• 한국해양학회지
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• v.22 no.2
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• pp.105-118
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• 1987

A series of anchor stations were occupied along the Keum EAstuary during six different periods of tidal and fluvial regimes. The results clearly show that the formation and evolution of the turbidity maximum play an important role in the sedimentary processes in this environment. The turbidity maximum in the Keum Estuary is primarily related to the tidal range at the mouth and is caused by the resuspension of bottom sediments. In this estuary, the turbidity maximum is not a permanent feature and shows semidiurnal, fortnightly and seasonal variations. Repetition of deposition and resuspension of fine sediments occur in response to the variation in current velocity associated with semidiurnal tidal cycles. The core of turbidity maximum shifts landward or seaward accordion to the flood-ebb succession. The turbidity maximum also shows a fortnightly variation in response to the spring-neap cycles. Thus, the turbidity maximum degenerates during neap-tide and regenerates during spring-tide. The freshwater discharge is also an important factor in the formation and destruction of the turbidity maximum. The increase in freshwater discharge in rainy season can create an ebb-dominant current pattern which enhances the seaward transport of suspended sediments, resulting in the shortening of residence time of suspended materials in the estuary. Thus, under this high discharge condition, the turbidity maximum exists only during spring-tide and starts to disappear as the tidal amplitude decreases.

• Journal of Practical Agriculture & Fisheries Research
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• v.23 no.2
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• pp.15-24
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• 2021

For the aquaculture industrialization of surf clam (Tresus keenae), it is important to basic data on the marine environment of the habitat of surf clam (T. keenae). In this study, we investigated the marine environment of habitat of surf clam (T. keenae) and sought to basic data for the preparation of surf clam (T. keenae) for artificial seed production. The water temperature of the habitat of surf clam (T. keenae) was the lowest in winter and appeared high in summer. The salt concentration showed it range from 31.2 to 33.9 psu. The pH showed it range from 7.69 to 8.70, with high pH in winter and low pH in summer. The dissolved oxygen(DO) was showed it range from 6.20 to 10.24 mg / L and the autumn was relatively higher than the spring and winter. The species composition of phytoplankton was about 30 to 40 species, and most of them were diatoms. The abundance of seasonal phytoplankton showed it range from 23.5 to 61.3 cells / ml, showing seasonal differences. The expression of dominant species also showed a difference depending on the season. As for the particle size composition of the sediment, sandy silt was the most distributed. Flow velocities appeared at 50-80 cm / s in the southeast direction at ebb tide and at 60-100 cm / s in the northwest direction at flood tide. The results of this study can be used as basic data for providing knowledge about the habitat and marine environment of surf clam (T. keenae) and for studying shellfish that inhabit the sedimentary layer.

• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.1021-1030
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• 2022

Currently, South Korea implements water resources management policies focusing on integrated water quantity, quality and hydro-ecology management. In particular, rehabilitation of natural rivers has become a major issue. As for reservoir operation during non-flood season, efforts have been made continuously to apply the Deficit Supply Method that can maximize water supply to address droughts and increase in water demand. When Deficit Supply Method is applied, the water supply capacity of reservoir can be maximized. However, downstream water flow would remain constant. In consideration that a natural stream, a long-time-created hydro-ecology, can be significantly influenced by flow variability, the Deficit Supply Method-based reservoir operation can generate effective water supply. Still, it may trigger adverse effects from the aspects of natural rehabilitation and hydro-ecology recovery. The main objective of this study is to analyze impacts on downstream flow duration through reservoir simulation by comparing the Firm Supply Method, the Deficit Supply Method and the Selective Deficit Supply Method, and examining each method's effects on reservoir operation. This study found that the Firm Supply Method could maintain water flow variability, but could not maximize water supply capacity. When the Deficit Supply Method was applied, water supply capacity could be increased while remaining vulnerable regarding water flow variability, as a difference between average flow and low flow was negligible at downstream. In comparison, the Selective Deficit Supply Method was found to sustain time-based reliability at 95% or higher, whereas downstream flow duration could be maintained at a level similar to the level generated by the Firm Supply Method.

