https://idj.iaid.ir/ Iranian Journal of Irrigation & Drainage en daily 1 Mon, 22 Jun 2026 00:00:00 +0330 Mon, 22 Jun 2026 00:00:00 +0330 https://idj.iaid.ir/article_236208.html Due to the quantitative and qualitative limitations of water resources in Iran, measuring and analyzing water productivity indexes in the agricultural sector has particular importance. This study aimed to analyze the spatial analysis of the physical and economic water productivity for three major crops—wheat, barley, and cotton—in Sabzevar Plain. To evaluate agricultural water productivity, three indices were used: crop yield per unit of irrigation water, gross income per unit of irrigation water, and net income per unit of irrigation water, calculated for the 2015–2016 cropping season. Results showed that the highest and lowest physical water productivity were observed for barley and cotton, with values of 1.28 and 0.35 kg m⁻³, respectively. The highest gross and net water productivity were obtained for wheat, at 15.04 × 10³ and 9.15 × 10³ Rial m⁻³, respectively. The average net income per unit of irrigation water for wheat, barley, and cotton was 5,740, 3,130, and 3,340 Rial m⁻³, respectively. Based on the results, it is recommended that policymakers prioritize wheat cultivation in the northern, central, and southern regions of the Sabzevar Plain, barley in the western region, and cotton in the eastern region. https://idj.iaid.ir/article_236524.html This study analyzes climate change risks in the arid and semi-arid regions of Khorasan Province, Iran. Initially, seven key climate risks were identified, including drought and water scarcity, flash floods, heatwaves, dust storms, desertification, soil and water salinity, and energy imbalance. Next, using the Best-Worst Method (BWM) and the expert opinions of 28 specialists collected in the spring and summer of 2025, the weights and priorities of each risk were determined. Subsequently, the impacts of each risk were evaluated across six dimensions: economic, social, environmental, infrastructural, agriculture and livestock, and health. The weighting results indicated that drought and water scarcity hold the highest priority with a weight of 0.295, followed by energy imbalance with a weight of 0.166. Heatwaves and soil salinity also emerged as significantly important, indicating increasing threats. Composite score analysis across various dimensions demonstrated that drought and energy imbalance exert the greatest impact on regional vulnerability. Additionally, notable correlations among risks such as heatwaves and soil salinity underscore the necessity of integrated and multisectoral risk management approaches. Ultimately, findings suggest that adaptation policies should prioritize the optimal management of water and energy resources, enhancement of infrastructure resilience, and restoration of ecosystems, while also emphasizing the critical role of social participation and education to reduce vulnerability and enhance preparedness. This research provides a comprehensive and localized framework for decision-makers and introduces energy imbalance as a key risk, offering novel insights for sustainable energy policies. https://idj.iaid.ir/article_237827.html Rainfall databases are valuable sources of information for regions with limited observational records. However, the performance of these datasets has typically been assessed at large spatial scales. Therefore, the present study evaluated the performance of three rainfall databases GPCC, MSWEP and TerraClimate for estimating monthly precipitation in the Kardeh watershed. For this purpose, rainfall data from six active ground stations in the studied area were collected and compared with the monthly data of the three databases over the period 1990–2019. To assess their accuracy, four statistical indices including Root Mean of Square Error (RMSE), Nash–Sutcliffe efficiency (NSE), coefficient of determination (R²), and Coefficient of Residual Mass (CRM) were applied. In addition, spider charts were used to examine monthly correlations, box plots to compare the distribution of indices, and a Taylor diagram to analyze the combined error and standard deviation. The results showed that the GPCC database exhibited the best agreement with the observational data, with RMSE, CRM, NSE, and R² values of 7.51, -0.07, 0.71 and 0.74, respectively, demonstrating superior performance compared with the other two datasets. MSWEP provided moderate and acceptable performance, whereas TerraClimate showed lower accuracy in representing the statistical characteristics of regional rainfall. Accordingly, the use of GPCC data is recommended for precipitation studies at the watershed scale in the Kardeh watershed. https://idj.iaid.ir/article_237828.html In this study, the temporal trends of 14 drinking water quality parameters in groundwater wells across Gilan Province were evaluated over a 10-year period (2013–2022) using the non-parametric Mann–Kendall test and Sen’s slope estimator. Data were obtained from the Statistical Database of Gilan Water and Wastewater Company, and one representative well was selected from each county. The Mann–Kendall test was used to determine trend significance, and Sen’s slope was applied to estimate the annual rate of change. Results indicated that parameters such as nitrate, electrical conductivity (EC), total dissolved solids (TDS), and iron showed both increasing and decreasing trends across different areas. Sodium, sulfate, calcium, total hardness, and manganese exhibited increasing trends, while magnesium, nitrite, and potassium showed decreasing trends. No significant trend was observed for chloride and bicarbonate. Out of 224 examined cases, 34 trends (15%) were statistically significant, including 18 increasing and 16 decreasing trends. Nitrate showed the highest number of significant trends (11 cases). The highest annual rate of change was observed in EC 12 and nitrate 1.2 mg/l in Rezvanshahr and Fuman counties, respectively. https://idj.iaid.ir/article_238087.html Water scarcity has limited the expansion of agricultural development. Sprinkler irrigation systems can enhance water use efficiency; however, poor design, improper operation, and inadequate maintenance reduce their performance and increase water losses. Accurate design, proper management, and regular maintenance are the three main pillars for improving the performance and sustainability of these systems. The aim of this study was to evaluate the hydraulic performance, design quality, and operation of several sprinkler irrigation systems in Qorveh Plain, Kurdistan Province. Eight classic solid-set sprinkler irrigation systems equipped with portable sprinklers were selected and evaluated. To assess their performance, the Christiansen’s Uniformity Coefficient (CU), Distribution Uniformity (DU), Potential Low Quarter Application Efficiency (PELQ), Actual Low Quarter Application Efficiency (AELQ), Wind Drift and Evaporation Losses (WDEL), Deep Percolation Losses (DP), and Adequacy of Irrigation (ADirr) indices were determined. The average values of these indices for the eight farms were 71.67%, 61.66%, 52.45%, 52.07%, 9.54%, 22.78%, and 68.31%, respectively. The results indicated that all systems had low application efficiency, and the water distribution uniformity was