Ha, Don-Woo;Park, Seung-Ho;Joo, Sungmin;Lee, Gi-Soon;Baek, Jong-Hun;Jung, Kang-Young;Lee, Youngjea;Kim, Kyunghyun;Kim, Young-Suk
Journal of the Korean Society for Environmental Technology
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v.19
no.6
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pp.503-513
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2018
In order to continuous watershed management and improve water quality at Yeong-san river system, we analyzed and evaluated data on the monitoring of small stream in city and county boundaries within the watershed. In-period monitoring is estimated to be more frequent in the second quarter than the first quarter, so it should be considered when evaluating the target water quality by setting the target water quality. A small stream in the Yeong-san river system has higher concentration in the downstream area than the upstream area. As a result of calculating the load of the measuring point, Y.b B3(Pungyeongjeongcheon) and Y.b E1(Sampocheon) were high. The result of correlation analysis by monitoring point in order to evaluate the correlation between BOD and T-P items, BOD was highly correlated with COD and TOC, and was affected by emission of pollutants related to organic matter. T-P was highly correlated with SS and COD, and was affected by rainfall. This study will provide basic data and direction for designing efficient and scientific method for water quality management by analyzing accumulated water quality data by conducting long-term monitoring.
KSCE Journal of Civil and Environmental Engineering Research
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v.39
no.6
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pp.713-723
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2019
Due to the climate change and various rainfall pattern, it is difficult to estimate a rainfall criterion which cause inundation for urban drainage districts. It is necessary to examine the result of inundation analysis by considering the detailed topography of the watershed, drainage system, and various rainfall scenarios. In this study, various rainfall scenarios were considered with the probabilistic rainfall and Huff's time distribution method in order to identify the rainfall characteristics affecting the inundation of the Hyoja drainage basin. Flood analysis was performed with SWMM and two-dimensional inundation analysis model and the parameters of SWMM were optimized with flood trace map and GA (Genetic Algorithm). By linking SWMM and two-dimensional flood analysis model, the fitness ratio between the existing flood trace and simulated inundation map turned out to be 73.6 %. The occurrence of inundation according to each rainfall scenario was identified, and the rainfall criterion could be estimated through the logistic regression method. By reflecting the results of one/two dimensional flood analysis, and AWS/ASOS data during 2010~2018, the rainfall criteria for inundation occurrence were estimated as 72.04 mm, 146.83 mm, 203.06 mm in 1, 2 and 3 hr of rainfall duration repectively. The rainfall criterion could be re-estimated through input of continuously observed rainfall data. The methodology presented in this study is expected to provide a quantitative rainfall criterion for urban drainage area, and the basic data for flood warning and evacuation plan.
Recently, runoff characteristics of urban area are changing because of the increase of impervious area by rapidly increasing of population and industrialization, urbanization. It needs to extract the accurate topologic and hydrologic parameters of watershed in order to manage water resource efficiently. Thus, this study developed more precise input data and more improved parameter estimating procedures using GIS(Geographic Information System) and GA(Genetic Algorithm). For these purposes, XP-SWMM (EXPert-Storm Water Management Model) was used to simulate the urban runoff. The model was applied to An-Yang stream basin that is a typical Korean urban stream basin with several tributaries. The rules for parameter estimation were composed and applied based on quantity parameters that are investigated through the sensitivity analysis. GA algorithm is composed of these rules and facts. The conditions of urban flows are simulated using the rainfall-runoff data of the study area. The data of area, slope, width of each subcatchment and length, slope of each stream reach were acquired from topographic maps, and imperviousness rate, land use types, infiltration capacities of each subcatchment from land use maps, soil maps using GIS. Also we gave the management scheme of urbanization runoff using XP-SWMM. The parameters are estimated by GA from sensitivity analysis which is performed to analyze the runoff parameters.
With groundwater data of seawater intrusion monitoring network in coastal areas of Korea's main land, we analyzed types of seawater intrusion through the coastal aquifer. The data including groundwater level, temperature and electrical conductivity obtained from 45 monitoring wells at 25 watershed regions were evaluated. Based on statistical analysis, correlation analysis and variation type analysis, groundwater levels were mainly affected by rainfall and artificial pumping. About 78% of the monitoring wells showed average temperature higher than $15^{\circ}C$ and about 58% of them showed minimum variations less than $0.2^{\circ}C$. Electrical conductivities showed a large magnitude of variation and irregular characteristics compared with groundwater levels and temperatures. Average electrical conductivities lower than $2,000\;{\mu}S/cm$ were observed at 28 monitoring wells while those of higher than $10,000\;{\mu}S/cm$ were done at 9 monitoring wells. From the cross-correlation analysis, groundwater levels were mostly affected by precipitation while temperature and electrical conductivity showed very low correlation. Meanwhile tidal variations strongly affected the groundwater levels comparing to precipitation. We classified the long-term monitoring data according to variation types such as constant process, linear trend, cyclic variation, impulse, step function and ramp. Impulse type was dominant for variations of groundwater level, which was largely affected by rainfall or artificial pumping, the constant process was dominant for temperature. Compared with groundwater level and temperature, electrical conductivities showed various types like linear trend, step function and ramp. According to the discrepancy of variation characteristics for monitoring data at each well in the same region, periodical analysis of monitoring data is essentially required.
