Research Article

Modelling Physical Water Losses in the Urban Water Supply Networks of Balıkesir Province Using Artificial Neural Networks

Number: 3 June 29, 2026
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Modelling Physical Water Losses in the Urban Water Supply Networks of Balıkesir Province Using Artificial Neural Networks

Abstract

Successive sluice gates are designed to maintain a stable discharge rate in open channels despite variations in upstream water levels. This study numerically investigates the hydraulic performance of successive sluice gates under different operational conditions. Four gate configurations and five upstream flow depths were simulated to analyze their flow regulation efficiency. The numerical results were validated against experimental data, revealing differences in outlet discharge of less than 10%, indicating that the simulation model provides reliable accuracy. Following model validation, the computed outflow rates for each configuration were compared with the corresponding design discharge, showing an average deviation of approximately 8% in all tested cases. These results confirm that successive sluice gates are capable of maintaining a nearly constant flow rate, even under fluctuating upstream water levels. Moreover, energy dissipation analysis showed that losses were negligible when only the first gate was active. However, as the upstream depth increased and additional gates were engaged, energy dissipation rose to about 15–22%. Overall, the findings demonstrate that successive sluice gate systems can effectively combine precise flow regulation with adequate energy dissipation, making them suitable for hydraulic structures requiring stable discharge control under variable inflow conditions.

Keywords

References

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Details

Primary Language

English

Subjects

Water Resources and Water Structures

Journal Section

Research Article

Publication Date

June 29, 2026

Submission Date

May 22, 2026

Acceptance Date

June 2, 2026

Published in Issue

Year 2026 Number: 3

APA
Özen, İ., & Yıldırım, G. (2026). Modelling Physical Water Losses in the Urban Water Supply Networks of Balıkesir Province Using Artificial Neural Networks. Turkish Journal of Hydraulic, 3. https://izlik.org/JA44HL43HN
AMA
1.Özen İ, Yıldırım G. Modelling Physical Water Losses in the Urban Water Supply Networks of Balıkesir Province Using Artificial Neural Networks. Turkish Journal of Hydraulic. 2026;(3). https://izlik.org/JA44HL43HN
Chicago
Özen, İbrahim, and Gürol Yıldırım. 2026. “Modelling Physical Water Losses in the Urban Water Supply Networks of Balıkesir Province Using Artificial Neural Networks”. Turkish Journal of Hydraulic, nos. 3. https://izlik.org/JA44HL43HN.
EndNote
Özen İ, Yıldırım G (June 1, 2026) Modelling Physical Water Losses in the Urban Water Supply Networks of Balıkesir Province Using Artificial Neural Networks. Turkish Journal of Hydraulic 3
IEEE
[1]İ. Özen and G. Yıldırım, “Modelling Physical Water Losses in the Urban Water Supply Networks of Balıkesir Province Using Artificial Neural Networks”, Turkish Journal of Hydraulic, no. 3, June 2026, [Online]. Available: https://izlik.org/JA44HL43HN
ISNAD
Özen, İbrahim - Yıldırım, Gürol. “Modelling Physical Water Losses in the Urban Water Supply Networks of Balıkesir Province Using Artificial Neural Networks”. Turkish Journal of Hydraulic. 3 (June 1, 2026). https://izlik.org/JA44HL43HN.
JAMA
1.Özen İ, Yıldırım G. Modelling Physical Water Losses in the Urban Water Supply Networks of Balıkesir Province Using Artificial Neural Networks. Turkish Journal of Hydraulic. 2026. Available at https://izlik.org/JA44HL43HN.
MLA
Özen, İbrahim, and Gürol Yıldırım. “Modelling Physical Water Losses in the Urban Water Supply Networks of Balıkesir Province Using Artificial Neural Networks”. Turkish Journal of Hydraulic, no. 3, June 2026, https://izlik.org/JA44HL43HN.
Vancouver
1.İbrahim Özen, Gürol Yıldırım. Modelling Physical Water Losses in the Urban Water Supply Networks of Balıkesir Province Using Artificial Neural Networks. Turkish Journal of Hydraulic [Internet]. 2026 Jun. 1;(3). Available from: https://izlik.org/JA44HL43HN