below the recommended range proposed by Merriam and Keller (1978). Furthermore, due to water shortages, the potential and actual application efficiencies were equal in all farms except for farm A5. The low potential application efficiency was mainly attributed to improper design and construction, with the most critical factor being unsuitable operating pressure. The simultaneous use of more than one sprinkler per lateral line and the use of sprinklers with different models and specifications, along with poor system design, installation, operation, and maintenance, were the main causes of reduced distribution uniformity. Overall, the results revealed that despite multiple design and implementation issues, the primary reason for the poor performance of the classic solid-set sprinkler irrigation systems with portable sprinklers in Qorveh Plain was improper management, maintenance, and operation. https://idj.iaid.ir/article_238088.html In this study, the long-term trends of hydrometeorological parameters, including precipitation, river discharge, Leaf Area Index (LAI), snow cover, and evapotranspiration (ET) in the Dez River basin were investigated over the period from 2002 to 2021 using ground-based and satellite data. Satellite data were extracted from the Google Earth Engine platform, and for trend analysis, the modified non-parametric Mann-Kendall (MMK) test, which removes the effects of autocorrelation, along with the Sen's slope estimator, were employed. The results indicated that most rain gauge stations showed no clear and significant trend in precipitation, with only Dorud station recording a significant decrease and Venaei station showing a significant increase. In contrast, the analysis of river discharge revealed a predominantly decreasing trend across the basin, particularly at the Sabbe Cham-Chit and Tele Zang stations, where significant decreases were observed at the 95% confidence level. Remote sensing data also indicated that snow cover experienced a significant decreasing trend at the 90% confidence level, while the Leaf Area Index showed a significant increase (Z=2.43). The evapotranspiration parameter exhibited no significant trend, which could be attributed to limited water resources and a balance between increased vegetation cover and soil moisture deficit. Overall, the findings indicate a decline in surface water resources due to a combination of climate change and human activities, highlighting the need for smart and sustainable water resource management and the evaluation of adaptation scenarios. https://idj.iaid.ir/article_239869.html The hydraulic jump is a key phenomenon in hydraulic engineering, playing a vital role in energy dissipation and the protection of downstream structures. This study presents an experimental investigation into the effects of using rectangular cubes in a zigzag arrangement on the characteristics of a hydraulic jump in a rectangular channel. The experiments were conducted in a flume with a width of 0.5 meters for initial Froude numbers ranging from 1.5 to 19.1. The independent variables included the relative block height (h/b = 2, 3, 4) and the relative longitudinal spacing between their rows (s/b = 1, 2, 4). A quantitative comparison of the laboratory data with the baseline (smooth bed) showed that the presence of these blocks leads to a reduction in the sequent depth and jump length, as well as an increase in energy dissipation. Analysis revealed that the block height parameter has a more dominant effect than the longitudinal spacing. Specifically, blocks with a relative height of 4, compared to a height of 2, resulted on average in an additional 57% to 69% reduction in the sequent depth and an additional 24% to 32% reduction in the jump length. The maximum increase in relative energy dissipation (16.4%) was also associated with the configuration featuring the greatest height and spacing. https://idj.iaid.ir/article_241872.html Achieving uniform water distribution and, consequently, improving the efficiency of a drip irrigation system depends on the proper hydraulic performance of the emitter as one of the main components of the system. Therefore, in this study, a laboratory experiment was conducted to evaluate the performance of four types of emitters available in the market (two pressure-compensating and two non-pressure-compensating) under five applied operating pressures (0.6, 0.8, 1.2, 1.6, and 2.4 bar). The evaluated parameters included distribution uniformity (EU), Christiansen’s uniformity coefficient (CU), manufacturing coefficient of variation (CV), discharge variation coefficient (qvar), discharge–pressure relationship and statistical uniformity coefficient (Us). The results confirmed the superior performance of the Eurodrip emitter among the non-pressure-compensating emitters (CV = 0.036, EU = 95.28%, CU = 97.26%, qvar = 23.2%, and Us = 96.18%). Among the pressure-compensating emitters, the Abafarin emitter exhibited better performance (CV = 0.082, EU = 87.36%, CU = 92.78%, qvar = 25.8%, and Us = 91.4%). Overall, the results indicated that, under the conditions of this study, the evaluated non-pressure-compensating emitters outperformed the pressure-compensating emitters in most hydraulic performance indices.Therefore, in order to improve irrigation system efficiency, the selection of emitters should be based on the evaluation of hydraulic performance indices under actual operating conditions, so that their real performance can be accurately determined, rather than relying solely on manufacturers’ reported specifications. https://idj.iaid.ir/article_241873.html Given the water shortage in different parts of the country, determining and evaluating the amount of virtual water and water productivity in important agricultural crops seems necessary and essential. In this study, the calculation and examination of three indicators of virtual water (VW), physical productivity (WP) and economic productivity (NBPD) of cucumber crop in the crop year 1401 in Hamedan province were carried out. The crop yield, cost and income, amount of water consumed and irrigation requirement of cucumber in the farms of the provinces were collected and calculated. The results of the study showed that the highest value of the index (VW) of cucumber is 497.7 liters per kilogram in Razan County and the lowest value is 225.1 liters per kilogram in Famenin County. Considering the area under cultivation of this crop in different counties of the province, on average and for the entire province, the value of this index was 366.3 liters per kilogram. Also, the highest value of cucumber index (WP) is 4.44 kg/m3, which is related to Famenin County and the lowest value is 2.01 kg/m3, which is related to Razan County. Considering the area under cultivation of this product in different counties of the province, on average and for the entire province, the value of this index was equal to 2.73 kg/m3. The calculated index (NBPD) also had the highest value in Famenin County, which was equal to 152.9 thousand rials/m3, and in Bahar County, it was the lowest value and equal to -40.9 thousand rials/m3. This index was also calculated by considering the area under cultivation of cucumber in different counties of the province, on average and for the entire province, and its value was equal to 5.7 thousand