• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.259-259
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• 2016

This study examined Artificial Neurons Networks model (ANNs) for forecast flash discharge at Southern part of Thailand by using rainfall data and discharge data. The Sungai Kolok River Basin has meant the border crossing between Thailand and Malaysia which watershed drains an area lies in Thailand 691.88 square kilometer from over all 2,175 square kilometer. The river originates in mountainous area of Waeng district then flow through Gulf of Thailand at Narathiwat Province, which the river length is approximately 103 kilometers. Almost every year, flooding seems to have increased in frequency and magnitude which is highly non-linear and complicated phenomena. The purpose of this study is to forecast runoff on Sungai Kolok at X.119A gauge station (Sungai Kolok district, Narathiwat province) for 3 days in advance by using Artificial Neural Networks model (ANNs). 3 daily rainfall stations and 2 daily runoff station have been measured by Royal Irrigation Department and Meteorological Department during flood period 2000-2014 were used as input data. In order to check an accuracy of forecasting, forecasted runoff were compared with observed data by pursuing Coefficient of determination ($R^2$). The result of the first day gets the highest accuracy and then decreased in day 2 and day 3, consequently. $R^2$values for first day, second day and third day of runoff forecasting is 0.71, 0.62 and 0.49 respectively. The results confirmed that the ANNs model can be used when the range of collected dataset is short and real-time operated. In conclusion, the ANNs model is suitable to runoff forecasting during flood incident of Sungai Kolok river because it is straightforward model and require with only a few parameters for simulation.

• Journal of Korea Water Resources Association
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• v.46 no.1
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• pp.59-71
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• 2013

The lack of sufficient flood data being kept across Korea has made it difficult to assess reliable estimates of the design flood while relatively sufficient rainfall data are available. In this regard, a rainfall simulation based derivation technique of flood frequency curve has been proposed in some of studies. The main issues in deriving the flood frequency curve is to develop the rainfall simulation model that is able to effectively reproduce extreme rainfall. Also the rainfall-runoff modeling that can convey uncertainties associated with model parameters needs to be developed. This study proposes a systematic approach to fully consider rainfallrunoff related uncertainties by coupling a piecewise Kernel-Pareto based multisite daily rainfall generation model and Bayesian HEC-1 model. The proposed model was applied to generate runoff ensemble at Daechung Dam watershed, and the flood frequency curve was successfully derived. It was confirmed that the proposed model is very promising in estimating design floods given a rigorous comparison with existing approaches.

• Journal of Korea Water Resources Association
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• v.38 no.11
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• pp.955-962
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• 2005

Even though the runoff volume is very sensitive to the antecedent soil moisture condition (AMC), the general rainfall-runoff analysis in Korea has accepted, without careful consideration of its applicability, the AMC classification of the Soil Conservation Service (SCS, 1972). In this study, by following the development procedure of SCS Curve Number (CN), the rainfall-runoff characteristics of the Jangpyung subbasin of the Pyungchang River Basin were analyzed to estimate the CN and evaluate the AMC classification of currently being used. As results, CN(I), CN(II), and CN(III) were estimated to be 72.1, 79.3, and 76.7, respectively. Among them CN(II) was found to be similar to the other reports but the other two were totally different from those of theoretically estimated. However, it is difficult to evaluate the AMC with CN, rather the frequency of each AMC could be a better indicator for its validity. This study developed the histogram of AMC and compared the frequency of each AMC. hs results we found that the criterion for AMC-III should be increased, Hut that for AMC-I decreased.

• Proceedings of the Korea Water Resources Association Conference
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• 2003.05a
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• pp.54-57
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• 2003

• Journal of Korea Water Resources Association
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• v.39 no.7 s.168
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• pp.575-581
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• 2006

This paper presents a systematic approach for the economical design of stormwater quality control systems. For the design of runoff quality control system (RQCS), the rainfall-runoff process requires the local rainfall data recorded continuously. In this study the rainfall probability distribution is assumed to follow an exponential decay function. Applying the exponential decay function, the normalized curves are derived to explain the non-exceedance probability distributions. The optimal curves for the determination of the RQCS size are derived based on the overflow risk. Comparison of the optimal capture volume and peak runoff rate to those computed by an urban rainfall-runoff model(ILLUDAS) demonstrates that the optimal CSOs(Combined Sewer Overflows) curves derived in this study can be utilized for the design of stormwater quality control systems in Korea avoiding an excessive computational effort based on over flow risks.

