رویکردهای نوین در مهندسی آب و محیط‌زیست

چکیده Objective: The primary objective of this study is to develop and evaluate two soft‑computing models (MLPNN and GMDH) for accurately predicting the discharge capacity of Semi‑Cylindrical Side-Contracted Flumes (SMBF) under both free‑flow and submerged regimes. The research aims to identify the optimal model structure, determine the most influential dimensionless parameters via dimensional analysis, and perform a comprehensive sensitivity analysis. A systematic comparison between the black‑box MLPNN and the interpretable GMDH model is conducted to recommend the most reliable and accurate predictive tool. Methods: The study employed two data‑driven soft‑computing models: a Multilayer Perceptron Neural Network (MLPNN) and the Group Method of Data Handling (GMDH). First, dimensional analysis using the Buckingham Π theorem was applied to derive the key dimensionless parameters (e.g., h/w, w/B, ht/hs) as model inputs. Experimental data (450 free‑flow and 170 submerged records) were collected from published sources and randomly split into training and testing sets (70‑30 ratio). Model performance was evaluated using statistical indices (R², RMSE), and sensitivity analysis was conducted to identify the most influential input parameters on discharge prediction. Results: The MLPNN model achieved outstanding accuracy with R² = 0.987 (free‑flow) and R² = 0.992 (submerged), and RMSE ≈ 0.001 for both regimes, significantly outperforming the GMDH model (R² ≈ 0.88–0.96). Sensitivity analysis revealed that the depth‑to‑throat ratio (h/w) is the most influential parameter under free‑flow conditions, while the contraction ratio (w/B) dominates under submerged flow. The GMDH model, though less accurate, provided superior interpretability due to its transparent, self‑organizing polynomial structure. Overall, MLPNN is recommended for high‑precision applications, whereas GMDH serves as a robust alternative when model transparency is prioritized. Conclusions: Both MLPNN and GMDH models demonstrated high capability in predicting SMBF flume discharge, with MLPNN showing superior accuracy (R² > 0.98) for both free and submerged flows, while GMDH offered better interpretability. Sensitivity analysis confirmed that h/w governs free‑flow discharge, whereas w/B dominates under submerged conditions due to backwater effects. The study concludes that MLPNN is recommended for high‑precision field applications, while GMDH serves as a transparent alternative when understanding parameter relationships is essential.

چکیده Objective: To experimentally assess how regular, connected three-dimensional volumetric porosity modifies the hydrodynamic and morphodynamic response of a spur dike, and to compare a fully porous modular Chine dike and a three-row hybrid porous-shell configuration (3RC) with a conventional impermeable spur dike under submerged and non-submerged conditions. Materials and Methods: Experiments were conducted in a 6.0 m long, 0.60 m wide recirculating flume at a flow depth of 0.15 m and discharge of 25.7 L/s. The approach flow was subcritical (U = 0.286 m/s, Fr approximately 0.23) and near the clear-water threshold (U/Uc = 0.96) over uniform non-cohesive sand with d50 = 1.2 mm. All dikes had a transverse length of 0.12 m. The Chine configuration was assembled from 2 x 2 x 2 cm cubic blocks with connected openings and a geometric volumetric porosity of approximately 0.25. Three-component velocities were measured using a Nortek Vectrino II ADV at 50 Hz for 120 s at each sampling node. Velocity records were despiked and filtered using correlation and SNR criteria. Each scour test continued for 24 h, and equilibrium bed topography was surveyed on a 1 x 1 cm grid with a laser profiler; dye and yarn tracers supported interpretation of the measured flow structures. Results and Discussion: Regular volumetric porosity produced a controlled bleed flow through the dike body, relieved upstream stagnation pressure, weakened near-bed downflow, and reduced the concentration of high-vorticity cores near the structure. Under submerged conditions, porous configurations reduced peak near-bed downflow by about 50% relative to the solid case, while the fully porous Chine reduced peak vorticity at the dike by about 84%. Maximum equilibrium scour depth decreased from 9.3 cm for the solid dike to 7.1 cm for the fully porous Chine under submerged flow (23.7% reduction) and from 12.3 to 9.5 cm under non-submerged flow (22.8% reduction). The fully porous configuration also reduced scour-hole width and longitudinal extent and shifted the submerged deposition-bar onset from 23.2 to 14.95 cm, 35.6% closer to the structure. The 3RC case showed intermediate hydraulic and morphodynamic behavior. Conclusion: A regular, hydraulically connected three-dimensional pore network can redistribute momentum through the structure, weaken coherent near-bed erosive motions, and reduce both scour depth and scour-hole extent. Within the tested conditions, the fully porous Chine configuration provided the most consistent scour mitigation, indicating that pore-network topology, in addition to overall permeability, is an important design variable for permeable river-training structures.

