https://ijwer.uoz.ac.ir/ Journal Of Iranian Water Engineering Research en daily 1 Fri, 22 Dec 2023 00:00:00 +0330 Fri, 22 Dec 2023 00:00:00 +0330 https://ijwer.uoz.ac.ir/article_233211.html Earthen dams are indispensable infrastructure components, playing a pivotal role in flood management, drinking water supply, agricultural irrigation, and energy production. These structures are critical for sustainable water resource management, particularly in regions prone to water scarcity or flooding, such as East Azerbaijan, Iran. The design and construction of earthen dams require meticulous attention to detail to ensure their long-term stability and safety. Among the most critical design considerations is the placement of the impermeable core, which serves as a barrier to control seepage, distribute internal pressures, and maintain structural integrity. Improper core placement can lead to excessive seepage, increased hydraulic gradients, and elevated uplift forces, all of which pose significant risks to the dam’s stability and the safety of downstream communities. This study, based on real-world data from an earthen dam in East Azerbaijan, investigates the impact of core position on two key performance metrics: hydraulic gradient and uplift force. By employing advanced numerical modeling techniques, the study provides actionable insights for optimizing earthen dam design, enhancing safety, and reducing the risk of structural failure.The primary objective of this study was to evaluate how different positions of the impermeable core affect the hydraulic and structural performance of an earthen dam. The impermeable core, typically constructed from materials such as clay with low permeability, is designed to minimize water seepage through the dam body. Seepage, if uncontrolled, can lead to internal erosion (piping), increased pore water pressure, and potential dam failure. Additionally, the core’s position influences the distribution of hydraulic pressures and uplift forces, which can destabilize the dam if not properly managed. The study focused on three core configurations—central, upstream inclined, and downstream inclined—to determine which position offers the best balance of seepage control, pressure distribution, and structural stability. The research was conducted using data from an operational earthen dam in East Azerbaijan, a region characterized by diverse hydrological and geotechnical conditions. This context underscores the importance of tailoring dam designs to local conditions while adhering to universal engineering principles.Numerical modeling was employed to simulate the behavior of the earthen dam under different core configurations. The study utilized the Seep/W module of GeoStudio, a widely recognized software for geotechnical and hydraulic analysis. The finite element method (FEM) was used to model seepage flow and pressure distribution within the dam. FEM is particularly suited for this purpose, as it allows for detailed simulation of complex geometries and material properties, capturing the intricate interactions between water flow and soil mechanics. The dam model was constructed based on real-world data, including soil properties, dam geometry, and hydrological conditions specific to the East Azerbaijan site. The material properties, such as permeability, porosity, and shear strength, were kept consistent across all models to isolate the effect of core position.Three core configurations were modeled: central, positioned at the midpoint of the dam’s cross-section, ensuring symmetry in pressure distribution; upstream inclined, tilted toward the upstream face, potentially reducing seepage but altering pressure gradients; and downstream inclined, tilted toward the downstream face, which may increase exposure to hydraulic pressures. Identical boundary conditions, including reservoir water levels and downstream drainage, were applied to all models to ensure a fair comparison. The models accounted for steady-state seepage under normal operating conditions, with the reservoir at full supply level. Key output parameters included the hydraulic gradient, a measure of the driving force for seepage, and uplift force, the upward pressure exerted by water on the dam’s foundation. These parameters were quantified to assess their impact on structural stability and the potential for failure mechanisms such as piping or foundation uplift.The results of the numerical simulations revealed significant differences in the performance of the three core configurations. The central core configuration demonstrated the most favorable outcomes across all measured parameters. It reduced the hydraulic gradient by 40% compared to baseline conditions, effectively limiting seepage to a rate of 2.5 liters per second per meter of dam width. This low seepage rate is critical for preventing internal erosion, which can weaken the dam over time. Additionally, the central core facilitated a uniform distribution of pore water pressure across the dam’s cross-section. This balanced pressure distribution minimized stress concentrations, reducing the likelihood of localized failures and ensuring optimal structural stability. The uplift force in the central core model was also significantly lower than in the inclined configurations, further contributing to its stability.In contrast, the upstream inclined core exhibited less favorable performance. The hydraulic gradient increased by 25% compared to the central core, indicating a higher driving force for seepage. This increase in gradient resulted in an uplift force of 120 kilopascals, suggesting elevated internal pressures that could compromise the dam’s stability. The higher uplift force is particularly concerning, as it indicates a potential for foundation instability, where water pressure could lift the dam base, leading to cracking or sliding. While the upstream inclined core still controlled seepage to some extent, its performance was suboptimal compared to the central core, highlighting the trade-offs associated with this configuration.The downstream inclined core performed the least effectively, with the most significant implications for dam safety. This configuration increased the uplift force by 35% compared to the central core, reaching 150 kilopascals. The elevated uplift force is a critical concern, as it significantly increases the risk of structural damage, particularly through mechanisms such as foundation uplift or internal cracking. The downstream inclined core also exhibited higher seepage rates and hydraulic gradients than the central core, further exacerbating the potential for instability. The increased pressure concentrations in the downstream region could lead to piping, where water erodes soil particles, creating channels that weaken the dam’s structure. These findings indicate that the downstream inclined core is the least desirable configuration for ensuring long-term dam safety.The study’s findings underscore the critical role of core placement in the design and performance of earthen dams. The central core configuration consistently outperformed the inclined alternatives, offering superior control over seepage, hydraulic gradient, and uplift forces. The 40% reduction in hydraulic gradient and the low seepage rate of 2.5 liters per second per meter highlight the central core’s ability to minimize water flow through the dam, reducing the risk of internal erosion and pressure-related failures. The uniform pressure distribution further enhances stability by preventing stress concentrations that could lead to cracking or sliding. In contrast, the upstream and downstream inclined cores introduced significant risks. The upstream inclined core’s 25% increase in hydraulic gradient and 120-kilopascal uplift force suggest a moderate risk of instability, while the downstream inclined core’s 35% increase in uplift force (150 kilopascals) poses a severe threat to structural integrity.The implications of improper core placement are profound. Excessive seepage and uplift forces can lead to catastrophic failures, such as dam breaches, which have devastating consequences for downstream communities, infrastructure, and ecosystems. Historical examples, such as the Teton Dam failure in 1976, illustrate the dangers of poor seepage control and inadequate design. By prioritizing a central core configuration, engineers can mitigate these risks, ensuring that the dam operates safely under a wide range of hydrological conditions. The study’s findings are particularly relevant for regions like East Azerbaijan, where earthen dams are integral to water management and flood control.This study provides practical guidance for civil engineers and dam designers, emphasizing the benefits of a centrally positioned impermeable core. This configuration minimizes seepage and hydraulic gradients while ensuring balanced internal forces, thereby enhancing dam safety and longevity. The findings are applicable not only to new dam construction but also to the retrofitting of existing structures to improve their performance. The study also sets the stage for future research, which could explore additional factors such as soil heterogeneity, varying hydraulic conditions, or long-term environmental impacts to further refine dam design practices. For