Iranian Water Research Journal

Abstract Introduction:
The replacement of linear weirs with nonlinear types, such as labyrinth weirs, is often considered as an effective alternative for increasing spillway discharge capacity without the need to widen the existing channel. Labyrinth weirs are frequently a desirable design choice for regulating upstream water elevations and enhancing flow capacity. They have been successfully used to increase weir capacity and manage upstream flooding during low-probability storm events. Staged labyrinth weirs (weirs with crest lowering) are employed to safely discharging water under both normal and flood conditions. Their unique shape allows for more efficient energy distribution, minimizing turbulence and potential damage to downstream structures. Furthermore, maintenance requirements for labyrinth weirs are generally lower due to their simple yet effective design. When combined with flood forecasting systems, staged labyrinth weirs offer enhanced operational control, ensuring safety during extreme hydrologic events.
Methods:
Physical models are used to study the performance of labyrinth weirs under various flow conditions. In this research, labyrinth weirs were analyzed with different crest lowering configurations, including the vertex of the weir (VW), left oblique wall (LW), and left and right straight crests (LRW) near the channel walls. Additionally, different angles, heights, and the presence or absence of a nappe breaker were considered. The experiments were conducted in a metal and glass flume with a rectangular cross section. The flume had a width of 0.25 m, a depth of 0.5 m, and a length of 10 m. In each test, the upstream subcritical depth was measured using point gauges with an accuracy of 0.1 mm. The total head upstream of the weir was measured at a horizontal distance of three to four times the maximum water head at the crest of the weir. Also, the discharge was measured using a triangular sharp-crested weir placed at the end of the flume. The discharge-head relationship (Q-h) for the triangular weir was found in the experiments. The trapezoidal labyrinth weir models were installed three meters from the beginning of the flume. In this study, experimental tests were conducted on trapezoidal labyrinth weirs with one cycle, testing three sidewall angles (15°, 18°, and 23°) and three weir heights (14 cm, 16 cm, and 18 cm), in a rectangular channel. The discharge coefficient of the weirs depends on several factors, including: the hydraulic properties of the passing flow, the weir crest, and the geometric properties of the weir. Based on the effective parameters sidewall angle (α), weir height (p), and hydraulic head (Ht), the discharge coefficient was evaluated.
Results:
The results showed that for trapezoidal labyrinth weirs without a nappe breaker, the discharge coefficient (C_d) was higher than in the presence of a nappe breaker. In the Ht/p range of 0.1 to 0.5, under conditions without a nappe breaker, flow interference was reduced as the flow adheres more closely to the weir, leading to an increase in discharge. Additionally, the discharge coefficient (C_d) decreased as the hydraulic head ratio (Ht/p) increased. As flow discharge increases, the mixing of flow over the weir also increases, which contributes to a decrease in the discharge coefficient. There is an inverse relationship between the discharge coefficient and the weir length. As the crest angle increases, the weir length decreases, resulting in a higher discharge coefficient. Furthermore, for a given crest angle, the discharge coefficient slightly decreased as the weir height (p) increased. For instance, for a weir with a height of 12 cm, the discharge coefficient was slightly higher than for the 14 cm and 16 cm weirs. The study also revealed that for different conditions in staged weirs, the discharge coefficient for the left oblique wall staged crest (LW) was higher than those for the left and right straight crests (LRW) and the vertex of the weir (VW). At high values of Ht/p, the discharge coefficient decreased due to the collision of the falling jets. Additionally, by increasing the sidewall angle, the decrease of C_d with H_t/P became more significant. Optimizing the crest angle and sidewall angle can lead to a more efficient design by balancing the trade-offs between weir length and flow aeration. The discharge coefficient for trapezoidal labyrinth weirs was the highest for weirs with a sidewall angle of 23°, followed by those with a sidewall angle of 18°, which showed approximately 4.5% and 3% higher performance, respectively, compared with weirs with a sidewall angle of 15°.
Conclusion:
These findings highlight the significant impact of geometric parameters on the hydraulic performance of trapezoidal labyrinth weirs. The presence or absence of nappe breakers influences the flow pattern and energy distribution, affecting both discharge capacity and stability. A comparison of the results indicated that for a staged trapezoidal weir with a ∆P of 3 cm, the discharge coefficient for the left oblique wall staged crest (LW) was, on average, 30% higher, for the left and right straight crests (LRW) was about 20% higher, and for the vertex of the weir (VW) was 10% higher, compared to normal labyrinth weirs.

