• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.433-442
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• 2018

The reservoir area is defined as the area surrounded by the planned flood level of the dam or the land under the planned flood level of the dam. In this study, supervised classification based on RF (Random Forest), which is a representative machine learning technique, was performed to detect cropland in the reservoir area. In order to classify the cropland in the reservoir area efficiently, the GLCM (Gray Level Co-occurrence Matrix), which is a representative technique to quantify texture information, NDWI (Normalized Difference Water Index) and NDVI (Normalized Difference Vegetation Index) were utilized as additional features during classification process. In particular, we analyzed the effect of texture information according to window size for generating GLCM, and suggested a methodology for detecting croplands in the reservoir area. In the experimental result, the classification result showed that cropland in the reservoir area could be detected by the multispectral, NDVI, NDWI and GLCM images of UAV, efficiently. Especially, the window size of GLCM was an important parameter to increase the classification accuracy.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.1
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• pp.107-120
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• 2019

Reservoir water level data identify the current water storage of the reservoir, and they are utilized as primary data for management and research of agricultural water. For the reservoir storage management, Korea Rural Community Corporation (KRC) installed water level stations at around 1,600 agricultural reservoirs and has been collecting the water level data every 10 minutes. However, various kinds of outliers due to noise and erroneous problems are frequently appearing because of environmental and physical causes. Therefore, it is necessary to detect outlier and improve the quality of reservoir water level data to utilize the water level data in purpose. This study was conducted to detect and classify outlier and normal data using two different models including the threshold model and the artificial neural network (ANN) model. The results were compared to evaluate the performance of the models. The threshold model identifies the outlier by setting the upper/lower bound of water level data and variation data and by setting bandwidth of water level data as a threshold of regarding erroneous water level. The ANN model was trained with prepared training dataset as normal data (T) and outlier (F), and the ANN model operated for identifying the outlier. The models are evaluated with reference data which were collected reservoir water level data in daily by KRC. The outlier detection performance of the threshold model was better than the ANN model, but ANN model showed better detection performance for not classifying normal data as outlier.

• Journal of Korean Society on Water Environment
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• v.27 no.6
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• pp.743-753
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• 2011

One of the most important water management issues of Soyang Reservoir, located in North Han River in Korea, is a long term discharge of turbid water to downstream during flood season. Installation of a selective withdrawal structure (SWS) is planned by the reservoir management institute as a control measure of outflow water quality and associated negative impacts on downstream water use and ecosystem. The objective of the study was to explore the effectiveness of the SWS on the control of outflow turbidity under two different hydrological years; one for normal flood year and another for extreme flood year. A two-dimensional (2D), laterally averaged hydrodynamic and water quality model (CE-QUAL-W2) was set up and calibrated for the reservoir and used to evaluate the performance of the proposed SWS. The results revealed that the SWS can be an effective method when the ${\Theta}$ value, the ratio between the amount of turbid water that containing suspended sediment (SS) greater than 25 mg/L and the total storage of the reservoir, is 0.59 during the normal flood year. However, the effectiveness of the SWS could be marginal or negative in the extreme flood year when ${\Theta}$ was 0.83. The results imply that the SWS is an effective alternative for the control of turbid water for moderate flood events, but not a sufficient measure for large flood events that are expected to happen more often in the future because of climate change.

• Journal of Korean Society on Water Environment
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• v.27 no.4
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• pp.445-460
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• 2011

The objective of this study was to construct and assess the applicability of the EFDC model for Saemangeum Reservoir as a 3D hydrodynamic and water quality modeling tool that is necessary for the effective management of water quality and establishment of conservation measures. The model grids for both reservoir system only and reservoir-ocean system were created using the most recent survey data to compare the effects of different downstream boundary conditions. The model was applied for the simulations of temperature, salinity, water quality variables including chemical oxygen demand (COD), chlorophyll-a (Chl-a), phosphorus and nitrogen species and algal biomass, and validated using the field data obtained in 2008. Although the model reasonably represented the temporal and spatial variations of the state variables in the reservoir with limited boundary forcing data, the salinity level was underestimated in the middle and upstream of the reservoir when the flow data were used at downstream boundaries; Sinsi and Garyuk Gates. In turn, the error caused to increase the bias of water quality simulations, and inaccurate simulation of density flow regime of river inflow during flood events. It is likely because of the loss of momentum of sea water intrusion at downstream boundaries. In contrast to flow boundary conditions, the mixing between sea water and freshwater was well reproduced when open water boundary condition was applied. Thus, it is required to improve the downstream boundary conditions that can accommodate the real operations of the sluice gates.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.6
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• pp.1-12
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• 2022

