model like the LSTM method is more applicable than the physics-based hydrological model having complexity due to various database pressure because it is able to memorize the preceding time series sequences and reflect them to prediction.

• Journal of Korea Water Resources Association
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• v.49 no.1
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• pp.1-9
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• 2016

A correlation analysis between raw water turbidity at two wide-area water treatment plants and hydrological data was conducted for efficient water supply, design and management of water treatment plant. Both correlation analysis and principal component analysis were conducted using hydrological time series data such as inflow discharge, outflow discharge, and rainfall at dam basin of intake station of wide-area water treatment plants. And, forecasting of change in turbidity was conducted using regression equation for turbidity prediction. The raw water turbidity of two water treatment plants was strongly related to time series of discharge. The raw water turbidity of Chungju water treatment plant is strongly related to outflow discharge at Chungju dam (0.708). Whereas, the raw water turbidity of Wabu water treatment plant is strongly related to inflow discharge at Paldang dam (0.805). Similar trends between turbidity forecasting result using regression equation and calculation result using estimation equation on Korea water supply facilities standard were obtained. The result of this study can provide basic data for construction and management of water treatment plant.

• Korean Journal of Ecology and Environment
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• v.43 no.2
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• pp.183-189
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• 2010

In this study long term rainfall-runoff model, developed based on SSARR, was applied to Geum river basin and its simulation results of major control points were compared with the corresponding observed channel discharges. The validities of the simulation results were examined with re-measured discharges of those control points. From the above procedure the points showing the unreliable results were found out and its principal causes are analyzed through hydrological inspection of runoff characteristics of their circumstances. Finally the simulation results were modified by the consideration of the effects by small-scale hydraulic structures which could directly affect the channel discharges. As a result the annual runoff simulations of two major points in Geum river basin, Yongdam and Daecheong dam sites, work well. However the low flow simulation of the point located between them, Sutong station, showed more or less the unreliable result. Its causes are considered by means of the hydraulic/hydrological inspection of the corresponding point.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.2
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• pp.319-326
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• 2015

Rainfall data is necessary component for water resources design and flood warning system. Most analysis are used long-term hourly data of surface synoptic stations from the Meteorological Administration, Ministry of land, Infrastructure and Transport and others. However, It will be used minutely data of more high density automatic weather stations than surface synoptic stations expecting to increase the frequency of heavy precipitation. But minutely data has a problem about quality of rainfall data by auto observation. This study analyzed about quality control method using automatic weather station's minutely rainfall data of meteorological administration. It was performed assessment of the quality control that was classified quality control of miss Data, outlier data and rainfall interpolation. This method will be utilized when hydrological analysis uses minute rainfall data.

• Journal of Korea Water Resources Association
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• v.43 no.3
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• pp.257-264
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• 2010

The amount and continuity of precipitation data used in a hydrological analysis may exert a big influence on the reliability of the analysis. It is a fundamental process to estimate the missing data caused by such as a breakdown of the rainfall recording machine or to expand a short period of rainfall data. In this study a linear programming method treated as a data-driven approach for estimating the missing rainfall data is compared with seven other methods widely used and its superiority is certified. The data used in this research are annual precipitation ones during 17 years at the Cheolwon station including an ungauged period of 15 years and its five surrounding stations. By use of this certified method the ungauged precipitation values at the Cheolweon station are estimated and the areal averages of annual precipitation data for 32 years at the Han River basin are calculated.

• Membrane and Water Treatment
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• v.10 no.1
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• pp.1-11
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• 2019

The Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) predicted that recent extreme hydrological events would affect water quality and aggravate various forms of water pollution. To analyze changes in water quality due to future climate change, input data (precipitation, average temperature, relative humidity, average wind speed and sunlight) were established using the Representative Concentration Pathways (RCP) 8.5 climate change scenario suggested by the AR5 and calculated the future runoff for each target period (Reference:1989-2015; I: 2016-2040; II: 2041-2070; and III: 2071-2099) using the semi-distributed land use-based runoff processes (SLURP) model. Meteorological factors that affect water quality (precipitation, temperature and runoff) were inputted into the multiple linear regression analysis (MLRA) and artificial neural network (ANN) models to analyze water quality data, dissolved oxygen (DO), biological oxygen demand (BOD), chemical oxygen demand (COD), suspended solids (SS), total nitrogen (T-N) and total phosphorus (T-P). Future water quality prediction of the Anseongcheon River basin shows that DO at Gongdo station in the river will drop by 35% in autumn by the end of the $21^{st}$ century and that BOD, COD and SS will increase by 36%, 20% and 42%, respectively. Analysis revealed that the oxygen demand at Dongyeongyo station will decrease by 17% in summer and BOD, COD and SS will increase by 30%, 12% and 17%, respectively. This study suggests that there is a need to continuously monitor the water quality of the Anseongcheon River basin for long-term management. A more reliable prediction of future water quality will be achieved if various social scenarios and climate data are taken into consideration.