Abstract Introduction:
The increasing scarcity of water resources in arid and semi-arid regions, driven by population growth, climate change and extended droughts, highlights the necessity for sustainable agricultural practices. Greenhouse cultivation offers a practical solution for such challenging environments, particularly in countries like Iran, which experience severe water shortages. Developing greenhouse cultivation and implementing smart water management systems are essential strategies for enhancing water-use efficiency. Accurate estimation of crop water requirement in greenhouses is essential for optimizing irrigation schedules and improving productivity. This study reviews various methods for estimating evapotranspiration (ET) in greenhouses, evaluates their effectiveness and provides recommendations. Greenhouse environments differ from open-field conditions, due to controlled factors such as air temperature, humidity and wind speed. In addition to the controlled variables, uncontrollable factors like altitude (which affects atmospheric pressure) and solar radiation can influence the performance of ET estimation methods. Understanding the strengths and limitations of different approaches is essential for developing reliable models tailored to greenhouse conditions.
Review of Research Studies:
Several methods have been proposed for estimating greenhouse evapotranspiration. Some methods, such as Turc, Jensen-Haise, Hargreaves-Samani and Blaney-Criddle, exhibit poor accuracy and are unsuitable for greenhouse applications. These methods oversimplify complex environmental interactions or rely on limited meteorological data, resulting in significant deviations from actual ET values. Other methods, including FAO-Radiation, Priestley-Taylor and FAO-Penman, provide relatively acceptable results but still show considerable errors under certain conditions. While they incorporate more variables than simpler methods, their reliance on assumptions about energy balance and climatic relationships limits their precision. The Penman-Monteith equation is a methods that widely used and recommended by many researchers. This approach is recognized by the Food and Agriculture Organization (FAO) as the standard for estimating reference evapotranspiration (ET₀) and integrates key meteorological parameters such as air temperature, humidity, wind speed and solar radiation into a comprehensive energy balance framework. Its adaptability to diverse climatic conditions makes it particularly suitable for greenhouse environments where microclimatic factors are precisely controlled. Another promising method is the Stanghellini equation, specifically designed for greenhouse conditions. Although fewer studies have evaluated this approach, initial findings suggest that Stanghellini equation provides highly accurate estimates when applied in technologically advanced greenhouses. In contrast, the FAO-Penman-Monteith variant shows weaker performance, especially in low-tech greenhouse settings, highlighting the importance of aligning methodology selection with greenhouse infrastructure. The diversity in the performance among some of these methods across various regions can be attributed to uncontrollable parameters such as altitude, which affects air pressure. Also, the variations in the amount of the important parameter such as solar radiation, despite the possibility of controlling it in greenhouses, can be important and lead to differ the results among the methods in distinct regions, due to the difference in its control methods. The choice of input parameters in the equations also influences accuracy. Therefore, careful calibration and validation based on local conditions are imperative. Alternative approaches, such as lysimeters and evaporation pans, offer high accuracy. Lysimeters, while providing direct measurements of plant water consumption, are time-consuming and impractical for large-scale applications. Similarly, evaporation pans require precise depth measurements and coefficient adjustments, making them less suitable for automated greenhouse management systems.
Conclusion:
The literature review showed that no single method can be universally recommended for all greenhouse conditions. However, the findings suggest that the Penman-Monteith, FAO-Penman-Monteith and Stanglini methods are more reliable and exhibit less error in estimating greenhouse evapotranspiration compared with other methods. Their ability to utilize multiple meteorological parameters, and adapt to controlled greenhouse environments has demonstrated greater accuracy than alternative methods. Additionally, the literature review revealed that for low-tech greenhouses, the Penman-Monteith and FAO-Penman-Monteith methods are preferred due to their ease of application; while in technologically advanced greenhouses, the Stanghellini equation is more beneficial, provided that careful calibration is performed. These methods enable smart irrigation systems, facilitating real-time adjustments and optimization of water use efficiency. Consequently, while lysimeters represent the most accurate method for direct measurement of evapotranspiration, their limitations make them unsuitable for widespread use in greenhouses. Similarly, evaporation pans lack the precision required for modern greenhouse management. Therefore, well-calibrated empirical equations such as Penman-Monteith and Stanghellini, can enhance water efficiency in greenhouses. It is recommended that future research concentrate on refining and calibrating these methods through extensive field testing and using technological advances such as sensors to improve data collection and model accuracy.

