• Title/Summary/Keyword: Real Time Runoff Analysis System

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Development and Evaluation of a Real Time Runoff Modelling System using Weather Radar and Distributed Model (기상레이더와 분포형 모형을 이용한 실시간 유출해석 시스템 개발 및 평가)

  • Choi, Yun Seok;Kim, Kyung Tak;Kim, Joo Hun
    • Journal of Wetlands Research
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    • v.14 no.3
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    • pp.385-397
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    • 2012
  • A grid based physically distributed model analyzes rainfall-runoff using physical parameters and grid-typed spatial and hydrological data. This study have developed a real time runoff modelling system using GRM RT(Grid based Rainfall-runoff Model Real Time) which is a real time flow analysis module in GRM, a grid based physically distributed rainfall-runoff model. Weather radar data received in real time are calibrated by using real time AWS from Korea Meteorological Administration(KMA), and they are applied to real time runoff modeling. And the runoff model is calibrated by using observed discharges from a water level gauge in real time. This study have designed and implemented the databases necessary to construct the real time runoff modelling system, and established the process of a real time runoff modelling. And the performances of the developed system have been evaluated. The system have been applied to Nerinheon watershed located in the upstream of Soyanggang Dam and the application results are evaluated.

Development of Rainfall-Runoff forecasting System (유역 유출 예측 시스템 개발)

  • Hwang, Man Ha;Maeng, Sung Jin;Ko, Ick Hwan;Ryoo, So Ra
    • Proceedings of the Korea Water Resources Association Conference
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    • 2004.05b
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    • pp.709-712
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    • 2004
  • The development of a basin-wide runoff analysis model is to analysis monthly and daily hydrologic runoff components including surface runoff, subsurface runoff, return flow, etc. at key operation station in the targeted basin. h short-term water demand forecasting technology will be developed fatting into account the patterns of municipal, industrial and agricultural water uses. For the development and utilization of runoff analysis model, relevant basin information including historical precipitation and river water stage data, geophysical basin characteristics, and water intake and consumptions needs to be collected and stored into the hydrologic database of Integrated Real-time Water Information System. The well-known SSARR model was selected for the basis of continuous daily runoff model for forecasting short and long-term natural flows.

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Development and Performance Assessment of the Nakdong River Real-Time Runoff Analysis System Using Distributed Model and Cloud Service (분포형 모형과 클라우드 서비스를 이용한 낙동강 실시간 유출해석시스템 개발 및 성능평가)

  • KIM, Gil-Ho;CHOI, Yun-Seok;WON, Young-Jin;KIM, Kyung-Tak
    • Journal of the Korean Association of Geographic Information Studies
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    • v.20 no.3
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    • pp.12-26
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    • 2017
  • The objective of this study was to develop a runoff analysis system of the Nakdong River watershed using the GRM (Grid-based Rainfall-runoff Model), a physically-based distributed rainfall-runoff model, and to assess the system run time performance according to Microsoft Azure VM (Virtual Machine) settings. Nakdong River watershed was divided into 20 sub-watersheds, and GRM model was constructed for each subwatershed. Runoff analysis of each watershed was calculated in separated CPU process that maintained the upstream and downstream topology. MoLIT (Ministry of Land, Infrastructure and Transport) real-time radar rainfall and dam discharge data were applied to the analysis. Runoff analysis system was run in Azure environment, and simulation results were displayed through web page. Based on this study, the Nakdong River real-time runoff analysis system, which consisted of a real-time data server, calculation node (Azure), and user PC, could be developed. The system performance was more dependent on the CPU than RAM. Disk I/O and calculation bottlenecks could be resolved by distributing disk I/O and calculation processes, respectively, and simulation runtime could thereby be decreased. The study results could be referenced to construct a large watershed runoff analysis system using a distributed model with high resolution spatial and hydrological data.

Development of Basin-wide runoff Analysis Model for Integrated Real-time Water Management (실시간 물 관리 운영을 위한 유역 유출 모의 모형 개발)

  • Hwang, Man-Ha;Maeng, Sung-Jin;Ko, Ick-Hwan;Park, Jeong-In;Ryoo, So-Ra
    • Proceedings of the Korean Society of Agricultural Engineers Conference
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    • 2003.10a
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    • pp.507-510
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    • 2003
  • The development of a basin-wide runoff analysis model is to analysis monthly and daily hydrologic runoff components including surface runoff, subsurface runoff, return flow, etc. at key operation station in the targeted basin. A short-term water demand forecasting technology will be developed taking into account the patterns of municipal, industrial and agricultural water uses. For the development and utilization of runoff analysis model, relevant basin information including historical precipitation and river water stage data, geophysical basin characteristics, and water intake and consumptions needs to be collected and stored into the hydrologic database of Integrated Real-time Water Information System. The well-known SSARR model was selected for the basis of continuous daily runoff model for forecasting short and long-term natural flows.

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A Stochastic Nonlinear Analysis of Daily Runoff Discharge Using Artificial Intelligence Technique (인공지능기법을 이용한 일유출량의 추계학적 비선형해석)

  • 안승섭;김성원
    • 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.

