• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.180-180
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• 2015

Weather radar has been widely used in measuring precipitation and discharge and predicting flood risks. The radar rainfall estimate has one of the essential problems in terms of uncertainty and accuracy. Previous study analyzed radar errors to reduce its uncertainty or to improve its accuracy. Furthermore, a recent analyzed the effect of radar error on rainfall-runoff using spatial error model (SEM). SEM appropriately reproduced radar error including spatial correlation. Since the SEM does not take the time dependence into account, its time variability was not properly investigated. Therefore, in the current study, we extend the SEM including time dependence as well as spatial dependence, named after Spatial-Temporal Error Model (STEM). Radar rainfall events generated with STEM were tested so that the peak runoff from the response of a basin could be investigated according to dependent error. The Nam River basin, South Korea, was employed to illustrate the effects of STEM on runoff peak flow.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.775-784
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• 2023

In terms of flood management, it is necessary to analyze quantitative rainfall and runoff from a spatial and temporal perspective and to analyze runoff for heavy rainfall events that are concentrated within a short period of time. The simulation and analysis results of rainfall-runoff models vary depending on the type and input data. In particular, rainfall data is an important factor, so calculating areal mean rainfall is very important. In this study, the areal mean rainfall of the Samcheok Osipcheon(Riv.) watersheds located in the mountainous terrain was calculated using the Arithmetic Mean Method, Thiessen's Weighting Method, and the Isohyetal Method, and the rainfall-runoff results were compared by applying the distributional model S-RAT and the lumped model HEC-HMS. The results of the temporal transferability study showed that the combination of the distributional model and the Isohyetal Method had the best statistical performance with MAE of 64.62 m³/s, RMSE of 82.47 m³/s, and R² and NSE of 0.9383 and 0.8547, respectively. It is considered that this study was properly analyzed because the peak flood volume occurrence time of the observed and simulated flows is within 1 hour. Therefore, the results of this study can be used for frequency analysis in the future, which can be used to improve the accuracy of simulating peak flood volume and peak flood occurrence time in mountainous watersheds with steep slopes.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.164-164
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• 2016

Radar rainfall estimates have been widely used in calculating rainfall amount approximately and predicting flood risks. The radar rainfall estimates have a number of error sources such as beam blockage and ground clutter hinder their applications to hydrological flood forecasting. Moreover, it has been reported in paper that those errors are inter-correlated spatially and temporally. Therefore, in the current study, we tested influence about spatio-temporal errors in radar rainfall estimates. Spatio-temporal errors were simulated through a stochastic simulation model, called Multivariate Autoregressive (MAR). For runoff simulation, the Nam River basin in South Korea was used with the distributed rainfall-runoff model, Vflo. The results indicated that spatio-temporal dependent errors caused much higher variations in peak discharge than spatial dependent errors. To further investigate the effect of the magnitude of time correlation among radar errors, different magnitudes of temporal correlations were employed during the rainfall-runoff simulation. The results indicated that strong correlation caused a higher variation in peak discharge. This concluded that the effects on reducing temporal and spatial correlation must be taken in addition to correcting the biases in radar rainfall estimates. Acknowledgements This research was supported by a grant from a Strategic Research Project (Development of Flood Warning and Snowfall Estimation Platform Using Hydrological Radars), which was funded by the Korea Institute of Construction Technology.

• Journal of Environmental Science International
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• v.7 no.4
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• pp.451-460
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• 1998

The objectives of this study Is to evaluate the total runoff yield, peak flow and peak flow travel time depending on the urbanization, return period and rainfall patterns at the downstream of Manchon urban watershed in TaeGu City. SWM(Storm Water Management Model) is used for runog analysis based on 5 different steps of urbanization and 4 different types of Hufrs quartile according to 8 return periods. It is analyzed that the order of total runoff yield according to raiun patterns is Huffs 4, Huffs 2. Huffs 3 and Huffs 1 quartile, that of peak flow magnitude is Huffs 2, Huffs 1, Huffs 4 and Huffs 3 quartile at present development ratio. under the 60, 70, 80 and 90ft of urbanization to the 50% of urbanization by means of the rainfall patterns, the mean Increasing ratio of total runoff yield for each case is 4.55, 11.43, 16.07 and 20.02%, that of peak flow is 5.82, 13.61, 17.15 and 18.83%, the mean decreasing ratio of peak flow travel time Is 0.00, 2.44, 5.07 and 6.26%, the mean increasing ratio of runoff depth Is 4.51, 11.42, 16.02 and 20.05% respectively. the mean increasing ratio of total runoff yield by means of each and 19.71%. Therefore, as the result of this study. it can be used for principal data as to storm sewage treatment and flood damage protection planning in urban small watershed.

• Water for future
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• v.24 no.1
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• pp.93-97
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• 1991

To design the minor structures in the small watersheds, it is required to calculate the peak discharge. For these calculations the simple peak flow prediction equations, the unit hydrograph method, the synthetic unit hydrograph methods or the runoff simulation models are adopted. To use these methods it is generally required to know the amount and the distributions, which are the uniform distribution, the triangular distribution, the trapezoidal distribution, or the Huff type distribution, of the design rainfall. In this study, the peak discharges are calculated by the different rainfall distribution and the values are compared.