Abstract Introduction:
The water crisis has become one of the fundamental challenges of the modern era, exacerbated by factors such as population growth, climate change, and uneven rainfall distribution. Iran, with its arid and semi-arid climate, faces significant limitations in water resource management, which impacts agriculture and the economy. Accurate runoff prediction is essential for sustainable water resource management and the design of water infrastructures. However, the complexity of nonlinear relationships and irregular flow distributions makes runoff prediction challenging. Various approaches, including physical, conceptual, and data-driven models, have been proposed. Data-driven models, leveraging machine learning, are particularly notable for their ability to analyze large datasets and uncover hidden patterns. Despite challenges (such as selecting suitable algorithms, determining effective inputs, and evaluating estimation accuracy), these models have been widely applied in hydrology. The aim of this research was to improve monthly runoff prediction in Mashhad basin by utilizing advanced machine learning approaches. In this regard, Variable Mode Decomposition (VMD) was employed as a data preprocessing method, and the Whale Optimization Algorithm (WOA) was used to enhance model accuracy. These methods were applied with the goal of achieving more accurate and efficient predictions in this field.
Methods:
The study area of Mashhad basin, located in Khorasan Razavi Province, is bordered by Hezar Masjid heights to the north and the Binalod heights to the south, with the longitudes of 59˚30' to 59˚42' East and the latitudes of 36˚12' to 36˚24' North. Meteorological and hydrometric data were provided for four stations (Ardak Band, Zoshk, Alang asadi and Kartian), from 1968 to 2022. The stationarity and stability of the time series for rainfall, evaporation, temperature, and discharge were first analyzed. Two distinct modeling approaches were employed to estimate runoff for the future month. In the first approach, three different combinations of parameters were used as model inputs. In the first scenario, all parameters with a three-month lag, determined based on the correlation coefficient of rainfall, temperature, evaporation, and discharge, were utilized. For the second scenario, after conducting sensitivity analysis on the first scenario, seven of the most influential parameters were selected. In the third scenario, the effect of using discharge with a three-month lag as the sole model input was evaluated. The Support Vector Machine (SVM) model and Long Short-Term Memory (LSTM) neural network, both in their basic and optimized forms, were applied to the data from each of the four studied stations. The accuracy of the developed models was assessed using statistical indices, including the Nash–Sutcliffe Efficiency (NSE), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Normalized Root Mean Square Error (NRMSE). In the second approach, the Variational Mode Decomposition (VMD) technique and the Whale Optimization Algorithm (WOA) were employed. Using this approach, the discharge time series was decomposed into several sub-series, each of which, with a three-month lag, was used as an input to both the basic and optimized SVM and LSTM models. Finally, the performance of the developed models was evaluated during the training and testing phases.
Results
This study aimed to evaluate the performance of VMD-WOA-SVM-WOA hybrid model for runoff estimation at four stations within Mashhad study basin. In this study, two different approaches for modeling runoff were investigated. In the first method, data preprocessing was performed using normalization, the optimized LSTM and SVR models performed better than the base models; however, due to the structural complexity of the hydrological data, the models' ability to identify accurate patterns and estimate runoff was limited. In the second method, data preprocessing was performed using Variable Mode Decomposition. This technique allowed for the extraction of more accurate features by separating hydrological data into components with different frequencies. The primary approach involved using the Variational Mode Decomposition (VMD) method to decompose the runoff time series into modes and optimize their frequencies with the Whale Optimization Algorithm (WOA). These modes were then used as inputs to the Support Vector Machine (SVM) model to estimate runoff for the future month. To assess the proposed model, its performance was compared with a simple SVM model using different input configurations. The results demonstrated that the VMD-WOA-SVM-WOA model achieved mean RMSE and Nash–Sutcliffe 0.185 and 0.979, respectively, with the minimum input variables. These findings align with the principles of regression modeling, emphasizing simplicity and avoiding unnecessary complexity. Furthermore, the results confirmed that increasing the number of input variables does not necessarily enhance estimation accuracy and can even introduce noise and reduce the model's generalizability. This research showed that by employing data preprocessing (VMD) and optimizing model parameters with WOA, a simple, accurate, and interpretable model can be developed. Additionally, the proposed model is not only effective for runoff estimation but also has the potential to be applied to similar studies of hydrological processes such as evapotranspiration and sediment modeling in different regions.
