Flood routing models in confluent and dividing channels

Hydrologic flood routing models have been, and continue to be, the primary tool of the flood forecaster. However, any advancement in our ability to model a wider variety of flow scenarios, including extreme flood events (for which no calibration may be available), dam break floods, or ice-related events, necessitates the use of deterministic (hydraulic) models. A more fundamental advantage of hydraulic flood routing models over hydrologic models, in terms of less dynamic events, is that output describing flood hydrographs between gauge sites is produced. Such output is valuable in flow forecasting, and as input to the hydraulic analyses required for floodplain delineation. To date, hydraulic flood routing models have not gained widespread use for two key reasons. First, they present a particularly challenging numerical problem. Second, they are seen to be data intensive, requiring geometric data over the entire modelled reach. The former problem is no longer the primary concern, as recent research has led to the development of numerous robust computational schemes. The intensive data requirements of hydraulic models are much more limiting from a practical perspective, as flood routing typically involves very long reaches and the cost of obtaining sufficient cross section data is generally prohibitive. In this investigation, the reliability of a hydraulic flood routing model based on limited cross section survey data is evaluated for the case of the Peace River in British Columbia and Alberta. Based on the successful results of these investigations, it is concluded that a reliable hydraulic flood routing model can be developed with limited field data supplemented with topographic map data. Key words: flood routing, St. Venant equations, Peace River, characteristic-dissipative Galerkin scheme, finite element method.

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A new partitioning approach for nonlinear Muskingum flood routing models with lateral flow contribution

Journal of Hydrology ◽

10.1016/j.jhydrol.2017.07.050 ◽

2017 ◽

Vol 553 ◽

pp. 142-159 ◽

Cited By ~ 6

Author(s):

M. Tamer Ayvaz ◽

Gurhan Gurarslan

Keyword(s):

Lateral Flow ◽

Flood Routing ◽

Routing Models

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Development of a New 8-Parameter Muskingum Flood Routing Model with Modified Inflows

Water ◽

10.3390/w13223170 ◽

2021 ◽

Vol 13 (22) ◽

pp. 3170

Author(s):

Eui Hoon Lee

Keyword(s):

Flood Routing ◽

The Self ◽

Correction Algorithm ◽

New Model ◽

Vision Correction ◽

Proposed Model ◽

Calculation Process ◽

Different Types ◽

And Storage ◽

Routing Models

Flood routing can be subclassified into hydraulic and hydrologic flood routing; the former yields accurate values but requires a large amount of data and complex calculations. The latter, in contrast, requires only inflow and outflow data, and has a simpler calculation process than the hydraulic one. The Muskingum model is a representative hydrologic flood routing model, and various versions of Muskingum flood routing models have been studied. The new Muskingum flood routing model considers inflows at previous and next time during the calculation of the inflow and storage. The self-adaptive vision correction algorithm is used to calculate the parameters of the proposed model. The new model leads to a smaller error compared to the existing Muskingum flood routing models in various flood data. The sum of squares obtained by applying the new model to Wilson’s flood data, Wang’s flood data, the flood data of River Wye from December 1960, Sutculer flood data, and the flood data of River Wyre from October 1982 were 4.11, 759.79, 18,816.99, 217.73, 38.81 (m3/s)2, respectively. The magnitude of error for different types of flood data may be different, but the error may be large if the flow rate of the flood data is large.

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

Earth Science Research ◽

10.5539/esr.v7n2p14 ◽

2018 ◽

Vol 7 (2) ◽

pp. 14 ◽

Cited By ~ 4

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.

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Addressing Spatial Heterogeneity in the Discrete Generalized Nash Model for Flood Routing

Water ◽

10.3390/w13213133 ◽

2021 ◽

Vol 13 (21) ◽

pp. 3133

Author(s):

Bao-Wei Yan ◽

Yi-Xuan Zou ◽

Yu Liu ◽

Ran Mu ◽

Hao Wang ◽

...