• Journal of Korea Water Resources Association
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• v.54 no.11
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• pp.933-942
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• 2021

The surface image velocimetry was developed to measure river flow velocity safely and effectively in flood season. There are a couple of methods in the surface image velocimetry. Among them the spatio-temporal image velocimetry is in the spotlight, since it can estimate mean velocity for a period of time. For the spatio-temporal image velocimetry analyzes a series of images all at once, it can reduce analyzing time so much. It, however, has a little drawback to find out the main flow direction. If the direction of spatio-temporal image does not coincide to the main flow direction, it may cause singnificant error in velocity. The present study aims to propose a new method to find out the main flow direction by using a fast Fourier transform(FFT) to a spatio-temporal (image) volume, which were constructed by accumulating the river surface images along the time direction. The method consists of two steps; the first step for finding main flow direction in space image and the second step for calculating the velocity magnitude in main flow direction in spatio-temporal image. In the first step a time-accumulated image was made from the spatio-temporal volume along the time direction. We analyzed this time-accumulated image by using FFT and figured out the main flow direction from the transformed image. Then a spatio-temporal image in main flow direction was extracted from the spatio-temporal volume. Once again, the spatio-temporal image was analyzed by FFT and velocity magnitudes were calculated from the transformed image. The proposed method was applied to a series of artificial images for error analysis. It was shown that the proposed method could analyze two-dimensional flow field with fairly good accuracy.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5B
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• pp.485-493
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• 2008

The Artificial Neural Network (ANN) model was suggested for predicting probability of precipitation (PoP) using RDAPS NWP model, observation at AWS and upper-air sounding station. The prediction work was implemented for flood season and the data period is the July, August of 2001 and June of 2002. Neural network input variables (predictors) were composed of geopotential height 500/750/1000 hPa, atmospheric thickness 500-1000 hPa, X & Y-component of wind at 500 hPa, X & Y-component of wind at 750 hPa, wind speed at surface, temperature at 500/750 hPa/surface, mean sea level pressure, 3-hr accumulated precipitation, occurrence of observed precipitation, precipitation accumulated in 6 & 12 hrs previous to RDAPS run, precipitation occurrence in 6 & 12 hrs previous to RDAPS run, relative humidity measured 0 & 12 hrs before RDAPS run, precipitable water measured 0 & 12 hrs before RDAPS run, precipitable water difference in 12 hrs previous to RDAPS run. The suggested ANN has a 3-layer perceptron (multi layer perceptron; MLP) and back-propagation learning algorithm. The result shows that there were 6.8% increase in Hit rate (H), especially 99.2% and 148.1% increase in Threat Score (TS) and Probability of Detection (POD). It illustrates that the suggested ANN model can be a useful tool for predicting rainfall event prediction. The Kuipers Skill Score (KSS) was increased 92.8%, which the ANN model improves the rainfall occurrence prediction over RDAPS.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.5B
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• pp.497-507
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• 2010

Climate changes affect greatly natural ecosystem, human social and economic system acting on constituting the climate system such as air, ocean, life, glacier and land, etc. and estimating the current impact of climate change would be the most important thing to adapt to the climate changes. This study set the target area to Nakdong river watershed and investigated the impact of climate changes through analyzing precipitation tendency, and to understand the impact of climate changes on hydrological elements, analyzed elasticity of precipitation-streamflow. For the analysis of precipitation trend, collecting the precipitation data of the National Weather Service from major points of Nakdong river watershed, resampling them at the units of year, season and month, used as the data of precipitation trend analysis. To analyze precipitation-streamflow elasticity, collecting area average precipitation and long-term streamflow data provided by WAMIS, annual and seasonal time-series were analyzed. In addition, The results of this study and elasticity, and other abroad study compared with the elasticity analysis and the validity of this study was verified. Results of this study will be able to be utilized for study on a plan to increase of flood control ability of flooding constructs caused by the increase of streamflow around Nakdong river watershed due to climate changes and on a plan of adapting to water environment according to climate changes.