Conclusion:
This study investigated two approaches for runoff modeling. The first approach used data normalization and application of optimized LSTM and SVR models, which showed some improvement compared to base models. However, due to the complexity of hydrological data, the models demonstrated limited accuracy, and the overall performance based on low Nash–Sutcliffe values was not satisfactory. The second approach employed for processing, was Variational Mode Decomposition (VMD), which allowed better extraction of temporal features. With parameter optimization using the Whale Optimization Algorithm (WOA), the VMD-WOA-SVR-WOA model achieved significantly better accuracy and generalization. While VMD-WOA-LSTM also performed well, the superior results of VMD-WOA-SVR-WOA model highlighted it as an effective tool for runoff prediction and water resource management.

Abstract Introduction:
Groundwater is a vital resource for human livelihoods and agricultural productivity, especially in arid and semi-arid regions. Therefore, the quantitative and qualitative management of these resources is of great importance. Traditional methods of analyzing groundwater levels often overlook the complex interdependencies among various influencing factors, such as precipitation, temperature, and land use. Over the past two decades, copula functions have emerged as a powerful statistical tool for modeling such dependencies, enabling the joint distribution of multiple variables affecting a given phenomenon. This paper reviews existing research on the application of copula functions in groundwater-related studies and attempts to highlight gaps in the current literature while suggesting potential directions for future research.
Methods:
Copula functions are mathematical tools that link univariate distribution functions to form a multivariate distribution. A copula can describe the dependence structure between two or more random variables and has gained significant attention over the past two decades as a practical and efficient method for modeling the overall dependence structure of variables in multidimensional phenomena. Three main approaches are used to construct copula functions in three or more dimensions: (1) symmetric multidimensional copulas, which are limited by mathematical constraints and symmetric dependence requirements; (2) nested (hierarchical) copulas, where bivariate copulas sequentially link pairs of variables or their joint distributions in a stepwise manner until reaching the desired dimensionality, and (3) vine copulas, which offer greater flexibility through structured pair-copula constructions.
Results:
In this study, methods based on copula functions in groundwater studies were investigated from different aspects. The results showed that one of the biggest challenges in this field is the selection of a suitable copula function that can accurately describe the dependencies between the variables. An incorrect choice of copula function can lead to poor modeling results. Also, the complexity of the calculations and the need for data with adequate accuracy and length are further limitations when using copula functions in groundwater studies, as access to groundwater monitoring data is limited in many areas. However, copula functions offer significant advantages in modeling groundwater systems. These functions provide the necessary flexibility to model nonlinear dependencies between variables, and allow the separation of marginal distributions from the dependency structure. These features help to improve the risk assessment and management of groundwater resources. To realize the full potential of copula functions in hydrological research, it is necessary to conduct more case studies in different environments. Priority should also be given to studying the long-term effects of climate change and the more complex interactions between socio-economic and environmental variables. Finally, integrating copula functions with innovative modeling approaches can help improve modeling accuracy, and ultimately lead to a better understanding and management of groundwater resources. The results of a review of published studies in various fields (including joint frequency analysis of quantitative and qualitative variables, joint simulation, spatial analysis, effects of other variables on groundwater quantity and quality, groundwater drought, etc.) indicate the favorable performance of copula functions in groundwater studies. This effectiveness is primarily attributed to their distribution-oriented nature of this method. Despite recent advances in the use of copula functions in hydrology, their application to complex groundwater systems, involving spatially distributed variables and structural heterogeneities, has yet remained underexplored. The development of basic copula methods to account for non-stationarity in groundwater data could also be an area for future study. In addition, the integration of copula functions with more advanced modeling methods, such as Bayesian hierarchical models, could open up new opportunities for future research. This integration could help to improve the modeling of complex dependencies between hydrological variables, especially in groundwater systems.
