During the past few years, Korea has experienced extraordinary floods, which have caused many damages of lives and properties. Flooding caused by typhoon is the most common disastrous phenomenon of nature among all catastrophes. As the average temperature of the earth has been increasing by global warming, the possibility of typhoon is also increased by abnormal climate changes. Along with the river improvement as a part of flood control, the time of concentration has been decreased, so the pick discharge has been increased. Moreover, with the land development activities, the area of storage has been diminishing, and the damages from inundation have been continuously increasing. There were a lot of damages to farmland in 1960's, industrial and public facilities in 1970's, and a lot of sufferings from the windstorm in 1980's. In 1990's, however, the amount of damages was increased substantially. So, there is need to decrease the number of the victims and loss of properties by applying preventive measures against natural calamities. This study has employed a simulation system to calculate the depth and amounts of inundation areas to forecast and prevent from flood damage by using rainfall-runoff model. In this study, a case study method is adopted to show inundation by using rainfall-runoff model, HEC-GeoRAS and Arcview. It is hoped that, this study would be conducive to professionals and organizations working in the field of disaster management.
Journal of the Korea Academia-Industrial cooperation Society
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v.20
no.2
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pp.412-424
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2019
In this study, the changes of the streamflow characteristics of the watershed were analysed depending on the infiltration methods of CAT. The study area, Boryeong-dam watershed located in Chungcheongnam-do area, has been suffered from severe drought in recent years and stabilized regarding on the storage rate through efforts such as constructing a channel connecting the upstream of Boryeong-dam from the downstream of the Geum river. In this study, the effects of soil infiltration parameters on the watershed streamflow characteristics were analyzed by the infiltration methods of CAT such as Rainfall Excess, Green&Ampt and Horton. And the parameter calibrations were conducted by SCEUA-P, a global optimization technique module of the PEST, the package for parameter optimization and uncertainty analysis, to compare the yearly variations of soil parameters for infiltration methods of CAT. In addition, the streamflow characteristics were analyzed for three infiltration methods by applying three different scenarios, such as applying calibrated parameters for every years to simulate the model for each years, applying calibrated parameters for the entire period to simulate the model for entire period, and applying the average value of yearly calibrated parameters to simulate the model for entire period.
It analyzed the efficiency of the runoff reduction of artificial reservoir by analyzing the influent and effluent of reservoir located downstream of the livestock area. Production of non point pollutants in livestock feeding areas, which is located at steep slope land, was mainly due to first flushes. Suspended Solid concentration of influent increased due to amount of rainfall, and T-P also increased over four times and 30 % of total nitrogen increased on average compared to those of dry season. While the concentration of nitrate nitrogen showed little variation, ammonia nitrogen increased over two times. The storage style nonpoint reduction facility showed the highest removal efficiency of 53 % for total phosphorus in dry weather, when the removal efficiency was 37 % for suspended solids, 10% for organic compounds, and 5 % for total nitrogen. Since algal bloom grows due to eutrophication in summer, the minus removal efficiencies of nitrogen concentration through the reservoir occurred with high frequency. Removal efficiency decreased during rainfall, showing 60 % for supended solids, and 22 % for total phosphorus. While having over nine times of capacity than the standard of non-point removal facility from Ministry of Environment, it was impounded with water during rainy season, showing not enough nonpoint removal efficiency, which indicates that maintenance is also an important factor to the nonpoint removal efficiency.
Due to urbanization and increase in impervious area, changes in natural water circulation system have become a cause of groundwater recharge reduction, streamflow depletion and other hydrological problems. Therefore, this study developed the infiltration planter techniques applied in an LID facility treating roof stormwater runoff such as, performance of small decentralized retention and infiltration through the reproduction of natural water circulation system and use of landscape for cleaning water. Assessment of an infiltration planter was performed through rainfall monitoring to analyze the water balance and pollutant removal efficiency. Hydrologic assessment of an infiltration planter, showed a delay in time of effluent for roof runoff for about 3 hours and on average, 79% of facilities had a runoff reduction through retention and infiltration. Based on the analysis, pollutant removal efficiency generated in the catchment area showed an average of 97% for the particulate matter, 94% for the organic matter and 86-96% and 92-93% for the nutrients and heavy metals were treated, respectively. Comparative results with other LID facilities were made. For this study, facilities compared the SA/CA to high pollutant removal efficiency for the determination to of the effectiveness of the facility when applied in an urban area.