Estuary reservoirs were artificial reservoir with seawalls built at the exit points of rivers. Although many water resources can be saved, it is difficult to manage due to the large influx of pollutants. To manage this, it is necessary to analyze watersheds and reservoirs through accurate modeling. Therefore, in this study, we linked the Hydrological Simulation Program-FORTRAN (HSPF), Environmental Fluid Dynamics Code (EFDC), and Water quality Analysis Simulation Program (WASP) models to simulate the hydrology and water quality of the watershed and the water level and quality of estuary lakes. As a result of applying the linked model in stream, R² 0.7 or more was satisfied for the watershed runoff except for one point. In addition, the water quality satisfies all within 15% of PBIAS. In reservoir, R² 0.72 was satisfied for water level and the water quality was within 15% of T-N and T-P. Through the modeling system, We applied upstream pollutant management scenarios to analyze changes in water quality in estuary reservoirs. Three pollution source management were applied as scenarios, the improvement of effluent water quality from the sewage treatment plant and the livestock waste treatment plant was effective in improving the quality of the reservoir water, while the artificial wetland had little effect. Water quality improvement was confirmed as a measure against upstream pollutants, but it was insufficient to achieve agricultural water quality, so additional reservoir management is required.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.5
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• pp.25-35
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• 2023

The estuary reservoir is a major source of agricultural water in Korea; for effective and sustainable water resource management of the estuary reservoir, it is crucial to comprehensively consider various water resource factors, including water supply, flood, and pollutant management, and analyze future runoff changes in consideration of environmental changes such as climate change. The objective of this study is to estimate the impact of future climate change on the runoff characteristics of an estuary reservoir watershed. Climate data on future Shared Socioeconomic Pathway (SSP) scenarios were derived from two Global Climate Models (GCMs) of the Coupled Model Intercomparison Project phase 6 (CMIP6). The Hydrological Simulation Program-Fortran (HSPF) was used to simulate past and future long-term runoff of the Ganwol estuary reservoir watershed. The findings showed that as the impact of climate change intensified, the average annual runoff in the future period was higher in the order of SSP5, SSP3, SSP1, and SSP2, and the ratio of runoff in July decreased while the ratio of runoff in October increased. Moreover, in terms of river flow regime, the SSP2 scenario was found to be the most advantageous and the SSP3 scenario was the most disadvantageous. The findings of this study can be used as basic data for developing sustainable water resource management plans and can be applied to estuary reservoir models to predict future environmental changes in estuary reservoirs.

• Journal of Korean Society of Rural Planning
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• v.30 no.3
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• pp.75-84
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• 2024

This study developed the procedure and method for the accuracy assessment of unmanned boat survey data, based on the reservoir water depth data of Misan Reservoir, measured by the manned and unmanned boats in 2009 by Korea Rural Community Corporation. In the first step, this study devised the method to extract the contour map of NGIS data in AutoCAD to generate easily the reservoir boundary map used to set the survey range of reservoir water depth and to test the survey accuracy. The surveyed data coordinate systems of the manned and the unmanned boat were also unified by using ArcGIS for the standards of accuracy assessment. In the accuracy assessment, the spatial correlation coefficient of the grid maps of the two measurement results was 0.95, showing high pattern similarity, although the average error was high at 78cm. To analyze in more detail assessment, this study generated randomly the 3,250m transverse profile route (PR), and then extracted grid values of water depth on the PR. In the results of analysis to the extracted depth data on PR, the error average difference of the unmanned boat measurements was 73.18cm and the standard deviation of the error was 55cm compared to the manned boat. This study set these values as the standard for the correction value by average shift and noise removal of the unmanned boat measurement data. By correcting the unmanned boat measurements with these values, this study has high accuracy results, the reservoir water depth and surface area curve with R² = 0.97 and the water depth and storage volume curve with R² = 0.999.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.04a
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• pp.467-470
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• 2003

This study tries to introduce the precision measurement of 3-dimensional terrain of reservoir using Echo Sounder and RTK-GPS which is unprecedented in domestic. In this study, to introduce the way to produce the plane figure, the cross section and data of underside reservoir by constructing the 3-dimensional terrain models using 3-Dimensional data gained by measurement.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1999.10c
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• pp.117-122
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• 1999

The state of drought was evaluated by the operation rule curve. From the present percentage of reservoir storage and the operation rule curve, it could be determined to ristrict the irrigation water supply to a certain level and eventually to overcome the shortage of water in the irrigation reservoir.

• Proceedings of the Korean Society of Environment and Ecology Conference
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• 2007.10a
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• pp.23-26
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• 2007