چکیده Objective: The use of intelligent irrigation management decision support systems has gained significant importance as a novel approach for optimizing water consumption and enhancing water productivity in the agricultural sector. This study, as a preliminary pilot case study, evaluates the initial performance of an intelligent irrigation management decision support system (named "HooshAb") in a 20-ha silage maize field in Qom Province. The main objective was to investigate the impact of this decision support system on optimizing irrigation management and reducing water consumption under conditions of water scarcity. Methods: For this purpose, two adjacent similar fields managed by the same farmer were selected as pilot sites for implementing and operating the decision support system. In one field, irrigation followed the farmer's traditional management method (control), while in the other, irrigation was carried out according to the schedules provided by the decision support system (treatment). Results: The results showed that by optimizing irrigation scheduling and appropriately simulating soil moisture patterns, the decision support system reduced water consumption by approximately 6% compared to the traditional method. Moreover, the use of the system increased irrigation water productivity by 6.3%. Field monitoring of soil moisture and saturated extract salinity indicated that the decision support system had high accuracy in predicting soil moisture and was effective in optimizing on-farm water management. Soil salinity monitoring results also highlighted the importance of updating irrigation water quality data during the growing season to enhance the accuracy of the decision support system in estimating saturated extract salinity. Conclusions: The preliminary findings suggest that irrigation DSS may enhance water productivity and support soil-water sustainability under climate change, though multi-season and multi-location studies are needed for validation. Such systems enable precise irrigation scheduling, reduce unnecessary water use, and support long-term soil health. Regular updating of key input data, especially water quality parameters, is essential for maintaining system accuracy and reliability throughout the growing season.

چکیده Objective: Treatment of highly turbid surface water remains challenging in low-cost decentralized systems. This study aims to evaluate the hydraulic performance of a novel integrated pre-sedimentation and multilayer horizontal roughing filtration system and to develop dimensionless design relationships for improved process optimization and scale-up. Methods: A laboratory-scale physical model was constructed in a hydraulic flume at the Khuzestan Water and Power Authority, Iran. The system combined a 1 m stilling basin with a three-layer roughing filter (20 mm, 10 mm, and 2 mm media). Experiments were conducted under three filter lengths (260, 350, and 450 cm), three filtration velocities (0.20, 0.60, and 1.00 m h⁻¹), three operation times (10, 20, and 30 min), and three influent turbidity ranges (1500–2500 NTU), resulting in 81 experimental runs. Turbidity removal efficiency was used as the performance criterion, and input predictability was assessed using the Gamma Test. Results: Filter length was identified as the dominant parameter, improving removal efficiency by approximately 9–10% when increased from 260 to 450 cm. Maximum efficiencies exceeded 94% at 0.20 m h⁻¹ and 450 cm length. Filtration velocity had a secondary negative effect (4–5% reduction across the tested range), while influent turbidity and operating time showed limited influence. The Gamma Test confirmed strong deterministic structure in the full-input configuration (Gamma = 0.0462; V-ratio = 0.1848). Conclusions: The findings demonstrate that, within the tested range, increasing the effective length of the multilayer horizontal roughing filter improved turbidity removal performance and enhanced the overall efficiency of the combined pre-sedimentation–filtration system. These results indicate that filter length is an important design parameter for treating highly turbid surface waters in resource-limited regions. However, the present study should be interpreted as an experimental performance assessment of selected configurations rather than a formal geometric optimization, and determination of the absolute optimal design would require further investigation over a wider range of configurations together with techno-economic evaluation.

