• Title/Summary/Keyword: Runoff forecast

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Real-time Flood Forecasting Model Based on the Condition of Soil Moisture in the Watershed (유역토양수분 추적에 의한 실시간 홍수예측모형)

  • 김태철;박승기;문종필
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.37 no.5
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    • pp.81-89
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    • 1995
  • One of the most difficult problem to estimate the flood inflow is how to understand the effective rainfall. The effective rainfall is absolutely influenced by the condition of soil moisture in the watershed just before the storm event. DAWAST model developed to simulate the daily streamflow considering the meteologic and geographic characteristics in the Korean watersheds was applied to understand the soil moisture and estimate the effective rainfall rather accurately through the daily water balance in the watershed. From this soil moisture and effective rainfall, concentration time, dimensionless hydrograph, and addition of baseflow, the rainfall-runoff model for flood flow was developed by converting the concept of long-term runoff into short-term runoff. And, real-time flood forecasting model was also developed to forecast the flood-inflow hydrograph to the river and reservoir, and called RETFLO model. According to the model verification, RETFLO model can be practically applied to the medium and small river and reservoir to forecast the flood hydrograph with peak discharge, peak time, and volume. Consequently, flood forecasting and warning system in the river and the reservoir can be greatly improved by using personal computer.

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Verification of Precipitation Forecast Model and Application of Hydrology Model in Kyoungan-chun Basin (경안천 유역에 대한 강수예보모델의 검증 및 수문모형활용)

  • Choi, Ji-Hye;Kim, Young-Hwa;Nam, Kyung-Yeub;Oh, Sung-Nam
    • Journal of Korea Water Resources Association
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    • v.39 no.3 s.164
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    • pp.215-226
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    • 2006
  • In this study, we performed verification of VSRF (Very Short Range Forecast of precipitation) model and application of NWSPC (National Weather Service PC) rainfall-runoff model in Kyoungan-chun basin. We used two methods for verification of VSRF model. The first method is a meteorological verification that evaluates the special quality feature for rain amount between AWS and VSRF model over Kyoungan-chun basin, while second method is a hydrological verification that compares the calculated Mean Area Precipitation (MAP) between AWS and VSRF Quantitatively. This study examines the usefulness of VSRF precipitation forecasting model data in NWSPC hydrological model. As a result, correlation coefficient is over 0.6 within 3 hour lead time. It represents that the forecast results from VSRF are useful for water resources application.

A Study on the Application of Flood Disaster Management Using GIS

  • Jeong, In Ju;Kim, Sang Young
    • Proceedings of the Korea Water Resources Association Conference
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    • 2004.05b
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    • pp.111-123
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    • 2004
  • Recently, though damage caused by intensive rainfall and typhoon happens frequently, we could not forecast or predict a disaster, due to the difficulty of obtaining exact information about it. For efficient disaster management, the most urgent need is the preparation of a flood forecast-warning system. Therefore, we need to provide a program that has the ability of inundation analysis and flood forecast-warning using a geographic information system, and using domestic technology rather than that from foreign countries. In this research, we constructed a FDMS(Flood Disaster Management System) that is able to analyze real-time inundation data, and usins the GIS(Ceographic Information System) with prompt analyzing of hydrologic-topographical parameters and runoff-computation. Moreover, by expressing inundation analysis in three-dimensions, we were able to get to the inundation area with ease. Finally, we expect that the application of this method in the (food forecast-warning system will have great role in reducing casualties and damage.

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Application of Urban Stream Discharge Simulation Using Short-term Rainfall Forecast (단기 강우예측 정보를 이용한 도시하천 유출모의 적용)

  • Yhang, Yoo Bin;Lim, Chang Mook;Yoon, Sun Kwon
    • Journal of The Korean Society of Agricultural Engineers
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    • v.59 no.2
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    • pp.69-79
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    • 2017
  • In this study, we developed real-time urban stream discharge forecasting model using short-term rainfall forecasts data simulated by a regional climate model (RCM). The National Centers for Environmental Prediction (NCEP) Climate Forecasting System (CFS) data was used as a boundary condition for the RCM, namely the Global/Regional Integrated Model System(GRIMs)-Regional Model Program (RMP). In addition, we make ensemble (ESB) forecast with different lead time from 1-day to 3-day and its accuracy was validated through temporal correlation coefficient (TCC). The simulated rainfall is compared to observed data, which are automatic weather stations (AWS) data and Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA 3B43; 3 hourly rainfall with $0.25^{\circ}{\times}0.25^{\circ}$ resolution) data over midland of Korea in July 26-29, 2011. Moreover, we evaluated urban rainfall-runoff relationship using Storm Water Management Model (SWMM). Several statistical measures (e.g., percent error of peak, precent error of volume, and time of peak) are used to validate the rainfall-runoff model's performance. The correlation coefficient (CC) and the Nash-Sutcliffe efficiency (NSE) are evaluated. The result shows that the high correlation was lead time (LT) 33-hour, LT 27-hour, and ESB forecasts, and the NSE shows positive values in LT 33-hour, and ESB forecasts. Through this study, it can be expected to utilizing the real-time urban flood alert using short-term weather forecast.