Conclusion:
A review of current literature on climate change impacts reveals that most studies focus on specific geographic regions, limiting the generalizability of their findings. There is a need for more extensive case studies across diverse environments to validate the effectiveness of copula functions in various hydrogeological contexts. While some research has begun using copulas to assess climate change effects on groundwater levels, comprehensive studies examining long-term trends and their implications for water resource management remain scarce. Although copulas can effectively capture dependencies among multiple variables, existing studies often concentrate on a limited set of factors. More complex interactions—such as those involving socio-economic variables, land-use changes, and policy impacts—require further exploration. Additionally, most studies assume stationarity in time series data, leaving room for future research to incorporate non-stationarity in both marginal distributions and copula functions.

Abstract Introduction:
Scour in cohesive sediment beds under hydraulic jets is a critical challenge in hydraulic engineering due to the complex interplay of jet energy and sediment properties. Cohesive beds, dominated by fine-grained clay, exhibit unique erosion resistance driven by inter-particle bonding, making scour prediction and control vital for the stability of hydraulic structures like dams and plunge pools. The novelty of this study lies in its comparative analysis of scour induced by single and symmetric crossing jets on a purely cohesive clay bed, a relatively underexplored area. Unlike previous research focusing on non-cohesive or mixed beds, this study investigates the specific effects of jet configuration, impingement angles, bed moisture, and nozzle distance on scour dimensions under controlled conditions. By examining a cohesive bed with 90% fines and 10% sand, the study addresses a critical gap in understanding scour dynamics in fine-grained sediments. The experimental findings aim to provide innovative insights into optimizing plunge pool design and developing effective scour control strategies, enhancing the resilience of hydraulic infrastructure in cohesive sediment environments.
Methods:
Experiments were conducted in a 16 m long, 1 m wide, and 0.8 m high rectangular flume with transparent plexiglas walls for direct observation of scour processes. The flume included an adjustable tailgate to maintain a 12 cm tailwater depth, and a pumping system to provide a 2 L/s steady flow rate, measured by an electromagnetic flowmeter. Circular nozzles (2.2 cm diameter for crossing jets; 3.11 cm equivalent diameter for single jets) were mounted on adjustable supports to maintain a fixed vertical angle of 85° for both single and crossing jets, with crossing angles set at 45°, 75°, and 105° for crossing jets only. The nozzle distances from the water surface were adjusted to 8, 10.5, and 13 cm. The cohesive bed, with 90% clay (illite, montmorillonite, kaolinite) and 10% fine sand, had a median particle size of 0.0126 mm, plastic limit of 20%, and liquid limit of 35%. Bed moisture contents (13%, 16%, 19%) were prepared by mixing soil with water using an electric mixer, followed by compaction in six 5 cm layers to a 30 cm thickness. A hand roller ensured uniform compaction, and a vane shear test verified bed shear strength. Scour dimensions (depth, length, width) were measured using a laser meter with 1 mm accuracy.The experiments were conducted for 180 minutes to ensure that scour had reached equilibrium. Dimensional analysis focused on scour characteristics as functions of crossing angle, moisture content, and nozzle distance, with constant flow rate, tailwater depth, and vertical jet angle.
Results:
The results revealed distinct scour patterns between single and crossing jets. Single jets, due to concentrated kinetic energy, produced deeper scour holes, with depths up to 30% greater than those from crossing jets. At a dimensionless fall height of 4.18 and 13% moisture content, single jets produced maximum scour depth. In contrast, crossing jets at 105° and 19% moisture content exhibited minimal scour, while no scour observed at higher moisture levels (16% and 19%) and a fall height of 4.18 due to increased bed resistance. Crossing jets reduced scour depth by 45–66% at 75° and up to 100% at 105° compared with single jets, attributed to energy dissipation from jet collision, which forms a radial flow with reduced shear stress. Moisture content significantly influenced scour, with a 12–55% reduction in depth and 33–40% in length as moisture increased from 13% to 19%. This reduction is attributed to the reflecting enhanced cohesion from montmorillonite clay in the bed material. Scour length followed similar trends, with single jets producing longer holes (up to 14% increase with fall height) and crossing jets reducing length by 19–100% at 105°. Width was also lower for crossing jets, with reductions of 24–100% at higher angles and moisture levels. These findings align with previous studies, confirming that increased fall height reduces relative scour depth due to energy dissipation. The study highlights the effectiveness of crossing jets in minimizing scour on cohesive beds, particularly at higher impingement angles and moisture contents, providing a basis for optimizing plunge pool designs.