• Journal of Korea Water Resources Association
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• v.41 no.7
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• pp.711-723
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• 2008

In this study, Hydrologic regime alterations(magnitude, magnitude and duration of annual extreme, frequency and duration of high and low pulse, rate and frequency of water condition changes, Range of Variability Approach) were analyzed by using Indicators of Hydrologic Alterations at the 11 major multi-purpose dam. The analysis result of the magnitude of monthly water conditions during drought season, inflow was $6.38m^3/sec{\sim}39.84m^3/sec$ and outflow was $20.36m^3/sec{\sim}49.43m^3/sec$, was increased $1.84%{\sim}200.98%$. The analysis result of the magnitude of monthly water conditions during flood season, inflow was from $79.06m^3/sec{\sim}137.12m^3/sec$ and outflow was from $65.32m^3/sec{\sim}80.16m^3/sec$, was decreased from $18.19%{\sim}40.39%$. The analysis result of the magnitude and duration of annual extreme, 1-day minimum was increased $82.86%{\sim}2,950%$, but 1-day maximum was decreased $34.78%{\sim}83.96%$. The analysis result of the frequency and duration of high and low pulse, low pulse count was decreased $29.67%{\sim}99.07%$ and high pulse count was also decreased $4.6%{\sim}92.35%$ after dam operation. Hydrograph rise rate was decreased $15.84%{\sim}79.31%$ and fall rate was $1.97%{\sim}107.10%$. RVA of 1-day minimum was increased $0.60{\sim}2.67$, also RVA of 1-day maximum was decreased $0.50{\sim}1.00$.

• Journal of the Korean Geographical Society
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• v.28 no.2
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• pp.112-122
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• 1993

Since more than 50${\%}$ of annual precipitation in Korea falls during Changma, the rainy season of early summer, and Late Changma, the rainy season of late summer, forcasting the onset days Changmas, and the amount related rainfalls would be necessary not only for agriculture but also for flood-control. In this study the authors attempted to build a prediction model for the forecast of the onset date of Changmas. The onset data of each Changma was derived out of daily rainfall data of 47 stations for 30 years(1961~1990) and weather maps over East Asia. Each station represent any of the 47 districts of local forecast under the Korea Meteorological Administration. The average onset dates of Changma during the period was from 21 through 26 June. The dates show a tendency to be delayed in El Ni${\~{n}}o years while they come earlier than the average in La Nina years. In 1982, the year of El Ni${\~{n}}o, the date was 9 Julu, two weeks late compared with the average. The relation of sea surface temperature(SST) over Pacific and Northern hemispheric 500mb height to the Changma onset dates was analyzed for the prediction model by polynomial regression. The onset date of Changma over Korea was correlated with SST in May(SST${_(5)}{^\circ}$C) of the district (8${^\circ}$~12${^\circ}S, 136${^\circ}~148${^\circ}W)of equatirial middle Pacific and the 500mb height in March (MB${_(3)}$"\;"m)over the district of the notrhern Hudson Bay. The relation between this two elements can be expressed by the regression: Onset=5.888SST${_5}"\;"+"\;"0.047MB${_(3)}$"\;"-251.241. This equation explains 77${\%}$ of variances at the 0.01${\%}$ singificance level. The onset dates of Late Changma come in accordance with the degeneration of the Subtro-pical High over northern Pacific. They were 18 August in average for the period showing positive correlation(r=0.71) with SST in May(SST)${_(i5)}{^\circ}$C) over district of IndiaN Ocean near west coast of Australia (24${^\circ}$~32${^\circ}$S, 104${^\circ}$~112${^\circ}$E), but negativ e with SST in May(SST${_(p5)}{^\circ}$ over district (12${^\circ}$~20${^\circ}$S,"\;"136${^\circ}$~148${^\circ}$W)of equatorial mid Pacific (r=-0.70) and with the 500mb height over district of northwestern Siberia (r=-0.62). The prediction model for Late Changma can be expressed by the regression: Onset=706.314-0.080 MB-3.972SST${_(p5)}+3.896 SST${_(i5)}, which explains 64${\%}$ of variances at the 0.01${\%}$ singificance level.

