• Journal of Korea Water Resources Association
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• v.51 no.4
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• pp.371-381
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• 2018

Domestic agricultural reservoir dam facilities are difficult to manage water resources because of the in summer rainfall increase due to aging and climate change, it is expected that the dam risk will be large due to the overflow. In this study, author selected study basin in order to evaluate hydrological safety of agricultural reservoir dam facilities. And calculated the probable rainfall, Present PMP, Future PMP considering climate change. Also, author carried quantitative analysis out for increasing rainfall due to climate change, analyze freeboard assessment of agricultural reservoir by calculate flood discharge, reservoir flood routing according to rainfall scenarios. As a result of evaluate hydrological safety of agricultural reservoir dam facilities using Future PMP considering climate change, Gosam, Kumkwang, Miho, Cheongcheon reservoir had the Highest Water Level over the design flood level, it is analyzed that it would be vulnerable to overflow risk.

• 한국방재학회:학술대회논문집
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• 2009.02b
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• pp.148.2-148.2
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• 2009

• 한국방재학회:학술대회논문집
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• 2009.02b
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• pp.146.2-146.2
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• 2009

• Proceedings of the Korea Contents Association Conference
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• 2010.05a
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• pp.638-640
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• 2010

본 연구에서는 조력발전소 가동조건을 적용한 발전량 산정 프로그램을 이용하여 시화호 홍수위를 분석하였다.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.10
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• pp.1012-1017
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• 2007

Rain data and water-level data are importantly used for dam operation at flood period. Because dams are directly controlled by the water-level data, the characteristic of the water-level gauges is necessary to be managed. Thus, we developed the standard test facility and method for testing the water-level gauges which are a float type, a supersonic type and a radar type. And we calculated the uncertainty of the standard test facility to maintain the accuracy of water-level gauges. Through development of this facility, we could obtain the characteristics and the calibration factor of the water-level gauges. And, this study showed that the standard test facility can be widely used for dam operation and basin management.

• 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 Advanced Navigation Technology
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• v.27 no.1
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• pp.133-138
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• 2023

As a side effect of recent rapid climate change and global warming, the frequency and scale of flood disasters are increasing worldwide. In Korea, the water level of the Han River is a major management target for preventing flood disasters in Seoul, the capital of Korea. In this paper, to improve the water level prediction of the Han River based on machine learning, we perform a comprehensive assessment of the quality of related dataset and propose data preprocessing methods to improve it. Specifically, we improve the dataset in terms of completeness, validity, and accuracy through missing value processing and cross-correlation analysis. In addition, we conduct a performance evaluation using random forest and LightGBM to analyze the effect of the proposed data improvement method on the water level prediction performance of the Han River.

• Journal of The Geomorphological Association of Korea
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• v.17 no.2
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• pp.29-39
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• 2010

Climate change recently causes rapid rises in sea level in Baramarae intertidal area and the rises present several socio-economic impacts to the affected area. We have assessed the vulnerability of the region by the rise of the sea level. Using quantitative GIS method on multi-temporal satellite images, we have first estimated the elevation (Digital Elevation Model: DEM) of Baramarae intertidal area and hence we were possibly able to identify the flooded areas under the IPCC SRES scenarios. As sea level rises by 20cm, 30cm, 40cm, 50cm and 60 cm, the estimated flooded areas of the tidal flat are 68ha, 85ha, 103ha, 121ha and 139ha, respectively. The most affected area is the tidal flat in Gagyeongju Village (Gonam-li, Gonam-myeon, Taean, Chungnam), because it has not only lower altitude but also, perhaps more significantly smooth slope. The potential affected areas are currently populated by farming of oysters and short-necked clams and therefore the areas expect significant economic loss by rise of sea level.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.1 no.1
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• pp.3-17
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• 1998

The purposes of this study is to investigate the possibility of planting trees at space land in the riverside. The space land is for the green space. Calculating the plantable space in the representation section and the flood flowing stability of the existing banks based on the hydrological and meteorological data of the Kap-Chon riverbasin located in Tae-jon, the following results are drawn. (1) The flood discharges in each flow section are $698.7m^3/s$ in section 1, $654.6m^3/s$ in section 2, and $1353.3m^3/s$ in section 3 during 100 years recurrence interval. Because the designed-flood discharges in those sections are $1719.9m^3/s$, $2119.7m^3/s$, and $1512.8m^3/s$ respectively, safety for flood flowing is sufficient in existing banks. (2) The possible clearance for planting trees is 1.80m in section 1, 3.90m in section 2, and 0.01m in section 3. Planting clearance is enough in section 1 and 2. However, planting should be planned after estimating a rise-height due to the bridge piers, because many piers under riverine-highway are now on the construction in section 2. The section 3 does not have sufficient clearance for planting trees, but the planting is possible after getting enough flow area with slope by cutting the terrace land on the river artificially heightened. (3) In case of planting a tree 70cm diameter in $1m^2$ in section 1, the water level increases by 0.60m. Planting a tree in a $48m^2$ area increases the water level by 0.90m. Considering that plantable clearance is 1.8m in section 1, it is sufficient to flow safely. But if the trees are planted so compactly from the upper stream, expected heavy resistance is expected due to caught materials on the trees. So, trees have to be planted widely in upper streams but compactedly in lower streams. (4) The river width without changing, Kap-Chon's flow channel can be snaked in accordance with the nature law the wide terrace land in the riverside. Decreased flow area due to planting trees will be compensated by the inclination of terrace land. And, it is theoretically proved that the flood discharge is safe even though the terrace land on the river is parked similar to the nature. Planting trees in the terrace land of the Kap-chon river to the extent that flood flowing is not adversely affected, we can get the enjoyable park to citizens not spending expensive cost. It also contributes to the recovery of ecosystem, which gives the natural beauty of river and shade to citizens and becomes good natural-educational places for children.

• Journal of Korea Water Resources Association
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• v.56 no.12
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• pp.981-992
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• 2023

Due to recent global climate change, the scale of flood damage is increasing as rainfall is concentrated and its intensity increases. Rain on a scale that has not been observed in the past may fall, and long-term rainy seasons that have not been recorded may occur. These damages are also concentrated in ASEAN countries, and many people in ASEAN countries are affected, along with frequent occurrences of flooding due to typhoons and torrential rains. In particular, the Bandung region which is located in the Upper Chitarum River basin in Indonesia has topographical characteristics in the form of a basin, making it very vulnerable to flooding. Accordingly, through the Official Development Assistance (ODA), a flood forecasting and warning system was established for the Upper Citarium River basin in 2017 and is currently in operation. Nevertheless, the Upper Citarium River basin is still exposed to the risk of human and property damage in the event of a flood, so efforts to reduce damage through fast and accurate flood forecasting are continuously needed. Therefore, in this study an artificial intelligence-based river flood water level forecasting model for Dayeu Kolot as a target station was developed by using 10-minute hydrological data from 4 rainfall stations and 1 water level station. Using 10-minute hydrological observation data from 6 stations from January 2017 to January 2021, learning, verification, and testing were performed for lead time such as 0.5, 1, 2, 3, 4, 5 and 6 hour and LSTM was applied as an artificial intelligence algorithm. As a result of the study, good results were shown in model fit and error for all lead times, and as a result of reviewing the prediction accuracy according to the learning dataset conditions, it is expected to be used to build an efficient artificial intelligence-based model as it secures prediction accuracy similar to that of using all observation stations even when there are few reference stations.