rials/m3. https://idj.iaid.ir/article_242645.html This study evaluated the effectiveness of black plastic mulch in mitigating water stress and its economic benefits in lemon balm (Melissa officinalis L.) cultivation. The experiment was conducted using a split-plot design based on a randomized complete block design with three replications. The main factor was plastic mulch at two levels [No mulch (NM) and black mulch (BM)], and the sub-factor was water stress at four levels (FC100, FC80, FC60, and FC40). The results indicated that water stress significantly reduced leaf area index, biomass, dry matter, water use efficiency, and photosynthetic pigments (chlorophyll a, b, total chlorophyll, and carotenoid content). Application of black plastic mulch mitigated the negative effects of water stress, enhancing plant growth and physiological traits. Economic analysis revealed that the highest net NBPD (Net profit per drop) and B/C (benefit/cost) ratio were obtained under mild water stress (FC80) combined with black mulch. In addition to improving yield, the use of mulch enhanced the economic feasibility of lemon balm cultivation. Therefore, integrating optimal irrigation management with black plastic mulch application can be recommended as an effective strategy to improve yield, water productivity, and economic profitability in lemon balm cultivation, even under humid climatic conditions. https://idj.iaid.ir/article_242887.html To investigate the effect of biochar application on some characteristics of Satureja hortensis L under deficit irrigation and partial root-zone drying conditions, a factorial experiment based on a completely randomized design with 3 replications was conducted in 2024 at the research greenhouse of Torbat Jam Higher Education Complex. In this experiment, treatments included three levels of irrigation (100% of water requirement, 50% deficit irrigation, and 50% partial root-zone drying) and three levels of biochar application (0, 2.5, and 5% by weight of soil per pot). The results showed that applying 50% deficit irrigation (DI) and partial root-zone drying (PRD) increased water use efficiency by 52.13% and 65.91%, respectively. The results also indicated that applying biochar at 2.5% and 5% by weight per pot increased water use efficiency compared to no biochar application. Based on the above results, it can be concluded that the savory plant was sensitive to drought stress, and deficit irrigation would lead to a reduction in yield in this plant. Furthermore, based on the results of this research, the partial root-zone drying (PRD) method was identified as a more suitable method than deficit irrigation (DI) in terms of increasing water use efficiency, elemental concentration, and essential oil percentage in Satureja hortensis L. https://idj.iaid.ir/article_243047.html This study aimed to investigate the effect of deficit irrigation based on the cut-off time of the inflow into the furrow on the yield and water productivity of forage maize in the research field of the University of Tehran in Karaj with clay loam soil texture. The experiment was conducted in a randomized complete block design with five treatments of the cut-off time based on the arrival of the wetting front to a specific soil depth at different distances from the furrow inlet and in three replications. TDR moisture sensors were placed at distances of 100 (L2), 90 (L3), 60 (L4) and 0 (L5) meters from the furrow inlet. In the control treatment (L1), the cut-off was after providing the required water depth of the plant at the end of the furrow. Four depths of 18, 20, 22 and 24 cm were determined for the sensors and during the growing season, before each irrigation, the sensor depth was selected according to the required irrigation water depth. The irrigation water depth in treatments L1, L2, L3, L4 and L5 was 100, 82.9, 75.4, 69.8 and 64.1 % of the water requirement, respectively. The highest values of fresh and dry biomass and grain yield, harvest index, 1000 kernel weight and plant height were recorded as 67.265, 27.196 and 13.858 tons/ha, 50.77 %, 367.89 g and 258.2 cm in L1 treatment, respectively, and the lowest values were recorded as 34.272, 17.150 and 7.511 tons/ha, 43.40 %, 252.67 g and 177.9 cm in L5 treatment. Deficit irrigation caused a significant decrease in all six traits. Irrigation water productivity based on fresh and dry biomass and grain yield did not show significant differences in different treatments, but in all three cases, the lowest values were related to L5 treatment. https://idj.iaid.ir/article_243124.html The rapid growth of the global population has placed considerable pressure on natural resources and has limited the availability of high quality water and soil for agricultural production. This situation poses serious challenges to food security and may lead to regional and global crises. In addition, the presence of heavy metals in the plant growth environment disrupts normal physiological processes and ultimately reduces plant growth. One of the proposed approaches for improving soil conditions is the use of magnetically treated water. The experiment was conducted in 2025 as a factorial arrangement in a randomized complete block design with three replications. The treatments included well water, various combinations of well water and wastewater at ratios of 25:75, 50:50, 75:25 and irrigation with 100% wastewater, under both the presence and absence of magnetic field. The effect of magnetized wastewater irrigation on soil chemical properties, including electrical conductivity (EC), pH, calcium, magnesium, and heavy metals such as lead and cadmium, was evaluated. The results of mean comparisons of soil chemical parameters indicated significant differences between magnetic and non magnetic treatments. Irrigation with magnetized water reduced electrical conductivity, calcium, magnesium, lead, and cadmium in the soil profile by 21.92%, 32.85%, 28.42%, 33.74%, and 45.69%, respectively. The findings of this study can contribute to improving agricultural production in regions facing water scarcity and provide effective strategies for the utilization of reclaimed water resources. https://idj.iaid.ir/article_243048.html Nanotechnology holds promising potential as an innovative approach for improving the physical and hydraulic properties of saline soils. In this study, a comparative evaluation was conducted on the effects of organic and mineral soil amendments applied at both nano and conventional scales on a loamy saline soil. The experimental treatments included pomegranate peel-derived biochar and nanobiochar, nano-bentonite, zeolite, micro-silica, and nano-silica, which were applied in soil columns (10 cm diameter × 35 cm height) under a completely randomized design with three replications. Results indicated that, before leaching, the highest electrical conductivity (EC = 23.597 dS m⁻¹) and sodium concentration (4903 mg kg⁻¹) were recorded in the pomegranate peel biochar treatment. Conversely, the lowest pre-leaching EC (13.817 dS m⁻¹) was observed in the nano-silica treatment, while nano-bentonite exhibited the lowest sodium concentration (2054 mg kg⁻¹). Analysis of leachate collected after irrigation with four pore volumes of water revealed that nano-bentonite produced the lowest EC and potassium and iron