Conclusion:
This study highlights the contrasting scour behaviors of single and crossing jets on cohesive sediment beds, emphasizing the role of jet configuration, bed moisture, and nozzle distance in scour dynamics. Regarding the results, single jets, with focused energy, produced deeper, longer, and wider scour holes, with maximum dimensions at 13% moisture and higher fall heights. Crossing jets, particularly at 105°, significantly reduced scour (up to 100% in depth, length, and width) due to energy dissipation, with minimal scour at 19% moisture. Increased moisture content enhanced bed cohesion, reducing scour dimensions across both jet types. These findings offer valuable insights for hydraulic engineers, enabling the design of plunge pools and spillways that mitigate scour risks in cohesive bed environments. The results advocate for the use of crossing jets in scenarios requiring scour control, particularly in high-moisture conditions. Future research should explore numerical modeling to validate these experimental outcomes and investigate additional parameters, such as varying flow rates and bed compositions, to further refine scour prediction models for cohesive sediments.

Abstract Introduction:
Piano key weirs have rectangular, triangular, and trapezoidal shapes in terms of plan and are presented in four types A, B, C, and D. Piano key weirs are the evolution of nonlinear weirs with high efficiency; therefore, it is essential to study the flow energy loss and the methods to increase it. In the present study the first time, various numbers of flow splitters were used in the trapezoidal piano key weir of type B to increase the flow energy loss. Also, two weirs with heights of 0.20 and 0.18 m were used. The flow splitters were cylindrical and are six, four, and two in each cycle.
Methods:
The experiments were conducted in a channel with 10 m length, 0.8 m width, and 1 m height. The slope of the channel was zero. Water temperature varied between 8 and 13°C. The flow was recharged into the tank by a pump, a 10,000 m³ underground tank, and a monitor. The pump had 0.01% error. Because the velocity profiles coincided at 3.5, 0.4, and 4.5 m from the beginning of the channel coincide, a weir was installed at a distance of 5.5 m from the start of the channel. The flow rates varied between 0.02 and 0.05 m³/s. Three ultrasonic sensors were used to measure the flow depth. The first sensor was installed at a distance of 2P upstream of the weir relative to its center, and the second sensor was positioned 8P downstream of the weir to record the flow depth. Two type B trapezoidal piano key weirs were used with constant geometry but different heights of 0.20 and 0.18 m. The width of the weir inlet keys (W_i) and outlet keys (W_o) was 0.215 m and 0.075 m respectively. The length of the weir side walls (B*) and the length of the upstream overhanging edges of the weirs (B_i) was 0.40 m and 0.15 m, respectively. The length of the weir crest (L) was 3.27 m, and the thickness of the weir (Ts) was 0.01 m.
Results:
The flow splitters act as a barrier and divert the upstream flow; increasing the water level upstream of the weir. The splitters also divide the water flow and enhance aeration at the inlet keys. By the results of this research, as the number of blades increased, the water flow became more distributed and more aeration occurred at the keys. In the last row of blades (downstream of the weir), the degree of flow separation was more significant. In the weir with a greater height, the energy loss was higher and mixing of the flow near the weir toe was more intense; therefore, the flow was transferred downstream with a slower velocity. For weirs without flow splitters, the discharge coefficient in the 0.20 m high weir was obtained about 5.60% lower than that of the 0.18 m high weir. Also, the discharge coefficient in the weir with six, four, and two flow splitters per cycle was about 6.80, 1.97, and 0.50% lower, respectively, compared with the 0.20 m height weir without blades. In the weir with a height of 0.20 m compared to the weir with a height of 0.18 m, both without flow splitters, the flow energy loss was reduced by about 8.52%. Also, in weirs with a height of 0.20 meters with six, four, and two flow splitters, the flow energy loss was about 5.06, 3.07, and 1.45 percent higher, respectively, comparing the weirs with the same height and without flow splitters.