instance, investigating the effects of seasonal variations in reservoir levels or the incorporation of advanced materials could provide additional insights into optimizing core performance.The results contribute to the broader field of earthen dam engineering by offering evidence-based recommendations for improving the safety and performance of critical infrastructure. In regions like East Azerbaijan, where water resource management is a priority, the adoption of a central core design can enhance the reliability of earthen dams, ensuring their ability to withstand operational and environmental stresses. By reducing seepage, hydraulic gradients, and uplift forces, the central core configuration minimizes the risk of failure, protecting both human lives and economic assets. The study also highlights the importance of rigorous numerical modeling in dam design, as tools like GeoStudio enable engineers to simulate complex scenarios and make informed decisions.In conclusion, this study demonstrates that the central core configuration is the optimal choice for earthen dam design, offering significant advantages in seepage control, pressure distribution, and structural stability. The upstream and downstream inclined cores, while viable in certain contexts, introduce unacceptable risks that could lead to failure under operational conditions. By adopting the central core design, engineers can enhance the safety and longevity of earthen dams, contributing to sustainable water resource management and flood control. The insights provided here are a valuable resource for dam designers, policymakers, and stakeholders involved in the planning and maintenance of critical infrastructure. https://ijwer.uoz.ac.ir/article_234672.html Abstract Reference evapotranspiration (ET0) plays a crucial role in the management and optimal use of water resources, climate studies, and the water cycle. Among the various approaches used to estimate ET0, the FAO Penman-Monteith (PM) model is recognized as the standard method. However, the requirement for extensive data limits the application of this method. Hybrid models show good performance in estimating ET0, among which the Penman Group (PG) models, by separating the contributions of aerodynamic and energy balance components, are widely used for calculating ET0. This study was conducted with the aim of evaluating and calibrating the Penman Group (PG) model for windy regions of Iran. For this purpose, long-term meteorological data from seven weather stations, Ardabil, Aligoudarz, Bijar, Torbat-e Jam, Rafsanjan, Zabol, and Manjil—were utilized. The results indicated that the Penman (P) model has the highest level of agreement with the standard model. Therefore, to improve the results, the mentioned model was calibrated for the studied stations, and the contribution of each of the aerodynamic and energy balance components was calculated using the calibrated model. The findings revealed that as wind speed increases, the contribution of the aerodynamic component rises for all the examined stations, and this increase is more pronounced for the Zabol station, which experiences higher wind speeds. Considering the significant impact of air flow and wind speed on the low values of ET0 in windy areas, implementing strategies such as installing windbreaks—both natural and artificial—can significantly help reduce ET0 values and, consequently, contribute to better water resource management.Keywords: Combination models, Penman-Monteith, water resources management, wind function.IntroductionReference evapotranspiration (ET₀) is a key indicator of crop water requirements, and its accurate estimation is essential and necessary for water resource management. The Food and Agriculture Organization of the United Nations (FAO) recommends the FAO Penman-Monteith (PM) model as the standard method for estimating reference evapotranspiration (ET₀). However, its application is not always feasible due to high data requirements. Previous studies indicate that combination-based models demonstrate the best performance in estimating ET₀. Solar radiation and air temperature are the primary meteorological factors influencing ET₀ (Ghiat et al., 2021). Nevertheless, in certain locations such as windy regions, wind speed also plays a significant role. Therefore, the objective of this study is to investigate the contribution of the aerodynamic component and the energy balance component to ET₀ in windy regions of Iran. For this purpose, the Penman-Monteith model was selected as the standard model, along with three combination models Penman, Penman-Kimberly, and Allen-Pruitt which separately estimate the contributions of the aerodynamic and energy balance components (Wright, 1996). Additionally, improving the performance of the selected models through calibration and adjustment for windy regions of Iran is another goal of this research. To achieve these objectives, daily meteorological data from seven synoptic stations across the country Ardabil, Aligoudarz, Bijar, Rafsanjan, Zabol, and Manjil were used (Mohamadi et al., 2021).MethodologyFor this purpose, based on a review of available sources, the meteorological stations of Ardabil, Aligoudarz, Bijar, Torbat-e Jam, Rafsanjan, Zabol, and Manjil were selected. The main reason for selecting these stations is their prolonged periods of high wind speed compared to other synoptic stations across the country. The meteorological data used include daily-scale parameters such as air temperature, solar radiation, relative humidity, sunshine hours, and wind speed over the time period from 2000 to 2024 (Table 1). In this study, the Penman-Monteith (PM) model was used as the standard method for evaluation and calibration. The general form of the Penman (P) model allows for separate calculation of the aerodynamic component γ/(∆+γ) F_w (e_s-e_a ) and the energy balance component ∆/(∆+γ) (R_n-G) (Wright, 1996). The dimensionless wind function (Fw) represents the effect of wind speed on the advection of sensible heat in ET₀ estimation. Various researchers have proposed different values for the wind function coefficients (aw and bw). In the original Penman equation (P), aw and bw are equal to 0.1 and 0.537, respectively; in the Penman-Kimberly (PK) model, they are 0.75 and 0.993, respectively; and in the Allen-Pruitt (AP) model, they are 0.1 and 0.862, respectively (Table 2). Therefore, in this study, three different versions of the Penman model were used. To calibrate the investigated models, the sum of squared errors (SSE) method was employed. Results and DiscussionET₀ values were calculated using the Penman group models (P, PK, and AP) for the selected stations and compared with the standard method. The results showed that, for all studied stations, all Penman group models overestimated ET₀ compared to the standard method. The highest agreement was observed for the P model (Penman, 1963), with agreement coefficients of 0.95, 0.98, 0.98, 0.99, 0.97, 1.00, and 0.97, respectively, for Ardabil, Aligoudarz, Bijar, Torbat-e Jam, Rafsanjan, Zabol, and Manjil. The lowest agreement belonged to the PK model (Penman-Kimberly, 1972), with agreement coefficients of 0.91, 0.88, 0.90, 0.90, 0.88, 0.89, and 0.85 for the same stations. Therefore, the P model was selected as the best-performing model for all stations and was calibrated by adjusting the wind function coefficients (Fw) through the error minimization method (least squares). After calibration, the ET₀ values estimated by the adjusted Penman model (Adjusted-P) became closer to those estimated by the standard method. The model efficiency (EF) also improved after calibration, reaching values of 0.99, 0.98, 0.99, 1.00, 1.00, 0.99, and 1.00 for Ardabil, Aligoudarz, Bijar, Torbat-e Jam, Rafsanjan, Zabol, and Manjil, respectively. The relationship between average wind speed and the average contribution of energy balance and aerodynamic components at the daily scale was also plotted for the studied stations. Results indicated that, for all stations, as wind speed increased, the contribution of the aerodynamic component clearly and significantly increased. Subsequently, the contributions of the aerodynamic and energy balance components were calculated for the calibrated Penman model. The contribution of the aerodynamic component was found to be considerable across all stations, particularly pronounced at Zabol station, which has the highest average wind speed. Therefore, the role of this component—which reflects airflow and wind speed—in determining ET₀ values cannot be ignored. Consequently, using simplified alternative models for ET₀ estimation that do not account for wind speed, such as radiation-based or temperature-based models, should be accompanied by appropriate calibration and adjustment of their coefficients to ensure accuracy in windy regions.ConclusionThe results indicate that as the average wind speed increases, the contribution of the aerodynamic component rises across all investigated stations. Overall, the contribution of the aerodynamic component is considerable compared to that of the energy balance component at all studied stations, with this effect being particularly pronounced at Zabol station, which has the highest average wind speed. Therefore, given the significant influence of airflow and wind speed on the magnitude of ET₀ in windy regions, implementing measures such as installing natural or artificial windbreaks in these areas could substantially contribute to reducing ET₀ and, consequently, improving water resource management. However, the effectiveness and practical implementation of such measures require further extensive investigation.  