• Journal of Korea Water Resources Association
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• v.43 no.8
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• pp.695-707
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• 2010

The frequency and size of typhoon and local severe rainfall are increasing due to the climate change and the damage also increasing from typhoon and severe rainfall. The flood forecasting and warning system to reduce the damage from typhoon and severe rainfall needs forecasted rainfall using radar data and short-term rainfall forecasting model. For this reason, this study examined the applicability of short-term rainfall forecast using translation model with weather radar data to point out that the utilization of flood forecasting in Korea. This study estimated the radar rainfall using Least-square fitting method and estimated rainfall was used as initial field of translation model. The translation model have verified accuracy of forecasted radar rainfall through the comparison of forecasted radar rainfall and observed rainfall quantitatively and qualitatively. Almost case studies showed that accuracy is over 0.6 within 4 hours leading time and mean of correlation coefficient is over 0.5 within 1 hours leading time in Kwanak and Jindo radar site. And, as the increasing the leading time, the forecast accuracy of precipitation decreased. The results of the calculated Mean Area Precipitation (MAP) showed forecast rainfall tend to be underestimated than observed rainfall but the correlation coefficient more than 0.5. Therefore it showed that translation model could be accurately predicted the rainfall relatively. The present results indicate that possibility of translation model application of Korea just within 2 hours leading forecasted rainfall.

• Journal of Wetlands Research
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• v.19 no.3
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• pp.366-374
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• 2017

The objective of this study is to explore the applicability of very short-range-forecast rainfall for the early warning of mud-debris flows. An artificial neural network was applied to use the very short-range-forecast rainfall data. The neural network is learned by using the relationship between the radar and the AWS, and forecasted rainfall is estimated by replacing the radar rainfall with the MAPLE data as the very short-range-forecast rainfall data. The applicability of forecasted rainfall by the MAPLE was compared with the AWS rainfall at the test-bed using the rainfall criteria for cumulative rainfall of 6hr, 12hr, and 24hr respectively. As a result, it was confirmed that forecasted rainfall using the MAPLE can be issued prior to the AWS warning.

• Journal of Korea Water Resources Association
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• v.44 no.11
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• pp.853-861
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• 2011

The objective of this study is to assess Sejong University River Forecast (SURF) model which consists of a continuous rainfall-runoff model and measured streamflow assimilation using ensemble Kalman filter technique for streamflow forecast on Nakdong river basin. The study area is divided into 43 subbasins. The forecasted streamflows are evaluated at 12 measurement sites during flood season from 2006 to 2007. The forecasted ones are improved due to the impact of the measured streamflows assimilation. In effectiveness indices corresponding to 1~5 h forecast lead times, the accuracy of the forecasted streamflows with the assimilation approach is improved by 46.2~30.1% compared with that using only the rainfall-runoff model. The mean normalized absolute error of forecasted peak flow without and with data assimilation approach in entering 50% of the measured rainfall, respectively, the accuracy of the latter is improved about 40% than that of the former. From these results, SURF model is able to be used as a real-time river forecast model.

• Environmental Engineering Research
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• v.20 no.3
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• pp.290-297
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• 2015

This paper presents the evaluation of the impact of climate change on water resources and yield capacity of Asa and Kampe reservoirs. Trend analysis of mean temperature, runoff, rainfall and evapotranspiration was carried out using Mann Kendall and Sen's slope, while runoff was modeled as a function of temperature, rainfall and evapotranspiration using Artificial Neural Networks (ANN). Rainfall and runoff exhibited positive trends at the two dam sites and their upstream while forecasted ten-year runoff displayed increasing positive trend which indicates high reservoir inflow. The reservoir yield capacity estimated with the ANN forecasted runoff was higher by about 38% and 17% compared to that obtained with historical runoff at Asa and Kampe respectively. This is an indication that there is tendency for water resources of the reservoir to increase and thus more water will be available for water supply and irrigation to ensure food security.

• Magazine of the Korean Society of Agricultural Engineers
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• v.36 no.2
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• pp.44-55
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• 1994

This paper describes the development of real-time irrigation reservoir operation models that adequately allocate available water resources for paddy rice irrigation. Water requirement deficiency index(WRDI) was proposed as a guide to evaluate the operational performance of release schemes by comparing accumulated differences between daily release requirements for irrigated areas and actual release amounts. Seven reservoir release rules were developed, which are constant release rate method (CRR), mean storage curve method(MSC), frequency analysis method of reservoir storage rate(FAS), storage requirement curve method(SRC), constant optimal storage rate method (COS), ten-day optimal storage rate method(TOS), and release optimization method(ROM). Long-term forecasting reservoir operation model(LFROM) was formulated to find an optimal release scheme which minimizes WRDIs with long-term weather generation. Rainfall sequences, rainfall amount, and evaporation amount throughout the growing season were to be forecasted and the results used as an input for the model. And short-term forecasting reservoir operation model(SFROM) was developed to find an optimal release scheme which minimizes WRDIs with short-term weather forecasts. The model uses rainfall sequences forecasted by the weather service, and uses rainfall and evaporation amounts generated according to rainfall sequences.