Conclusion:
Investigation of flow energy loss in piano key weirs is of interest and importance due to their high efficiency in the flow passage. In the present study, flow energy loss was researched in a trapezoidal piano key weir type B, with and without varying numbers of flow splitters. Dimensional analysis was also used to extend the results to other weirs and different types of piano key weirs in channels. The key findings of the current study are as follows: (1) Increasing the number of flow splitters (thereby reducing the effective length of the weir crest) led to a decrease in the discharge coefficient and increase in the flow energy loss. (2) Increasing the height of the weir resulted in a higher discharge coefficient, and reduced the flow energy loss. (3) The presence of splitters shifted the flow farther from the weir toe and reduced the specific energy downstream. (4) Increasing values of Hu/P and Le/P, the flow energy loss decreased. (5) A relationship was developed to calculate the flow energy loss with a correlation coefficient of 99.91%

Abstract Introduction:
Water scarcity and pollution have emerged as critical global issues, driven by population growth, resource overexploitation, climate change, and escalating environmental threats. Among various water pollutants, crude oil and its derivatives pose significant hazards to both ecosystems and human health. Accidental oil spills during extraction, transportation, or refining processes can result in long-lasting damage to aquatic environments and severely impact biodiversity. To mitigate such risks, numerous oil removal methods have been developed, with sorbent-based approaches gaining attention for their simplicity and efficiency. Sorbent materials can selectively absorb oil from oil–water mixtures through surface and capillary interactions. Among these, technical textiles—particularly nonwoven fabrics made from polyester (PET), polypropylene (PP), and bi-component (BC) blends—have shown great potential due to their high porosity, low density, scalability, and mechanical durability. While prior research has explored their structural and surface characteristics, their dynamic behavior under varying operational conditions remains under-investigated. Mathematical modeling provides a valuable tool to simulate and predict filtration performance over time. By modeling the oil absorption process, key factors such as initial oil concentration, textile type, and flow dynamics can be quantitatively analyzed. This study designs a simple textile-based filtration system using PET, PP, and BC fabrics, aiming to model oil separation performance and evaluate each material’s behavior under different concentration levels.
Methods:
A custom-made filtration system was developed to evaluate the oil absorption performance of three nonwoven technical textiles: polyester (PET), polypropylene (PP), and bi-component (BC) fabrics. The filter body was constructed using 3 mm thick polyethylene-based plastic sheets, known for their high chemical resistance. The filter had a rectangular shape (10 × 10 × 20 cm), with a 3 cm thick textile layer placed at the bottom to serve as the sorbent medium. Three oil–water mixtures with crude oil concentrations of 10%, 20%, and 30% by weight were prepared using tap water. Each mixture was passed through the filter, and the oil concentration in the effluent was measured at regular time intervals to monitor separation efficiency. To analyze the oil absorption behavior, a mathematical model based on the mass balance principle was developed, assuming first-order kinetics for oil sorption. The governing equation was calibrated using experimental data, and key parameters, including the rate coefficient (λ) and pollutant load (W), were estimated via curve-fitting. Model accuracy was evaluated using the coefficient of determination (R²) and normalized root mean square error (NRMSE). The validated model was then employed to predict effluent oil concentrations under various conditions, providing valuable insights into the filtration performance of the different textiles.
Results:
The proposed mass balance model effectively simulated the release of oil from textiles at different initial concentrations (10%, 20%, and 30%) for BC, PET, and PP fabrics. The pollutant load (W) and the transfer coefficient (λ) were used to evaluate the dynamics of oil transfer. The results showed that oil release varied significantly based on both textile type and concentration. BC fabrics released the highest amount of oil at all concentrations, indicating a greater tendency for oil desorption, while PP exhibited the lowest release. PET showed intermediate behavior. The model accurately estimated the pollutant load for all textile types, with R² values between 0.84 and 0.98, indicating a strong fit between observed and predicted values. The NRMSE ranged from 2.1% to 12.9%, confirming high model accuracy. Interestingly, the transfer coefficient (λ) decreased with increasing oil concentration for BC and PET, suggesting a saturation or resistance effect at higher loads. In contrast, PP showed an increasing λ trend, potentially due to differences in surface properties or oil interaction mechanisms. These patterns highlight the model’s capability to capture the distinct release behaviors of each fabric type under varying conditions. Overall, the study demonstrates the reliability and applicability of the proposed model in predicting oil release from textiles, offering valuable insight for environmental pollution modeling and textile waste management strategies.