https://ijwer.uoz.ac.ir/article_235410.html Accurate prediction of suspended sediment transport is importance for the sustainability of river engineering. The aim of this study is to investigate the feasibility of a new intelligent model called the M5 tree model with radial function basis (RM5Tree) for predicting suspended sediment load using daily data at the Trenton meteorological station, located on the Delaware River (USA). For this purpose, several combinations of input characteristics have been defined based on sediment and river flow information. The prediction accuracy of the proposed model has been validated by statistical evaluations and graphical displays in comparison with several well-known predictive models, including the ANN method and the classical M5 tree-based model. The results obtained from the values of root mean square error and coefficient of determination show the remarkable prediction accuracy of the proposed RM5Tree model.Keywords: Sediment transport prediction, river engineering sustainability, RM5TreeIntroduction : Among the types of sediment load, including bed load and suspended load (SSL), SSL is the main part of sediment transport and has a more complex pattern compared to bed load. Therefore, providing an intelligent and reliable predictive model for SSL is a fundamental research topic for water resources researchers. The SSL pattern has many stochastic characteristics due to the influence of several hydrological, and morphological variables related to the characteristics of the watershed (Kisi and Yaseen 2019). Laboratory determination of sediment concentration requires extensive efforts to collect samples and perform several analytical processes. In addition, these processes are time-consuming and unreliable in flood conditions. To overcome these disadvantages, computational tools have provided suitable and practical solutions, which are introduced in the form of machine learning models. According to the review of the research literature, very limited studies have addressed the estimation of SSL using the potential of decision tree models(MT). Talebi, Mahjoobi et al. (2017) used MT and regression tree (RT) to predict daily sediment discharge using stream discharge and precipitation as predictor variables in the Heidarabad basin of Iran. They compared the used decision MT with ANN and concluded the high performance of decision MT.The present study emphasizes on the implementation of a new version of the M5Tree model integrated with the radial basis function in the form of a hybrid model for predicting SSL on a daily time scale (RM5Tree). The results of the newly developed model are validated in comparison with the classical M5Tree models.Methodology: This study utilized 32 years of daily river discharge (Q) and suspended sediment load (SSL) data from the Trenton Station on the Delaware River, USA (USGS Station No. 01463500). The data were split into training (70%) and testing (30%) sets. Descriptive statistics for the input variables are provided in Table 1, and the study area is illustrated in Figure 1.To capture temporal dependencies, six input combinations (scenarios) were developed using current and lagged values of Q and SSL:i. Qt,St-1,St-2.ii. Qt,Qt-1,St-1.iii. Qt,Qt-1,Qt-2.iv. Qt,Qt-1,St-1,St-2.v. Qt,Qt-1,Qt-2,St-1.vi. Qt,Qt-1,Qt-2,St-1,St-2Three predictive models were applied: Multilayer Perceptron Neural Network (MLPNN), classical M5 Model Tree (M5Tree), and the proposed Radial Basis M5Tree (RM5Tree). MLPNN used the Levenberg–Marquardt backpropagation algorithm (Figure 2a). M5Tree created regression-based decision trees, while RM5Tree enhanced this by mapping input data into radial space via a normal cumulative distribution function (Figure 2b, 2c).Performance was evaluated using Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Nash–Sutcliffe Efficiency (NSE), and Agreement Index (d). These metrics, computed for all models and input combinations, are presented in Table 2 to determine the most effective approach for daily SSL prediction.Results and Discussion: The proposed Radial Basis M5Tree (RM5Tree) model demonstrated superior performance in predicting daily suspended sediment load (SSL) compared to benchmark models (ANN, and classical M5Tree) across all six input scenarios. Evaluation metrics, including RMSE, MAE, NSE, and agreement index (d), are presented in Table 2, revealing that RM5Tree consistently outperformed others in both training and testing phases. The optimal input combination included current discharge (Qt) and two lagged values each of discharge and sediment load (Qt, Qt-1, Qt-2, SSLt-1, SSLt-2). This configuration, combined with a 15-center radial transformation, yielded the lowest RMSE (2090 t/day), highest NSE (0.86), and best overall agreement (d = 0.92). The enhanced performance is further illustrated in Figure 3, showing the highest d/MAE ratio, and Figure 4, where RM5Tree’s predictions most closely align with observed data.The innovation of this study lies in integrating radial basis transformation with the M5Tree framework to improve generalization and handle nonlinearity more effectively. By mapping input data into a radial space using a normal cumulative distribution function, RM5Tree captures subtle variations in SSL dynamics that traditional models overlook. Compared to previous models such as GEP, ANN, W-GEP, and neuro-fuzzy approaches used by Shiri and Kişi (2012) and Vafakhah (2012), RM5Tree achieved significantly lower RMSE values—improving prediction accuracy by up to 66%. While models like CART (Choubin et al., 2018b) and MT (Talebi et al., 2017) also leveraged decision trees, they lacked the hybrid transformation mechanism that distinguishes RM5Tree, limiting their adaptability to high-stochasticity environments. A major strength of RM5Tree is its adaptability across varying input configurations. Unlike ANN, which is sensitive to input dimensionality and structure, RM5Tree maintained stable performance across all scenarios. Additionally, it avoids overfitting by transforming data into a smoother, radially-distributed input space, improving its generalization capability. In summary, this study introduces a novel hybrid machine learning framework for SSL prediction, which outperforms both conventional and state-of-the-art models in accuracy and robustness. The results contribute a practical and scalable solution for sediment management in river engineering, offering significant implications for sustainable water resource planning.Conclusion: This study introduced a novel hybrid model (RM5Tree) for predicting daily suspended sediment load (SSL) using river discharge and historical sediment data. Among six tested input scenarios, the best performance was achieved using current discharge and two preceding values of discharge and SSL. The RM5Tree model significantly outperformed benchmark models (ANN, M5Tree), achieving the lowest RMSE (2090 t/day) and highest NSE (0.86), as shown in Table 2. The innovation lies in transforming input data into radial space, enhancing the model's ability to capture nonlinear, stochastic sediment patterns. Compared to previous models such as ANN, GEP, and CART, RM5Tree demonstrated higher accuracy and generalization. This approach offers a reliable tool for sediment prediction and river engineering applications, contributing to better watershed management and infrastructure planning. https://ijwer.uoz.ac.ir/article_235994.html IntroductionIn order to estimate the environmental water rights of rivers in the sustainable management of water resources and the preservation of ecosystems in watersheds, various methods are examined, taking into account hydrological, ecological, and hydraulic conditions, and flexibility and compatibility with the region. Methods for determining environmental flows are classified into four groups: hydrological, hydraulic, habitat simulation, and comprehensive. The evaluations conducted indicate that the assessment of environmental needs in important rivers is a priority and therefore it is necessary to estimate them in accordance with the conditions of the region. In this regard, this important issue has been carried out in the present study using hydrological methods as a case study in the Tajan River using statistical data collected during the water years 1370-1395.Methodology The Tajan River basin, with an area of about 4015.88 square kilometers and geographical coordinates of 52 degrees and 56 minutes to 54 degrees and 59 minutes east longitude and 35 degrees and 56 minutes to 36 degrees and 49 minutes north latitude, is located in Zone 39 of the UTM geographical system in Mazandaran Province. The perimeter of the basin is close to 414 kilometers due to its large extent and elongation. The Shahid Rajaee Reservoir Dam is a double-arch concrete type that was built on the Tajan River about 40 kilometers south of Sari city at the location of