Choi, Gi Jun;Jung, Jeong Sung;Choi, Ki Choon;Hwang, Tae Young;Kim, Ji Hye;Kim, Won Ho;Lee, Eun Ja;Sung, Kyung Il;Lee, Ki-Won
Journal of The Korean Society of Grassland and Forage Science
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v.40
no.2
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pp.87-97
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2020
This experiment was carried out to study the effects of different environmental conditions and cultivation techniques on productivity of grasslands in central and southern area of Korea on 2017 and 2018. Average dry matter yield of grasslands at 10 actual production sites was 7,496 kg/ha. that was ranged from 4,652 to 13,292 kg/ha with least significant difference(LSD) of 1,577kg/ha between grasslands (p<0.05) on 2017. Average dry matter yield of grasslands at 10 actual production sites was 7,914 kg/ha. that was ranged from 3,927 to 12,372 kg/ha with LSD of 1,577kg/ha between grasslands(p<0.05) on 2018. Dry matter(DM) yield of grasslands have positive correlation with soil fertility (p<0.01) but not correlated with rainfall and air temperature among cultivation environments. And also DM yield of grasslands have positive correlation with grassland management techniques(p<0.01). These results suggest that practices of grassland management techniques and improvement of soil fertility are more important than cultivation environments by climate change for increasing the DM yield of grassland in central and southern area of Korea.
Field measured sediment yield from an experimental urbanized basin was compared with the predicted sediment yields with RUSLE (Revised Universal Soil Loss Equation), and MUSLE (Modified Universal Soil Loss Equation). The experimental basin is 3.1km2 in area and fifty six percent of the total area had been urbanized. The hydrological data have been measured with T/M at the outlet of the experimental basin. Runoff from the basin and rainfall depth of the basin were measured every minute. Bed load and suspended load were also measured for a given flow rate. Runoff rating curves and sediment rating curve were developed for the last three years. RUSLE showed scattered prediction results but the average of the prediction values was close to the measured one. Meanwhile, MUSLE showed linear correlation between the measured sediment yield and predicted one with high correlation coefficient. But MUSLE predicts high values than the real one. Therefore, adjustment is necessary to apply MUSLE in estimation of sediment yield from the experimental urbanized basin.
This study was conducted to analyze the runoff characteristics of the highway depending on the number of vehicles and to provide the installation proposal of an NPS pollution reduction facility. There were a total of 5 monitoring sites used for the study namely, Gyeongbu, Seohaean, Honam and Tongyeoung Dageon highway. Monitoring events started from 2006 until 2015 having a total of 44 storm events. According to monitoring statistics, the average antecedent dry days (ADD) and rainfall was 6.2 days and 19.2 mm, respectively. The Gyeongbu Highway (H-4) was recorded having the highest Average Daily Traffic and Catchment Area (ADT/CA) with $49.4car/day{\cdot}m^2$ while other site were less than $10car/day{\cdot}m^2$. The average concentration of the NPS pollutants generated from monitoring sites were 63.5 mg/L(TSS), 24.9 mg/L(BOD), 3.35 mg/L(TN), 0.63 mg/L(TP) and 298 ug/L(Total Zn). This exhibited lower values in comparison to the remarks of highway related runoff EMC values published in Korea. Moreover, through the results of the correlation analysis between the contaminant concentration and ADT/CA, $R^2$ value of SS showed the highest correlation with 585. Through the correlation equation between ADT/CA and EMC of TSS, when there is 73.7 mg/L of TSS EMC found from a domestic highway, ADT/CA ratio is normally $13car/day{\cdot}m^2$. Therefore, in a case of more than 13 cars passing through a certain area, the area can be considered and present as the point of generation of nonpoint source pollutants. Also, in this study, since it considered a unit area ADT indicated in previous studies, it was determined that it has a high applicability and utilization in generalized units than conventional study which were conventionally done.