• Journal of Environmental Science International
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• v.28 no.1
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• pp.125-135
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• 2019

For the purposes of enhancing usability of Numerical Weather Prediction (NWP), the quantitative precipitation prediction scheme by machine learning has been proposed. In this study, heavy rainfall was corrected for by utilizing rainfall predictors from LENS and Radar from 2017 to 2018, as well as machine learning tools LightGBM and XGBoost. The results were analyzed using Mean Absolute Error (MAE), Normalized Peak Error (NPE), and Peak Timing Error (PTE) for rainfall corrected through machine learning. Machine learning results (i.e. using LightGBM and XGBoost) showed improvements in the overall correction of rainfall and maximum rainfall compared to LENS. For example, the MAE of case 5 was found to be 24.252 using LENS, 11.564 using LightGBM, and 11.693 using XGBoost, showing excellent error improvement in machine learning results. This rainfall correction technique can provide hydrologically meaningful rainfall information such as predictions of flooding. Future research on the interpretation of various hydrologic processes using machine learning is necessary.

• Journal of the Korean Society of Hazard Mitigation
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• v.7 no.5
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• pp.167-178
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• 2007

Based on the kinematic wave equations, the influence of moving rainstorms on the surface runoff were analyzed with a focus on the rainfall distribution types. Applied hypothetical rainfall distribution types of moving rainstorms used are uniform, advanced, delayed and intermediate type. The moving rainstorm velocities applied in this study were $0.125{\sim}2.0m/s$ of moving upstream and downstream direction of plane surface. Simulations were undertaken by varying the rainfall distribution type, moving rainstorm velocity and moving direction, and the results were compared with that of stationary rainfall. The results indicate significant differences in peak discharges and hydrograph shapes for moving rainstorms of various rainfall patterns and moving directions. It shows that the moving rainstorms of downstream direction generate the largest peak runoff at all rainfall distributions. The sensitivity of runoff to rainfall distribution types decreases as storm velocity increases. It is clear that faster rainstorm velocity generates faster peak time and becomes thin hydrographs rapidly.

• Journal of Forest and Environmental Science
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• v.10 no.1
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• pp.57-65
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• 1994

This study was carried out to clarify the sediment export by measuring suspended solids included in streamflow during the rainy season. The study area is located in Experimental Forests, Kangwon National University, where the forest road is under construction. For this purpose, the forest watershed with construction of forest road was compared with normal forest watershed in amount of rainfall and discharge, suspended solids and discharge, and the amount of rainfall and suspended solids. The results were shown as followings. 1. The relationship of discharge and the amount of rainfall was shown as Table 3 and Fig. 3. The delay time of peak point observed in hydrograph was changed by rainfall intensity and amount of previous rainfall. That is, when there was a rain on 12. Jun(more than 20mm/hour for hours), the peak point began three hours after the rainfall intensity over 20mm/hour, and showed $1514m^3/hour$ in automatic water level recorder. In case of the 8th of Aug.(maximum rainfall intensity: 40mm/hour), the peak point of discharge was $1246m^3/hour$ in the same time with maximum rainfall intensity. And on the 20th of Aug.(the maximum rainfall intensity: 17.2mm/hour), the peak point of discharge was $1245m^3/hour$ two hours after the maximum rainfall intensity. 2. On watershed under forest road construction, the relationship between discharge and suspended solids is that suspended solids was proportionately increased by raising discharge. That is, on the 12th of Jun, the maximum of discharge per hour was $1514m^3/hour$ and 1261mg/l of suspended solids was observed an hour after peak point of discharge. And in case of 8th and 20th Aug., each of peak points is $1246m^3/hour$ and $1245m^3/hour$ by measuring time. The maximums of suspended solids measured within two watersheds were examined in value of 4952mg/l and 472mg/l at the same time. 3. During the rainy season, the concentration of suspended solids was influenced by rainfall intensity and indicated especially curve-regressional increase in case of strong rainfall intensity. In each of watersheds, the maximums of suspended solids were 1261mg/l and 125mg/l, 4952mg/l and 44mg/l, and 472mg/l and 4mg/l by the order of rain(a), (b), and (c). Two watersheds showed a remarkable difference.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.2
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• pp.1-13
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• 2011

This study is to analyze the relationship between rainfall and water level using the measured data. During the rainfall event from September 9 to September 12, 2010, the rainfall and water level data were measured from automatic weather systems and automatic water level measurement systems which have been installed throughout Gangwon province. The result showed that the relationship between rainfall and peak flow change was different by basin and tributary. It is expected that this study will help to build a plan for preventing disasters and rainfall-runoff models for the river basins in Gangwon province.

• Journal of Environmental Health Sciences
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• v.31 no.1
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• pp.1-6
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• 2005

This study was conducted to identify the runoff characteristics of non-point source according to rainfall in Nam watershed. Land-uses of the Nam watershed were surveyed paddy field 4.5%, crop field 6.8%, mountainous 78.7%, urban 2.4%, and etc. 7.7%. Mean runoff coefficients in each area were observed Ⅰ area 0.08, Ⅱ area 0.08, and Ⅲ area 0.05. In the relationship between the rainfall and peak-flow, correlation coefficients(r) were investigated Ⅰ area -0.8609, Ⅱ area 0.6035, and Ⅲ area -0.4913. In the relationship between the antecedent dry period and first flow runoff, correlation coefficients(r) were investigated Ⅰ area -0.9093, Ⅱ area -0.1039, and Ⅲ area -0.7317. The discharge of pollutant concentrations relates to the flow rate of storm-water. In the relationship between the rainfall and watershed loading, exponent values of BOD, COD, SS, and T-N were estimated to 1.2751, 1.2003, 1.3744, and 1.1262, respectively.