J. Hydrol. Hydromech., Vol. 73, No. 3, 2025, p. 230 - 247, doi: https://doi.org/10.2478/johh-2025-0018
Scientific Paper, English

Reza Ahmadi, Hossein Afzalimehr, Hussam Jabbar Abed, Saeid Okhravi: Hydrodynamic effects of porous baskets on scour patterns at elliptical and hexagonal piers

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• This study investigates the effectiveness of a newly introduced scour countermeasure, the porous basket (PB), in modifying flow structure and mitigating scour around elliptical and hexagonal piers with varying length-to-width ratios (l/w). Experimental analysis of near-bed flow velocities revealed a significant reduction at the pier face, followed by velocity recovery after reattachment in the second half of the pier for both geometries. However, in elliptical piers, lateral imbalances in vortex shedding and flow separation led to localized variations in velocity profiles, while l/w had no influence on the location of flow separation. The results indicate that piers with l/w = 5 ratio experienced 50% reduction in scour volume due to lower Reynolds Shear Stress (RSS) in the downflow region. In general, increasing l/w resulted in a more confined scour area and reduced scour volume. Implementation of the PB, effectively trapped over 65% of turbulence kinetic energy (TKE), significantly reducing scour at the pier base. As turbulence dissipated and flow stabilized, RSS values approached zero. Among the tested installation distances, the smaller placement exhibited the best scour mitigation performance by enhancing localized turbulent energy dissipation. This finding highlights the potential of the PB in improving bridge pier stability and reducing local scour effects.
  
  KEY WORDS: Local scour; Length-to-width ratio; Flow structure; Porous basket; Reynolds shear stress.
  
  Address:
  - Reza Ahmadi, Faculty of Civil Engineering, Iran University of Science and Technology, Tehran, 1684613114, Iran.
  - Hossein Afzalimehr, Faculty of Civil Engineering, Iran University of Science and Technology, Tehran, 1684613114, Iran. (Corresponding author. Tel.: Fax.: Email: hafzali@iust.ac.ir)
  - Hussam Jabbar Abed, Faculty of Civil Engineering, Iran University of Science and Technology, Tehran, 1684613114, Iran.
  - Saeid Okhravi, Institute of Hydrology, Slovak Academy of Sciences, Dúbravská cesta 9, 84104, Bratislava, Slovakia. (Corresponding author. Tel.: Fax.: Email: saeid.okhravi@savba.sk)

J. Hydrol. Hydromech., Vol. 73, No. 3, 2025, p. 248 - 259, doi: https://doi.org/10.2478/johh-2025-0019
Scientific Paper, English

Yujie Fan, Zhonghua Yang, Wenxin Huai, Shuolin Li, Peng Zhang, Xichen Wang: Effect of shape and size on the transport of floating vegetation debris: A La-grangian experimental study

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• Flood-generated floating vegetation debris can accumulate near hydraulic structures, posing risks to power generation and engineering safety. Understanding the transport characteristics of different types of floating aquatic vegetation debris is fundamental for modeling their movement. A Lagrangian experiment was conducted in a laboratory straight water channel using six models of floating vegetation debris (categorized as leaf-type and rod-type) with varying shapes and sizes. The trajectories of the models were tracked and processed using image analysis technology, and diffusion coefficients were calculated based on distribution data. Results indicate that centimeter-sized models move at the same velocity as the surface flow. The diffusion coefficient in the flow direction was approximately twice that of the spanwise diffusion coefficient. The shape and size of the debris models influenced diffusion characteristics: leaf-type models diffused faster than rod-type models, while leaf-type models with a center of mass offset showed greater spanwise diffusion. Shorter models exhibited higher diffusion tendencies in the spanwise direction. Diffusion properties in the two directions vary significantly with flow conditions and debris model characteristics. Formulas were proposed for estimating dimensionless diffusion coefficients in both directions. These findings are valuable for predicting the potential accumulation zones of floating vegetation debris under varying flow conditions.
  
  KEY WORDS: Floating vegetation debris; Lagrangian experiment; Transport velocity; Diffusion properties; Dimensionless diffusion coefficients equation.
  
