• Journal of Korea Water Resources Association
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• v.49 no.12
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• pp.1007-1014
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• 2016

The FORGEX (Focused Rainfall Growth Extension) method was developed to estimate rainfall quantiles in the United Kingdom. This method does not need any regional grouping and can estimate rainfall quantiles with relatively long return period. The spatial dependence formula (ln $N_e$) was derived to consider the distance from growth curve of proper population to the distributed network maximum (netmax) data using the UK rainfall data. For this reason, there is an inaccurate problem in rainfall quantiles when this formula is applied in Korea. In this study, the new formula was derived in order to improve such shortcomings using rainfall data of 64 sites from the Korea Meteorological Administration (KMA). A 42-year period (1973~2014) was taken as the reference period from rainfall data, then the formula was derived using three parameters such as rainfall duration, number of site, area of network. Then the new formula was applied to the FORGEX method for regional rainfall frequency analysis. In addition, rainfall quantiles were compared with those from the UK formula. As a result, the new formula shows more accurate results than the UK formula, in which the FORGEX method by the UK formula underestimates rainfall quantiles. Finally, the new improved formula may estimate accurate rainfall quantiles for long return period.

• Journal of Korea Water Resources Association
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• v.34 no.2
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• pp.119-130
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• 2001

At-site and regional frequency analyses of annual maximum 1-, 2-, and 3-days rainfall in Han River basin was performed and compared based on the regional L-moments algorithm. To perform regional frequency analysis, Han River basin was subdivided into 3 sub-basins such as South Han River, North Han River, and downstream regions. For each sub-basin, the discordancy and homogeneity tests were performed. As the results of goodness of fit tests, lognormal model was selected as an appropriate probability distribution for both South Han River and downstream regions and gamma-3 model for North han River region. From Monte carlo simulation, RBIAS and RRMSE of the estimated quantiles from regional frequency analysis and at-site frequency analysis were calculated and compared each other. Regional frequency analysis shows less RRMSE of the estimated quantiles than at-sites frequency analysis in overall return periods. The differences of BRMSE between two approaches increase as the return period increases. As a result, it is shown that regional frequency analysis performs better than at-site analysis for annual maximum rainfall data in Han River basin.

• Spatial Information Research
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• v.15 no.2
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• pp.159-167
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• 2007

In this study, we investigated the application of extending the Huff's method to design discharge being used at present up to the event of concentrated rainfall. As our field study site, we selected Odae Cheon basin in Pheongchang, which was affected by concentrated rainfall in July 2006. Actual concentrated rainfall and design rainfall derived from the Huff's method were used to calculate the discharge and storm water levels, which were compared with the directly measured water-level marks of storm discharges. The results showed that the peak storm discharge from the torrential rainfall was twice higher than the design rainfall. The short term discharges from concentrated rainfall closely corresponded to the rainfall discharges of 150 years storm frequency.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.166-166
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• 2020

Recently, As the frequency of localized heavy rains increases, the use of high-resolution radar data is increasing. The produced radar rainfall has still gaps of spatial and temporal compared to gauge observation rainfall, and in many studies, various statistical techniques are performed for correct rainfall. In this study, the precipitation correction of the S-band Dual Polarization radar in use in the flood forecast was performed using the ConvAE algorithm, one of the Convolutional Neural Network. The ConvAE model was trained based on radar data sets having a 10-min temporal resolution: radar rainfall data, gauge rainfall data for 790minutes(July 2017 in Cheongju flood event). As a result of the validation of corrected radar rainfall were reduced gaps compared to gauge rainfall and the spatial correction was also performed. Therefore, it is judged that the corrected radar rainfall using ConvAE will increase the reliability of the gridded rainfall data used in various physically-based distributed hydrodynamic models.

• Journal of Wetlands Research
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• v.3 no.1
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• pp.49-59
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• 2001

The objective of this study is to provide the results of frequency analysis for Dong-eup reservoir, in which the environmental and ecological roles in addition to the water supply and flood control capacity of the reservoir are increased rapidly. The suggested results are the frequency analysis of annual maximum rainfall data based on eight different rainfall duration data at Masan and Milyang raingauge stations. We also provide the probabilistic inflows from subbasins and evaluate the stage increases of the reservoir. As results, the 24-hour and 100-year return period rainfall is 291.8 mm and consequently inflows are 361.79 cms for Junam, 192.57 for Sannam and 408.28 for Dongpan reservoirs. The 24-hour and 100-year return period reservoir stages are expected as 5.08 m, 5.51 m and 6.89 m depending on the initial reservoir stage. The suggested results of frequency analysis of rainfalls, inflows and reservoir stages in this study will be useful for the scientific and systematic management of the reservoir.