Sulayman-Tangeh with a geographical longitude of 53 degrees and 13 minutes and a geographical latitude of 36 degrees and 14 minutes. The distinction and innovation aspect of this research compared to research on a similar subject is based on the fact that, at first, one of the rivers in the north of the country, which is located in the vicinity of the main and important dam in the study area, was studied. Secondly, the assessment of the effects of dam construction is very extensive and in addition to evaluating the hydrological characteristics on the river flow conditions, the situation resulting from its impact on other parameters is also carried out. The selection of a station (hydrometry) to analyze the flow conditions in the Tajan River depends on the location of the dam in the region. For this purpose, the statistics of the stations obtained from the Regional Water Company of Mazandaran Province are evaluated with respect to the dispersion of the stations relative to the dam.Results and Discussion This study was conducted to investigate the environmental characteristics and impacts of Shahid Rajaee Dam on the conditions of the study area. In addition, using hydraulic and hydrological methods, the amount of environmental flow of this river in the upstream and downstream stations was estimated and its impact on the characteristics of the river was presented. The chemical quality of Tajan River water for agricultural purposes was determined as C2S1 based on the minimum and maximum changes in the average values of two factors: sodium absorption coefficient and electrical conductivity according to the Wilcox classification. In terms of drinking, the quality of river water in all study stations was acceptable in terms of total hardness and concentration of dissolved substances in the upstream and middle areas. Biologically, in all studied stations, the river water is unsuitable for drinking purposes and requires purification and chlorination. Monthly flow rate changes at two stations, Soleiman-Tangeh and Rig-Cheshmeh, as upstream and downstream stations of the dam, were investigated during the 26-year statistical period from 1991 to 2016. The results for Soleiman-Tangeh station indicate flow control in the periods after the construction of the dam from the beginning of the water year to Farvardin. After that, due to the release of flow during the cultivation seasons, the peak flow value increases significantly compared to before the construction of the dam. In the hydrological method, the flow continuity curve transfer method, Tennant and Tasman, and in the hydraulic method, the wetted medium method were used as appropriate approaches in this regard. The results indicated that the average environmental flow in the Tajan River using different methods was different according to the desired method, and on the other hand, the construction of the dam led to the released amount not being in good agreement with the calculated amount. The highest value obtained in the flow continuity transfer curve method was 25 cubic meters per second, so that in these conditions, from a management perspective, it is in biological class C with the approach of maintaining the minimum biological conditions of the river. The average flow value in the presence of the dam during the release period is about 16 cubic meters per second, which is relatively consistent with the values calculated in other methods.Conclusion The amount of released flow is about one-third of the minimum environmental flow required by the river downstream. Comparing the statistics of the two stations shows that the changes in water quality parameters at the Sulayman-Tangeh station are more noticeable than at other stations. Also, the changes in parameters at the Rig-Cheshmeh station are significant compared to Sulayman-Tangeh. The study of environmental flow conditions and also flow quality after the construction of the dam indicates that despite the fact that the amount of released flow is about one-third of the environmental requirement obtained from the flow continuity curve method, for various reasons such as high groundwater levels, appropriate rainfall in the basin, temporal distribution of rainfall, etc., no serious problems have been observed, and as a result, no significant changes have been observed in the environmental characteristics and quality characteristics. https://ijwer.uoz.ac.ir/article_235995.html IntroductionPiano key weirs (PKWs) are a new form of non-linear weir that has a higher flow capacity than other similar weirs. These weirs have rectangular, triangular, and trapezoidal shapes in plan. They are available in four types: A, B, C, and D. Many researchers have investigated the effects of flow, additional structures, bed material diameter, and other factors on the maximum scour depth. Researchers such as Fathi et al. (2024, 2025), Abdi Chooplou et al. (2024a & b), and Kazerooni et al. (2024) have investigated the effect of flow, material diameter, tailwater depth, and additional structures on the maximum scour depth. Considering the existing studies on localized scour downstream of PKWs, there is still a need for cheaper and more efficient solutions to reduce scour in these weirs, especially type B PKWs. In the present study, a type B trapezoidal PKW with riprap downstream was used under submerged flow conditions. Also, three different flow rates, three different tailwater depths, gravel bed materials, and riprap materials with lengths of 0.10, 0.20, and 0.30 m were used downstream of the weir. Furthermore, an equation derived through dimensional analysis demonstrated a high correlation (93.73%) with the observed data for predicting the maximum scour depth.Methodology The experiments were conducted in a flume 10 m long, 0.8 m wide, and 1 m high. The flow was fed into the channel from an underground reservoir by a Programmable Logic Controller (PLC), a pump, and an 8-inch diameter pipe. The width of the weir inlet keys (Wi) is 0.215 m, the width of the weir outlet keys (Wo) is 0.075 m, the length of the weir side wall (B*) is 0.4 m, the length of the upstream overhang of the weir (Bi) is 0.15 m, the thickness of the weir crest (Ts) is 0.01 m, and the length of the weir crest (L*) is 3.27 m. The weir has three outlet keys, two inlet keys, and two inlet half keys (Fig. 2). The average diameter of the riprap material (dr) is 0.033 m. Three different lengths of riprap, 0.1, 0.2, and 0.3 m, were used downstream of the weir. The thickness of the ripraps was constant in all experiments and was three times the diameter of the riprap material (i.e., 0.1 m) (Lidya et al., 2022). Table 1 presents the hydraulic and sedimentary parameters that affect downstream scouring for a type B PKW with riprap under submerged flow conditions. A total of 27 experiments were conducted under these conditions to calculate the maximum scour depth.Results and DiscussionThe flow from the weir inlet keys was transferred downstream as a free jet into the outlet keys and downstream as an inclined jet from the outlet keys. The flow converged at the beginning of the outlet keys and entered them. Unlike in free-flow conditions, a localized immersion zone does not form at the beginning of the outlet keys under submerged flow. Consequently, a higher flow height is also not observed in that area. The formation of surface vortices in the outlet keys results from the interaction of two flows: the undercurrent in the outlet keys and the overriding current from the inlet keys. As mentioned, these vortices entered the bed superficially and with less force. Ripraps are heavier, and surface eddies cannot easily carry them downstream. Clearly, the data show that the maximum scour depth increases with increasing flow rate. Furthermore, the maximum scour depth decreases significantly with increasing riprap length. As the tailwater depth increases, the flow downstream of the weir has a lower velocity, and the tailwater depth reaches a point where it mixes with the flow exiting the weir. The flow slows down, and its velocity decreases. As the depth of the outfall increases, the propagation length of the jets that hit the bed materials increases. Figures 3, 4, and 5 show the effect of flow rate, tailwater depth, and riprap length on the maximum scour depth under submerged flow conditions. On average, in a 0.10 m riprap, the maximum scour depth increases by 65.1% and 76.5%, which is associated with a 14.3% and 25% increase in flow rate, respectively. Similarly, in a weir with a 0.20 m riprap, the maximum scour depth increases by 71.9% and 81.5% with 14.3% and 25% increase in flow rate, respectively. Furthermore, in a weir with a riprap of 0.30 m, the maximum scour depth increases by approximately 76.6% and 85.4% with a 14.3% and 25% increase in flow rate, respectively. On average, in a weir with a 0.10 m riprap, the maximum scour depth decreases by approximately 1.24% and 1.51% with an 8% and 14.8% increase in the tailwater depth, respectively. Similarly, in a weir with a 0.20 m riprap, the maximum scour depth decreases by approximately 28% and 48.8%, with 8% and 14.8% increase in the tailwater depth, respectively. Furthermore, in the weir with a 0.30 m riprap, the maximum scour depth decreases by about 28.2% and 55.9%, respectively, and is accompanied by 8% and 14.8% increase in the tailwater depth.Conclusion This study investigated the reduction of local scour downstream of the PKW Type B using riprap under submerged flow conditions. The presence of riprap significantly reduced the maximum scour depth, with ripraps of 0.30 m length being more effective than ripraps of other lengths.Key Findings:• Riprap significantly reduces scour depth in submerged flow mode.