  Address:
  - Yujie Fan, State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan, Hubei, 430072, China.
  - Zhonghua Yang, State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan, Hubei, 430072, China. (Corresponding author. Tel.: Fax.: Email: yzh@whu.edu.cn)
  - Wenxin Huai, State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan, Hubei, 430072, China.
  - Shuolin Li, State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan, Hubei, 430072, China.
  - Peng Zhang, State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan, Hubei, 430072, China.
  - Xichen Wang

J. Hydrol. Hydromech., Vol. 73, No. 3, 2025, p. 260 - 272, doi: https://doi.org/10.2478/johh-2025-0020
Scientific Paper, English

Aditya Nugraha Putra, Sephia Dewi Meila Chrisaputri, Cindy Monica Manurung, Michelle Talisia Sugiarto, Novandi Rizky Prasetya, Irma Ardi Kusumawati, Istika Nita Sudarto, Mohd Hasmadi Ismail, Silvia Kohnová, Kamila Hlavčová: Utilising land use scenario modeling and machine learning for mitigating drought risks in degraded landscapes

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• Land-use change is a key driver of environmental degradation and increasing drought risk. This study assesses drought dynamics in the South Malang Plateau, East Java, by integrating remote sensing data with the Random Forest (RF) algorithm. Three land use scenarios were developed: Business-as-Usual (BAU) for 2030 (predicted using the CA-ANN method in QGIS), participatory mapping (PM), and land capability classification (LCC). Using 175 stratified random field points (70% for training, 30% for validation), the analysis integrated 25 predictor variables across climatic, anthropogenic, topographic, and vegetation index factors. The RF model used for drought classification achieved an overall accuracy of 92.57%. Based on unsupervised classification of historical satellite imagery, between 2017 and 2023 multistrata agroforestry declined by nearly 50%, natural forest cover decreased by 27.6%, and settlements more than doubled. Under the 2030 BAU scenario, forest cover is projected to decline further to 9,195.16 ha. Drought analysis shows a peak in 'Severe Drought' at 18.1% in 2019, dropping to 3.1% by 2030, while 'Extreme Drought' steadily rises from 6.2% to 7.0%, particularly in deforested areas. Among the scenarios, the integrated LCCPM approach demonstrated higher potential to reduce drought vulnerability and land degradation. The integrated land capability classification- participatory mapping (LCCPM scenario) is recommended to strengthen landscape resilience and promote sustainable land management.
  
  KEY WORDS: Remote sensing; Land cover; Machine learning; Geographic information system; Water management.
  
  Address:
  - Aditya Nugraha Putra, Department of Land and Water Resources Management, Faculty of Civil Engineering, Slovak University of Technology in Bratislava, Bratislava 81005, Slovakia. Soil Science Department, Faculty of Agriculture, Brawijaya University, Veteran Street, Malang 65145, Indonesia. (Corresponding author. Tel.: Fax.: Email: aditya.putra@stuba.sk)
  - Sephia Dewi Meila Chrisaputri, Agroecotechnology Study Program, Faculty of Agriculture, Brawijaya University, Veteran Street, Malang 65145, Indonesia.
  - Cindy Monica Manurung, Agroecotechnology Study Program, Faculty of Agriculture, Brawijaya University, Veteran Street, Malang 65145, Indonesia.
  - Michelle Talisia Sugiarto, Soil and Water Management Study Program, Faculty of Agriculture, Brawijaya University, Veteran Street, Malang 65145, Indonesia.
  - Novandi Rizky Prasetya, Soil and Water Management Study Program, Faculty of Agriculture, Brawijaya University, Veteran Street, Malang 65145, Indonesia.
  - Irma Ardi Kusumawati, Yayasan Bumi Hijau Lestari, Telaga Bodas Raya, Semarang 50235, Indonesia.
  - Istika Nita Sudarto, Soil Science Department, Faculty of Agriculture, Brawijaya University, Veteran Street, Malang 65145, Indonesia.
  - Mohd Hasmadi Ismail, Faculty of Forestry and Environment, Universiti Putra Malaysia, Serdang, Selangor 43400, Malaysia.
  - Silvia Kohnová, Department of Land and Water Resources Management, Faculty of Civil Engineering, Slovak University of Technology in Bratislava, Bratislava 81005, Slovakia.
  - Kamila Hlavčová, Department of Land and Water Resources Management, Faculty of Civil Engineering, Slovak University of Technology in Bratislava, Bratislava 81005, Slovakia.

J. Hydrol. Hydromech., Vol. 73, No. 3, 2025, p. 273 - 283, doi: https://doi.org/10.2478/johh-2025-0021
Scientific Paper, English

Carlos Lázaro Castillo García, Yosvany Aguila Domínguez, Víctor Manuel Carvajal González, Jorge Jimenez, Lisdelys González-Rodríguez: Design and assessment of sustainable retention ponds for flood reduction in an urban drainage system in Cuba

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• Flooding may cause substantial environmental, economic and human losses. This study proposes a design and assessment of sustainable retention ponds to reduce flood risk in an urban drainage system of Capiro-Bengochea, Santa Clara, Cuba. The design integrates green infrastructure principles with hydrological and hydraulic modeling tools. The study analyzed 11 rainfall events to simulate runoff behavior and the effectiveness of proposed solutions. Retention ponds significantly reduced peak runoff by up to 77%, mitigating flooding risks, enhancing urban aesthetics and offering recreational benefits while addressing technical challenges. This study introduces innovative sustainable urban drainage strategies to Cuban contexts, aligning with global practices and demonstrating the multifunctionality of nature-based solutions in stormwater management.
  