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The Study on the Analysis of Stormwater Runoff Using RMS (Remote Monitoring System) (원격수위계측기를 이용한 강우유출 분석에 관한 연구)

  • Ham, Kwang-Jun;Kim, Joon-Hyun;Yi, Geon-Ho;Choi, Ji-Yong;Jeong, Ui-Ho
    • Journal of Environmental Impact Assessment
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    • v.13 no.6
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    • pp.285-294
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    • 2004
  • The purpose of this study is to understand the quantitative change of water resources using RMS(Remote Monitoring System) which takes real time data with high reliability. Also, the characteristic of stormwater runoff was understood by the application of the above system for three streams (Jiam, Yulmun, and Gongji stream) in Chuncheon City. The detailed results of these studies are as follows; RMS(Remote Monitoring System) was constructed by the combination of the automatic water-level meter, which measures water-level of streams at all times, and the wireless communication system sending real-time data from the meter. This system is used to evaluate the stormwater runoff in watersheds and the quantitative changes of streams. It is possible to overcome the limit of field investigations needed, which takes a lot of manpower and time, and it is very efficient to provide the reliable flowrate data. Also, it can be applied to the disaster prevention system for flood because the change of flowrate in stream is monitored at real-time. For 3 streams with different watershed characteristics, correlation equations induced from the relation analysis results. In terms of the relation between water-level and flowrate, flowrate was increased rapidly as the water-level rises in case of small watershed and steep slope. The application results of the proposed system for 3 streams (Jiam, Yulmun, Gongji) in Chuncheon city are as follows; The remote monitoring system was very useful for acquisition of the flow rate in stream that are basic data to understand pollutants runoff in watershed. In case of no-rainy day, the runoff ratio for pollutant loading rate was the highest level in Yulmun stream(BOD:2.3%, TN:20.2%, TP:1.2%). So, it shows the management of pollution source is needed such as rehabilitation of sewer line. Runoff ratio of total phosphorus by rainfall in Gongji watershed was increased about 19 times than no-rainy day, which is estimated as the influence of sewer overflow.

Urban Watershed Runoff Analysis Using Urban Runoff Models (도시유출 모형을 이용한 도시화 유역의 유출 해석)

  • Jeong, Dong-Guk;Lee, Beom-Hui
    • Journal of Korea Water Resources Association
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    • v.36 no.1
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    • pp.75-85
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    • 2003
  • Urban rainfall-runoff procedures are more complex than the agricultural procedures due to the spreading and development of town. And the applications of theses models are more difficult due to the change of real basins. In this study, I applied SWMM and Expert System to get runoff characteristics of an urbanized basin. Noen in Daejeon is selected as a study basin. Real basin data of facilities, rainfall, runoff, and various rainfall intensity equations are used. An Expert System is used to get the parameters of this model. These results can be applied to analyze the reaction tendencies of the urban basin with the time distributions of design rainfall and the urbanization.

Development & Evaluation of Real-time Ensemble Drought Prediction System (실시간 앙상블 가뭄전망정보 생산 체계 구축 및 평가)

  • Bae, Deg-Hyo;Ahn, Joong-Bae;Kim, Hyun-Kyung;Kim, Heon-Ae;Son, Kyung-Hwan;Cho, Se-Ra;Jung, Ui-Seok
    • Atmosphere
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    • v.23 no.1
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    • pp.113-121
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    • 2013
  • The objective of this study is to develop and evaluate the system to produce the real-time ensemble drought prediction data. Ensemble drought prediction consists of 3 processes (meteorological outlook using the multi-initial conditions, hydrological analysis and drought index calculation) therefore, more processing time and data is required than that of single member. For ensemble drought prediction, data process time is optimized and hardware of existing system is upgraded. Ensemble drought data is estimated for year 2012 and to evaluate the accuracy of drought prediction data by using ROC (Relative Operating Characteristics) analysis. We obtained 5 ensembles as optimal number and predicted drought condition for every tenth day i.e. 5th, 15th and 25th of each month. The drought indices used are SPI (Standard Precipitation Index), SRI (Standard Runoff Index), SSI (Standard Soil moisture Index). Drought conditions were determined based on results obtained for each ensemble member. Overall the results showed higher accuracy using ensemble members as compared to single. The ROC score of SRI and SSI showed significant improvement in drought period however SPI was higher in the demise period. The proposed ensemble drought prediction system can be contributed to drought forecasting techniques in Korea.

Real-time Recursive Forecasting Model of Stochastic Rainfall-Runoff Relationship (추계학적 강우-유출관계의 실시간 순환예측모형)

  • 박상우;남선우
    • Water for future
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    • v.25 no.4
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    • pp.109-119
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    • 1992
  • The purpose of this study is to develop real-time streamflow forecasting models in order to manage effectively the flood warning system and water resources during the storm. The stochastic system models of the rainfall-runoff process using in this study are constituted and applied the Recursive Least Square and the Instrumental Variable-Approximate Maximum Likelihood algorithm which can estimate recursively the optimal parameters of the model. Also, in order to improve the performance of streamflow forecasting, initial values of the model parameter and covariance matrix of parameter estimate errors were evaluated by using the observed historical data of the hourly rainfall-runoff, and the accuracy and applicability of the models developed in this study were examined by the analysis of the I-step ahead streamflow forecasts.

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