• Journal of the Korean Society of Industry Convergence
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• v.2 no.2
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• pp.51-59
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• 1999

This study aims at the development of the techniques for the rainfall forecasting in river basins by applying neural network theory and compared with results of Multivariate Model (MVM). This study forecasts rainfall and compares with a observed values in the San Chung gauging stations of Nakdong river basin for the rainfall forecasting of river basin by proposed Neural Network Model(NNM). For it, a multi-layer Neural Network is constructed to forecast rainfall. The neural network learns continuous-valued input and output data. The result of rainfall forecasting by the Neural Network Model is superior to the results of Multivariate Model for rainfall forecasting in the river basin. So I think that the Neural Network Model is able to be much more reliable in the rainfall forecasting.

• Journal of Soil and Groundwater Environment
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• v.26 no.6
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• pp.118-129
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• 2021

The sediment transportation caused by soil erosion due to rainfall-discharge in the large watershed scale plays critical role in human society. The relationship between rainfall-discharge-sediment transportation is depending on the start time of rainfall and end of rainfall but, the studies related with rainfall characteristics are insufficient. In this study, The Soil and Water Assession Tool (SWAT) model was used to study the relationship between rainfall-discharge-sediment transportation at the Sook river watershed which is monitored by the Ministry of Environment. To do this, first of all, the sensitivity analysis about model attributes was performed using monitored data. The accuracy analysis of SWAT model was conducted using the model's efficiency index (Nash and Sutcliffe model efficiency; NSE) and the coefficient of determination (R²). After that, it was studied what results could be obtained according to changes in rainfall timing and end points. In the result of discharge simulation, the modified rainfall values (sum of total rainfall starting time and end time) showed more high accuracy values (R²:0.90, NSE: 0.8) than original rainfall values (R²:0.76, NSE: 0.72). In the result of sediment transportation simulation, during calibration had more resonable results(R²:0.87, NSE: 0.86) than compared with original rainfall values (R²:0.44, NSE: 0.41). However, validation results of sediment transportation simulation showed low accuracy values compared with calibration results. This results maybe cause monitoring periods of sediment flow compared with discharge monitoring periods. Nevertheless, since rainfall characteristic plays critical rule in model results, continuous research on rainfall characteristic is needed.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.152-152
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• 2022

Only employing historical data limits the estimation of the full distribution of probable Tropical Cyclone (TC) risk due to the insufficiency of samples. Addressing this limitation, this study introduces a semi-physical TC rainfall model that produces spatially and temporally resolved TC rainfall data to improve TC risk assessments. The model combines a statistical-based track model based on the Markov renewal process to produce synthetic TC tracks, with a physics-based model that considers the interaction between TC and the atmospheric environment to estimate TC rainfall. The simulated data from the combined model are then fitted to a probability distribution function to compute the spatially heterogeneous risk brought by landfalling TCs. The methodology is employed in South Korea as a case study to be able to implement a country-scale-based vulnerability inspection from damaging TC impacts. Results show that the proposed model can produce TC tracks that do not only follow the spatial distribution of past TCs but also reveal new paths that could be utilized to consider events outside of what has been historically observed. The model is also found to be suitable for properly estimating the total rainfall induced by landfalling TCs across various points of interest within the study area. The simulated TC rainfall data enable us to reliably estimate extreme rainfall from higher return periods that are often overlooked when only the historical data is employed. In addition, the model can properly describe the distribution of rainfall extremes that show a heterogeneous pattern throughout the study area and that vary per return period. Overall, results show that the proposed approach can be a valuable tool in providing sufficient TC rainfall samples that could be an aid in improving TC risk assessment.

• 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.

• Atmosphere
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• v.26 no.1
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• pp.141-158
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• 2016

The objective of this study is to examine the impact of urban canopy and the horizontal resolution on simulated meteorological variables such as 10-m wind speed, 2-m temperature and precipitation using WRF model for a local, convective rainfall case. We performed four sensitivity tests by varying the use of urban canopy model (UCM) and the horizontal resolution, then compared the model results with observations of AWS network. The focus of our study is over the Seoul metropolitan area for a convective rainfall that occurred on 16 August 16 2015. The analysis shows that mean diurnal variation of temperature is better simulated by the model runs with UCM before the convective rainfall. However, after rainfall, model shows significant difference in air temperature among sensitivity tests depending on the simulated rainfall amount. The rainfall amount is significantly underestimated in 0.5 km resolution model run compared to 1.5 km resolution, particularly over the urban areas. This is due to earlier occurrence of light rainfall in 0.5 km resolution model. Earlier light rainfall in the afternoon eliminates convective instability significantly, which prevents occurrence of rainfall later in the evening. The use of UCM results in a higher maximum rainfall in the domain, which is due to higher temperature in model runs with urban canopy. Earlier occurrence of rainfall in 0.5 km resolution model is related to rapid growth of PBL. Enhanced mixing and higher temperature result in rapid growth of PBL, which provides more favorable conditions for convection in the 0.5 km resolution run with urban canopy. All sensitivity tests show dry bias, which also contributes to the occurrence of light precipitation throughout the simulation period.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.2
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• pp.63-74
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• 2019