• Journal of Korea Water Resources Association
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• v.50 no.5
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• pp.335-346
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• 2017

This study generated the radar-based forecasted rainfall using spatial-scale decomposition method (SCDM) and evaluated the hydrological applicability with forecasted rainfall by KMA (MAPLE, KONOS) in terms of urban flood forecasting. SCDM is to separate the small-scale field (convective cell) and large-scale field (straitform cell) from radar rainfield. And each separated field is forecasted by translation model and storm tracker nowcasting model for improvement of QPF accuracy. As the evaluated results of various QPF for three rainfall events in Seoul and Metropolitan area, proposed method showed better prediction accuracy than MAPLE and KONOS considering the simplicity of the methodology. In addition, this study assessed the urban hydrological applicability for Gangnam basin. As the results, KONOS simulated the peak of water depth more accurately than MAPLE and SCDM, however cannot simulated the timeseries pattern of water depth. In the case of SCDM, the quantitative error was larger than observed water depth, but the simulated pattern was similar to observation. The SCDM will be useful information for flood forecasting if quantitative accuracy is improved through the adjustment technique and blending with NWP.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.1
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• pp.17-27
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• 2020

The objective of this study was to assess the flood probability based on temporal distribution of forecasted-rainfall in Cheongmicheon watershed. In this study, 6-hr rainfalls were disaggregated into hourly rainfall using the Multiplicative Random Cascade (MRC) model, which is a stochastic rainfall time disaggregation model and it was repeated 100 times to make 100 rainfalls for each storm event. The watershed runoff was estimated using the Clark unit hydrograph method with disaggregated rainfall and watershed characteristics. Using the peak discharges of the simulated hydrographs, the probability distribution was determined and parameters were estimated. Using the parameters, the probability density function is shown and the flood probability is calculated by comparing with the design flood of Cheongmicheon watershed. The flood probability results differed for various values of rainfall and rainfall duration. In addition, the flood probability calculated in this study was compared with the actual flood damage in Cheongmicheon watershed (R² = 0.7). Further, this study results could be used for flood forecasting.

• Journal of the Korean Society of Hazard Mitigation
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• v.11 no.3
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• pp.17-28
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• 2011

This study applied the Kalman Filter for real-time forecasting the G/R (ground rain gauge rainfall/radar rainfall) ratio to correct the mean field bias of the very-short-range-forecast (VSRF) rainfall. The MAPLE-forecasted rainfall was used as the VSRF rainfall, also the methodology for deciding the G/R ratio was improved by evaluating the change of G/R ratio characteristics depending on the threshold and accumulation time. This analysis was done for the inland, mountain, and coastal regions, separately, for their comparison. As the results, more stable G/R ratio could be estimated by applying the threshold and accumulation time, whose forecasting accuracy could also be secured. The accuracy of the corrected rainfall forecasting by the forecasted G/R ratio was the best in the inland region but the worst in the coastal region.

• Environmental Engineering Research
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• v.22 no.2
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• pp.162-168
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• 2017

Rainfall is one of the most important phenomena of the natural system. In Bangladesh, agriculture largely depends on the intensity and variability of rainfall. Therefore, an early indication of possible rainfall can help to solve several problems related to agriculture, climate change and natural hazards like flood and drought. Rainfall forecasting could play a significant role in the planning and management of water resource systems also. In this study, univariate Seasonal Autoregressive Integrated Moving Average (SARIMA) model was used to forecast monthly rainfall for twelve months lead-time for thirty rainfall stations of Bangladesh. The best SARIMA model was chosen based on the RMSE and normalized BIC criteria. A validation check for each station was performed on residual series. Residuals were found white noise at almost all stations. Besides, lack of fit test and normalized BIC confirms all the models were fitted satisfactorily. The predicted results from the selected models were compared with the observed data to determine prediction precision. We found that selected models predicted monthly rainfall with a reasonable accuracy. Therefore, year-long rainfall can be forecasted using these models.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.5
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• pp.91-99
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• 2016

High resolution rainfall data at 1-hour or a finer scale are essential for reliable flood analysis and forecasting; nevertheless, many observations, forecasts, and climate projections are still given at coarse temporal resolutions. This study aims to evaluate a chaotic method for disaggregation of 6-hour rainfall data sets so as to apply operational 6-hour rainfall forecasts of the Korean Meteorological Association to flood models. We computed parameters of a state-of-the-art multiplicative random cascade model with two combinations of cascades, namely uniform splitting and diversion, using rainfall observations at Seoul station, and compared statistical performance. We additionally disaggregated 6-hour rainfall time series at 58 stations with the uniform splitting and evaluated temporal transferability of the parameters and changes in multifractal properties. Results showed that the uniform splitting outperformed the diversion in reproduction of observed statistics, and hence is better to be used for disaggregation of 6-hour rainfall forecasts. We also found that multifractal properties of rainfall observations has adequate temporal consistency with an indication of gradually increasing rainfall intensity across South Korea.