• Journal of Korea Water Resources Association
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• v.35 no.2
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• pp.173-186
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• 2002

Rainfall-runoff model is usually used in estimating the design flood, and the most important elements in this model are probable rainfall and unit hydrograph. So, it is the most important step to estimate probable rainfall reasonably and exactly. If a basin area exceeds a certain scale, probable areal rainfall should be used as probable rainfall, but, Probable point- mean rainfall be usually used in Korea. Consequently, probable rainfall is used too high and unit hydrograph is used relatively too low. Thus the improvement is unavoidable. So, in this study, the parameters are proposed that transform the 1day, 2day rainfall to 24hr, 48hr rainfall, and areal rainfall data series are composed by using the same time rainfall data. Also, the areal reduction factor(ARF) is developed as the increase of area by the calculated probable point mean rainfall and probable areal rainfall by frequency analysis in Han-River basin. It can be the measure to easily transform probable point- mean rainfall to probable areal rainfall.

• 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.

• 한국방재학회:학술대회논문집
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• 2007.02a
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• pp.501-504
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• 2007

Slope-related disasters have occurred in the rainy season. It can be assumed that one of the most important factor slope-related disasters is rainfall intensity. Slope-related disasters occurred in relatively short time and had characteristics that lead to huge damage. Therefore, if rainfall characteristics were applied to estimate slope stability effectively, slope-related disasters could be predicted and prepared in advance. In this study, the SEEP/W program was used and the frequency rainfall estimated by using precipitation data($1961{\sim}2005$) in Seoul was applied to analyze the change of groundwater level according to rainfall intensity.

• Journal of Korean Society of Water and Wastewater
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• v.22 no.1
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• pp.65-71
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• 2008

This study collected the latest 30-year (1976~2005) continuous rainfall data hourly recorded at 61 meterological observatories in Korea, and the continuous rainfall data was divided into individual rainfall events. In addition, distribution charts of average rainfall event-depth were created to facilitate the application to the overflow risk-based design of detention storage basin. This study shows that 4 hour is appropriate for SST (storm separation time) to separate individual rainfall events from the continuous rainfall data, and the one-parameter exponential distribution is suitable for the frequency distribution of rainfall event depths for the domestic rainfall data. The analysis of the domestic rainfall data using SST of 4 hour showed that the individual rainfall event was 1380 to 2031 times, the average rainfall event-depth was 19.1 to 32.4mm, and ranged between 0.877 and 0.926. Distribution charts of average rainfall event-depth were created for 4hour and 6 hour of SST, respectively. The inland Gyeongsangbuk-do, Western coastal area and inland of Jeollabuk-do had relatively lower average rainfall event-depth, whereas Southern coastal area, such as Namhae, Yeosu, and Jeju-do had relatively higher average rainfall event-depth.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.208-208
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• 2022

Recently, the frequency of abnormal weather due to complex factors such as global warming is increasing frequently. From the past rainfall patterns, it is evident that climate change is causing irregular rainfall patterns. This phenomenon causes difficulty in predicting rainfall and makes it difficult to prevent and cope with natural disasters, casuing human and property damages. Therefore, accurate rainfall estimation and rainfall occurrence time prediction could be one of the ways to prevent and mitigate damage caused by flood and drought disasters. However, rainfall prediction has a lot of uncertainty, so it is necessary to understand and reduce this uncertainty. In addition, when accurate rainfall prediction is applied to the rainfall-runoff model, the accuracy of the runoff prediction can be improved. In this regard, this study aims to increase the reliability of rainfall prediction by analyzing the uncertainty of the Korean rainfall ensemble prediction data and the outflow analysis model using the Limited Area ENsemble (LENS) and the Grid based Rainfall-runoff Model (GRM) models. First, the possibility of improving rainfall prediction ability is reviewed using the QM (Quantile Mapping) technique among the bias correction techniques. Then, the GRM parameter calibration was performed twice, and the likelihood-parameter applicability evaluation and uncertainty analysis were performed using R², NSE, PBIAS, and Log-normal. The rainfall prediction data were applied to the rainfall-runoff model and evaluated before and after calibration. It is expected that more reliable flood prediction will be possible by reducing uncertainty in rainfall ensemble data when applying to the runoff model in selecting behavioral models for user uncertainty analysis. Also, it can be used as a basis of flood prediction research by integrating other parameters such as geological characteristics and rainfall events.