The objective of this study is to understand the status of the water pollution in rural areas and to furnish a basic material for the management of the water pollution in rural areas. For this purpose, the Bokha river basin, Ichon-Gun, Kyungki-Do considering as a typical agricultural area was selected as a representative experimental watershed. The characteristics of water pollution in streams of the Bokha river basin was revealed by investigating and analyzing data collected for the source of pollution, water qualities in reaches of the stream, the degree of contribution to the river contamination by pollution mass produced from each source, and the status of the self-purification at the main stream. The most important source of the water pollution in investigated watershed was livestock, and the next important one were in the order of population, land use, and industry. The water quality of the Bokha river was relatively favorable judging from the BOD and COD concentration, however since the concentration of T-N and T-P showed significantly large values, it was concluded that the river was seriously contaminated by the nutrient material. The main cause of the river contamination was proved due to livestock waste. For the T-N, both land use and livestock were much more contributied to the pollution than any other source, which characterized the typical water pollution of rural areas. Run-off ratios for the Bokha river tributaries to the main stream were changed according to the similar trend to the variation of discharges in the branch streams. For the value of the self-purification constant at the main stream, it showed smaller value in the downstream reach than the middle-stream and upstream reaches, where could possibly have smaller reoxidation action due to slower velocity and deeper water depth.
Kim, Min Ji;Park, Kyung Woon;Kim, Seok-Woo;Kim, Tae-Woong
Journal of Korea Water Resources Association
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v.55
no.10
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pp.737-748
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2022
Due to the lack of flood data, the water engineering practice calculates the design flood using rainfall frequency analysis and rainfall-runoff model. However, the rainfall frequency analysis for arbitrary duration does not reflect the regional characteristics of the duration and amount of storm event. This study proposed a practical method to calculate the design flood in a watershed considering the characteristics of storm event, based on the bivariate rainfall frequency analysis. After extracting independent storm events for the Pyeongchang River basin and the upper Namhangang River basin, we performed the bivariate rainfall frequency analysis to determine the design storm events of various return periods, and calculated the design floods using the HEC-1 model. We compared the design floods based on the bivariate rainfall frequency analysis (DF_BRFA) with those estimated by the flood frequency analysis (DF_FFA), and those estimated by the HEC-1 with the univariate rainfall frequency analysis (DF_URFA). In the case of the Pyeongchang River basin, except for the 100-year flood, the average error of the DF_BRFA was 11.6%, which was the closest to the DF_FFA. In the case of the Namhangang River basin, the average error of the DF_BRFA was about 10%, which was the most similar to the DF_FFA. As the return period increased, the DF_URFA was calculated to be much larger than the DF_FFA, whereas the BRFA produced smaller average error in the design flood than the URFA. When the proposed method is used to calculate design flood in an ungauged watershed, it is expected that the estimated design flood might be close to the actual DF_FFA. Thus, the design of the hydrological structures and water resource plans can be carried out economically and reasonably.
