Citation: Sihag, P.; Nouri, M.;
Ahmadpari, H.; Seyedzadeh, A.; Kisi,
O. Approximation of the Discharge
Coefficient of Radial Gates Using
Metaheuristic Regression
Approaches. Sustainability 2022, 14,
15145. https://doi.org/10.3390/
su142215145
Academic Editors: Andrzej Walega
and Miklas Scholz
Received: 24 September 2022
Accepted: 11 November 2022
Published: 15 November 2022
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sustainability
Article
Approximation of the Discharge Coefficient of Radial Gates
Using Metaheuristic Regression Approaches
Parveen Sihag
1
, Meysam Nouri
2,3
, Hedieh Ahmadpari
4
, Amin Seyedzadeh
5
and Ozgur Kisi
6,7,
*
1
Department of Civil Engineering, Chandigarh University, Punjab 43521-15862, India
2
Department of Water Engineering, Faculty of Agriculture, Urmia University, Urmia 57561-51818, Iran
3
Department of Civil Engineering, Saeb University, Abhar 45717-74783, Iran
4
Department of Irrigation and Reclamation Engineering, College of Aburaihan, University of Tehran,
Tehran 57561-51818, Iran
5
Department of Water Engineering, Faculty of Agriculture, Fasa University, Fasa 57561-51818, Iran
6
Department of Civil Engineering, Technical University of Lübeck, 23562 Lübeck, Germany
7
Department of Civil Engineering, Ilia State University, 0162 Tbilisi, Georgia
* Correspondence: ozgur.kisi@th-luebeck.de
Abstract: Radial gates are widely used for agricultural water management, flood controlling, etc. The
existence of methods for the calculation of the discharge coefficient (C
d
) of such gates are complex
and they are based on some assumptions. The development of new usable and simple models is
needed for the prediction of C
d
. This study investigates the viability of a metaheuristic regression
method, the Gaussian Process (GP), for the determination of the discharge coefficient of radial gates.
For this purpose, a total of 2536 experimental data were compiled that cover a wide range of all the
effective parameters. The results of GP were compared with the Group Method of Data Handling
(GMDH), Multivariate Adaptive Regression Splines (MARS), and linear and nonlinear regression
models for predicting C
d
of radial gates in both free-flow and submerged-flow conditions. The results
revealed that the radial basis function-based GP model performed the best in free-flow condition
with a Correlation Coefficient (CC) of 0.9413 and Root Mean Square Error (RMSE) of 0.0190 while the
best accuracy was obtained from the Pearson VII kernel function-based GP model for the submerged
flow condition with a CC of 0.9961 and RMSE of 0.0132.
Keywords: gates; submerged flow; free-flow; discharge coefficient; estimation models
1. Introduction
Flow controller and flow regulator structures play important roles in flow distribution
in irrigation systems and the success rate of irrigation systems depends on the performance
of these structures [1]. The maximum discharge condition is the main criteria for designing
irrigation systems, while in practice, in the majority of cases, the maximum discharge is not
observed. So, in such systems, flow controller and flow regulator structures are used for
providing gravity irrigation conditions and for setting the water level at required water
levels [2]. Gates are the most common types of structures that are commonly utilized in
irrigation networks [3]. In addition, flow discharge measurement is another important
application of gates in these systems, and estimation of flow discharge under gates can
be classified as one of the most important issues in hydraulic engineering [3]. In other
words, the precision of flow discharge information has a direct influence on operational
management and water-saving policies [4]. According to gate applications all over the
world, the hydraulic performance of gates has been studied by many researchers. Gibson [5]
and Henry [6] carried out the earliest studies on gates. Henry [6] presented the slice gate
discharge coefficient (C
d
) in the form of a graph considering a dimensionless form of
effective parameters in both submerged and free-flow conditions. The study by Henry [6]
is the basis of some other studies and some other C
d
equations. After that, Rajaratnam
Sustainability 2022, 14, 15145. https://doi.org/10.3390/su142215145 https://www.mdpi.com/journal/sustainability