The objective of this study was to evaluate the influence of rainfall observation network on daily dam inflow using artificial neural networks(ANNs). Chungju Dam and Soyangriver Dam were selected for the study watershed. Rainfall and dam inflow data were collected as input data for construction of ANNs models. Five ANNs models, represented by Model 1 (In watershed, point rainfall), Model 2 (All in the Thiessen network, point rainfall), Model 3 (Out of watershed in the Thiessen network, point rainfall), Model 1-T (In watershed, area mean rainfall), Model 2-T (All in the Thiessen network, area mean rainfall), were adopted to evaluate the influence of rainfall observation network. As a result of the study, the models that used all station in the Thiessen network performed better than the models that used station only in the watershed or out of the watershed. The models that used point rainfall data performed better than the models that used area mean rainfall. Model 2 achieved the highest level of performance. The model performance for the ANNs model 2 in Chungju dam resulted in the $R^2$ value of 0.94, NSE of 0.94 $NSE_{ln}$ of 0.88 and PBIAS of -0.04 respectively. The model-2 predictions of Soyangriver Dam with the $R^2$ and NSE values greater than 0.94 were reasonably well agreed with the observations. The results of this study are expected to be used as a reference for rainfall data utilization in forecasting dam inflow using artificial neural networks.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.976-976
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• 2012

The applicability of a distributed rainfall-runoff model for large river basin flood forecasts is analyzed by applying the model to the Nakdong River basin. The spatially explicit hydrologic model was constructed and calibrated by the several storm events. The assimilation of the large scale Nakdong River basin were conducted by calibrating the sub-basin channel outflow, dam discharge in the basin rainfall-runoff model. The applicability of automatic and semi-automatic calibration methods was analyzed for real time calibrations. Further an ensemble distributed rainfall runoff model has been developed to measure the runoff hydrograph generated for any temporally-spatially varied rainfall events, also the runoff of basin can be forecast at any location as well. The results of distributed rainfall-runoff model are very useful for flood managements on the large scale basins. That offer facile, realistic management method for the avoiding the potential flooding impacts and provide a reference for the construct and developing of flood control facilities.

• Journal of Korean Society of Water and Wastewater
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• v.36 no.4
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• pp.229-237
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• 2022

The sewer capacity design have been based on the Huff model or the rational equation in South Korea and often failed to determine optimal capacity, resulting in frequent urban flooding or over-sizing. A time distribution of rainfall (i.e., Huff or ABM method) could be used instead of a rainfall hyetograph obtained from statistical analysis of previous rainfalls. In this study, the Huff method and the ABM method, which predict the time distribution of rain intensity, which are widely used to calculate sewage pipe drainage capacity using the SWMM, were compared with the standard rainfall intensity hyetograph of Seoul. If the rainfall duration was 30 minutes to 180 minutes, the rainfall intensity value calculated by the Huff model tended to be less than the rainfall intensity value of the standard rainfall intensity in the initial 5-10 minutes. As a result, more than 10% to 30% of under-design would be made. In addition, the rainfall intensity value calculated by the Huff model from the section excluding the initial 5-10 minutes of rainfall to the rainfall duration was calculated larger than the value using the standard rainfall intensity equation, which would result in an over-design of 10% to 30%. In the case of a relatively long rainfall duration of 360 minutes (6 hours) to 1,440 minutes (24 hours), it showed an lower rainfall intensity of 60 to 90% in the early stages of rainfall, but the problem of under-design had been solved as the rainfall duration time had elapsed. On the other hand, in the alternating block method (ABM) method, it was found that the rainfall intensity at the entire period at each assumed rainfall duration accurately matched the standard rainfall intensity hyetograph of Seoul.

• Magazine of the Korean Society of Agricultural Engineers
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• v.24 no.1
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• pp.63-72
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• 1982

To maintain an optimum condition for the plant growth on upland soil, the irrigation planning after the natural rainfall should be given enormous considerations on the rainfall effectiveness. This study has been intended to develop the computer model for estimating the effec- tiveness of the rainfall. The computer model should also estimated the infiltration due to the rainfall and the soil moisture deficiency at the root zone of the plant. For this purpose, the experiments of infiltration using rainfall simulator and the observations of the change of soil moisture content before and after rainfall were carried out. Needed input data for the developed model include final infiltration capacity and field capacity of the soil, porosity of the top soil, root depth of the plant, rainfall intensity and duration, and the Horton's decay coefficient. Among the needed input data for the developed model, final infiltration capacity and Horton's decay coefficient were determined by the experiments of infiltration. And from the result of the experiments, it is found that there is a great correlation between initial infiltration capacity and initial moisture content. And it is also found that the infiltration due to rainfall can be estimated with the Horton's equation. The developed model was tested by the experimental data with two rainfall intensities. Tests were conducted on the different root depths at each rainfall. Observed and estimated effective rainfalls were found to have great correlation. The result of the experiments showed that the effectiveness of the rainfall were 100%, so the comparisons were conducted by the comsumption rates of infiltration at each depth. The developed model can be also used for estimating the deficiency of rainfall, if the rainfall is not sufficient to the needed soil moisture. But, test was not carried out.

• Journal of Korea Water Resources Association
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• v.43 no.6
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• pp.533-541
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• 2010

It is basic for a flood prediction to calculate direct runoff from rainfall in a basin by the rainfall-runoff model. The direct runoff is calculated from rainfall excess or effective rainfall based on a rainfall-runoff model. The total rainfall minus rainfall loss equals rainfall excess with time. This loss can be treated equal to an infiltration loss under the assumption that the infiltration is a major one among the losses in the rainfall-runoff model. Practically obtaining the infiltration loss $\Phi$ index method, W index method or modified ones of these have been used. In this study it is assumed the loss of rainfall in a basin be a well-known Horton infiltration mechanism. And in case that the parameter set is given in the Horton infiltration model a procedure and assumption for calculating hourly infiltration loss and rainfall excess are offered and the results of its application are compared with those of $\Phi$ index method. By this study it is well shown the value of Horton infiltration function is exponentially decay with time as the Horton infiltration mechanism.