• Journal of Korea Water Resources Association
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• v.55 no.11
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• pp.931-939
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• 2022

In Korea, about two-thirds of the precipitation is concentrated in the summer season, so the problem of turbidity in the summer flood season varies from year to year. Concentrated rainfall due to abnormal rainfall and extreme weather is on the rise. The inflow of turbidity caused a sudden increase in turbidity in the water, causing a problem of turbidity in the dam reservoir. In particular, in Korea, where rivers and dam reservoirs are used for most of the annual average water consumption, if turbidity problems are prolonged, social and environmental problems such as agriculture, industry, and aquatic ecosystems in downstream areas will occur. In order to cope with such turbidity prediction, research on turbidity modeling is being actively conducted. Flow rate, water temperature, and SS data are required to model turbid water. To this end, the national measurement network measures turbidity by measuring SS in rivers and dam reservoirs, but there is a limitation in that the data resolution is low due to insufficient facilities. However, there is an unmeasured period depending on each dam and weather conditions. As a sensor for measuring turbidity, there are Optical Backscatter Sensor (OBS) and YSI, and a sensor for measuring SS uses equipment such as Laser In-Situ Scattering and Transmissometry (LISST). However, in the case of such a high-tech sensor, there is a limit due to the stability of the equipment. Therefore, there is an unmeasured period through analysis based on the acquired flow rate, water temperature, SS, and turbidity data, so it is necessary to develop a relational expression to calculate the SS used for the input data. In this study, the AEM3D model used in the Water Resources Corporation SURIAN system was used to improve the accuracy of prediction of turbidity through the turbidity-SS relationship developed based on the measurement data near the dam outlet.

• Journal of Korea Water Resources Association
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• v.50 no.7
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• pp.475-488
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• 2017

To simulate accurate drought, a drought index is needed to reflect the hydrometeorological phenomenon. Several studies have been conducted in Korea using the Modified Surface Water Supply Index (MSWSI) to simulate hydrological drought. This study analyzed the limitations of MSWSI and quantified the uncertainties of MSWSI. The influence of hydrometeorological components selected as the MSWSI components was analyzed. Although the previous MSWSI dealt with only one observation for each input component such as streamflow, ground water level, precipitation, and dam inflow, this study included dam storage level and dam release as suitable characteristics of the sub-basins, and used the areal-average precipitation obtained from several observations. From the MSWSI simulations of 2001 and 2006 drought events, MSWSI of this study successfully simulated drought because MSWSI of this study followed the trend of observing the hydrometeorological data and then the accuracy of the drought simulation results was affected by the selection of the input component on the MSWSI. The influence of the selection of the probability distributions to input components on the MSWSI was analyzed, including various criteria: the Gumbel and Generalized Extreme Value (GEV) distributions for precipitation data; normal and Gumbel distributions for streamflow data; 2-parameter log-normal and Gumbel distributions for dam inflow, storage level, and release discharge data; and 3-parameter log-normal distribution for groundwater. Then, the maximum 36 MSWSIs were calculated for each sub-basin, and the ranges of MSWSI differed significantly according to the selection of probability distributions. Therefore, it was confirmed that the MSWSI results may differ depending on the probability distribution. The uncertainty occurred due to the selection of MSWSI input components and the probability distributions were quantified using the maximum entropy. The uncertainty thus increased as the number of input components increased and the uncertainty of MSWSI also increased with the application of probability distributions of input components during the flood season.