• Due to the absence of an overhang downstream of the Type B PKW, the outflow from the inlet keys flows close to the weir toe, which increases scour along the weir toe. • Riprap lengthens the scour hole and moves the maximum scour depth away from the weir toe.• With taller ripraps, the scour depth is reduced.• The scour index shows the lowest value for the submerged flow condition with the longer riprap. https://ijwer.uoz.ac.ir/article_235996.html Water distribution systems (WDSs) are vulnerable to accidental or intentional contamination events due to their large size and complex configurations. In this research, to reduce the impact of pollution on the health of consumers, the optimization-simulation approach was used to determine the optimal locations of quality sensors in a part of Mashhad water distribution network. EPANET software as simulator and multi-objective genetic algorithm as an optimizer are employed to a) maximize the detection likelihood b) minimize expected detection time and c) minimize the mass of contamination consumed. To achieve more realistic answers, the contaminant injection node, injection time, mass rate and duration of injection are considered indefinitely. The results showed that by installing only one or two sensors, 21.3% and 41.6% of contamination events can be detected, respectively. Also, by installing only one sensor in the Mashhad water distribution network, the detection time and the amount of polluted water consumed can be reduced by 17.8 and 37 percent, respectively.IntroductionWater distribution systems are essential infrastructures that deliver drinking water to consumers. Ensuring their safety is a critical public concern, as these systems are vulnerable to both accidental and intentional contamination.When an event occurs, it can have a significant impact on society and the economy. For example, in 2016, the water distribution networks of Beijing and Hong Kong were contaminated. Unfortunately, the contamination was not identified until people consumed the contaminated water for a long time. Such incidents highlight the urgent need for rapid contamination detection, accurate source identification, and effective mitigation strategies to minimize adverse consequences.Previous studies have investigated the optimal placement of contamination detection sensors in water distribution networks. Harif et al. (2023) addressed this problem using NSGA-III, determining optimal sensor locations based on four objective functions: (1) maximizing detection coverage, (2) minimizing detection time, (3) maximizing redundancy, and (4) minimizing the number of contaminated nodes. Shahra and Wu (2023) studied optimal sensor placement in two different distribution networks by randomly selecting contamination scenarios. For these scenarios, they identified optimal sensor locations using an evolutionary optimization algorithm considering two objectives: minimizing the volume of contaminated water consumed and minimizing the detection time of contamination events.A review of previous studies on sensor placement optimization shows that, significant simplifications have often been applied to reduce computational complexity. These include limiting injection nodes, constraining the number of sensors, and considering only a restricted set of contamination scenarios. Moreover, many uncertainties associated with contamination events, such as the time, duration, and injection rate of pollutants, have been neglected.To address these limitations, this study proposes a multi-objective optimization approach to determine optimal sensor locations in a part of Mashhad’s water distribution network, aiming to: (a) maximize detection likelihood, (b) minimize detection time, and (c) minimize the volume of contaminated water consumed.Methodology In this study, EPANET was employed to simulate the hydraulic behavior and water quality within the distribution network. For the optimization process, both single and multi-objective genetic algorithms were applied. Figures 1 and 2 show, respectively, the general flowchart of the NSGA-II algorithm and the study zone.Construction of contamination matrixContamination scenarios are defined as follows:a) Intrusion can occur at all nodes except dead ends.b) Events may start anytime from 00:00 to 24:00.c) Injection rates range from 1–30 g/min.d) Injection durations vary between 30–180 minutes.To define contamination scenarios, the following assumptions are made:a) Contaminants are introduced every 30 minutes (Start Time).b) Injection rates of 5, 10, 20, and 30 g/min are considered (Mass).c) Durations of 40, 80, 120, and 160 minutes are used (Duration Time).This results in 559,104 possible scenarios (728 × 4 × 4 × 48). Due to this large number, a representative subset of 1,000 scenarios is selected to form the contamination matrix for optimization. Figure 3 presents the flowchart of the steps involved in selecting the top 1000 contaminants for the contamination matrix.Results and Discussion Since the number of sensors is not predetermined, it is also considered as an objective function. The allowable range is set between 1 and 20 sensors. Initially, the number of sensors was investigated versus the maximum detection of pollutants. As shown in Figure 4, results showed that the detection likelihood reaches its maximum value of 100% when 18 sensors are deployed. Conversely, the minimum detection likelihood, observed when only a single sensor is used, is limited to 21.3%. Figure 5 illustrates the relationship between the number of sensors and the minimum detection time, showing that the shortest detection time (91 minutes) occurs with the maximum number of sensors (20), whereas with only one sensor, detection time rises to 1184.6 minutes.The analysis of the number of sensors versus the volume of contaminated water consumed showed that the optimal solution is one that prevents the consumption of contaminated water with the minimum number of deployed sensors. As expected, achieving the lowest volume of contaminated water consumption requires the maximum number of sensors (20), reducing the consumed contaminated water to 24.9 million liters. In contrast, when only a single sensor is installed, the consumed volume reaches its maximum, totaling 237.2 million liters (Figure 6).The optimal Pareto front was analyzed for two sets of conflicting objectives in sensor placement within water distribution networks. The first set considered maximizing detection likelihood (F1) versus minimizing the expected detection time (F2). As shown in Figure 7, to maximize detection probability, sensors should be located at the downstream nodes of the network. In contrast, minimizing detection time requires placing sensors near input nodes, which conflicts with maximizing detection likelihood. Consequently, sensor locations must be optimized by simultaneously considering both objectives. The second set of objectives involved maximizing detection likelihood (F1) versus minimizing the volume of contaminated water consumed by users (F3). According to figure 8, aggain, while detection probability favors sensor placement at the downstream nodes of the network, reducing contaminated water consumption necessitates locating sensors close to injection points. These trade-offs highlight the need for a multi-objective optimization approach to determine sensor locations that effectively balance detection efficiency and public health protection in water distribution systems.Conclusion This study employed a simulation-optimization framework using EPANET and genetic algorithms to determine optimal sensor locations in Mashhad’s drinking water network. Three objectives were considered: maximizing detection likelihood (F1), minimizing detection time (F2), and minimizing the volume of contaminated water consumed (F3). Results showed that a single sensor could detect over 20% of contamination events, reducing detection time by 17.8% and contaminated water consumption by 37%. To maximize detection likelihood, sensors should be placed at downstream nodes, whereas minimizing detection time and contaminated water volume requires placement near input nodes. These conflicting objectives emphasize the need for multi-objective optimization for effective sensor placement. https://ijwer.uoz.ac.ir/article_240968.html Agriculture is one of the most important environmental factors influencing the growth and development of plants, especially in the arid and semi-arid regions of Iran. However, due to the rising cost of water consumption and the decreasing availability of water in these areas, considerable attention has been paid to water scarcity stress and its effects on plants. This highlights the necessity of managing water resources with a comprehensive and precise approach. Therefore, this study aimed to investigate the effects of surface and