concentrations, whereas nano-silica produced the lowest calcium concentration. In contrast, the pomegranate peel biochar treatment yielded the highest EC and concentrations of calcium, potassium, and iron in the leachate. These findings demonstrate that nano-engineered amendments particularly nano-bentonite and nano-silica, exhibit significant efficacy in mitigating salinity and modulating the leaching dynamics of key ions (Na⁺, K⁺, Ca²⁺, and Fe²⁺/³⁺), thereby offering viable, sustainable strategies for the reclamation and management of saline soils. https://idj.iaid.ir/article_243126.html Water turbidity, as one of the most important physical indicators of water quality, plays a crucial role in ecological dynamics, light penetration, and the health of aquatic ecosystems. Zarivar Lake in Marivan, recognized as the largest natural freshwater lake in Iran, has experienced considerable water quality fluctuations in recent years due to increasing anthropogenic pressures and hydroclimatic changes. Therefore, accurate and continuous monitoring of water turbidity in this aquatic system is of great importance. The present study aimed to evaluate and compare the performance of various spectral indices for estimating water turbidity in Zarivar Lake using Sentinel-2 satellite imagery on a seasonal scale during 2019. For this purpose, four spectral indices including NDTI, TurbBow, TurbChip, and TurbLath were extracted from Sentinel-2 images after applying radiometric and geometric corrections. Field-measured turbidity data collected from 15 sampling stations were used as reference data for the calibration and validation of linear regression models. Model performance was assessed using the coefficient of determination (R²) and the root mean square error (RMSE). The results indicated that the NDTI index exhibited the highest explanatory power for turbidity variations (R² ranging from 0.76 to 0.89) and the lowest prediction error (RMSE ranging from 0.00413 to 0.00533 NTU) across all selected seasons, outperforming the other indices. Furthermore, the spatiotemporal patterns of turbidity revealed a significant increase during warm seasons, particularly in the marginal zones of the lake, and lower values during cold seasons and in the central parts of the lake. Overall, the findings demonstrate that the integration of the NDTI index with Sentinel-2 data provides a reliable, cost-effective, and efficient approach for spatiotemporal monitoring of water turbidity in shallow lakes and can serve as a robust scientific basis for sustainable management, environmental conservation, and decision-making processes concerning Zarivar Lake. https://idj.iaid.ir/article_243218.html Vertical farming, as a new agricultural method, allows for the production of quality products in limited spaces and with less resource consumption. The aim of this study was to investigate the effect of irrigation duration and intervals along with different nutritional treatments on morphological traits and nutrient distribution of lettuce in a vertical cropping system. The experiment was conducted as a factorial with three replications and three levels for each factor (short irrigation with short intervals, medium and long irrigation with long intervals; and high nitrogen, high potash and full balance solutions) in PVC pipe structures. The results showed that the long irrigation treatment with long intervals and complete equilibrium solution achieved the highest plant height (20.2 cm), fresh weight (508 g), dry weight (50.3 g), and root length (18.1 cm), which was significantly higher than the other treatments. Also, the nitrogen content in this treatment was 8 to 10 percent higher. This combination improved growth, increased nutrient uptake, and improved lettuce quality in vertical cultivation. Therefore, the combination of long irrigation intervals with a complete balance solution helps improve growth and nutrient uptake and is recommended as the optimal method for vertical cultivation of lettuce in controlled environments. https://idj.iaid.ir/article_243294.html The present research، aimed at developing a comprehensive flood modeling toolkit based on hybrid dual-AI frameworks، evaluated six models، including two individual models (FCMR and GRNN) and four hybrid dual models (FCMR-NARX، FCMR-ACOR، GRNN-NARX، and GRNN-ACOR) at five hydrometric stations in the Kraj watershed (Gachsar، Sira-kalvan، Sira-karaj، Neshatarud، and Morud) over a 30-year period from the beginning of the water year 1990 to the end of the water year 2018. The results، based on statistical criteria (R، NSE، RMSE، MAE)، indicated that hybrid models based on FCMR (particularly FCMR-NARX and FCMR-ACOR) have the highest accuracy. However، statistical tests did not show a significant difference in accuracy between these models and the individual GRNN model. On the other hand، hybridizing the GRNN model with NARX and ACOR catalysts due to structural incompatibilities reduced its accuracy. Considering the computational complexity، long training time، and higher implementation costs of hybrid models، the individual GRNN model is proposed as an optimized option with economic and operational justification for use in flood warning systems and water resource management in similar watersheds. This study emphasizes the necessity of coordination between the base model structure and the hybridization method to achieve effective performance improvement. https://idj.iaid.ir/article_243611.html The decline in groundwater levels in Mashhad Plain, primarily driven by anthropogenic factors, presents a significant challenge to sustainable water resource management. The heavy reliance on these resources necessitates accurate prediction of changes for effective managerial decision-making. This study employs machine learning methods to simulate and predict groundwater level variations in the central part of the plain. Initially, key input variables and optimal time lags were identified using the Partial Autocorrelation Function (PACF) and Frequency Lasso Regression (FLR). Subsequently, the performance of Least Squares Support Vector Regression (LS-SVR), Adaptive Neuro-Fuzzy Inference System (ANFIS), Multi-Layer Perceptron Neural Network (MLP), and Radial Basis Function Neural Network (RBF) was evaluated for monthly prediction of groundwater level fluctuations over 30 years (1991-2021). Results demonstrated that all four models simulate groundwater levels with acceptable accuracy. The RBF model exhibited superior performance with R², MSE, NSE, and RMSE values of 1.00, 0.00, 1.00, and 0.009, respectively. The findings affirm the high potential of data-driven models in simulating hydrological processes and can serve as a foundation for developing intelligent tools for groundwater resource management in Mashhad Plain and similar regions, including resource allocation and warning system design. https://idj.iaid.ir/article_243728.html Local scour around buried pipelines in riverbeds is one of the major factors contributing to bed instability and the vulnerability of fluid‑transport infrastructure. Incorrect estimation of scour geometry can lead to significant technical, economic, and environmental damages. Therefore, the development of reliable methods for predicting scour hole geometry plays an important role in the safe