  KEY WORDS: Retention ponds; Sustainable urban drainage systems (SuDS); Stormwater drainage design; Flood risk mitigation.
  
  Address:
  - Carlos Lázaro Castillo García, Facultad de Ingeniería, Universidad de Concepción, Concepción, 4030000, Chile.
  - Yosvany Aguila Domínguez, Empresa de Investigaciones y Proyectos Hidráulicos de Villa Clara, Libertadores 201 e/ Jesús Menéndez y Danielito Santa Clara 50100, Cuba.
  - Víctor Manuel Carvajal González, Facultad de Construcciones, Universidad Central “Marta Abreu” de Las Villas, Carretera a Camajuaní Km 9 1/2, Santa Clara 50100, Cuba.
  - Jorge Jimenez, Facultad de Ingeniería, Universidad de Concepción, Concepción, 4030000, Chile.
  - Lisdelys González-Rodríguez, Facultad de Ingeniería y Negocios, Universidad de Las Américas, Sede Concepción, Concepción 4030000, Chile. Centro de Modelación Ambiental y Dinámica de Sistemas (CEMADIS), Universidad de Las Américas, Universidad de Las Américas, Santiago 7500000, Chile. (Corresponding author. Tel.: Fax.: Email: lgonzalezr@udla.cl)

J. Hydrol. Hydromech., Vol. 73, No. 3, 2025, p. 284 - 294, doi: https://doi.org/10.2478/johh-2025-0022
Scientific Paper, English

Rayane Saci, Mehdi Keblouti, Okan Mert Katipoglu, Bojan Đurin, Habiba Majour, Lamine Sayad, Faiza Bouzahar, Leila Benchaiba: Assessing the efficacy of various predictive models in simulating monthly reference evapotranspiration patterns and its impact on water resource management for agriculture in the Kebir-West watershed, North-East of Algeria

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• The estimation of monthly reference evapotranspiration (ET₀) is important for the efficient management of water resources, especially in regions with limited meteorological station coverage such as Algeria. For this purpose, different prediction models including support vector machines, multiple regression, bagged trees, and neural networks were applied to estimate Penman-Monteith FAO-56-based monthly ET₀ in the Oued El Kebir watershed in northeastern Algeria. Eight combinations of climate inputs, including wind speed, relative humidity, and maximum and minimum temperatures, were examined. Four metrics were used to assess the models' performance: coefficient of determination (R²), mean relative error (MRE), mean absolute error (MAE), and root mean square error (RMSE). Sobol sensitivity analysis was conducted to determine the most influential parameter in ET₀ estimation. According to the results, the variable with the highest impact was maximum temperature. The findings indicate that the proposed models achieved high estimation accuracy. Among them, neural networks outperformed the other models, with a correlation coefficient of 0.99, RMSE = 0.37, MAE = 0.28, and MRE = 0.005, for a period spanning (1984-2022). This superior performance is attributed to their ability to simulate complex and nonlinear relationships between climatic variables and ET₀. These results contribute to improved irrigation planning and more efficient water resource management for farmers, climate scientists, and water managers.
  
  KEY WORDS: Algeria; Reference evapotranspiration ET0; Penman-Monteith FAO-56; Machine learning models; Kebir-West watershed.
  
  Address:
  - Rayane Saci, Geology Research Laboratory (GRL), Department of Geology, Faculty of Earth Sciences, Badji Mokhtar-Annaba University, 12, P.O. Box, 23000 Annaba, Algeria.
  - Mehdi Keblouti, Environmental Engineering and Technology Laboratory, Abdelhafid Boussouf University Center, P.O. Box 26, 43000, Mila, Algeria. (Corresponding author. Tel.: Fax.: Email: m.keblouti@centre-univ-mila.dz)
  - Okan Mert Katipoglu, Erzincan Binali Yildirim University, Faculty of Engineering Architecture, Department of Civil Engineering, Erzincan, Türkiye.
  - Bojan Đurin, Department of Civil Engineering, University North, Jurja Križanića 31b, 42000 Varaždin, Croatia.
  - Habiba Majour, Geology Research Laboratory (GRL), Department of Geology, Faculty of Earth Sciences, Badji Mokhtar-Annaba University, 12, P.O. Box, 23000 Annaba, Algeria.
  - Lamine Sayad, Geology Research Laboratory (GRL), Department of Geology, Faculty of Earth Sciences, Badji Mokhtar-Annaba University, 12, P.O. Box, 23000 Annaba, Algeria.
  - Faiza Bouzahar, Kasdi Merbah University, Ouargla Ghardaia Road, BP.511, 30,000, Algeria.
  - Leila Benchaiba, Department of Hydraulics, University of Batna 2, Batna, 05000, Algeria.