• 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.

• Journal of Korean Society of Water and Wastewater
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• v.27 no.3
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• pp.313-324
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• 2013

It is widely known that untreated Combined Sewer Overflows (CSOs) that directly discharged from receiving water have a negative impact. Recent concerns on the CSO problem have produced several large scale constructions of treatment facilities, but the facilities are normally designed under empirical design criteria. In this study, several criteria for defining CSOs (e.g. determination of effective rainfall, sampling time, minimum duration of data used for rainfall-runoff simulation and so on) were investigated. Then this study suggested a standard methodology for the CSO calculation and support formalized standard on the design criteria for CSO facilities. Criteria decided for an effective rainfall was over 0.5 mm of total rainfall depth and at least 4 hours should be exist between two different events. An Antecedent dry weather period prior to storm event to satisfy the effective rainfall criteria was over 3 days. Sampling time for the rainfall-runoff model simulation was suggested as 1 hour. A duration of long-term simulation CSO overflow and frequency calculation should be at least recent 10 year data. A Management plan for the CSOs should be established under a phase-in of the plan. That should reflect site-specific conditions of different catchments, and formalized criteria for defining CSOs should be used to examine the management plans.

• Journal of The Korean Society of Agricultural Engineers
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• v.48 no.2
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• pp.45-55
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• 2006

This study analyze the hydrologic conditions and the effects of selected runoff characteristics as an attempt to estimate the optimal dredge amount for Asan Lake in Korea. The runoff feature was calculated by utilizing the water balance simulation from DIROM (Daily Irrigation Reservoir Operation Model), which allowed changes in landuse to be quantified using remote sensing for 14 years. The distribution of prospective sediment deposits was been tallied based on the changes in landuse, and quantity of incoming sediment estimated. From these findings, we were then able to simulate the fluctuation of water level, gauging the pumping days not already in use, to determine the frequency of the distribution for around the. requirement annual water storage and the changing water level. The optimal dredge amount was calculated on the basis of the distribution of frequency, taking into account the design criteria for agricultural water with the 10-year frequency of resistant capacity.

• Journal of Wetlands Research
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• v.14 no.4
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• pp.571-580
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• 2012

This study is on the purpose of leading Geomorphoclimatic Instantaneous Unit Hydrograph(GcIUH) by using GIS Techniques, and estimating trigger rainfall for predicting flash flood in Seolmacheon catchment, mountain river watershed. This study leads GcIUH by using GIS techniques, calculates NRCS-CN values for effective rainfall rate, and analyzes 2011 main rainfall events using estimated GcIUH. According to the results, the case of Memorial bridge does not exceed the amount of threshold runoff, however, the case of Sabang bridge shows that simulated peak flow, approximately $149.4m^3/s$, exceeds the threshold runoff. To estimate trigger rainfall, this study determines the depth of 50 year-frequency designed flood amount as a threshold water depth, and estimates trigger rainfall of flash flood in consideration of duration. Hereafter, this study will analyze various flood events, estimate the appropriateness of trigger rainfall as well as threshold runoff through this analysis, and develop prototype of Flash Flood Prediction System which is considered the characteristics of mountain river watershed on the basis of this estimation.

• Journal of Korean Society on Water Environment
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• v.31 no.3
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• pp.241-252
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• 2015

Runoff behaviors by five bias correction methods were analyzed, which were Change Factor methods using past observed and estimated data by the estimation scenario with average annual calibration factor (CF_Y) or with average monthly calibration factor (CF_M), Quantile Mapping methods using past observed and estimated data considering cumulative distribution function for entire estimated data period (QM_E) or for dry and rainy season (QM_P), and Integrated method of CF_M+QM_E(CQ). The peak flow by CF_M and QM_P were twice as large as the measured peak flow, it was concluded that QM_P method has large uncertainty in monthly runoff estimation since the maximum precipitation by QM_P provided much difference to the other methods. The CQ method provided the precipitation amount, distribution, and frequency of the smallest differences to the observed data, compared to the other four methods. And the CQ method provided the rainfall-runoff behavior corresponding to the carbon dioxide emission scenario of SRES A1B. Climate change scenario with bias correction still contained uncertainty in accurate climate data generation. Therefore it is required to consider the trend of observed precipitation and the characteristics of bias correction methods so that the generated precipitation can be used properly in water resource management plan establishment.