and economical design of such structures. Recent studies have shown that machine learning techniques and artificial intelligence algorithms have attracted considerable attention as effective tools for analyzing and predicting complex hydraulic phenomena. In this study, the performance of three machine learning approaches, namely Artificial Neural Networks (ANN), Support Vector Machines (SVM), and the k‑Nearest Neighbors (KNN) algorithm, was evaluated for predicting the geometry of local scour holes, including maximum scour depth and maximum scour length, around buried pipelines in the presence of an impermeable plate. The analysis was conducted using 64 sets of laboratory experimental data. The hydraulic and geometric input parameters included the flow Froude number, the ratio of initial burial depth of the pipeline to channel width (e/B), and the ratio of pipeline diameter to channel width (D/B). The results indicated that the ANN model achieved more accurate and stable predictions than the other methods, with coefficients of determination greater than 0.96 for predicting both scour depth and scour length, while the SVM and KNN models showed comparatively lower accuracy. Sensitivity analysis also revealed that the ratio of initial burial depth to channel width (e/B) is the most influential parameter affecting local scour geometry. Overall, the findings demonstrate that machine learning approaches, particularly artificial neural networks, can serve as effective tools for predicting scour and improving the design and safety of buried pipelines in riverbeds. https://idj.iaid.ir/article_243899.html Wheat is one of the most strategic crops for food security and occupies a large proportion of agricultural lands in Iran. However, climate change, increasing water scarcity, and the limitations of traditional field-based statistics have made accurate monitoring of wheat cultivated areas a challenging task. In this study, an integrated framework based on multi-source remote sensing data and a machine learning approach was developed to identify rainfed and irrigated wheat fields and to estimate their cultivated area in the Maroon watershed in southwest Iran. A set of spectral, radar, and thermal features representing the biophysical, structural, and water-related characteristics of wheat was extracted and used as input variables for the model. The Random Forest algorithm was selected due to its robustness against overfitting and its ability to handle heterogeneous and non-linear data. Model performance was evaluated using a confusion matrix, overall accuracy, and the kappa coefficient. The results demonstrated a high classification performance, with an overall accuracy of approximately 97% and a kappa coefficient of about 0.96 for the test dataset. In addition, the estimated wheat cultivated area showed a low bias of around 3%, indicating a high level of reliability in distinguishing between rainfed and irrigated wheat fields. https://idj.iaid.ir/article_243967.html One of the factors that cause the destruction of bridge piers is the erosion of the foundation. As this phenomenon spreads, the scour created around the pier will weaken the foundation and threaten the destruction of the entire structure. In this research, a combination of slot and crack methods is used to control this phenomenon. Using slots is one of the new methods in controlling local scour. The evaluation was conducted in a laboratory around the bridge pier in clear water conditions for 4 hours for each test. First, the pier without a gap and collar (control sample), then the combined method with a gap and collar in different positions were examined and compared. In the combined method of integrating the collar in 2 positions: low (on the bed level) and middle (distance between the bed and the water surface), the gap with an opening rate D of 25% (25% of the base diameter), i.e. with a width of 1 cm of the base diameter and a length of 2 cm, was placed in 3 positions: high (1 cm gap above the water surface), middle and low (1 cm gap below the sedimentary bed). The tests were conducted at two flow rates of 11.5 and 23 liters per second. The combined models were compared in different modes with the control sample (without collar and gap). The results showed that the presence of gap and collar has a better performance in reducing scour than the control sample. Also, in the case of low collar and gap, the scour rate was reduced by 62.5 percent and showed the highest performance in scour control. https://idj.iaid.ir/article_243968.html The contamination of water resources by heavy metals, particularly cadmium, represents a severe environmental crisis due to its high toxicity and biopersistence. This research evaluates the performance of an eco-friendly biochar adsorbent for optimal cadmium ion removal from aqueous solutions. The structural and morphological characteristics of the biochar surface were investigated using Brunauer-Emmett-Teller (BET) analysis, Scanning Electron Microscopy (SEM), Energy Dispersive X-ray Spectroscopy (EDS), Fourier Transform Infrared Spectroscopy (FT-IR), and X-ray Diffraction (XRD). Batch adsorption experiments were conducted at cadmium concentrations ranging from 50 to 200 mg/L with varying adsorbent doses (0.01 to 0.5 g). Residual cadmium concentrations were determined using Atomic Absorption Spectroscopy (AAS). The biochar adsorbent demonstrated excellent performance at both investigated doses, achieving removal efficiencies exceeding 98%. Adsorption isotherm and kinetic studies revealed that the experimental data best fit the Langmuir isotherm and pseudo-second-order kinetic models, indicating that cadmium adsorption occurs as a monolayer on a homogeneous surface through chemisorption via interaction with surface functional groups. Thermodynamic analysis at 298 K yielded negative standard Gibbs free energy values (ΔG° = −30 to −30.46 kJ/mol), demonstrating the spontaneous nature and high feasibility of the cadmium adsorption process. Given its superior efficiency and economic viability, biochar is proposed as an effective option for treating heavy metal-contaminated wastewater. https://idj.iaid.ir/article_244089.html Optimized irrigation management is crucial even in humid regions due to rainfall variability and uneven distribution during the growing season, which may cause transient water stress. In this study, A factorial experiment in a randomized complete block design with three replications was conducted at the growth season 2024-2025. Treatments included three water stress levels: no-water stress (NWS), irrigation withheld at flowering (WSF), and irrigation withheld at pod-filling (WSP), and four shade net levels (0%, 30%, 50%, and 80%). Results showed that WSF and WSP reduced seed yield by approximately 12% and 27%, respectively, compared to NWS. The 30% shade net increased seed yield by about 14% and improved water productivity compared to 50%, 80%, and no shade treatments. Water stress at pod-filling (WSP) increased oleic acid and decreased linoleic and particularly linolenic acids by up to 28%. Dense shading (80%) reduced biomass by about 27% and negatively affected some quality traits. Overall, the findings indicate that combining appropriate irrigation management with mild shading (30%) can be an effective strategy