چکیده Objective: While SBR and hybrid SBR-AOP systems have been investigated for conventional wastewater treatment, their application and optimization for highly detergent-rich gray water presents unique challenges, such as biomass inhibition and low initial biodegradability (BOD5/COD ratio of 0.25). The distinct novelty of this study lies in the systematic configuration optimization and phase-duration management of an integrated SBR and UV/H2O2 system specifically tailored for gray water containing elevated detergent concentrations. Unlike traditional hybrid systems that apply chemical oxidation as a polishing step, this research evaluates and demonstrates the significant advantages of operating the UV/H2O2 process as a pre-treatment stage. This specific sequencing effectively breaks down non-biodegradable surfactants and mineralizes complex organic compounds prior to the biological stage, thereby enhancing the overall system efficiency to a COD removal rate of 97%.
Methods: Gray water with initial pollutant concentrations of 600 mg/L COD, 200 mg/L BOD, 4 mg/L TP, and 15 mg/L TKN was treated using an SBR system combined with UV/H₂O₂ chemical oxidation. Additionally, the potential of granular activated carbon (GAC) added during the SBR aeration phase to enhance pollutant removal was evaluated. Different chemical oxidation conditions were evaluated, and the effects of anaerobic pre-treatment and anaerobic phase duration were assessed.
Results: The SBR reduced BOD₅ to 40 mg/L and COD to 162 mg/L, while activated carbon had a limited effect. The optimal chemical oxidation conditions were 12 mg/L H₂O₂ and a reaction time of 3 hours. Under these conditions, the integrated system achieved removal efficiencies of 90.6% for COD, 85% for BOD, 82.5% for TP, and 65% for TKN. Chemical oxidation as a pre-treatment step improved the biodegradability of organic compounds by 6%. In addition, the inclusion of an anaerobic unit before aeration improved phosphorus removal, although extending the anaerobic phase beyond two hours provided no further benefit.
Conclusions: the integrated SBR and UV/H₂O₂ system is an effective method for treating gray water with high detergent concentrations, significantly reducing pollutant levels and improving biodegradability. The use of anaerobic pre-treatment can further enhance phosphorus removal, but longer anaerobic durations are not necessarily advantageous.

چکیده Objective: The main objective of this study is to propose a water change detection index, which directly extracts water body changes from two temporal images in a single step, instead of extracting surface waters from each temporal image separately and then comparing the results to detect the changes.
Methods: The formulation of NDWCI incorporated the difference between the green and shortwave-infrared bands from two temporal Landsat scenes, aiming to create contrast between areas where water surfaces have changed versus those that remained stable over time. The primary goal behind constructing NDWCI was to fuse multi-temporal images of a given location into a single composite image, such that unchanged pixels were minimized or suppressed while water-related changes between the two acquisition dates were clearly emphasized.
Results: The results demonstrate that although the accuracies of the NDWCI and NDWI differencing methods were close to each other, NDWCI consistently outperforms both NDWI and MNDWI differencing in terms of overall accuracy, Kappa coefficient, and commission and omission errors across the two test sites. At test site 1, NDWCI achieved the highest overall accuracy (98.33%) and Kappa (0.98), followed by NDWI (97.11%, 0.97) and MNDWI (94.85%, 0.91). A similar pattern is observed at test site 2, where NDWCI again records the best performance (96.32% accuracy, 0.93 Kappa), while MNDWI shows a marked drop in agreement (91.23% accuracy, 0.76 Kappa).
Conclusions: The NDWCI index can be applied to detect changes across various water types. Nevertheless, a key challenge remains in identifying an appropriate threshold value to reliably differentiate changed from unchanged areas. In conclusion, the proposed method showed strong capability for monitoring water body changes at the selected test sites. Therefore, this approach holds potential for enhancing water body change detection in future research.

