Aysar Tuama Al-Awadi

Accurate calibration of Manning’s roughness coefficients is essential for reliable river hydraulic modelling, flood prediction, and water resources management, yet conventional calibration methods often struggle with high-dimensional parameter spaces and nonlinear hydraulic interactions. This study proposes and evaluates a hierarchical artificial intelligence framework for the inverse calibration of spatially distributed Manning’s roughness coefficients across three channel zones (left bank, main channel, and right bank), using a 48 km reach of the Tigris River in Baghdad as a case study. A one-dimensional HEC-RAS hydraulic model based on 30 measured cross-sections generated 18,360 simulations by systematically varying Manning’s roughness coefficients (0.02–0.045). Three calibration strategies were evaluated: (i) a simple Gradient Boosting Regression model based on a weighted composite roughness formula, (ii) conventional machine learning models (Random Forest, Gradient Boosting, and Multi-Layer Perceptron), and (iii) a deep learning framework combining a three-layer neural network (64 → 32 → 16 neurons), Differential Evolution optimisation, and cubic spline interpolation. Calibration accuracy increased with model complexity. The deep learning framework achieved the best performance, reducing the root mean square error by 96.6% (from 1.202 to 0.041 m), with R² = 0.992 and negligible bias (−0.004 m). Conventional machine learning models produced spatially variable Manning’s roughness distributions, with the calibrated main-channel roughness (mean n = 0.0512) being 34.0–57.5% higher than the corresponding bank values. The proposed framework provides an effective approach for calibrating spatially distributed roughness coefficients in one-dimensional hydraulic models, with strong potential to improve river hydraulic simulations and support future applications to flood modelling.

Clean water supply is one of the major factors contributing significantly to society’s socio-economic transformation by improving living standards, health, and increasing productivity. It is imperative to plan and construct appropriate water supply systems in modern society, which supply various segments of society with safe drinking water according to their requirements to ensure adequate and quality water supply In this study, the Al-Intifada Al-Thalitha neighborhood in Karbala was chosen as a case study to assess the performance of its water distribution network and to develop multiple scenarios reflecting increased water demand and network aging. The analysis aimed to propose optimal strategies for improving network performance under adverse conditions Since Scenario 1 represents the actual state of the network after calibration, the pressure results in this case ranged from 6.14 to 14.24 meters. The results indicated that implementing a pump in scenario 7 offered the most effective solution from both technical and economic perspectives. Specifically, scenario 7 increased pressure by approximately 86.6% at the network’s lowest point and 68.1% at the highest point compared to scenario 6. Economically, the cost difference between scenarios 6 and 7 was minimal: 0.36% for replacing the main pipelines and 1.2% for applying epoxy relative to scenario 6. Furthermore, this solution enabled more uniform pressure distribution across residential units, potentially eliminating the need for household pumps and thereby reducing electricity consumption, leading to substantial annual savings for residents

Water treatment plants (WTPs) encompass numerous components necessitating extensive maintenance efforts incurring high costs. This study introduces a fuzzy-based multi-criteria decision support system (FBMCDS) model, integrating failure mode and effect analysis (FM-EA), applied to several water treatment projects in Karbala Governorate, Iraq. The of this research is to prepare an optimal management strategies and maintenance policies for related projects. Comprehensive data on component details, maintenance activities, and associated costs were gathered through field visits, interviews, and insights from 22 experts via a structured questionnaire. Fuzzy logic was employed to assess failure modes and impacts, determining Failure Mode Risk Priority Index (FMRPI) and Failure Mode Technical Importance (FMTI) for each mode. This facilitated the prioritization of maintenance tasks and weights for WTP failure modes. The FMRPI-FMTI diagram aided in identifying the most critical maintenance needs for each failure mode. Notably, Electrical Transformers failure emerged as the highest priority, contrasting with building failure mode, which ranked lowest. Electrical failure modes were deemed most crucial, followed by mechanical failure modes and combined mechanical-electrical failures. Building failure modes were assigned the lowest priority due to their low likelihood of occurrence. The developed model proves effective, mirroring real-world scenarios and offering user-friendly interpretation and visualization of results. Moreover, its applicability extends to other projects such as wastewater treatment plants and irrigation systems.