to enhance yield, improve water productivity, and maintain soybean seed quality in humid regions. https://idj.iaid.ir/article_244414.html This study aims to assess the spatial patterns of soil erosion and sediment dynamics in the Shalmanrud watershed, eastern Gilan Province, Iran, using an integrated modeling framework combining the RUSLE and WaTEM/SEDEM models within the Google Earth Engine (GEE) platform. Rainfall erosivity (R) was estimated from 20 years of monthly precipitation records using the Modified Fournier Index, while soil erodibility (K) was derived from soil texture and organic matter content based on the Wischmeier equation. The topographic factor (LS) was calculated from a 30-m resolution digital elevation model using the Desmet and Govers algorithm, and the cover-management factor (C) was obtained from NDVI values derived from Landsat 8 imagery. Owing to the absence of effective soil conservation measures, the support practice factor (P) was assumed to be unity across the watershed. The spatially distributed RUSLE outputs were subsequently used as inputs to the WaTEM/SEDEM model to simulate sediment production, transport, and deposition processes. Results indicate that annual soil erosion rates range from near zero to approximately 44.15 t ha⁻¹ yr⁻¹, with nearly 72% of the watershed classified as very low erosion (<5 t ha⁻¹ yr⁻¹). WaTEM/SEDEM simulations estimate total annual sediment production at about 73,829 t yr⁻¹ (≈1.46 t ha⁻¹ yr⁻¹), whereas internal sediment deposition reaches approximately 603,840 t yr⁻¹. These findings suggest that the Shalmanrud watershed predominantly functions as a sediment sink rather than a sediment-exporting system. https://idj.iaid.ir/article_244857.html The agricultural sector accounts for a large portion of the water and energy consumptionو in Iran, So any reduction in water and energy consumption in this sector can play an important role in increasing productivity in the country. In this study, the volume of irrigation water, yield, productivity of water as well as energy consumption for alfalfa irrigated in surface and sprinkler irrigation methods under farmer’s management were recorded and analyzed. The measurements were made over 2019-2020 on 20 fields across Chaharmahal and Bakhtiari province. Based on the results, the average volume of irrigation water for surface and sprinkler irrigation methods were 10442 and 8552 m3/ha, respectively, and water productivity was 1.26 and 1.70 kg/ m3.Their difference was significant at the five percent probability level. By shifting the irrigation method from surface to sprinkler, the volume of irrigation water decreased by about 18% and the irrigation water productivity of alfalfa fields increased by 35%. The results of energy indicators showed that the amount of irrigation energy in sprinkler and surface irrigation methods was 76332 and 53739 MJha-1, there was a significant difference. However, the net energy, energy ratio and energy productivity indices in the two mentioned systems did not show any significant difference. The energy productivity in surface and sprinkler irrigation methods was 0.14 kg/MJ and the energy ratio was 2.45 and 2.44, respectively and indicating that alfalfa production is highly energy efficient. According to the results of this study and water scarcity in Iran,, sprinkler irrigation method for alfalfa fields are recommended to increase alfalfa water productivity, with taking into account the stability of salts in the soil and observing the technical conditions of the system. https://idj.iaid.ir/article_244958.html Water scarcity in arid and semi-arid regions necessitates the adoption of innovative management strategies such as deficit irrigation and the application of organic soil amendments in agriculture. This study aimed to evaluate the main and interactive effects of deficit irrigation and biochar application on growth traits, yield components, and water use efficiency of peppermint. A pot experiment was conducted using a factorial arrangement based on a randomized complete block design with three replications under greenhouse conditions. The first factor was deficit irrigation at three levels (supplying 100%, 75%, and 50% of the plant's water requirement), and the second factor was biochar at three levels (0, 5, and 10% by soil volume). Analysis of variance revealed that the main effect of deficit irrigation on fresh and dry weights of leaves, stems, and roots, as well as water use efficiency based on fresh weight, was significant at the one percent probability level. A significant reduction in the biomass of aerial organs and roots was observed as the irrigation water decreased from 100% to 50% of the water requirement. The main effect of biochar was also significant on all traits, with the highest values of organ fresh and dry weights and WUE obtained with 10% biochar application. The interaction effect of the two factors on root fresh and dry weights was significant, such that under mild stress and in the presence of biochar, the roots exhibited a compensatory response exceeding that observed under non-stress conditions. However, this compensatory mechanism collapsed under severe stress. treatments under severe stress but amended with biochar showed no significant difference in water use efficiency based on dry weight compared to the fully irrigated treatment without biochar. The integration of deficit irrigation with biochar application is an effective strategy for reducing water consumption while maintaining WUE in peppermint cultivation. https://idj.iaid.ir/article_245044.html Faced with growing challenges from climate change and rising water demand, accurate prediction of reference evapotranspiration (ET0) has become a key component of sustainable water resource management. Traditional models like FAO-Penman-Monteith, although scientifically reliable, often lose accuracy in areas with limited meteorological data. This study aims to improve ET0 prediction by combining MODIS remote sensing data with advanced machine learning algorithms. Two models were developed: the basic Extreme Gradient Boosting (XGB) and an enhanced version called Hybrid XGB (HXGB), which offers better generalization. Meteorological and satellite data from Ramsar and Bandar Anzali stations (2001–2023) were used for training and evaluation. Results showed that HXGB outperformed the base model at both stations. In Bandar Anzali, Scenario 8 (using both meteorological data and satellite-based ETMODIS) reduced RMSE to 0.11 mm/day. In Ramsar, the same scenario achieved an RMSE of 0.19 mm/day. This data fusion approach increased the models sensitivity to spatial and temporal variations, significantly improving prediction accuracy. https://idj.iaid.ir/article_245443.html Maize (Zea mays L.), as one of the strategic crops in arid and semi-arid regions, is highly affected by water resource limitations; therefore, the adoption of sustainable management strategies is essential to maintain its productivity. This study aimed to evaluate the combined effects of biochar, nitrogen, and different levels of deficit irrigation on yield, morphological traits, and water and nitrogen use efficiencies of maize under the conditions of the Sistan Plain. The experiment was conducted as a split-plot arrangement based on a randomized complete