Keyword(s):

Spatial Heterogeneity ◽

Cross Sections ◽

Model Performance ◽

Flood Routing ◽

Ungauged Basins ◽

Nash Model ◽

Model Efficiency ◽

S Curve ◽

Relative Errors ◽

Routing Models

River flood routing is one of the key components of hydrologic modeling and the topographic heterogeneity of rivers has great effects on it. It is beneficial to take into consideration such spatial heterogeneity, especially for hydrologic routing models. The discrete generalized Nash model (DGNM) based on the Nash cascade model has the potential to address spatial heterogeneity by replacing the equal linear reservoirs into unequal ones. However, it seems impossible to obtain the solution of this complex high order differential equation directly. Alternatively, the strict mathematical derivation is combined with the deeper conceptual interpretation of the DGNM to obtain the heterogeneous DGNM (HDGNM). In this work, the HDGNM is explicitly expressed as a linear combination of the inflows and outflows, whose weight coefficients are calculated by the heterogeneous S curve. Parameters in HDGNM can be obtained in two different ways: optimization by intelligent algorithm or estimation based on physical characteristics, thus available to perform well in both gauged and ungauged basins. The HDGNM expands the application scope, and becomes more applicable, especially in river reaches where the river slopes and cross-sections change greatly. Moreover, most traditional routing models are lumped, whereas the HDGNM can be developed to be semidistributed. The middle Hanjiang River in China is selected as a case study to test the model performance. The results show that the HDGNM outperforms the DGNM in terms of model efficiency and smaller relative errors and can be used also for ungauged basins.

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Mass and momentum conservation in the simplified flood routing models

Journal of Hydrology ◽

10.1016/j.jhydrol.2007.08.017 ◽

2007 ◽

Vol 346 (1-2) ◽

pp. 51-58 ◽

Cited By ~ 14

Author(s):

D. Gąsiorowski ◽

R. Szymkiewicz

Keyword(s):

Momentum Conservation ◽

Flood Routing ◽

Routing Models

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Estimation of Fuzzy Parameters in the Linear Muskingum Model with the Aid of Particle Swarm Optimization

Sustainability ◽

10.3390/su13137152 ◽

2021 ◽

Vol 13 (13) ◽

pp. 7152

Author(s):

Mike Spiliotis ◽

Alvaro Sordo-Ward ◽

Luis Garrote

Keyword(s):

Particle Swarm Optimization ◽

Fitness Function ◽

Particle Swarm ◽

Flood Routing ◽

Performance Criteria ◽

Extension Principle ◽

Swarm Optimization ◽

Muskingum Model ◽

Muskingum Method ◽

Fuzzy Parameters

The Muskingum method is one of the widely used methods for lumped flood routing in natural rivers. Calibration of its parameters remains an active challenge for the researchers. The task has been mostly addressed by using crisp numbers, but fuzzy seems a reasonable alternative to account for parameter uncertainty. In this work, a fuzzy Muskingum model is proposed where the assessment of the outflow as a fuzzy quantity is based on the crisp linear Muskingum method but with fuzzy parameters as inputs. This calculation can be achieved based on the extension principle of the fuzzy sets and logic. The critical point is the calibration of the proposed fuzzy extension of the Muskingum method. Due to complexity of the model, the particle swarm optimization (PSO) method is used to enable the use of a simulation process for each possible solution that composes the swarm. A weighted sum of several performance criteria is used as the fitness function of the PSO. The function accounts for the inclusive constraints (the property that the data must be included within the produced fuzzy band) and for the magnitude of the fuzzy band, since large uncertainty may render the model non-functional. Four case studies from the references are used to benchmark the proposed method, including smooth, double, and non-smooth data and a complex, real case study that shows the advantages of the approach. The use of fuzzy parameters is closer to the uncertain nature of the problem. The new methodology increases the reliability of the prediction. Furthermore, the produced fuzzy band can include, to a significant degree, the observed data and the output of the existent crisp methodologies even if they include more complex assumptions.

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Research and Application on Technology of Flood-Storage and Flood-Detention of Coal Mining Subsidence Area of Suzhou Coal Mine

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.641-642.80 ◽

2014 ◽

Vol 641-642 ◽

pp. 80-83

Author(s):

Jia Zhong Zheng ◽

Mei Zhu ◽

Zheng Long Wang

Keyword(s):

Coal Mining ◽

Dynamic Change ◽

Storage Conditions ◽

Flood Routing ◽

Mining Subsidence ◽

Subsidence Area ◽

The Status ◽

Suzhou City ◽

Change Trend ◽

Coal Mining Subsidence

The artical is based on the investigation of the basis of the status quo of Zhuxianzhuang and Luling coal mining subsidence area in Anhui province Suzhou city(hereinafter referred to as the "Zhu Lu subsidence area"), a preliminary analysis of the dynamic change trend of detention space in Zhu Lu subsidence area, and based on the hysteresis storage conditions of subsidence area, use the flood routing model to simulate the hysteresis effect of storage at different subsidence scenarios of different frequency flood. Finally, using the experience type channel evolution model and peak delay routing model further revealed storage effect on flood process of Zhu Lu subsidence area.

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