• Journal of Korea Water Resources Association
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• v.37 no.5
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• pp.407-424
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• 2004

Using geomorphoclimatic unit hydrograph(GCUH), we estimated the fitness to calculate the mountainous area discharge and flash flood trigger rainfall(FFTR). First, we compared the GCUH peak discharge with the existing report using the design storm at the Dukcheon basin. Second, we compared the HEC-HMS(Hydrologic Engineering Center-Hydrologic Modeling System) model and GCUH with the observed discharge using the real rainfall events at the Taesu stage gage. Third, GCUH and NRCS(Natural Resources Conservation Service) were used for calculating FFTR and proper calculation method was shown. At the Dukcheon basin, the comparison result of using design storm was shown in Table 11, and it was not in excess of 1.1, except for the 30 year return period. In case of real rainfall events, the result was shown in Table 12, and GCUH discharges were all larger than the HEC-HMS model discharges, and they were very similar to the observed data at the Taesu stage gage. In this study, we found that GCUH was a very proper method in the calculation of mountainous discharge. At the Dukcheon basin, FFTR was 12.96 mm in the first 10 minutes when the threshold discharge was 95.59 $m^3$/sec.

• Journal of Korea Water Resources Association
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• v.54 no.12
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• pp.1317-1328
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• 2021

This study aims to provide a predictive model based on climate models for simulating continuous daily rainfall sequences by combining bias-correction and spatio-temporal downscaling approaches. For these purposes, this study proposes a combined modeling system by applying conditional Copula and Multisite Non-stationary Hidden Markov Model (MNHMM). The GloSea5 system releases the monthly rainfall prediction on the same day every week, however, there are noticeable differences in the updated prediction. It was confirmed that the monthly rainfall forecasts are effectively updated with the use of the Copula-based bias-correction approach. More specifically, the proposed bias-correction approach was validated for the period from 1991 to 2010 under the LOOCV scheme. Several rainfall statistics, such as rainfall amounts, consecutive rainfall frequency, consecutive zero rainfall frequency, and wet days, are well reproduced, which is expected to be highly effective as input data of the hydrological model. The difference in spatial coherence between the observed and simulated rainfall sequences over the entire weather stations was estimated in the range of -0.02~0.10, and the interdependence between rainfall stations in the watershed was effectively reproduced. Therefore, it is expected that the hydrological response of the watershed will be more realistically simulated when used as input data for the hydrological model.

• Journal of the Korean Geosynthetics Society
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• v.16 no.2
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• pp.165-174
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• 2017

There are natural disasters caused by abnormal climate in the world. In particular, there are frequent disasters such as floods and landslides caused by rainfall in summer. Rainfall will have a major impact on the stability of a retaining wall. If drainage during rainfall activities within the retaining wall is not made properly, permeated water brings a significant increase in pore pressure inside of the backfill soil and reduces the shear strength of the soil. Therefore, research how to install the drainage layers to reduce the infiltrated water inside of the backfill soil is very necessary. In this study, we performed a numerical modeling to find the optimum installation conditions of the location and number of drainage layer related to stability of the reinforced retaining wall during rainfall installed geosynthetics.

• The Journal of the Korea Contents Association
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• v.19 no.3
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• pp.261-274
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• 2019

This paper aims to develop an appropriate methodology for establishing an investment strategy for 'demonstration of artificial rainfall technology using UAV' and that include establishment of a technology classification, set of indicators for technology evaluation, suggestion of final key technology as a whole study area. It is designed to complement the latest research trend analysis results and expert committee opinions using quantitative analysis. The key indicators for technology evaluation consisted of three major items (activity, technology, marketability) and 10 detailed indicators. The AHP questionnaire was conducted to analyze the importance of indicators. As a result, it was analyzed that the attribute of the technology itself is most important, and the order of closeness to the implementation of the core function (centrality), feasibility (feasibility). Among the 16 technology groups, top investment priority groups were analyzed as ground seeding, artificial rainfall verification, spreading and diffusion of seeding material, artificial rainfall numerical modeling, and UAV sensor technology.