subsurface irrigation methods at different irrigation levels (100%, 90%, and 80%) on potato yield, land productivity, and water use efficiency at the research station of the South Kerman Agricultural Research Center in Jiroft.Keywords: ELP, Water Productivity, Water needs, Under-irrigationIntroductionConsidering the shortage of water resources in the country, the high water requirement of potato plants, and the climatic conditions of Jiroft — located in one of the arid regions of Iran — planning for the optimal use of water resources in this area is both necessary and inevitable. Furthermore, due to the limited number of studies on subsurface drip irrigation in potato cultivation in Iran, the implementation of appropriate irrigation systems, along with targeted planning, can contribute significantly to sustainable agriculture. Therefore, this study was conducted to evaluate potato cultivation under different irrigation methods and levels in the climatic conditions of Jiroft. The results of this research can serve as a useful reference for future irrigation planning and design..MethodologyConsidering the shortage of water resources in the country, the high water requirement of potato plants, and the climatic conditions of Jiroft — located in one of the arid regions of Iran — planning for the optimal use of water resources in this area is both necessary and inevitable. Furthermore, due to the limited number of studies on subsurface drip irrigation in potato cultivation in Iran, the implementation of appropriate irrigation systems, along with targeted planning, can contribute significantly to sustainable agriculture. Therefore, this study was conducted to evaluate potato cultivation under different irrigation methods and levels in the climatic conditions of Jiroft. The results of this research can serve as a useful reference for future irrigation planning and design..Results and DiscussionThe study of the effect of irrigation levels on yield showed that reducing the irrigation level by up to 10% compared to the optimal level did not lead to a significant decrease in yield. However, a 20% reduction resulted in a statistically significant decline, consistent with the findings of Mousavi Fazl and Akhyani (2020), Ebrahimi Pak and Pezra (2008), Niu et al. (2024), and Hassan et al. (2002), which confirmed the negative impact of deficit irrigation on yield. Based on the analysis of variance in the study of irrigation levels on water use efficiency, there was no significant difference between the full irrigation treatment (100%) and the 90% treatment. However, both of these levels were significantly different from the 80% treatment. Therefore, 90% irrigation was identified as the optimal level for maximizing water use efficiency. At this level, 354.2 cubic meters of water per hectare were saved. The findings of Afshar et al. (2011) also support this conclusion; in their study on different irrigation levels in potato cultivation, full irrigation (100%) decreased water use efficiency, while 75% irrigation increased it.These results suggest that reducing irrigation to approximately 90% of the crop water requirement improves water use efficiency without significantly compromising yield. This irrigation level not only ensures efficient water use but also maintains high yield levels. Furthermore, other studies such as Lamm et al. (2005) and Wang et al. (2018) have demonstrated that subsurface irrigation methods can significantly enhance water use efficiency compared to surface irrigation.ConclusionOverall, the results indicated that both the individual and interactive effects of irrigation level and irrigation method were significant for crop yield, water use efficiency, and the land value index. The highest yield and land value index were observed at the 90% irrigation level with subsurface irrigation, while the lowest values for these parameters occurred under 80% irrigation with subsurface irrigation. Therefore, it is recommended that farmers adopt a 90% irrigation level in combination with efficient subsurface irrigation systems to achieve optimal water use efficiency and crop performance. https://ijwer.uoz.ac.ir/article_240969.html Introduction: Accurate forecasting of rainfall is essential in modern flood prediction systems. Among various meteorological models, the Weather Research and Forecasting (WRF) model is recognized as one of the most reliable mesoscale models for simulating precipitation in diverse climatic and geographic conditions. However, like many numerical models, WRF is subject to temporal and spatial uncertainties, particularly in regions with complex topography such as western and southwestern Iran. This study evaluates the accuracy of WRF’s rainfall predictions across multiple storm events that resulted in significant flooding in these regions between 2014 and 2016.The primary objective of this research is to assess the spatial and temporal accuracy of rainfall forecasts produced by the WRF model over lead times of 24, 48, 72, and 96 hours. The study specifically aims to quantify overestimation or underestimation errors and determine how these errors evolve with increased forecast horizon.Methodology: Five major storm events associated with significant flooding were selected for evaluation. These storms occurred in the western and southwestern basins of Iran, which are prone to intense rainfall and flash flooding due to their topographic and climatic features. WRF model outputs for precipitation were obtained for each event at different lead times (24–96 hours). Observational rainfall data from 100 synoptic stations operated by the Iranian Meteorological Organization were used as ground truth.The spatial distribution of observed and predicted rainfall was analyzed using Geographic Information System (GIS) tools, and statistical indices such as Mean Error (ME), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Bias were used to validate the model’s performance. Time series comparisons and hydrographs were also produced to compare observed and modeled rainfall for selected stations within the basins.Results and Discussion: The results indicate that the WRF model tends to overestimate rainfall in the majority of stations, while in a smaller number of cases it underestimates it. The extent of overestimation was more significant in short-term forecasts (24 hours), with an average over-prediction error of around 30%. Interestingly, this error gradually decreased with increasing forecast horizon, reaching about 25% at the 96-hour lead time.Spatially, the highest discrepancies were observed in stations located in mountainous areas, where orographic effects and convective activity are more pronounced and harder to simulate. The hydrograph comparison for two major dams—Karun 4 and Dez—demonstrated that although the model captures the timing and general shape of the flood hydrograph, it often overestimates the peak discharge, especially in the shorter forecast windows.These findings emphasize the importance of calibrating model outputs and incorporating ensemble forecasting or data assimilation techniques to improve the reliability of flood warnings based on WRF outputs.Conclusion: This study confirms that while the WRF model provides valuable forecasts for flood prediction applications, there is a consistent pattern of rainfall overestimation, particularly at shorter lead times. However, the decline in error with extended lead times suggests model stability in longer forecasts. These insights can be used to enhance early warning systems in Iran by adjusting model outputs or integrating them with local observations and hydrological models such as HEC-1 for flood routing. https://ijwer.uoz.ac.ir/article_240970.html Abstract This study develops a decision-oriented groundwater modeling framework for the Marvdasht-Kharameh aquifer (Fars Province, Iran) to diagnose long-term drawdown and salinity exposure. A 127-month hydroclimatic and groundwater-level record (Oct-2010-Mar-2021) underpins a transient MODFLOW model coupled with MODPATH particle tracking. The calibrated simulation (final RMSE ≈ 2.59 m) reproduces a basin-mean decline of ≈ 7.79 m and highlights eastern–southeastern hotspots where pumping concentrates. Advective pathways connect wetlands/surface waters to vulnerable cells; observed chloride increases are consistent with transport along high-conductivity corridors. Sensitivity analysis elevates horizontal hydraulic conductivity and storage as first-order controls, suggesting targeted abstraction curbs, managed aquifer recharge at high-decline sites, and operational oversight of river/wetland stages.Keywords: Groundwater Resources; MODFLOW; MODPATH; Water Resources Management; Climate Change; Salinity Intrusion; Hydraulic Conductivity.1- IntroductionGroundwater is the principal and, in many districts, the only reliable source for domestic and agricultural supply across Iran’s arid and semi-arid plains. Persistent over-abstraction and quality degradation-particularly salinization driven by surface-water–groundwater interactions-threaten this security. While numerous studies document declining heads, fewer provide an integrated, decision-relevant quantification of (i) decadal dynamics under observed stresses, (ii) the physical pathways by