Velocity predictions in compound channels with vegetated floodplains using genetic programming

Harris, Emmanuel; Babovic, Vladan; Falconer, Roger Alexander

doi:10.1080/15715124.2003.9635198

Cited by 64 publications

(26 citation statements)

References 11 publications

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“…This condition, which is typical in river systems with extreme discharge conditions and extensive floodplains (Augustijn et al, 2008;Harris et al, 2003), has been less frequently studied. Previous studies (Augustijn et al, 2008) found that the equations proposed and tested for medium submergences are not sufficiently accurate for high submergences.…”

Section: Introductionmentioning

confidence: 99%

Use of conventional flow resistance equations and a model for the Nikuradse roughness in vegetated flows at high submergence

Gualtieri

Felice

Pasquino

et al. 2017

Journal of Hydrology and Hydromechanics

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This study examines the problem of flow resistance due to rigid vegetation in open channel flow. The reliability of the conventional flow resistance equations (i.e. Keulegan, Manning and Chézy-Bazin) for vegetated flows at high submergence, i.e. h/k >5, (where h = flow depth and k = vegetation height) is assessed. Several modern flow resistance equations based on a two-layer approach are examined, showing that they transform into the conventional equations at high submergences. To compare the conventional flow resistance equations at high submergences, an experimental methodology is proposed and applied to the experimental data reported in the literature and collected for this study. The results demonstrate the reliability of the Keulegan equation in predicting the flow resistance. Based on the obtained results, a model to evaluate the Nikuradse equivalent sand-grain roughness, k N , starting from the vegetation height and density, is proposed and tested.

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Section: Introductionmentioning

confidence: 99%

Use of conventional flow resistance equations and a model for the Nikuradse roughness in vegetated flows at high submergence

Gualtieri

Felice

Pasquino

et al. 2017

Journal of Hydrology and Hydromechanics

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“…That research direction led to the development of more general framework for the introduction of background knowledge in data-driven knowledge discovery by GP (e.g. Keijzer and Babovic, [30] Harris, Babovic, [31] Baptist, Babovic [32] ), and the work of Meshgi, Schmitter [33] who used genetic programming to approximate stream base-flow time series. Also, it is worth mentioning the effort of Giustolisi and Savic, [34] where they build upon Giustolisi, [29] and applied symbolic regression to find an explicit polynomial function for the Colebrook-White friction factor (Colebrook & White, 1937); their findings showed that an eleven-term polynomial plus the bias presented the best results.…”

Section: Related Workmentioning

confidence: 99%

Can we obtain viable alternatives to Manning’s equation using genetic programming?

Gaitán

Balaji

Moore

2016

AIR

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Applied water research, like the one derived from open-channel hydraulics, traditionally links empirical formulas to observational data; for example Manning's formula for open channel flow driven by gravity relates the discharge (Q), cross-sectional average velocity (V ), the hydraulic radius (R), and the slope of the water surface (S) with a friction coefficient n, characteristic of the channel's surface needed in the location of interest. Here we use Genetic Programming (GP), a machine learning technique inspired by nature's evolutionary rules, to derive empirical relationships based on synthetic datasets of the aforementioned parameters. Specifically, we evaluated if Manning's formula could be retrieved from datasets with: a) 300 pentads of A, n, R, S, and Q (from Manning's equation), b) from datasets containing an uncorrelated variable and the parameters from (a), and c) from a dataset containing the parameters from (b) but using values of Q containing noise. The cross-validated results show success retrieving the functional form from the synthetic data in the first two experiments, and a more complex solution of Q for the third experiment. The results encourage the application of GP on problems where traditional empirical relationships show high biases or are non-parsimonious. The results also show alternative flow equations that might be used in the absence of one or more predictors; however, these equations should be used with caution outside of the training intervals.

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“…In Figures 5 and 6, the measured and calculated data with (6) and (8) are plotted against the identity function to obtain the correlation coefficient (r Tw,Tw1 ), checking the linearity in the fitting. Results given by Figures 3-6 show an improvement in calculated data when standardization is applied; residuals are slightly reduced, fluctuations become softer, and this is verified by the correlation coefficient.…”

Section: One-hour Average Datamentioning

confidence: 99%

“…Evolutionary computing has been widely used in hydraulics and hydrology, for example, the studies ofSavic et al [1], Madsen et al [2], and Dorado et al [3], related to rainfallrunoff processes, modeling of an urban aquifer as was discussed by Hong and Rosen [4], or the modifications of genetic programming algorithms attempting to get an agreement with the problem dimension in natural and compounded channels as applied by Keijzer and Babovic [5], Harris et al [6], and Keijzer et al [7]. On the other hand, water temperature is an important parameter to consider because of the changes it can experience due to human activities.…”

Section: Introductionmentioning

confidence: 99%

Genetic Programming and Standardization in Water Temperature Modelling

Arganis¹,

Val

Prats

et al. 2009

Advances in Civil Engineering

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An application of Genetic Programming (an evolutionary computational tool) without and with standardization data is presented with the aim of modeling the behavior of the water temperature in a river in terms of meteorological variables that are easily measured, to explore their explanatory power and to emphasize the utility of the standardization of variables in order to reduce the effect of those with large variance. Recorded data corresponding to the water temperature behavior at the Ebro River, Spain, are used as analysis case, showing a performance improvement on the developed model when data are standardized. This improvement is reflected in a reduction of the mean square error. Finally, the models obtained in this document were applied to estimate the water temperature in 2004, in order to provide evidence about their applicability to forecasting purposes.

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Velocity predictions in compound channels with vegetated floodplains using genetic programming

Cited by 64 publications

References 11 publications

Use of conventional flow resistance equations and a model for the Nikuradse roughness in vegetated flows at high submergence

Use of conventional flow resistance equations and a model for the Nikuradse roughness in vegetated flows at high submergence

Can we obtain viable alternatives to Manning’s equation using genetic programming?

Genetic Programming and Standardization in Water Temperature Modelling

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