• Journal of Korean Society on Water Environment
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• v.26 no.1
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• pp.61-70
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• 2010

The increase of impervious cover (IC) in a watershed is known as an important factor causing alteration of water cycle, deterioration of water quality and biological communities of urban streams. The study objective was to assess the impact of IC changes on the surface runoff characteristics of Kap Stream basin located in Geum river basin (Korea) using the Storm Water Management Model (SWMM). SWMM was calibrated and verified using the flow data observed at outlet of the watershed with 8 days interval in 2007 and 2008. According to the analysis of Landsat satellite imagery data every 5 years from 1975 to 2000, the IC of the watershed has linearly increased from 4.9% to 10.5% during last 25 years. The validated model was applied to simulate the runoff flow rates from the watershed with different IC rates every five years using the climate forcing data of 2007 and 2008. The simulation results indicated that the increase of IC area in the watershed has resulted in the increase of peak runoff and reduction of travel time during flood events. The flood flow ($Q_{95}$) and normal flow ($Q_{180}$) rates of Kap Stream increased with the IC rate. However, the low flow ($Q_{275}$) and drought flow ($Q_{355}$) rates showed no significant difference. Thus the subsurface flow simulation algorithm of the model needs to be revisited for better assessment of the impact of impervious cover on the long-term runoff process.

• Journal of Korea Water Resources Association
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• v.33 no.4
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• pp.393-405
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• 2000

Monthly runoff was estimated using TOPMODEL which simulates ground water movement as well as surface runoff in the area of catchment. SAYUN dam which is being operated by Korea Water Resources Corporation was selected for the study, and the topographic factors of the watershed were analyzed using 1/5,000 digital map and GIS software(Arc/Info). The comparison shows good agreement between observed monthly runoff and the computation results simulated by using TOPMODEL. The catchment area of SAYUN dam was modeled by using various grid sizes in order to check the sensitivity of grid size, and the grid size of 180m was found most proper among 6 different sizes. TOPMODEL was also found superior to the existing monthly runoff models such as Kajiyama, KRIHS and Tank. Because the model requires limited number of parameters and considers topographic aspects, it is reckoned to be very useful for practical use.

• Journal of Korea Water Resources Association
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• v.39 no.10 s.171
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• pp.833-844
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• 2006

The objective of this study is to evaluate the snowmelt effects on the hydrological components, especially on the runoff, by using the soil water assessment tool(SWAT) which is a continuous semi-distributed long term rainfall-runoff model. The model was applied to the basin located in the upstream of the Chungju Dam. Some parameters in the snowmelt algorithm were estimated for the Chungju basin in order to reflect the snowmelt effects. The snowmelt effects were assessed by comparing the simulated runoff with the observed runoff data at the outlet of the basin. It was found out that the simulated runoff with considering the snowmelt component matches more satisfactorily to the observed one than without considering snowmelt effect. The simulation results revealed that the snowmelt effects were noticeable on March and April. Similar results were obtained at other two upstream gauging points. The effect of the elevation bands which distribute temperature and precipitation with elevation was analyzed. This study also showed that the snowmelt effect significantly affects the temporal distribution as well as quantity of the hydrological components. The simulated runoff was very sensitive to the change of temperature near the threshold temperature which the snowmelt can occur. However, the reason was not accounted for this paper, Therefore, further analyses related to this feature are needed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1D
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• pp.145-151
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• 2009

Recently, the rapid development of GIS technology has made it possible to handle a various data associated with spatially hydrological parameters with their attribute information. Therefore, there has been a shift in focus from lumped runoff models to distributed runoff models, as the latter can consider temporal and spatial variations of discharge. This research is to evaluate the feasibility of GIS based distributed model using radar rainfall which can express temporal and spatial distribution in actual dam watershed during flood runoff period. K-DRUM (K-water hydrologic & hydaulic Distributed flood RUnoff Model) which was developed to calculate flood discharge connected to radar rainfall based on long-term runoff model developed by Kyoto- University DPRI (Disaster Prevention Research Institute), and Yondam-Dam watershed ($930km^2$) was applied as study site. Distributed rainfall according to grid resolution was generated by using preprocess program of radar rainfall, from JIN radar. Also, GIS hydrological parameters were extracted from basic GIS data such as DEM, land cover and soil map, and used as input data of distributed model (K-DRUM). Results of this research can provide a base for building of real-time short-term rainfall runoff forecast system according to flash flood in near future.

• Journal of Korean Society on Water Environment
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• v.25 no.2
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• pp.268-280
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• 2009

Oncheon basin which are located in Busan is divided into 43 basin on the basis of main pipe, constructed with Storm Water Management Model (SWMM). Occurrence situation for Outflow and pollutant loads by long-term continuous rainfall is examined for treatment district and river analysis point of Oncheon basin and a reduction vs effectiveness table for effective CSOs managements is made for each of treatment districts according to each of managements. In case that treatment equipment is located at the discharge point of CSO, treatment efficiency is analysed. It is supposed that treatment equipment have an efficiency on the basis of a concentration and runoff discharge over a critical flow is discharged with it untreated and treating runoff discharge with treatment equipment at each of runoff discharge points and treating it gathered at sewage treatment plant (STP) through trunk sewer is compared for a relative treatment efficiency.