• Environmental Engineering Research
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• v.14 no.1
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• pp.13-18
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• 2009

In this study, specific pollutant releases during the Asian monsoon season were estimated and the information was applied to the non-point pollutant sources management from two forested watersheds of the Soyang Lake. The two watersheds are part of the 2,703 km2 Soyang Lake watershed in the northern region of the Han River. The outlets of the two watersheds were respectively analyzed for continuous water quality concentration and for discharge during various single rainfall events. Statistical power function methods are utilized to compare stream discharge and pollutant flux release during the study period. Based on the monitoring data during the study period, the specific load flux method using simulated discharge was conducted and validated in the two watersheds. The model predictions corresponded well with the measured and calculated pollutant releases. The modeling approach taken in this study was found to be applicable for the two forested watersheds.

• Magazine of the Korean Society of Agricultural Engineers
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• v.36 no.2
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• pp.79-87
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• 1994

A real-time flood forecasting system(FLOFS) was developed for the real-time and predictive determination of flood discharges and stages, and to aid in flood management decisions in the Keum River Estuary Dam. The system consists of three subsystems : data subsystem, model subsystem, and user subsystem. The data subsystem controls and manages data transmitted from telemetering systems and simulated by models. The model subsystem combines various techniques for rainfall-runoff modeling, tidal-level forecasting modeling, one-dimensional unsteady flood routing, Kalman filtering, and autoregressivemovingaverage(ARMA) modeling. The user subsystem in a menu-driven and man-machine interface system.

• The Korean Journal of Applied Statistics
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• v.27 no.4
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• pp.655-665
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• 2014

An adequate understanding and response to natural hazards such as heat wave, heavy rainfall and severe drought is required. We apply extreme value theory to analyze these abnormal weather phenomena. It is common for extremes in climatic data to be nonstationary in space and time. In this paper, we analyze summer rainfall data in South Korea using exceedance values over thresholds estimated by quantile regression with location information and time as covariates. We group weather stations in South Korea into 5 clusters and t extreme value models to threshold exceedances for each cluster under the assumption of independence in space and time as well as estimates of uncertainty for spatial dependence as proposed in Northrop and Jonathan (2011).

• Journal of Environmental Impact Assessment
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• v.15 no.6
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• pp.435-441
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• 2006

For the calibration of rainfall-runoff model, automatic calibration methods are used instead of manual calibration to obtain the reliable modeling results. When mathematical programming techniques such as linear programming and nonlinear programming are applied, there is a possibility to arrive at the local optimum. To solve this problem, genetic algorithm is introduced in this study. It is very simple and easy to understand but also applicable to any complicated mathematical problem, and it can find out the global optimum solution effectively. The objective of this study is to develope a parameter optimization program that integrate a genetic algorithm and a rainfall-runoff model. The program can calibrate the various parameters related to the runoff process automatically. As a rainfall-runoff model, SWMM is applied. The automatic calibration program developed in this study is applied to the Jangcheon watershed flowing into the Youngrang Lake that is in the eutrophic state. Runoff surveys were carried out for two storm events on the Jangcheon watershed. The peak flow and runoff volume estimated by the calibrated model with the survey data shows good agreement with the observed values.

• Journal of Korean Society of Water and Wastewater
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• v.20 no.4
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• pp.573-584
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• 2006

This study was carried out to investigate the causes of fish kills in the Yudeung Stream in Daejeon, Korea using literature reviews, governmental and our water quality monitoring data of the study site, rainfall data, intensive water quality monitoring during rainfall events, sediment pollutant contents and laboratory bioassay tests. Fish kill in urban streams can be caused by combined effect of reduction in dissolved oxygen concentration, increase in toxic material or increase in turbidity in waterbody due to introduction of surface runoff or effluent of combined sewer overflows after rainfall from the watershed areas. Despite of extensive and intensive field surveys and laboratory tests, it was found that those conventional methods have limitations to identify causes of fish kills in urban streams. It would be necessary to use dynamic water quality modeling to predetermine the range and level of water pollution in the stream and automatic water quality monitoring system that can collect water samples and detect water quality continuously.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.5
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• pp.1-10
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• 2016

Drought is a slow-varying natural hazard that is characterized by various factors such that reliable drought forecasting along with uncertainties estimation has been a major issue. In this study, we proposed a stochastic simulation technique based scheme for providing a set of drought scenarios. More specifically, this study utilized a nonstationary Hidden markov model that allows us to include predictors such as climate state variables and global climate model's outputs. The simulated rainfall scenarios were then used to generate the well-known meteorological drought indices such as SPI, PDSI and PN for the three dam watersheds in South Korea. It was found that the proposed modeling scheme showed a capability of effectively reproducing key statistics of the observed rainfall. In addition, the simulated drought indices were generally well correlated with that of the observed.