Real Time Flood Forecasting Using Artificial Neural Networks (인공신경망 이론을 이용한 실시간 홍수량 예측 및 해석)

  • Kang, Moon-Seong;Park, Seung-Woo
    • Proceedings of the Korean Society of Agricultural Engineers Conference
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    • 2002.10a
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    • pp.277-280
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    • 2002
  • An artificial neural network model was developed to analyze and forecast real time river runoff from the Naju watershed, in Korea. Model forecasts are very accurate (i.e., relative error is less than 3% and $R^2$ is great than 0.99) for calibration data sets. Increasing the time horizon for validation data sets, thus making the model suitable for flood forecasting, decreases the accuracy of the model. The resulting optimal EBPN models for forecasting real time runoff consists of ten rainfall and four and ten runoff data (ANN0410 and ANN1010 models). Performances of the ANN0410 and ANN1010 models remain satisfactory up to 6 hours (i.e., $R^2$ is great than 0.92).

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Combining Four Elements of Precipitation Loss in a Watershed (유역내 네가지 강수손실 성분들의 합성)

  • Yoo, Ju-Hwan
    • Proceedings of the Korea Water Resources Association Conference
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    • 2012.05a
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    • pp.200-204
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    • 2012
  • In engineering hydrology, an estimation of precipitation loss is one of the most important issues for successful modeling to forecast flooding or evaluate water resources for both surface and subsurface flows in a watershed. An accurate estimation of precipitation loss is required for successful implementation of rainfall-runoff models. Precipitation loss or hydrological abstraction may be defined as the portion of the precipitation that does not contribute to the direct runoff. It may consist of several loss elements or abstractions of precipitation such as infiltration, depression storage, evaporation or evapotranspiration, and interception. A composite loss rate model that combines four loss rates over time is derived as a lumped form of a continuous time function for a storm event. The composite loss rate model developed is an exponential model similar to Horton's infiltration model, but its parameters have different meanings. In this model, the initial loss rate is related to antecedent precipitation amounts prior to a storm event, and the decay factor of the loss rate is a composite decay of four losses.

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Development of Real-Time River Flow Forecasting Model with Data Assimilation Technique (자료동화 기법을 연계한 실시간 하천유량 예측모형 개발)

  • Lee, Byong-Ju;Bae, Deg-Hyo
    • Journal of Korea Water Resources Association
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    • v.44 no.3
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    • pp.199-208
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    • 2011
  • The objective of this study is to develop real-time river flow forecast model by linking continuous rainfall-runoff model with ensemble Kalman filter technique. Andong dam basin is selected as study area and the model performance is evaluated for two periods, 2006. 7.1~8.18 and 2007. 8.1~9.30. The model state variables for data assimilation are defined as soil water content, basin storage and channel storage. This model is designed so as to be updated the state variables using measured inflow data at Andong dam. The analysing result from the behavior of the state variables, predicted state variable as simulated discharge is updated 74% toward measured one. Under the condition of assuming that the forecasted rainfall is equal to the measured one, the model accuracy with and without data assimilation is analyzed. The model performance of the former is better than that of the latter as much as 49.6% and 33.1% for 1 h-lead time during the evaluation period, 2006 and 2007. The real-time river flow forecast model using rainfall-runoff model linking with data assimilation process can show better forecasting result than the existing methods using rainfall-runoff model only in view of the results so far achieved.

An analysis of effects of seasonal weather forecasting on dam reservoir inflow prediction (장기 기상전망이 댐 저수지 유입량 전망에 미치는 영향 분석)

  • Kim, Seon-Ho;Nam, Woo-Sung;Bae, Deg-Hyo
    • Journal of Korea Water Resources Association
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    • v.52 no.7
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    • pp.451-461
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    • 2019
  • The dam reservoir inflow prediction is utilized to ensure for water supply and prevent future droughts. In this study, we predicted the dam reservoir inflow and analyzed how seasonal weather forecasting affected the accuracy of the inflow for even multi-purpose dams. The hindcast and forecast of GloSea5 from KMA were used as input for rainfall-runoff models. TANK, ABCD, K-DRUM and PRMS models which have individual characteristics were applied to simulate inflow prediction. The dam reservoir inflow prediction was assessed for the periods of 1996~2009 and 2015~2016 for the hindcast and forecast respectively. The results of assessment showed that the inflow prediction was underestimated by comparing with the observed inflow. If rainfall-runoff models were calibrated appropriately, the characteristics of the models were not vital for accuracy of the inflow prediction. However the accuracy of seasonal weather forecasting, especially precipitation data is highly connected to the accuracy of the dam inflow prediction. It is recommended to consider underestimation of the inflow prediction when it is used for operations. Futhermore, for accuracy enhancement of the predicted dam inflow, it is more effective to focus on improving a seasonal weather forecasting rather than a rainfall-runoff model.

Rainfall Forecasting Using Satellite Information and Integrated Flood Runoff and Inundation Analysis (II): Application and Analysis (위성정보에 의한 강우예측과 홍수유출 및 범람 연계 해석 (II): 적용 및 분석)

  • Choi, Hyuk Joon;Han, Kun Yeun;Kim, Gwangseob
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.6B
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    • pp.605-612
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    • 2006
  • In this study(II), The developed rainfall forecast model was applied to the NakDong River Basin for the heavy rainfall on 6th to 16th of August in 2002. The results demonstrated that the rainfall forecasts of 3 hours lead time showed good agreement with observed data. The inundation aspect of simulation depends on actual levee failure in the same basin. Rainfall forecasts were used for flood amount computation in the target watershed. Also the flood amount in the target watershed was used on boundary condition for flood inundation simulation in a protected lowland and a river. The results of simulation are consistent with actuality inundation traces and flood level data of the target watershed. This study provides practical applicability of satellite data in rainfall forecast of extreme events such as heavy rainfall or typhoon. Also this study presented an advanced integrated model of rainfall, runoff, and inundation analysis which can be applicable for flood disaster prevention and mitigation.