The stability of bridge piers against scouring phenomena require to estimate the scour depth carefully at different hydraulic condition to ensure safe design. In this study, laboratory experiments were carried out to examine and compare the scour depth for vertical and inclined cylindrical piers with downstream direction under clear water scour conditions. The measured scour depth in front of three inclined configurations (ϴ = 10°, 16° and 22°) for single cylindrical pier was compared to that observed at vertical cylindrical pier (ϴ = 0°). The experiments were conducted at four flow intensities (V/VC=0.495, 0.714, 0.824 and 0.989) for sand bed material of d50=0.72 mm. The obtained results revealed and confirmed the inverse relationship between the measured scour depth and the angle of inclination of pier, whereas the maximum and the minimum scour depth was observed at ϴ = 0°, and ϴ = 22° respectively. The results of this study showed that the scour depth near threshold conditions (V/VC=0.989) can be reduced approximately by (5%, 10%, and 15%) for inclined piers with (ϴ = 10°, 16° and 22°) respectively. Furthermore, by assessment of five existing formulas, new modified empirical formula has been proposed for scour depth estimation of inclined piers with ± 9% error margins.

The scour and flow field patterns with accumulation of debris around bridge piers are completely different due to the reduction of flow area and the increase in depth average velocity. Accordingly, the risks of bridge piers failure are increased due to the evolution of scour depth. This paper aims to analyse the effect of rectangular debris accumulation around single and dual cylindrical piers on river bed morphology in three dimensional simulation under clear water conditions. An experimental and numerical investigations were conducted to implement computational fluid dynamic (CFD) models that reveal the influence debris accumulation on the characteristics of scour hole and the increase in depth average velocity. The large eddy simulation model (LES) was coupled with three morphological models (Meyer-Peter, and Muller; Van Rijn model, and Nielsen) to assess the performance of simulation and produce efficient CFD morphological models. It was found that coupling of LES turbulence model and Nielsen morphological model yield best agreement with measured scour depth and scour hole characteristics according to the indication of statistical analysis, while the under prediction was noted for other models. As compared with temporal scour development and scour hole morphology of experiments of this study, good agreement was achieved for implemented CFD morphological models for single pier and dual piers with debris accumulation for (6.2 and 16.6% obstructed area to the flow area) respectively. According to the indications of this study, the increase in depth average velocity due to debris accumulation can be ranged from 26 to 44% and from 17 to 41% during the first ten minutes of accumulation around single and dual piers respectively. More consideration should be taken to mitigate bridge piers from debris accumulation.

The countermeasures versus local scour around bridge piers are essential for safe bridge hydraulic design. In this study, laboratory experiments were conducted to investigate the effectiveness of downstream bed sill location as countermeasure method to decrease the local scour under clear water conditions for single cylindrical pier. Four flow intensities were tested (from 0.48 to 0.96 of the threshold velocity of sediment) with five different bed sill locations (from 0 to 4 pier diameter). The measured scour depths were compared with that observed at the exposed pier (four tests for unprotected pier) to estimate the percentage reduction in scour depth for each flow intensity and to assess the aspects of bed sill location. The results revealed a significant effect of bed sill location on decreasing the scour depth with in downstream distance equal to pier diameter. Accordingly, the percentage decrease in scour depth was ranged from 4 to 30%. New empirical formula has been proposed to estimate scour depth near circular bridge piers according to different bed sill configuration. Graphical abstract

Rivers may carry a considerable amount of debris during floods, and the accumulation of this debris around bridge piers can change the hydraulic behaviour of flow fields and influence scour depth development. In this study, the effect of debris jam on scour depth at cylindrical bridge piers was investigated and a comparison carried out for the main existing empirical formulas. A series of 27 tests of rectangular geometry in three different groups according to width, length, submerged depth, and blocked area were studied. The results showed that the accumulation of debris increased scour depth from 10.3% to 62.1%, 22.4% to 103.4%, and 20.7% to 139.7% as the percentage blocked area of debris increased from 2.07% to 6.2%, 5.52% to 16.55%, and 8.96% to 26.89% for groups (1), (2), and (3) respectively. The comparison of the experimental results with the most commonly used empirical formulas revealed general overestimation of scour depth with debris accumulation. The Richardson and Davis (1995) and Lagasse et al. (2009) formulas were the most acceptable methods for scour prediction under debris jams, though further study is recommended for bridge pier scour depth estimation in the presence of debris.