• Ocean and Polar Research
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• v.26 no.1
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• pp.33-42
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• 2004

Effect of freshwater discharge on the long-term salt balance in the Northern and Central Indian River Lagoon (IRL) is successfully simulated by a new analytical solution to a water balance-based one-dimensional salt conservation equation. Sensitivity tests show that the salinity levels drop abruptly even during the dry season (November to May) due to the high surface runoff discharge caused by tropical storms, depressions, and passage of cold fronts. Increasing surface runoff and direct precipitation has risen by ten times, lowering the salinity level down to 12psu in the Northern Central zone, and to 17 psu in the Northern zone. However, the salinity level in the Southern Central zone has decreased to 25 psu. High sensitivity of the Northern Central zone to freshwater discharge can be partially explained by a rapid urbanization in this zone. During the dry season, less sensitivity of the Southern Central zone to the increased surface runoff is attributed to the proximity of the zone to the Sebastian Inlet and a strong diffusion condition possibly resulting from the seawater intrusion to the surficial aquifer at the Vero Beach. During the wet season, however, the whole study area is highly sensitive to freshwater discharge due to the weak diffusion conditions. High sensitivity of the IRL to the given diffusion conditions guarantees that the fresh-water release occurs during strong wind conditions, achieving both flood control in the drainage basin and a proper salinity regime in the IRL.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.6
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• pp.2237-2244
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• 2013

In this study, physics based K-DRUM(K-water Distributed RUnoff Model) using GIS spatial hydrologic data as input data was developed to account for the temperature variation according to the altitude change considering snow melt and cover. The model was applied for Pakistan Kunhar River Basin($2,500km^2$) to calculate long-term discharge considering snow melt and cover. Time series analysis of the temperature and rainfall data reveals that temperature and rainfall of the river basin differs significantly according to altitude change compared to domestic basin. Thus, applying temperature and altitude lapse rate during generate input data generation. As a result, calculated discharge shows good agreement with observed ones considering snow melt and accumulation characteristic which has the difference of 4,000 meter elevation above sea level. In addition, the simulated discharge strongly showed snow melting effect associated with temperature rise during the summer season.

• Journal of Korea Water Resources Association
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• v.41 no.6
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• pp.643-651
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• 2008

This study was conducted to promote reliability of the simulated result for the long-term streamflow in Daecheong watershed. This system was constructed by the SSARR model that considered the effect of small scale irrigation facilities. We investigated the present condition of small scale irrigation facilities and analyzed the relation between irrigation facilities and river discharge. According to the analysis result about the effect of irrigation facilities, the error occurrence frequency was increased at the sub-basin that has many reservoirs and during the second quarter except for the 2003 year. Therefore, we created the relative equation between small irrigation facilities and river water and estimated the simulated streamflow for the main stations. Consequently, error of the runoff simulated with considering small scale irrigation facilities was decreased than that without considering small scale irrigation facilities at all.

• Journal of Korean Society on Water Environment
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• v.27 no.4
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• pp.405-412
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• 2011

Increased Non-permeable areas which have resulted from civilization reduce the volume of groundwater infiltration that is one of the important factors causing water shortage during a dry season. Thus, seeking the efficient method to analyze the volume of groundwater in accurate should be needed to solve water shortage problems. In this study, two different watersheds were selected and precipitation, soil group, and land use were surveyed in a particular year in order to figure out the accuracy of estimated infiltration recharge ratio compared to Web-based Hydrograph Analysis Tool (WHAT). The volume of groundwater was estimated considering Antecedent soil Moisture Condition (AMC) and Curve Number (CN) using Long Term Hydrologic Impact Assessment (L-THIA) model. The results of this study showed that in the case of Kyoung-an watershed, the volume of both infiltration and baseflow seperated from WHAT was 46.99% in 2006 and 33.68% in 2007 each and in Do-am watershed the volume of both infiltration and baseflow was 33.48% in 2004 and 23.65% in 2005 respectively. L-THIA requires only simple data (i.e., land uses, soils, and precipitation) to simulate the accurate volume of groundwater. Therefore, with convenient way of L-THIA, researchers can manage watershed more effectively than doing it with other models. L-THIA has limitations that it neglects the contributions of snowfall to precipitation. So, to estimate more accurate assessment of the long term hydrological impacts including groundwater with L-THIA, further researches about snowfall data in winter should be considered.

• Journal of Korea Water Resources Association
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• v.54 no.3
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• pp.157-166
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• 2021

Forecasting dam inflow based on high reliability is required for efficient dam operation. In this study, deep learning technique, which is one of the data-driven methods and has been used in many fields of research, was manipulated to predict the dam inflow. The Long Short-Term Memory deep learning with Sequence-to-Sequence model (LSTM-s2s), which provides high performance in predicting time-series data, was applied for forecasting inflow of Soyang River dam. Various statistical metrics or evaluation indicators, including correlation coefficient (CC), Nash-Sutcliffe efficiency coefficient (NSE), percent bias (PBIAS), and error in peak value (PE), were used to evaluate the predictive performance of the model. The result of this study presented that the LSTM-s2s model showed high accuracy in the prediction of dam inflow and also provided good performance for runoff event based runoff prediction. It was found that the deep learning based approach could be used for efficient dam operation for water resource management during wet and dry seasons.