which salinity reaches production zones, and (iii) which parameters and processes most strongly condition management outcomes.This study addresses that gap for the Marvdasht–Kharameh aquifer (Figure 1) by combining transient flow modeling and particle tracking with targeted sensitivity analysis. The objectives are to (1) reconstruct spatiotemporal drawdown over 2010–2021, (2) delineate advective salinity pathways from adjacent rivers/wetlands, and (3) identify leverage points for policy and operations.2-Materials and MethodsData and study window: This study assembled 127 monthly observations of groundwater levels alongside hydroclimatic inputs and hydrogeologic characterization. The archive exhibits a multi-year decline with regular seasonal oscillations (Table 1).Numerical model: Transient flow was simulated using MODFLOW on a finite-difference grid (representative cell size on the order of a few hundred meters), with monthly stress periods, spatially variable recharge, and head-dependent boundaries representing river/wetland connectivity.Calibration and validation: A split record was used for calibration/validation against observation wells. Performance was assessed via RMSE, MAE, and mean error; the final transient fit achieved RMSE ≈ 2.59 m. Calibrated statistics indicate horizontally heterogeneous conductivity and low storage, consistent with alluvial media.Transport diagnostics: MODPATH particle tracking delineated advective pathways from identified saline surface sources into the aquifer to map exposure zones and likely travel directions under the calibrated flow field.Sensitivity analysis: Structured perturbations to horizontal hydraulic conductivity, anisotropy, recharge, river–aquifer exchange, and storage were used to rank controls on heads and on particle-based exposure metrics.Figure 1. Geographic location of the Marvdasht–Kharameh Aquifer study areaTable 1. Optimized Hydrogeological Parameter Values Across Calibration Stages for the Marvdasht–Kharameh Aquifer (MODFLOW–MODPATH)Parameter Min Max Mean Median Standard deviation UnitHorizontal hydraulic conductivity (Kx) 0.0376 139.9163 27.7992 12.5539 32.7247 m/dayVertical hydraulic conductivity (Kz) 0.0151 98.2843 14.2547 9.0636 19.9783 m/dayHorizontal hydraulic anisotropy (Anisotropy) 0.0533 16.3287 1.7024 1.1892 1.9784 –Storage coefficient (S) 0.0001 0.0053 0.0008 0.0005 0.0014 –Transmissivity (T) 0.02 25.6832 5.7982 3.5097 7.8634 m²/dayRecharge (R) 0.0011 0.0452 0.0154 0.0102 0.0138 m/dayVertical hydraulic anisotropy (Kz/Kx) 0.05 3.57 0.98 0.78 0.75 –3- Results and DiscussionDecadal dynamics and spatial structure: The model reproduces the observed downward trend, yielding a basin-mean decline of ≈ 7.79 m over 127 months. Drawdown concentrates in the east and southeast, where abstraction density is high and transmissivity troughs sharpen gradients. Hydrographs show deeper summer depressions consistent with peak demand and evaporative losses (Figure 2).Salinity exposure pathways: Particle tracking reveals hydraulic connectivity from wetlands/surface waters to production areas through high-conductivity corridors. Field-informed chloride increases-from ~70 to ~110 mg L⁻¹ in a southeastern focus area and ~50 to ~75 mg L⁻¹ in a central tract-corroborate the modeled exposure pattern, indicating that advective transport, rather than solely local evapoconcentration, is a credible driver of quality risk.Process controls and management leverage: Sensitivity diagnostics consistently rank horizontal hydraulic conductivity and storage as first-order controls. Higher conductivity steepens local cones near pumping centers and accelerates advective travel from saline sources; higher storage damps seasonal oscillations and mitigates cumulative decline. River–aquifer exchange terms are influential along boundary reaches, underscoring that surface-water operations co-determine groundwater outcomes.Implications: Three levers emerge: (i) targeted abstraction curbs in high-impact sub-basins; (ii) siting managed aquifer recharge (MAR) where modeled declines are greatest and infiltration capacity is adequate; and (iii) operational oversight of river/wetland stages and continuous salinity monitoring to interrupt pathways before chloride fronts intersect supply wells.Figure 2. MODPATH-simulated salinity migration pathways and hydraulic connectivity to surface saline sources in the Marvdasht–Kharameh aquifer4- ConclusionAn integrated MODFLOW–MODPATH framework, calibrated to a 127-month record, quantifies a substantial basin-mean decline (≈ 7.79 m) and delineates advective salinity pathways linking surface waters to vulnerable production zones. Horizontal hydraulic conductivity, storage, and river-aquifer exchange dominate system response, suggesting actionable interventions: redistribute and reduce pumping in identified hotspots, deploy MAR where it is hydraulically effective, and manage/monitor surface-water stages and salinity as part of a coupled operations plan. The framework is transferable to other arid and semi-arid aquifers facing coupled quantity-quality stresses and provides a defensible basis for adaptive management. https://ijwer.uoz.ac.ir/article_241866.html Abstract: This study analyzes LULC (Land use and land cover) changes in the Urmia Plain, northwestern Iran, from 2000 to 2020, and projects future patterns for 2040. Landsat, ETM, and OLI images were classified into six categories—agriculture, orchards, urban areas, saline lands, barren lands, and water bodies—using the supervised maximum likelihood algorithm, achieving Kappa coefficients above 0.85. Between 2000 and 2020, agricultural lands declined by 17.4%, while barren and saline areas expanded by over 25% combined. Urban areas increased modestly (2.3%) , reflecting localized expansion near major settlements. Water bodies, mainly associated with Lake Urmia and its wetlands, experienced a sharp decline and in some years nearly disappeared, highlighting severe hydrological stress. Using a Markov chain model derived from 2000–2010 transitions, the 2040 scenario predicts an additional 12% agricultural loss, with barren lands encroaching on former orchards. Results indicate that anthropogenic factors, including unsustainable agriculture and groundwater depletion, are the dominant drivers of degradation. The integrated remote sensing–Markov framework offers transferable tools for historical and predictive LULC assessment, supporting targeted land restoration and sustainable management in dryland environments.Keywords: Land use change, Remote sensing, Urmia Plain, Markov chain, LandsatIntroduction Land use and land cover (LULC) changes represent significant contributors to environmental degradation, particularly in arid and semi-arid regions where limited water resources and fragile ecosystems exacerbate vulnerability. The Urmia Plain, located within the Lake Urmia Basin in northwestern Iran, serves as a crucial agricultural and ecological zone that is currently facing significant stress due to prolonged drought, climate change, and anthropogenic pressures. The overexploitation of groundwater, coupled with inefficient irrigation practices and uncontrolled land conversion, has resulted in soil salinization, loss of vegetation, and the expansion of barren lands, thereby jeopardizing regional food security and ecological stability (Daryanto et al. 2016; Kheyruri et al. 2024b).Numerous investigations in Iran have utilized remote sensing techniques to observe land use and land cover (LULC) trends, employing statistical or simulation models for forecasting changes. Nonetheless, only a limited number have concentrated on the Urmia Plain or integrated historical trend assessments with future predictions. Given its vital importance within the Lake Urmia ecosystem, it is essential to assess both historical alterations and anticipated future conditions to guide effective management approaches (Fatema et al. 2023; Vohra et al. 2024).Remote sensing provides long-term, consistent datasets for monitoring LULC changes, while Markov chain modeling offers a probabilistic approach for predicting future land use patterns based on observed transitions (Mortezaii et al. 2020; Feizizadeh et al. 2022). Integrating these techniques enables both accurate historical mapping and robust forecasting.This study aims to: (1) classify LULC for 2000, 2010, and 2020 using Landsat imagery; (2) evaluate classification accuracy; (3) analyze dominant LULC transitions over two decades; and (4) project the 2040 LULC map using a Markov chain model. The findings provide essential information for sustainable land management and conservation planning in the Urmia Basin.Methodology The study focuses on the Urmia Plain, West Azerbaijan Province. Land use/land cover (LULC) maps were generated for 2000, 2010, and 2020 using a supervised maximum likelihood classification. Six categories were defined: agriculture, orchards, urban areas, barren lands, saline lands, and water bodies. Accuracy assessment using confusion matrices and Kappa statistics confirmed values above 0.85, ensuring reliable spatial classification.Post-classification statistics were used to quantify the areal extent of each class, supported by corresponding maps (Figures 2–5). Transition probability matrices were calculated to