• Journal of Wetlands Research
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• v.12 no.1
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• pp.51-61
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• 2010

Changes in climate have largely increased concentrated heavy rainfall, which in turn is causing enormous damages to humans and properties. Therefore, it is important to understand the spatial-temporal features of rainfall. In this study, RADAR rainfall was used to calculate gridded areal rainfall which reflects the spatial-temporal variability. In addition, Kalman-filter method, a stochastical technique, was used to combine ground rainfall network with RADAR rainfall network to calculate areal rainfall. Thiessen polygon method, Inverse distance weighting method, and Kriging method were used for calculating areal rainfall, and the calculated data was compared with adjusted areal RADAR rainfall measured using the Kalman-filter method. The result showed that RADAR rainfall adjusted with Kalman-filter method well-reproduced the distribution of raw RADAR rainfall which has a similar spatial distribution as the actual rainfall distribution. The adjusted RADAR rainfall also showed a similar rainfall volume as the volume shown in rain gauge data. Anseong-Cheon basin was used as a study area and the RADAR rainfall adjusted with Kalman-filter method was applied in $Vflo^{TM}$ model, a physical-based distributed model, and ModClark model, a semi-distributed model. As a result, $Vflo^{TM}$ model simulated peak time and peak value similar to that of observed hydrograph. ModClark model showed good results for total runoff volume. However, for verifying the parameter, $Vflo^{TM}$ model showed better reproduction of observed hydrograph than ModClark model. These results confirmed that flood runoff simulation is applicable in domestic settings(in South Korea) if highly accurate areal rainfall is calculated by combining gauge rainfall and RADAR rainfall data and the simulation is performed in link to the distributed hydrological model.

• Journal of Korean Society of Environmental Engineers
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• v.39 no.3
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• pp.140-148
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• 2017

The effectiveness of the first flush treatment system using settling process was evaluated to reduce urban nonpoint source pollutant loads to surface water during storm events. A pilot scale system was constructed and tested in the field and surface runoff samples were collected automatically according to pre-defined conditions. Nine rainfall events were tested and average removal efficiencies of TSS (Total Suspended Solid), TP (Total Phosphorus) and TN (Total Nitrogen) were evaluated as 87.4%, 75.3%, and 43.6%, respectively. Concentration and removal efficiency of pollutants were found to be affected by an amount of rainfall and rainfall intensities of the respective events. This seemed to be caused by the greater particulate fractions of first flushed samples than the samples collected in later time periods during the same rainfall events. The study showed that it is possible to remove a significant portion of the nonpoint source pollutant loads in initial rainfall runoff by using a simple settling process for TSS and TP without requiring additional power or chemicals.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.3
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• pp.127-133
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• 2009

In this study, dimensionless-cumulative rainfall curves were generated by multivariate Monte Carlo method. For generation of rainfall curve rainfall storms were divided and made into dimensionless type since it was required to remove the spatial and temporal variances as well as differences in rainfall data. The dimensionless rainfall curves were divided into 4 types, and log-ratio method was introduced to overcome the limitations that elements of dimensionless-cumulative rainfall curve should always be more than zero and the sum total should be one. Orthogonal transformation by Johnson system and the constrained non-normal multivariate Monte Carlo simulation were introduced to analyse the rainfall characteristics. The generative technique in stochastic rainfall variation using multivariate Monte Carlo method will contribute to the design and evaluation of hydrosystems and can use the establishment of the flood disaster prevention system.

• Journal of Wetlands Research
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• v.10 no.2
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• pp.105-114
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• 2008

Growth in population and urbanization has progressively increased the loadings of pollutants from non-point sources as well as point sources. Separated sewer overflows(SSO) have been considered as a major cause of water-quality deterioration of natural water-courses in the vicinity of the heavily urbanized areas. The factors defining the magnitude and occurrence of SSO are site-specific. It is important to know exact properties of pollutants contained in SSO to address water quality impacts that are caused by SSO inputs to the receiving waters. Site and event parameters found to have significant influences on urban runoff pollutant EMCs include total event rainfall, antecedent dry period, rainfall intensity. In this study, a field survey was carried out in some selected areas of Cheongju city. Literature from previous similar studies was consulted and some important factors affecting the runoff characteristics of urban drainage areas were analyzed for some selected survey points. It was found that the factors most affecting BOD are the number of dry days prior to rainfall and the intensity of the rainfall. The factor most affecting CODcr is the number of dry days prior to rainfall. The factors most affecting SS are the amount of rainfall and the number of dry days prior to rainfall. The factor most affecting TN is the amount of rainfall. The factor most affecting TP is the amount of rainfall and the number of dry days prior to rainfall.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.6
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• pp.55-69
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• 2016

RUSLE (Revised Universal Soil Loss Equation) is the empirical formular widely used to estimate rates of soil erosion caused by rainfall and associated overland flow. Among the factors considered in RUSLE, rainfall erosivity factor (R factor) is the major one derived by rainfall intensity and characteristics of rainfall event. There has been developed various methods to estimate R factor, such as energy based methods considering physical schemes of soil erosion and simple methods using the empirical relationship between soil erosion and annual total rainfall. This study is aimed to quantitatively evaluate the variation among the R factors estimated using different methods for South Korea. Station based observation (minutely rainfall data) were collected for 72 stations to investigate the characteristics of rainfall events over the country and similarity and differentness of R factors calculated by each method were compared in various ways. As results use of simple methods generally provided greater R factors comparing to those for energy based methods by 76 % on average and also overestimated the range of factors using different equations. The variation coefficient of annual R factors was calculated as 0.27 on average and the results significantly varied by the stations. Additionally the study demonstrated the rank of methods that would provide exclusive results comparing to others for each station. As it is difficult to find universal way to estimate R factors for specific regions, the efforts to validate and integrate various methods are required to improve the applicability and accuracy of soil erosion estimation.