Climate change brought on by global warming increased the frequency of flood and drought on the Korean Peninsula, along with the casualties and physical damage resulting therefrom. Preparation and response to these water disasters requires national-level planning for water resource management. In addition, watershed-level management of water resources requires flow duration curves (FDC) derived from continuous data based on long-term observations. Traditionally, in water resource studies, physical rainfall-runoff models are widely used to generate duration curves. However, a number of recent studies explored the use of data-based deep learning techniques for runoff prediction. Physical models produce hydraulically and hydrologically reliable results. However, these models require a high level of understanding and may also take longer to operate. On the other hand, data-based deep-learning techniques offer the benefit if less input data requirement and shorter operation time. However, the relationship between input and output data is processed in a black box, making it impossible to consider hydraulic and hydrological characteristics. This study chose one from each category. For the physical model, this study calculated long-term data without missing data using parameter calibration of the Soil Water Assessment Tool (SWAT), a physical model tested for its applicability in Korea and other countries. The data was used as training data for the Long Short-Term Memory (LSTM) data-based deep learning technique. An anlysis of the time-series data fond that, during the calibration period (2017-18), the Nash-Sutcliffe Efficiency (NSE) and the determinanation coefficient for fit comparison were high at 0.04 and 0.03, respectively, indicating that the SWAT results are superior to the LSTM results. In addition, the annual time-series data from the models were sorted in the descending order, and the resulting flow duration curves were compared with the duration curves based on the observed flow, and the NSE for the SWAT and the LSTM models were 0.95 and 0.91, respectively, and the determination coefficients were 0.96 and 0.92, respectively. The findings indicate that both models yield good performance. Even though the LSTM requires improved simulation accuracy in the low flow sections, the LSTM appears to be widely applicable to calculating flow duration curves for large basins that require longer time for model development and operation due to vast data input, and non-measured basins with insufficient input data.
The purpose of this study was to quantitatively analyze and investigate changes in the structural characteristics of the warm-temperate evergreen broad-leaved forest community in Mt. Cheomchalsan on Jindo Island. The Mt. Cheomchalsan has high conservation value because the representative warm temperate species such as Quercus acuta and Castanopsis sieboldii are distributed there. The community classification with TWINSPAN and DCA identified 4 communities: C. sieboldii community (I), C. sieboldii-Q. Salicina community (II), Q. acuta-C.sieboldii community (III), and deciduous broad-leaved trees-evergreen broad-leaved trees community (IV). According to the results of the mean importance percentage (MIP) analysis, C. sieboldii, Q. salicina, and Q. acuta were dominant species in the canopy layer, Camellia japonica, Ligustrum japonicum, and Cinnamomum yabunikkei were dominant in the understory layer, and Trachelospermum asiaticum, C. japonica, and C. sieboldii were dominant in the shrub layer. The comparison of the results of the diameter of breast height (DBH) analysis with the past data showed that the ratio of large-sized trees in the C. sieboldii and Q. acuta, which dominated the canopy layer, increased. However, there was no difference in the distribution of C. japonica and L. japonicum in the understory layer. In the future, it is necessary to generate a precision inhabiting vegetation map around the Natural Reserve to understand the actual habitation of evergreen broad-leaved trees and rezone the protective districts of evergreen broad-leaved trees forest with the watershed concept to preserve the evergreen broad-leaved forests of Mt. Cheomchalsan in Jindo.
Kim, Jin-Guk;Kim, Jin-Young;Ban, Woo-Sik;Kwon, Hyun-Han
Journal of Korea Water Resources Association
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v.52
no.12
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pp.985-999
/
2019
Over the last decade, droughts have become more severe and frequent in many regions, and several studies have been conducted to explore the recent drought. Copula-based bivariate drought frequency analysis has been widely used to evaluate drought risk in the context of point frequency analysis. However, the relatively significant uncertainties in the parameters are problematic when available data are limited. For this reason, the primary purpose of this study is to develop a regional drought frequency model based on the Copula function. All parameters, including marginal and copula functions in the regional frequency model, were estimated simultaneously. Here, we present a case study of recent drought 2013-2015 over the Han-River watershed where severe drought risk is consistently found to increase. The proposed model provided a reliable way to significantly reduce the uncertainty of parameters with a Bayesian modeling framework. The uncertainty of the joint return period in the regional frequency analysis is nearly three times lower than that of the point frequency analysis. Accordingly, DIC values in the regional frequency analysis model are significantly decreased by 15. The results confirm that the proposed model is not only reliably representing characteristics of historical droughts and dependencies between drought variables, but also providing the efficacy of understanding regional drought characteristics.
Journal of the Korean Society of Hazard Mitigation
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v.10
no.4
/
pp.95-104
/
2010
The storage function model is one of the most commonly used models for flood forecasting and warning system in Korea. This paper studies the physical significance of the storage function model by comparing it with kinematic wave model. The results showed universal applicability of the storage function model to Korean basins. Through a comparison of the basic equations for the models, the storage function model parameters, K, P and $T_l$, are shown to be related with the kinematic wave model parameters, k and p. The analysis showed that P and p are identical and K and $T_l$ can be related to k, basin area, and coefficients of Hack's law. To apply the storage function model throughout the southern part of Korean peninsular, regional parameter relationships for K and $T_l$ were developed for watershed area using data from 17 watersheds and 101 flood events. These relationships combine the kinematic wave parameters with topographic information using Hack's Law.
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