چکیده Objective: The accurate prediction of the discharge coefficient (e hydraulic design of labyrinth weirs. While existing literature extensively covers conventional vertical-sidewall geometries, there is a critical knowledge gap regarding the synergistic effect of sloped sidewalls and arced planform geometry on discharge capacity. This study addresses this limitation by investigating and predicting C_d​ for arced labyrinth weirs with varying sidewall slopes.
Methods: Using a comprehensive dataset of 277 experimental runs from a laboratory flume, five dimensionless parameters—namely sional analysis to capture both geometric and hydraulic complexity- were used as inputs for three soft computing approaches: Support Vector Machine (SVM), Gene Expression Programming (GEP), and Artificial Neural Network (ANN).
Results: All three data‑driven approaches produced satisfactory predictions of Cd. However, the ANN model based on a multilayer perceptron (MLP) demonstrated the best performance. The optimal architecture was MLP 5‑9‑1 trained using the BFGS algorithm, with the SOS error function, a logistic activation function in the hidden layer, and an identity activation function in the output layer. During training and validation, the performance metrics (RMSE, MAE, R², C_d(DDR(max))) were (0.022, 0.0145, 0.8402, 11.436) and (0.0199, 0.0145, 0.8961, 12.805), respectively. Graphical analyses also showed strong agreement between observed and predicted Cd values across different dataset quartiles.
Conclusions: The findings confirm that the MLP framework provides a robust and reliable alternative for hydraulic engineers, filling the current modeling void for non-conventional labyrinth weirs. This approach offers a practical tool for spillway optimization where complex geometric interactions preclude the use of simplified linear regressions.

چکیده Objective: This study evaluated the environmental impacts of the 5,000-hectare Shavur irrigation and drainage network in the central Karkheh Basin, Khuzestan Province. By utilizing both conventional and modified ICOLD/Leopold matrix methods, the assessment focused on the physical, biological, and socio-economic environments during the project’s operation phase. To achieve this, the research utilized a panel of 15 senior environmental and engineering experts, applying a standardized scoring system (+5 to -5) alongside specific weighting coefficients within both conventional and modified matrix frameworks to systematically quantify and compare the operational environmental consequences.
Results: The most significant positive outcomes occurred within the socio-economic sphere. For the physical environment, the conventional method yielded 161 positive and 226 negative scores, while the modified method showed 303.57 positive and 435.91 negative scores, suggesting the project offers physical benefits but poses adverse impacts requiring careful management. In the biological environment, the conventional method produced 80 positive and 148 negative scores, compared to 111.51 positive and 286.87 negative scores via the modified approach. This suggests that vegetation, wildlife habitats, and ecological balance may face negative pressures. Conversely, the socio-economic environment demonstrated superior positive outcomes; the conventional method recorded 532 positive and 26 negative scores, whereas the modified method showed 1212 positive and 72 negative scores. These data underscore the project’s capacity to significantly boost agricultural productivity, employment, and local economic stability.
Conclusion: Overall, the Shavur network acts as a catalyst for socio-economic growth, specifically increasing production, income, and employment. However, the project concurrently exerts negative pressures on physical and biological systems. Consequently, robust environmental management and mitigation strategies are vital to minimize ecological damage and ensure long-term environmental sustainability.