• Journal of Environmental Science International
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• v.26 no.3
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• pp.401-410
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• 2017

This study analyzed the changes in the concentrations of organic matters in constructed treatment wetlands, coming from discharge water from a sewage treatment plant and non-point pollutant sources during rainfall events. At the beginning of a rainfall event, a massive amount of particulate organic matter flowed in, and was removed from the sedimentation basin (S1, S2); dissolved organic matter was removed after passing through stepwise treatment processes in the wetland. During dry period in the wetland, the removal efficiency rate for COD and TOC was -21 and -7%, respectively; during the rainfall event, the removal efficiency rate for COD and TOC were 47 and 43%, respectively. The highly-concentrated organic matters that flowd in at the beginning of the rainfall event was stabilized by various structures in the wetland before water discharge. Cyanobacteria blooms annually at the confluence of the So-ok stream and Daecheong Lake. Therefore, it is expected that the wetland will contribute significantly to reducing cyanobacteria and improving water quality in the area.

• Journal of Korean Society on Water Environment
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• v.31 no.4
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• pp.407-417
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• 2015

Soil loss is one of the significant disasters which have threatened human community and ecosystem. Particularly, Korea has high vulnerability of soil loss because rainfall is concentrated during summer and mountainous regions take more than 70% of total land resources. Accordingly, the sediment control management plan are required to prevent the loss of soil resources and to improve water quality in the receiving waterbodies. In this regard, the objectives of this study are 1) to quantify the effect of the Vegetative Filter Strip (VFS) on sediment runoff reduction and 2) to analyze the relationship of rainfall intensity and sediment runoff. For this, SATEEC and VFSMOD were used to estimate sediment runoff according to rainfall intensity and to quantify the effect of VFS on sediment runoff reduction, respectively. In this study, the VFS has higher impact on sediment reduction for lower maximum rainfall intensity, which means that the maximum rainfall intensity is one of significant factors to control sediment runoff. Also, the sediment with VFS considered was highly correlated with maximum rainfall intensity. For these results, this study will contribute to extend the applicability of VFS in establishing eco-friendly sediment control plans.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.150-150
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• 2022

This study investigates the roles of decomposition methods on high accuracy in daily rainfall prediction from light gradient boosting machine (LightGBM) algorithm. Here, empirical mode decomposition (EMD) and singular spectrum analysis (SSA) methods were considered to decompose and reconstruct input time series into trend terms, fluctuating terms, and noise components. The decomposed time series from EMD and SSA methods were used as input data for LightGBM algorithm in two hybrid models, including empirical mode-based light gradient boosting machine (EMDGBM) and singular spectrum analysis-based light gradient boosting machine (SSAGBM), respectively. A total of four parameters (i.e., temperature, humidity, wind speed, and rainfall) at a daily scale from 2003 to 2017 is used as input data for daily rainfall prediction. As results from statistical performance indicators, it indicates that the SSAGBM model shows a better performance than the EMDGBM model and the original LightGBM algorithm with no decomposition methods. It represents that the accuracy of LightGBM algorithm in rainfall prediction was improved with the SSA method when using multivariate dataset.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.2
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• pp.45-57
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• 2003

An artificial neural network model was developed to analyze and forecast Short-term river runoff from the Naju watershed, in Korea. Error back propagation neural networks (EBPN) of hourly rainfall and runoff data were found to have a high performance In forecasting runoff. The number of hidden nodes were optimized using total error and Bayesian information criterion. Model forecasts are very accurate (i.e., relative error is less than 3% and $R^2$is greater than 0.99) for calibration and verification data sets. Increasing the time horizon for application data sets, thus mating the model suitable for flood forecasting. decreases the accuracy of the model. The resulting optimal EBPN models for forecasting hourly runoff consists of ten rainfall and four runoff data(ANN0410 model) and ten rainfall and ten runoff data(ANN1010 model). Performances of the ANN0410 and ANN1010 models remain satisfactory up to 6 hours (i.e., $R^2$is greater than 0.92).

• Journal of Korea Water Resources Association
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• v.48 no.6
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• pp.451-461
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• 2015

This study aimed to estimate the future design rainfall through a non-stationary frequency analysis using the rainfall separation technique. First, we classified rainfall in the Korean Peninsula into local downpour and TC-induced rainfall through rainfall separation technique based on the path and size of a typhoon. Furthermore, we performed the analysis of regional rainfall characteristics and trends. In addition, we estimated the future design rainfall through a non-stationary frequency analysis using Gumbel distribution and carried out its quantitative comparison and evaluation. The results of the analysis suggest that the increase and decrease rate of rainfall in the Korean Peninsula were different and the increasing and decreasing tendencies were mutually contradictory at some points. In addition, a non-stationary frequency analysis was carried out by using the rainfall separation technique. The outcome of this analysis suggests that a relatively reasonable future design rainfall can be estimated. Comparing total rainfall with the future design rainfall, differences were found in the southern and eastern regions of the Korean peninsula. This means that climate change may have a different effect on the typhoon and local downpour. Thus, in the future, individual assessment of climate change impacts needs to be done through moisture separation. The results presented here are applicable in future hydraulic structures design, flood control measures related to climate change, and policy establishment.