block design with three replications. Treatments included irrigation levels (50, 75, and 100% of soil field capacity), nitrogen fertilizer rates (100, 150, and 200 kg ha⁻¹), and biochar application rates (0, 1.25, and 2.5% w/w of soil). At the end of the experiment, stem diameter, plant height, fresh and dry forage yield, fresh and dry ear weight, irrigation water use efficiency, and nitrogen use efficiency were measured. Analysis of variance indicated that the main and interactive effects of irrigation, nitrogen, and biochar on the studied traits were significant at the 1% and 5% probability levels. The highest forage yield, growth traits, and water and nitrogen use efficiencies were obtained under full irrigation combined with 200 kg ha⁻¹ nitrogen and 1.25% biochar application, which did not differ significantly from the treatment receiving 150 kg ha⁻¹ nitrogen. In contrast, severe deficit irrigation combined with low nitrogen input and no biochar application resulted in the lowest values. Overall, the results demonstrated that biochar application at an optimal rate, along with proper nitrogen management, can substantially mitigate the negative effects of deficit irrigation, enhance resource use efficiency, and serve as an effective and sustainable approach to improving maize yield and increasing water and nitrogen use efficiencies, particularly in water-limited regions such as the Sistan area. https://idj.iaid.ir/article_245770.html In recent decades, the decline of groundwater levels and the increasing salinity of aquifers have become among the most significant challenges in water resources management in arid and semi‑arid regions. Excessive exploitation of groundwater resources, expansion of agricultural activities, and land‑use changes are considered some of the most important factors intensifying this trend. However, the simultaneous assessment of quantitative and qualitative changes in groundwater and their relationship with land‑use patterns has not yet been comprehensively investigated in many plains of the country. The aim of this study is to analyze groundwater level fluctuations and water salinity and to examine the role of land‑use changes in the Taybad and Qazvin plains. In this study, changes in groundwater resources were investigated in the Taybad plain during the period 2004–2022 and in the Qazvin plain during the period 2001–2023. For this purpose, groundwater level data, electrical conductivity (EC) measurements, and land‑use maps were analyzed using statistical analysis, spatial interpolation methods, and Geographic Information System (GIS). The results indicated that in the Qazvin plain, the groundwater level declined by approximately 1 meter per year on average, while water salinity increased by about 6%. In the Taybad plain, a significant decline in groundwater levels was also observed, with an estimated average annual decrease of about 2 meters, and groundwater salinity showed an overall increase of approximately 3% during the study period. Furthermore, the greatest changes were observed in urban areas and agricultural lands, indicating the significant role of human activities and land‑use changes in intensifying groundwater depletion and aquifer salinization. https://idj.iaid.ir/article_245771.html The aim of the present study was to evaluate 19 potato genotypes in a commercial greenhouse in Minadasht, Isfahan, at two levels of full irrigation and deficit irrigation and to introduce superior genotypes based on yield, irrigation water productivity, and economic irrigation water productivty. This study was conducted in split plots and in a completely randomized design including two levels of full irrigation and deficit irrigation, 19 genotypes, and three replications. These genotypes were selected with the aim of producing mini-tubers and using them in breeding programs. A drip irrigation system was used for irrigation, and irrigation management was performed based on the water requirement of potatoes inside the greenhouse. The results showed that the effect of irrigation on the number of tubers per plant, the number of commercial tubers per plant, the weight of all tubers per plant, irrigation water productivity, and economic irrigation water productivity was significant (p<0.01). Also, the effect of genotype on the number of tubers per plant, the number of commercial tubers per plant, the weight of one tuber, the weight of all tubers per plant, irrigation water productivity and economic irrigation water productivity was significant (p<0.01). The interaction effect of irrigation and genotype on all the mentioned traits except the weight of a single tuber was significant (p<0.01). Two indices of the number of commercial tubers and economic irrigation water productivity were considered to determine suitable and unsuitable genotypes. The genotypes AD15, AD50, and AD2 with the number of commercial tubers of 13-17 and the economic irrigation water productivity of 151-206 million Rials/m3were the best choices. The use of selected genotypes in the production of potato mini-tuber can simultaneously improve the economic yield and economic irrigation water productivity. https://idj.iaid.ir/article_245772.html Various types of vegetation cover in riverine ecosystems, streams, and wetlands constitute an important component of these environments and influence their surroundings. Vegetation can play a significant role in improving water quality by reducing contaminant concentrations through adsorption and dilution processes. Therefore, this study experimentally investigated the effects of no vegetation and reed vegetation cover on pollutant transport in a laboratory flume, as well as the variation of contaminant concentration downstream of the injection point. The experiments were conducted in a rectangular channel with a length of 12 m, a width of 0.5 m, and a depth of 0.7 m. Sodium chloride (NaCl) solution was used as a tracer in the main flow, and potassium permanganate (KMnO₄) solution was used as a colored tracer to examine hyporheic exchanges in the sediment bed. In the experiments, 225 g of tracer was dissolved in 6 L of water and injected into the flow as the contaminant. Reed was used to simulate channel vegetation. The results showed that increasing the flow rate (Q) from 4 to 22.5 L/s led to an increase in the maximum hyporheic exchange length (LHZ) from 0.14 to 0.32 m, corresponding to 128%, and the mean hyporheic residence time (RT) from 290 to 584 s, corresponding to 50%. The results also showed that increasing the vegetation length (L) from 2 to 6 m caused a 15–52% reduction in residence time (RT) under different flow conditions, while in some cases the maximum hyporheic exchange length (LHZ) increased by up to 56%. These findings indicate the direct influence of vegetation length (L) in regulating hyporheic exchange and altering the pattern of flow penetration into the sediment bed. https://idj.iaid.ir/article_246255.html Farmers’ adaptation to water scarcity is of vital importance, because their ability to manage water resources and adopt resilient agricultural practices directly affects food security and the sustainability of household livelihoods. In addition, increasing adaptation capacity reduces production risk and strengthens the resilience of agricultural systems to climate