A linked simulation–optimization model for simultaneously estimating the Manning’s surface roughness values and their parameter structures in shallow water flows

Ayvaz, M. Tamer

doi:10.1016/j.jhydrol.2013.07.019

Cited by 36 publications

(19 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Other parameters usually require extra in-situ observations to accurately calculate the river slope, or the roughness coefficient that depends on the bed material, and often needs to be calculated empirically. [14] Previous studies used idealized conditions in hydraulic laboratories -constrained by the capacity and flow design limitations from their water tanks/channels, or modeling techniques (e.g., [13,14,46] ). Here, our maximum river discharge is similar to the average discharge of the Yangtze River in China, and we include the usual range of n and S values.…”

Section: Datamentioning

confidence: 99%

See 1 more Smart Citation

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

Gaitán

Balaji

Moore

2016

AIR

View full text Add to dashboard Cite

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.

show abstract

Section: Datamentioning

confidence: 99%

“…Ayvaz [13] and Ding, Jia [14] ) and/or for different riverbed materials (e.g. Candela, Noto [15] ), as even the presence of biological soil crusts can affect the surface roughness, runoff and erodibility of the channel.…”

Section: Introduction 11 Overviewmentioning

confidence: 99%

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

Gaitán

Balaji

Moore

2016

AIR

View full text Add to dashboard Cite

show abstract

“…The ranges of the parameter values have been extensively studied over the last decades [34][35][36]. In order to evaluate the impact of the parameter values on the water flow outputs, we perform 3 simulation configurations for every selected rainfall event, within which the parameters of configuration 2 are set to the optimized values, while the parameters of configurations 1 and 3 are set to their upper limits and lower limits, respectively.…”

Section: Scenario 2: the Influence Of The Calibration Of Typical Modementioning

confidence: 99%

Development and Assessment of the Physically-Based 2D/1D Model “TRENOE” for Urban Stormwater Quantity and Quality Modelling

Bonhomme

Chebbo

2016

Water

View full text Add to dashboard Cite

Abstract:The widespread use of separate stormwater systems requires better understanding of the interactions between urban landscapes and drainage systems. This paper describes a novel attempt of developing urban 2D-surface and 1D-drainage model "TRENOE" for urban stormwater quantity and quality modelling. The physically-based TREX model and the conceptual CANOE model are integrated into the TRENOE platform, highlighting that the roofs of buildings are represented separately from the surface model, but simulated as virtual "sub-basins" in the CANOE model. The modelling approach is applied to a small urban catchment near Paris (Le Perreux sur Marne, 0.12 km 2 ). Simulation scenarios are developed for assessing the influences of different "internal" (model structure, numerical issues) and "external" (parameters, input data) factors on model performance. The adequate numerical precision and the detailed information of land use data are identified as crucial elements of water quantity modelling. Contrarily, the high-resolution topographic data and the common variations of the water flow parameters are not equally significant at the scale of a small urban catchment. Concerning water quality modelling, particle size distribution is revealed to be an important factor, while the empirical USLE equations need to be completed by a raindrop detachment process.

show abstract

“…Ayrıca, problemin çözümü için karar değişkenlerinin özel bir başlangıç değeri almasına ihtiyaç yoktur. Yöntem, günümüze kadar farklı bir çok mühendislik optimizasyon probleminin çözümü için kullanılmıştır [20]- [24]. …”

Section: Parçacık Sürü Optimizasyonuunclassified

Optimum design of reinforced concrete cantilever retaining walls with particle swarm optimization

Kayhan¹,

Demir²

2016

Pamukkale J Eng Sci

View full text Add to dashboard Cite

A linked simulation–optimization model for simultaneously estimating the Manning’s surface roughness values and their parameter structures in shallow water flows

Cited by 36 publications

References 38 publications

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

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

Development and Assessment of the Physically-Based 2D/1D Model “TRENOE” for Urban Stormwater Quantity and Quality Modelling

Optimum design of reinforced concrete cantilever retaining walls with particle swarm optimization

Contact Info

Product

Resources

About