KSCE Journal of Civil and Environmental Engineering Research
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v.40
no.3
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pp.273-283
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2020
Because of climate change, the occurrence of localized and heavy rainfall is increasing. It is important to predict floods in urban areas that have suffered inundation in the past. For flood prediction, not only numerical analysis models but also machine learning-based models can be applied. The LSTM (Long Short-Term Memory) neural network used in this study is appropriate for sequence data, but it demands a lot of data. However, rainfall that causes flooding does not appear every year in a single urban basin, meaning it is difficult to collect enough data for deep learning. Therefore, in addition to the rainfall observed in the study area, the observed rainfall in another urban basin was applied in the predictive model. The LSTM neural network was used for predicting the total overflow, and the result of the SWMM (Storm Water Management Model) was applied as target data. The prediction of the inundation map was performed by using logistic regression; the independent variable was the total overflow and the dependent variable was the presence or absence of flooding in each grid. The dependent variable of logistic regression was collected through the simulation results of a two-dimensional flood model. The input data of the two-dimensional flood model were the overflow at each manhole calculated by the SWMM. According to the LSTM neural network parameters, the prediction results of total overflow were compared. Four predictive models were used in this study depending on the parameter of the LSTM. The average RMSE (Root Mean Square Error) for verification and testing was 1.4279 ㎥/s, 1.0079 ㎥/s for the four LSTM models. The minimum RMSE of the verification and testing was calculated as 1.1655 ㎥/s and 0.8797 ㎥/s. It was confirmed that the total overflow can be predicted similarly to the SWMM simulation results. The prediction of inundation extent was performed by linking the logistic regression with the results of the LSTM neural network, and the maximum area fitness was 97.33 % when more than 0.5 m depth was considered. The methodology presented in this study would be helpful in improving urban flood response based on deep learning methodology.
Jun, Sang Min;Song, Jung-Hun;Choi, Soon-Kun;Lee, Kyung-Do;Kang, Moon Seong
Journal of The Korean Society of Agricultural Engineers
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v.60
no.5
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pp.135-147
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2018
The objective of this study was to analyze the characteristics of combined 1D/2D inundation simulation of riverside farmland using the Hydrologic Engineering Center - River Analysis System (HEC-RAS). We compared and analyzed inundation simulation results between 1D and combined 1D/2D hydraulic simulation using HEC-RAS. Calibration and validation of stream stage were performed using three rainfall events. The coefficient of determination ($R^2$) and root mean square error (RMSE) between simulated and observed stream stage were 0.935 - 0.957 and 0.250 m - 0.283 m in calibration and validation, respectively. The inundation area showed no significant difference in 1D and combined 1D/2D simulation ($8.48km^2$ in 1D simulation, $8.75km^2$ in combined 1D/2D simulation). The average inundation depth by 1D simulation was 1.4 m deeper than combined 1D/2D simulation. In the lower inundation depth, the inundation area by combined 1D/2D simulation was larger than inundation area by 1D simulation. As the inundation depth increased, the inundation area by 1D simulation became wider. In the case of the 1D/2D combined simulation, low elevation areas along the river bank were inundated widely. Compared to 1D/2D combined simulation, the flood radius in some sections was longer in 1D simulation. In the 1D analysis, because the low altitude riverside farmlands are also assumed to stream, it is calculated that riverside farmlands have the same stage as the mainstream when the stream is overflowed. Therefore, the inundation area seems to be overestimated in those sections. In other regions, the inundation areas tend to be broken depending on overflow by each stream cross-section. In the case of river flooding, the overflow is expected to flow to the lower area depending on the terrain, such as the results of the combined 1D/2D simulation. It is concluded that the results of combined 1D/2D inundation simulation reflected the topographical characteristics of low-lying farmland.
In korea, debris-flow disasters are induced by typhoon and localized torrential rainfall annually. These disasters are particularly severe in the Korean national park due to its geomorphological characteristics. This study was conducted to analyze the landslide characteristics and forest environmental factors of landslide areas located in rugged mountain range in the Korean national park (Mt. Seorak, Mt. Jiri, and Mt. Sobaek). Overall, landslides occurred at 474 sites. The average area of the landslide scar among these sites was 1,212 ㎡. The average landslide sediment was 1,389 ㎥, average landslide length was 75 m, and the average width was 12.9 m. The landslides frequently occurred in regions with igneous rock and coniferous forest. In addition, slope gradient degree (31°-40°), slope gradient direction (N), vertical slope (concave), cross slope (concave), altitude (401-800 m), position (middle), stream order (first order), forest type (mixed), parent rock (igneous), and soil depth (<46 cm). The relationship between landslide soil volume and environmental factors showed positive correlation. The variables of vertical slope (complex), altitude (<1,201 m), and soil depth (<46 cm) correlated significantly at 1 % level.
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