analyze historical changes between the periods, allowing the identification of spatial patterns, trends, and areas with significant land use changes. Comparative percentage changes across the three periods are summarized in Table 5.This approach provides a comprehensive assessment of past spatial dynamics, highlighting areas of degradation and land use change, which can inform future studies and support planning for sustainable land management in this vulnerable region. No predictions for future land use are made, and the focus remains on understanding historical patterns.Results and Discussion The analysis of the 2005 LULC map (Figure 2) and statistical data (Table 1) reveals that mixed orchard–crop lands dominated the Urmia Plain, accounting for nearly 40% of the area, followed by orchards (18.9%) and urban areas (12.1%). In contrast, water bodies represented only 0.16% and wetlands 0.42%, showing their marginal presence even at the beginning of the study period. These results highlight that while agricultural and orchard activities were still relatively strong, natural water resources were already critically reduced, and barren lands began expanding around the lake’s margins, suggesting early signs of ecological stress.By 2010, significant shifts were evident (Figure 3, Table 2). Surface water completely disappeared, and wetlands declined to 0.67%, marking the onset of severe hydrological degradation. Mixed orchard–crop expanded to nearly 47%, but this was accompanied by rising poor vegetation (11%) and the continued encroachment of barren lands in the north and east. The spatial patterns indicate unsustainable agricultural expansion, particularly in water-stressed areas, which contributed to land fragmentation and ecological instability. This period also reflects accelerated land conversion driven more by human intervention than by climatic variability.The 2015 classification (Figure 4, Table 3) demonstrated intensification of these trends. Mixed orchard–crop surged to nearly 60%, while independent orchards dropped to just over 6%. Poor vegetation areas increased to 12.7%, confirming the weakening of ecological resilience. Wetlands remained below 1%, and water bodies continued to be absent, reflecting the persistent water crisis. Urban areas grew to almost 13%, driven by the expansion of Urmia city and surrounding settlements. The combination of orchard expansion into unsuitable lands and the sharp decline of natural vegetation emphasizes the anthropogenic stress dominating land-use transitions during this period.By 2020, urban growth reached its highest share at 15.3%, while independent orchards rebounded to 17.9% (Figure 5, Table 4). Mixed orchard–crop declined to 42.3%, reflecting a shift toward more fragmented agricultural practices. Water bodies remained absent, and wetlands persisted at only 0.82%. The Markov projection for 2040 (Figure 6, Table 5) predicts a further ~12% decline in agriculture, significant orchard losses compared to 2005 and 2020, and a +26% urban increase relative to 2000. Barren and poor vegetation classes are expected to dominate the northern and eastern plain, while water and wetlands remain negligible. These findings confirm that without immediate intervention, the Urmia Plain faces continued ecological degradation and heightened desertification risk.Conclusion This study demonstrates that the Urmia Plain has undergone substantial LULC changes over the past two decades, with agricultural and orchard areas declining sharply and barren and saline lands expanding significantly. The Markov chain model projects further degradation by 2040, with agricultural lands potentially decreasing by an additional 12% if current practices continue.Findings highlight the predominance of anthropogenic factors—particularly unsustainable agriculture and groundwater overexploitation—over climatic drivers in shaping LULC patterns. The integration of multi-temporal Landsat imagery and Markov chain modeling offers a reliable and transferable framework for both retrospective analysis and future prediction in semi-arid regions.Urgent adoption of conservation-oriented land management, improved irrigation efficiency, and groundwater regulation is essential to halt degradation. The study’s results can guide policymakers and stakeholders in designing targeted strategies for restoring land productivity and safeguarding the ecological integrity of the Urmia Basin. https://ijwer.uoz.ac.ir/article_241867.html IntroductionScouring downstream of weirs, due to high velocity and turbulence of the flow, has always been one of the major challenges in the design and operation of these hydraulic structures. Previous studies have shown that various factors, including jet velocity, water drop height, flow rate, and weir plan, affect the amount and pattern of scouring. Labyrinth weirs are used in places that have width limitations and are used to increase the crest length. If a proper foundation is not built, there is a possibility of destruction of these weirs due to downstream scouring. On the other hand, excessive increase in the depth of the weir foundation will entail high costs. Therefore, the aim of this study is to carefully investigate the amount, pattern, and trend of scour changes downstream of triangular and arched convoluted weirs in two single-cycle and two-cycle modes in uniform sediments.Materials and MethodsThe experiments were conducted in a laboratory flume 12 m long and 80 cm wide. The discharge was measured using an ultrasonic flowmeter with an accuracy of ±0.01 lit/s, and the water level was measured with a point gauge. Four types of labyrinth weirs, including single-cycle triangular, double-cycle triangular, single-cycle arched and double-cycle arched with a crest length of 1.26 m and a magnification ratio of 1.58, were installed at a distance of 6 m from the beginning of the channel. The weirs were made of iron with a thickness of 4 mm and a height of 35 cm. Coarse-grained sediments were used up to a height of 20 cm upstream of the weirs, and uniform sediments with a median diameter of 3 mm were used downstream with a length of 70 cm and a height of 20 cm. 15 cm of the weir height was placed above the sediments and 20 cm of it was placed as a foundation under the sediments. The depth of the tailwater was set to 10 cm in all experiments. Experiments were conducted at three discharges of 5, 10, and 15 lit/s. The topography was measured with a 3x3 cm grid and the data were analyzed in Sigma Plot software to draw a three-dimensional scour shape.3Results and DiscussionThe results of the experiments showed that the greatest scour depth always occurs at the junction of the weir with the channel wall. The presence of severe transverse curvature of flow and nappe interference lead to increased turbulence and, as a result, more scour on the sides. In single-cycle weirs, the second maximum scour point was observed near the weir apex. In double-cycle weirs, the second maximum scour point occurs at the intersection of the two cycles and then at the weir apex. This is due to the nappe interference and the transverse curvature of the flow at the intersection of the cycles, which, similar to near the channel wall, creates more turbulence. A comparison of single-cycle and double-cycle weirs showed that with an increase in discharge and water head ratio, the discharge coefficient in single-cycle weirs decreases faster. This faster decrease in the efficiency of single-cycle weirs leads to a faster increase in the scour rate in them compared to double-cycle weirs. So that in the curved single-cycle weir, the increase in scour from a discharge of 5 to 15 lit/s was 101%, while in the curved double-cycle weir this increase was 27%. For triangular weirs, these values were 53% for single-cycle and 39% for double-cycle, respectively. This difference in the scour increase trend shows that despite the better initial hydraulic performance of single-cycle weirs at low discharges, with increasing discharge, two-cycle weirs are more stable in terms of scour. Therefore, despite the lower discharge coefficient, two-cycle weirs are structurally more resistant to scour.4ConclusionThe studies showed that the maximum scour location always occurs at the junction of the weir with the channel wall. In single-cycle weirs, the second maximum scour is near the weir apex; but in two-cycle weirs, this phenomenon is observed at the intersection of the two cycles and then near the weir apex. This is due to the increased turbulence caused by the transverse curvature of the flow and the nappe interference at low angles of flow exit from the weir. The studies showed that increasing discharge leads to an increase in scour depth. This increase is more significant in single-cycle weirs than in double-cycle weirs due to the faster decrease in discharge coefficient. The Froude number study showed that although a higher Froude number usually means more scour, in conditions where different of Froude number in two weirs are insignificant, the nappe interference and discharge coefficient play a major role in the scour rate. Finally, it was found that double-cycle weirs, although hydraulically less efficient than single-cycle weirs, are structurally more suitable due to the lower scour depth.