چکیده Objective: This study presents a technical soil stabilization solution by utilizing Gorgan Bay sludge ash (GBSA), a processed, problematic environmental by-product, for the stabilization of clayey soils with varying plasticity characteristics.”
Methods: In the present study, the feasibility of using Gorgan Bay sludge ash as a pozzolanic additive for clay soil improvement while reducing the environmental impact of waste disposal was experimentally investigated. For this purpose, a wide range of clay soils, including four samples with plasticity indices of 21, 32, 40, and 68, were selected and blended with GBSA at weight fractions of 0%, 5%, 10%, 15%, 20%, and 25% based on the dry weight of the base soil. The mechanical properties of the specimens were evaluated using Atterberg limits, standard Proctor compaction, and unconfined compressive strength (UCS) tests (at curing ages of 1, 7, 28, and 56 days).
Results: Experimental results show that the maximum dry unit weight increased by 5–7%, peaking consistently at 15% additive content. For strength parameters, the optimum GBSA dosage for peak UCS was 15% for lower-plasticity soils and 20% for higher-plasticity soils, indicating that additive demand scales with the initial plasticity index. At the 56-day curing mark, the relative UCS improvement ranged from 193% to 297%, with the most plastic soil (PI = 68) achieving the highest gain. While strength and density showed distinct optima, the plasticity index decreased continuously, reaching a total reduction of 58% to 75% at the 25% ash level. “These quantitative shifts, possibly associated with pozzolanic reactions and the high specific gravity of GBSA (Gs = 2.73), suggest that GBSA is a highly efficient stabilizer, particularly for high-plasticity (CH) clays.”
Conclusions: These findings identify Gorgan Bay sludge ash as an effective additive for stabilizing problematic clay soils and offer a practical, low-cost approach for the environmentally sustainable management of this sediment waste in the region.
ی مورد مطالعه شده است. هرچند با افزایش بیشتر درصد افزودنی به 20 و 25 درصد، روند افزایش وزن مخصوص خشک و مقاومت فشاری محصور نشده در تمامی نمونه‌ها کند یا معکوس شد که به واسطه لخته‌شدن ذرات رس بر اثر پرشدگی منافذ توسط ذرات سنگینتر خاکسترلجن قابل تبیین است. در مقابل، کاهش شاخص خمیری حتی تا25% افزودنی بین 58 تا 75 درصد ادامه یاقت. نتیجه این فرآیند افزایش وزن مخصوصخشک و مقاومت محصورنشده و کاهش شاخص خمیری خاک است که همگی به بهبود قابل‌توجه رفتار مهندسی خاک منجر می‌شوند.
نتیجه‌گیری: این یافته‌ها ضمن معرفی خاکستر لجن خلیج گرگان به‌عنوان افزودنی مؤثر برای تثبیت خاک‌های رسی مسئله‌دار، راهکاری عملی و کم‌هزینه برای مدیریت زیست‌محیطی پسماند این رسوبات در منطقه ارائه می‌دهد.

چکیده Objective: This experimental-intervention study was conducted at a pilot scale in 2022 to optimize the biogas production process from sugarcane vinasse, specifically focusing on reducing the inhibitory effects of toxic compounds and optimizing operational parameters. Methods: The experiments were carried out based on the Biochemical Methane Potential (BMP) method at the Faculty of Agriculture, Ferdowsi University of Mashhad, Iran. The effect of six variables, including temperature (37 and 55 °C), residence time (14 and 21 and 28 days), C/N ratio (1:20, 1:25, and 1:30), pH (6, 7, and 8), hydrogen peroxide concentration (2, 3 and 5 mg/L) and initial vinasse loading volume (5000 and 10,000 mL) was investigated. Response surface methodology (RSM) and central composite design (CCD) were used to design the experiments. The amount of biogas produced in the process was measured using gas chromatography (GC). Results: The results showed that the optimal conditions for biogas production were as follows: temperature 37 °C (mesophilic), time: 21 days, pH equal to 7, C/N ratio equal to 1:25, H2O2 amount equal to 3 g/L and loading volume 10,000 mL. Under these conditions, the maximum biogas production efficiency reached 43.2%. Using a hydrogen peroxide concentration of 3 mg/L under these conditions helped to reduce the inhibitory effects of toxic compounds present in the vinasse and facilitated the biogas production process. Conclusions: These results indicate that the addition of hydrogen peroxide can be considered an effective strategy to reduce toxicity and increase the efficiency of the biogas production proces