Conclusion:
The results of this study demonstrated that technical textiles can serve as an effective and economical method for removing oil from aqueous mixtures. Among the three fabric types examined, the BC composite fabric, due to its high porosity and suitable structural composition, exhibited the highest absorption efficiency and model accuracy under most conditions. The developed mathematical model, based on the mass balance principle and assuming first-order reaction kinetics, successfully captured the dynamic behavior of oil absorption, particularly at low and medium oil concentrations. However, at higher contamination levels and with specific fabrics such as PP, the model’s accuracy decreased, indicating the need for further refinement and enhancement of the model under these conditions. Statistical analyses and comparative plots confirmed that kinetic modeling is a reliable tool for predicting the performance of oil-absorbing filters. Moreover, the findings can inform the design and optimization of industrial filters for treating water contaminated with oil and other organic pollutants. Ultimately, this study lays the groundwork for developing more advanced modeling approaches and the application of environmentally friendly technologies in managing oil pollution.

Abstract Introduction:
Intensive and controlled greenhouse cultivation can be effective to some extent in improving food security. Greenhouses have a distinct advantage due to their ability to support continuous crop production throughout the year, resulting in increased productivity, especially when compared with open-field cultivation. Water is one of the main and influential inputs on food production and security, and it should be used optimally to achieve high productivity and efficiency. Determining the optimal amount of water requirement and the performance of each crop provides valuable guidance for planners to increase the food security factor. Water shortage is also a significant threat to the agricultural sector. Determining irrigation scheduling is effective in enhancing the production of agricultural products, especially greenhouse crops. Appropriate knowledge of water consumption and the water use efficiency of various crops, including tomatoes and bell peppers, can effectively assist planners and officials at the regional and national levels in optimizing the production of various greenhouse crops throughout the seasons.
Methods:
This research was conducted in the Kakulak greenhouse complex located in Shahrekord city, Iran, during 2022-2023 cropping season. Cultivation was carried out in two greenhouses in the autumn of 2023, simultaneously with cultivation in the corresponding control greenhouses. Each crop (bell pepper and tomato) was planted in one greenhouse with three replicates, each replicate consisting of three pots. A grass lysimeter and an evaporation pan (class A) were installed in each greenhouse, and another evaporation pan was placed outside the greenhouse. Bell pepper seeds were sown in seedling trays using a culture medium and were transferred to the pot environment after about five weeks. Crop management practices (irrigation, weed removal, spraying, fertilization, pruning, measuring the height and number of fruits per plant) and harvesting were carried out during the cultivation period. Irrigation was typically performed daily. Fertilization and pesticide application of the pots were the same the greenhouse schedule. Daily recorded data included: volume of water added to the pots, the grass lysimeter volume of drained water, volume of water evaporated from the evaporation pans inside and outside the greenhouses, the temperature parameters, the instantaneous and maximum, and minimum daily relative humidity inside and outside the greenhouse and the amount of light intensity inside the greenhouse. In addition, the volume of water consumed in the bell pepper greenhouse was measured using a two-inch meter. Actual evapotranspiration (the amount of water consumed by the plant) was calculated and estimated using the water balance equation and considered for the desired crops. Water use efficiency index (WUE) was also calculated as a function of the yield of each crop (kilograms per hectare) and the amount of water used (cubic meters per hectare).
Conclusion:
In order to increase the food security factor, considering the challenges and tensions caused by the shortage of water resources globally and in Iran use of high-yield intensive cropping systems such as greenhouses cultivation, is essential. Development of greenhouses cultivation, due to higher productivity (lower water consumption and increased yield per unit area), can partially help solve the problems of water stress. According the results of the current research on water requirements and water use efficiency of tomatoes and bell peppers in greenhouses, the bell pepper crop consumed 4993 cubic meters per hectare of water during the growing season (341 days), with a yield and production of 115634 kilograms per hectare and a water use productivity index of 23.56 kilograms per cubic meter. The ratio of water used for bell pepper production to grass evapotranspiration and transpiration was 52.1 percent, and to the amount of evaporation from a class A evaporation pan was 58.31 percent. The tomato crop with 165-days growing season, water consumption of 2844 cubic meters per hectare, yield of 89191 kg per hectare, with a water use efficiency index of 31.36 kg per cubic meter was obtained. The irrigation hydromodule of both crops, considering the water requirement of pad and fan, was 0.45 liters per second per hectare. Future reaearch is suggested with focus on scaling these finding to larger greenhouse systems. Additionally, investigating the impact of varying greenhouse use across diverse agricultural contexts. These advancements could support local policymakers and farmers in developing resilint food production systems while conserving critical water resources.