• Journal of Korea Water Resources Association
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• v.51 no.1
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• pp.81-88
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• 2018

The rainfall-runoff model made of sewer networks in the urban area is vast and complex, making it unsuitable for real-time urban flood forecasting. Therefore, the rainfall-runoff model is constructed and simplified using the sewer network of Daerim baisn. The network simplification process was composed of 5 steps based on cumulative drainage area and all parameters of SWMM were calculated using weighted area. Also, in order to estimate the optimal simplification range of the sewage network, runoff and flood analysis was carried out by 5 simplification ranges. As a result, the number of nodes, conduits and the simulation time were constantly reduced to 50~90% according to the simplification ranges. The runoff results of simplified models show the same result before the simplification. In the 2D flood analysis, as the simplification range increases by cumulative drainage area, the number of overflow nodes significantly decreased and the positions were changed, but similar flooding pattern was appeared. However, in the case of more than 6 ha cumulative drainage area, some inundation areas could not be occurred because of deleted nodes from upstream. As a result of comparing flood area and flood depth, it was analyzed that the flood result based on simplification range of 1 ha cumulative drainage area is most similar to the analysis result before simplification. It is expected that this study can be used as reliable data suitable for real-time urban flood forecasting by simplifying sewer network considering SWMM parameters.

• Journal of the Korean Geosynthetics Society
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• v.17 no.4
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• pp.267-275
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• 2018

The dredged sediment management system was developed to have an objective, quantitative and scientific decision for the optimum removal time of dredged sediments behind debris barrier and was set up at the real site. The dredged sediment management system is designed and developed to directly measure the dredged sediments behind debris barrier in the field. This management system is composed of Data Acquisition System (DAS), Solar System and measurement units for measuring the weight of dredge sediments. The weight of dredged sediments, the water level and the rainfall are measured in real time using the monitoring sensors, and their data can be transmitted to the office through a wireless communication method. The monitoring sensors are composed of the rain gauge to measure rainfall, the load cell system to measure the weight of dredged sediments, and water level meter to measure the water level behind debris barrier. The management criteria of dredged sediments behind debris barrier was suggested by using the weight of dredged sediments. At first, the maximum weight of dredged sediments that could be deposited behind debris barrier was estimated. And then when 50%, 70% and 90% of the maximum dredged sediments weight were accumulated behind debris barrier, the management criteria were divided into phases of Outlooks, Watch and Warning, respectively. The weight of dredged sediments can be monitored by using the dredged sediment management system behind debris barrier in real time, and the condition of debris barrier and the removal time of dredged sediments can be decided based on monitoring results.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.2 no.3
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• pp.43-56
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• 1982

A recursive algorithms for prediction of streamflows by Kalman filtering theory and Self-tuning predictor based on the state space description of the dynamic systems have been studied and the applicabilities of the algorithms to the rainfall-runoff processes have been investigated. For the representation of the dynamics of the processes, a low-order ARMA process has been taken as the linear discrete time system with white Gaussian disturbances. The state vector in the prediction model formulated by a random walk process. The model structures have been determined by a statistical analysis for residuals of the observed and predicted streamflows. For the verification of the prediction algorithms developed here, the observed historical data of the hourly rainfall and streamflows were used. The numerical studies shows that Kalman filtering theory has better performance than the Self-tuning predictor for system identification and prediction in rainfall-runoff processes.

• Water Engineering Research
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• v.2 no.2
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• pp.113-121
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• 2001

The objective of this study is to develop a prediction mode for a flood forecasting system in the downstream of the Nakdong river basin. Ranging from the gauging station at Jindong to the Nakdong estuary barrage, the hydraulic flood routing model(DWOPER) based on the Saint Venant equation was calibrated by comparing the calculated river stage with the observed river stages using four different flood events recorded. The upstream boundary condition was specified by the measured river stage data at Jindong station and the downstream boundary condition was given according to the tide level data observed at he Nakdong estuary barrage. The lateral inflow from tributaries were estimated by the rainfall-runoff model. In the calibration process, the optimum roughness coefficients for proper functions of channel reach and discharge were determined by minimizing the sum of the differences between the observed and the computed stage. In addition, the forecasting lead time on the basis of each gauging station was determined by a numerical simulation technique. Also, we suggested a model structure for a real-time flood forecasting system and tested it on the basis of past flood events. The testing results of the developed system showed close agreement between the forecasted and observed stages. Therefore, it is expected that the flood forecasting system we developed can improve the accuracy of flood forecasting on the Nakdong river.

