scholarly journals Investigation of flood routing by a dynamic wave model in trapezoidal channels

2017 ◽  
Author(s):  
B. A. Sulistyono ◽  
L. H. Wiryanto
Keyword(s):  
Wave Model ◽  
Flood Routing ◽  
Dynamic Wave

scholarly journals Evaluation of the Simplified Dynamic Wave, Diffusion Wave and the Full Dynamic Wave Flood Routing Models

2018 ◽  
Vol 7 (2) ◽  
pp. 14 ◽  
Author(s):  
John Perdikaris ◽  
Bahram Gharabaghi ◽  
Ramesh Rudra
Keyword(s):  
Wave Model ◽  
Ease Of Use ◽  
Flood Routing ◽  
Diffusion Wave ◽  
Event Simulation ◽  
Wave Diffusion ◽  
Wave Models ◽  
Accuracy Of Prediction ◽  
Routing Models ◽  
Dynamic Wave

The accuracy of prediction and ease of use of the three popular flood routing models; simplified dynamic Wave, diffusion wave, and full dynamic wave were evaluated. The models were evaluated along a reach of the Credit River Watershed, in Southern Ontario, Canada. The simplified dynamic wave model showed better accuracy and easier formulation when compared against the diffusion wave and the full dynamic wave models. Indicating that the simplified dynamic wave model can be applied to reaches where the diffusion wave and the full dynamic wave models may not be applicable. The principle novel contributions of the paper are (a) the extension of the flood routing formulations by Keskin and Agiralioglu, (b) the use of a prismatic channel and floodplain with varying top-widths, (c) the validation of the methodology through the application of an event simulation to an actual river reach, and (d) comparison of the modeling results to those obtained using the full dynamic wave model and the diffusion wave models.

Modèle de prévision pour la gestion en temps réel : application aux réseaux d'assainissement

2000 ◽  
Vol 27 (2) ◽  
pp. 327-337
Author(s):  
Abderrahman Assabbane ◽  
Saad Bennis
Keyword(s):  
Kalman Filter ◽  
Transfer Function ◽  
Real Time ◽  
Time Management ◽  
Wave Model ◽  
Transfer Function Model ◽  
Function Model ◽  
Proposed Model ◽  
Kalman Filter Algorithm ◽  
Dynamic Wave

The work presented here aims at developing a flow forecast model dedicated to real-time management. The proposed model is based on the notion of a transfer function for a linear system identified through the Kalman filter algorithm. In a first step, the transfer function model is linked to the Muskingum semi-empirical model; then it is modified to eliminate the autoregressive component. The Kalman filter algorithm allows the parameters of the proposed model to be updated upon the reception of each new measure with respect to the forecast errors observed in real time. To analyze the performance of the proposed model, its results are compared with those obtained using the dynamic wave model and the simplified kinematic wave model. Because of the absence of measured downstream flow values corresponding to the input hydrograph, the results from the dynamic wave model are used as reference values to evaluate the performance of the other models. These results are also used with the addition of noises to simulate measured values and feed, in "real-time," the identification algorithm of the transfer function in order to adjust, a posteriori, its parameters according to its differences in the flow prediction. The results obtained by the transfer function model agree with those obtained by the dynamic model following the three performance criteria employed. The Nash coefficient and the ratio between the peak flows are close to unity in all of the cases. Also, the lag between the peak flows estimated by the two models is negligible.Key words: waste water networks, real-time management, flow propagation models, forecast, transfer function, Kalman filter.[Journal Translation]

scholarly journals ESTIMATING THE 2011 LARGEST FLOOD DISCHARGE AT THE KUMANO RIVER USING THE 2D DYNAMIC WAVE MODEL AND PARTICLE FILTERS

2013 ◽  
Vol 69 (4) ◽  
pp. I_163-I_168 ◽  
Author(s):  
Yeonsu KIM ◽  
Yasuto TACHIKAWA ◽  
Sunmin KIM ◽  
Michiharu SHIIBA ◽  
Seong Jin NOH ◽  
...  
Keyword(s):  
Particle Filters ◽  
Wave Model ◽  
Flood Discharge ◽  
Dynamic Wave

scholarly journals Investigation of Flood Routing Using Variable Parameter Kinematic Wave Model (VPKWM) for Non-Prismatic Natural Channel in an Ungauged Basin

2020 ◽  
Vol 10 (2) ◽  
pp. 111-118
Author(s):  
B. Bharali ◽  
U.K. Misra
Keyword(s):  
Variable Parameter ◽  
Wave Model ◽  
Flood Routing ◽  
Peak Time ◽  
Kinematic Wave ◽  
Ungauged Basin ◽  
Venant Equation ◽  
Channel Slope ◽  
Rainfall Runoff Model ◽  
Kinematic Wave Model

AbstractThis research concerns about the development and application of Variable Parameter Kinematic Wave Numerical model (VPKWM) based on 1-D Saint-Venant equation, to study the behaviour of the propagation of a flood wave in Non-prismatic natural waterways in an ungauged basin. The channel slope and wetted perimeter are considered as variable because of the irregularity of the boundary of the channel and the change in magnitude of discharge. The scarcity of reliable inflow data at upstream is a serious problem for the flood routing process in an ungauged basin. In this study the inflow hydrograph and lateral inflow hydrographs are obtained using SCS-CN method as rainfall runoff model. The performance of the model assessed considering four parameters such as root mean square error (RMSE), peak discharge, peak time and total volume. The results indicated that the VPKWM for non-prismatic channel provided reasonable output compared with the observed data.

scholarly journals Application of newtonian nudging data assimilation method in hydrodynamic model of flood flow in the lower Biebrza basin

2012 ◽  
Vol 34 (2) ◽  
pp. 91-105 ◽  
Author(s):  
Dorota Mirosław-Świątek
Keyword(s):  
Boundary Condition ◽  
Data Assimilation ◽  
Water Table ◽  
Flow Model ◽  
Wave Model ◽  
Spring Flood ◽  
One Dimensional ◽  
Using Data ◽  
Flood Flow ◽  
Dynamic Wave

Abstract The paper presents a 1D hydrodynamic flood flow model employing a data assimilation procedure based on Newtonian nudging. Data assimilation was used to determine correctly the upstream boundary condition defined as a discharge hydrograph. In the model developed, “nudging to individual observations” method was used. The data chosen for assimilation were water table levels recorded by a D-Diver automatic sensor installed in the river channel c. 1.5 km below a computational cross-section opening the analysed stretch of the river and the adjacent valley. This hydrological model of flood flow containing the data assimilation procedure is based on a one-dimensional Saint-Venant system of equations (dynamic wave model). The calculations were performed for the 2010 spring flood event at a 20-km stretch of the river and the floodplain in the upper part of the Lower Biebrza Basin. Modifying the boundary condition by using data assimilation has dramatically improved the accuracy of water table predictions during floods in the area of the Lower Biebrza Basin.

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