J. Hydrol. Hydromech., Vol. 73, No. 3, 2025, p. 295 - 309, doi: https://doi.org/10.2478/johh-2025-0023
Scientific Paper, English

Faris Belaabed, Leila Arabet, Kamel Goudjil, Ahmed Ouamane: Optimized machine learning models for accurate prediction of the discharge coefficient in hydraulic weirs

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• Despite the growing reliance on machine learning (ML) models in hydraulic applications, it remains essential to compare both optimized and non-optimized models (regardless of their novelty) to identify the most accurate and reliable predictor. In this study, we developed ML models to predict the discharge coefficient (Cw) of Piano Key Weirs (PK-Weirs), using experimental data collected from our own lab tests. A total of six models were evaluated, including baseline and optimized versions of NGBoost and XGBoost, as well as Random Forest and a hybrid M5'-IWOA model, with optimization performed using bio-inspired algorithms (MPA and OOA). The comparative analysis revealed the clear superiority of optimized NGBoost and XGBoost models, which achieved outstanding performance (R² > 0.999, RMSE ≤ 0.0125), significantly outperforming their non-optimized counterparts. To ensure transparency and assess real-world robustness, we validated all models using an independent external dataset not included in our experimental database. The optimized models maintained strong accuracy (R² > 0.90), while others showed noticeable degradation, especially under extreme or noisy conditions. This work highlights the importance of comparing enhanced and standard models, and of validating them with external data for unbiased performance assessment. Additionally, a PyQt6-based interface was developed to facilitate user interaction and real-time predictions.
  
  KEY WORDS: Machine learning; Piano keys weir; Discharge coefficient; Bio-inspired algorithms; Predictive modeling; PyQt6 interface.
  
  Address:
  - Faris Belaabed, Laboratory of Hydraulic Planning and Environment, University of Biskra, Algeria. (Corresponding author. Tel.: Fax.: Email: bellabed.faris@univ-jijel.dz)
  - Leila Arabet, Department of Civil and Hydraulic Engineering, Laboratory LGCE, Faculty of Sciences and Technologies, University of Jijel, Algeria.
  - Kamel Goudjil, Department of Civil Engineering, Mohammed Cherif Messaadia University, Laboratory INFRARES, Souk-Ahras, Algeria.
  - Ahmed Ouamane, Laboratory of Hydraulic Planning and Environment, University of Biskra, Algeria.

J. Hydrol. Hydromech., Vol. 73, No. 3, 2025, p. 310 - 321, doi: https://doi.org/10.2478/johh-2025-0024
Scientific Paper, English

Manisha Panthi, Brian M. Crookston: Non-cohesive sediment cleaning patterns and processes upstream of a Type A piano key weir for steady and unsteady flow conditions

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• The piano key weir has been used in channel and spillway rehabilitation projects due to their compact footprint, hydraulic efficiency and cost-effectiveness. Despite these advantages, sediment deposition upstream of the weir can impact hydraulic performance, raising concerns about the long-term functionality and performance during flood events. Therefore, the present study investigates the self-cleaning behavior of non-cohesive sediments deposited immediately upstream of a Type A piano key weir in a run-of-river setting. Laboratory flume experiments were conducted under clearwater conditions, examining both steady and, for the first time, unsteady inflow conditions. Analyses of the sediment-flow interactions and flow field characteristics were augmented with Reynolds-Averaged Navier-Strokes (RANS) based single fluid computational fluid dynamics (CFD) simulations. Findings revealed that frontal scour was primarily driven by localized vortices formed by the piano key weir geometry while general upstream riverbed degradation was governed by inflow conditions, including unit discharge and the level of sediment deposition relative to the weir crest. Frontal scour and riverbed degradation reached the base elevation of the weir for densimetric Froude numbers exceeding 2.15. Notable sediment transport was initiated at densimetric Froude numbers as low as 1.45. The self-cleaning efficiency was closely linked to local velocities and bed shear stresses. For the steady-state cases, the rate of sediment removal reduced with time until equilibrium conditions were established. Tests showed that the unsteady inflow conditions were equally effective at sediment removal, as 80-85% of total transported sediment occurred during initial 30% of time of laboratory testing for any given unit discharge.
  
  KEY WORDS: Frontal scour; Piano key weirs; Sediment self-cleaning; Sediment transport; Riverbed connectivity.
  
  Address:
  - Manisha Panthi, Utah Water Research Laboratory, Department of Civil and Environmental Engineering, Utah State University, Logan, UT 84321, United States.
  - Brian M. Crookston, Utah Water Research Laboratory, Department of Civil and Environmental Engineering, Utah State University, Logan, UT 84321, United States. (Corresponding author. Tel.: Fax.: Email: brian.crookston@usu.edu)