• Journal of Korea Water Resources Association
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• v.41 no.7
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• pp.737-746
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• 2008

The purpose of developing a rainfall-runoff and reservoir model is to provide an analysis tool for hydrological engineers in order to forecast discharge of rivers and to accomplish reservoir operations easily and accurately. In this study, based on the short-term rainfall-runoff storage function model which has gained popularity for real time flood forecast in practical water management affairs, a long-term runoff model was developed for the improvement of the calculation method of effective rainfall and percolation at the infiltration area. Annual discharge was simulated for three dam watersheds(Andong, Hapcheon, Milyang) in Nakdong River basin to analyze the accuracy of the developed model and compare it to SSARR model, which is used as the long-term runoff model in current practical water management affairs. As the result of the comparison of hydrographs, SSARR model showed relatively better results. However, it is possible for the developed model to simulate reliable long-term runoff using relatively little available data and is useful for hydrological engineers in practical affairs.

• 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.

• Journal of Korea Water Resources Association
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• v.30 no.4
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• pp.389-399
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• 1997

The heavy strom of July 26-28, 1996, which occurred over the Northern Kyungi Province and Western Kangwon Province, is analyzed to investigate the hydrometeorological characteristics and frequency of occurrences of the storm. The study region is limited to the watershed area of Hantan River on which the partially destructed Yeonchon Dam is located. Hourly rainfall data at 21 rain gauging stations in and near the Hantan river basin are collected and the cumulative rainfall mass curves constructed and compared each other to judge the credibility and consistency of rainfall data at nearby stations. In order to analyze the spatially moving characteristics of rain storm the isochrones based on real time are constructed using the several fixed-percentage cumulative rainfalls at the stations. The basin average rainfalls of various durations are computed for Yeonchon dam and the return period of July/1996 storm are evaluated based on the rainfall frequency curves at Cheolwon and Yeonchon rain gauging stations. A comparison is also made between the July/1996 storm and PMP of the region, which demonstrated the severity of the heavy storm.

• Journal of Korea Water Resources Association
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• v.39 no.1 s.162
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• pp.47-57
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• 2006

This study derives an event-based tank model with a conceptual rainfall-infiltration process, modifying conventional tank models. The model comprises two serial tanks, one parallel tank and an infiltration regulating element. The infiltration process within the element is not represented as a function of only time, but as a function of soil moisture content for three possible cases owing to the relationship between rainfall intensity and infiltration capacity. This study considers the previous soil moisture condition of a watershed by using antecedent precipitation index. Six parameters of the model are identified by using the real coded genetic algorithm. The applicability and validity of the proposed model are assessed for the observed stormwater data from the research basin of the International Hydrological Program, the Pyeongchanggang River basin, Republic of Korea. The results computed streamflows show relatively good agreement with observed ones.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.9
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• pp.1215-1223
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• 2020

Recently, the number of natural disasters caused by inclement weather conditions such as localized heavy rainfall, Typhoon, etc. is increasing in Korea, which requires relevant prevention and water management measures. Rain gauges installed on the ground have strengths in continuously·directly measures ground precipitation but cannot provide accurate information on spatial precipitation distribution in the areas without the rain gauges. The present research has designed and developed an electromagnetic-based multi-purpose precipitation gauge(EWRG, Electromagnetic Wave Rain Gauge) that can measure rainfall at the real time, by overcoming spatial representativeness. In this paper, we propose an FPGA-based signal processing design method for EWRG. The signal processing of the EWRG was largely designed by calculating the ADC and DDC of the LFM waveform, pulse compression, correlation coefficient and estimating the precipitation parameter. In this study, the LFM waveform and pulse compressed signal were theoretically analyzed.

• Magazine of the Korean Society of Agricultural Engineers
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• v.39 no.6
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• pp.54-66
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• 1997

The objectives of this study is to introduce and apply neural network theory to real hydrologic systems for stochastic nonlinear predicting of daily runoff discharge in the river catchment. Back propagation algorithm of neural network model is applied for the estimation of daily stochastic runoff discharge using historical daily rainfall and observed runoff discharge. For the fitness and efficiency analysis of models, the statistical analysis is carried out between observed discharge and predicted discharge in the chosen runoff periods. As the result of statistical analysis, method 3 which has much processing elements of input layer is more prominent model than other models(method 1, method 2) in this study.Therefore, on the basis of this study, further research activities are needed for the development of neural network algorithm for the flood prediction including real-time forecasting and for the optimal operation system of dams and so forth.