change. In line with this, the present study was conducted with the general aim of investigating the effect of demographic, economic and institutional factors, climatic and social factors on the use of adaptation strategies in water scarcity conditions. The statistical population of the study included all farmers in Dezful County. The sample size was 412 people selected using the Krejci and Morgan table with stratified sampling method with proportional assignment. The main data collection tool was a questionnaire whose validity was confirmed by a panel of experts and its reliability was confirmed by Cronbach’s alpha coefficient. The results showed that the variables of age, education, agricultural experience, household size, farm size (land), access to credit, membership in organizations, and access to climate information have a significant effect on the use of adaptation strategies. In other words, the research variables were able to explain 60.5 percent of the use of adaptation strategies. In general, the results of this study can provide the basis for the use of adaptation strategies in the direction of sustainable production in the agricultural sector. https://idj.iaid.ir/article_246256.html Improving irrigation water quality management is a pivotal factor in enhancing the stability and productivity of agricultural systems, particularly when unconventional water resources such as treated wastewater are utilized. This study was conducted to determine the optimal hydrochemical parameters of irrigation water (including EC, Na⁺, SAR, Ca²⁺, and Mg²⁺) for maximizing the yield of forage corn (Zea mays L. SC 704). The research was implemented in three principal phases: (i) exploratory and statistical analysis of raw field data (45 observations); (ii) fitting and evaluation of three regression models (linear, interaction, and quadratic); and (iii) multi algorithm optimization employing genetic algorithm (GA), particle swarm optimization (PSO), and simulated annealing (SA). The results revealed that the regression model incorporating interaction effects among the parameters, which achieved the highest adjusted coefficient of determination (R²ₐⱼ = 0.9197) and the lowest error (RMSE = 0.338 ton.ha⁻¹), was selected as the superior model. In the optimization process, the PSO algorithm outperformed GA and SA, yielding a mean predicted yield of 30.064 ton.ha⁻¹, a success rate of 100%, and the highest stability. The optimal values proposed by the algorithms fell within a range that is practically achievable under field conditions. By integrating the weights extracted from the correlation matrix of the parameters in the optimum region with the values optimized by PSO, a blending ratio of 62% treated wastewater and 38% well water was established as the operational optimum. The findings of this research demonstrate that intelligent optimization of the qualitative composition of irrigation water can simultaneously promote the sustainable use of unconventional water resources, such as wastewater, and increase forage corn yield. https://idj.iaid.ir/article_246428.html The hysteresis phenomenon in unsteady flows causes a discrepancy between the actual discharge and the discharge estimated from single valued rating curves, thereby reducing the accuracy of flow monitoring and measurement. This study investigates the effect of hydrograph characteristics on hysteresis intensity, focusing on symmetric triangular hydrographs. To generalize the results, the effective physical parameters—including base discharge, hydrograph height, and base time—were transformed into three dimensionless parameters: the base flow Froude number, the hydrograph height Froude number, and the dimensionless time. The study is based on 192 physical experiments conducted in a hydraulically long flume 60 m in length with a trapezoidal cross section (30 cm bed width, 1:1 side slopes, and 25 cm depth). The results show that hysteresis intensity is directly influenced by hydrograph characteristics. With other parameters held constant, increasing the dimensionless time initially increases hysteresis intensity, reaches a maximum at mid range values, and subsequently decreases it. Furthermore, increasing the hydrograph height Froude number intensifies hysteresis across the entire range of dimensionless time, whereas increasing the base flow Froude number diminishes it. https://idj.iaid.ir/article_246573.html In order to investigate and compare two methods of surface and subsurface drip irrigation and find out the possible problems and obstacles of these methods in grape orchards, a research was carried out from 2019 for two years in the orchards of the Center for Research and Education of Agriculture and Natural Resources of Semnan province (Shahroud). In this research, the effects of two methods of surface (DI) and subsurface (SDI) drip irrigation and different amounts of irrigation water on the quantitative and qualitative characteristics of the crop, the growth characteristics of grapes and the growth of weeds were investigated. This research was done with two factors and three repetitions. The factors included Drip irrigation method in two levels (surface drip irrigation and subsurface drip irrigation) and irrigation water amounts (in three levels 50, 75, and 100% of water required by the plant). Irrigation water was calculated by the Penman-Mantith method and based on the mentioned water levels, it was given to the plants with irrigation period 3 day. In this research, the effect of experimental factors on crop yield, fruit quality characteristics such as pH, brix, acidity and bunch weight, length and diameter of pods The results of composite data analysis showed that the effect of both experimental factors, irrigation method and amount of irrigation water, as well as their mutual effects on crop yield (at the 5% level) is significant. The effect of irrigation method on the quality parameters of the product including Brix (BRX), acidity, pH, cluster weight, weight of 30 kernels per cluster, kernel length and diameter was not significant. But the effect of the amount of irrigation water on fruit Brix (1% level) was significant. Also, the interaction effect of irrigation method and amount of water on fruit acidity and pH was also significant. https://idj.iaid.ir/article_247409.html In arid regions with low surface water resources, proper management and protection of groundwater resources is crucial to ensure their sustainability. This study conducted a comprehensive assessment of groundwater quality in the critical and important Minab Plain, located in Hormozgan Province, over a ten-year period between 2012 and 2022, with the aim of identifying temporal trends in changes and determining the hydrogeochemical status. The main physicochemical parameters of 12 monitoring wells were investigated in two irrigation and non-irrigation periods. The methodology was based on Kendall rank correlation analysis to determine the correlation and trend of quality parameters over time and using the Water Quality Index (WQI) and Schuller diagrams, Wilcox diagrams to assess groundwater quality for different uses and using the Piper diagram to determine the hydrogeochemical facies. The results of the Kendall test showed that the dominant trend in the plain is towards a decrease in groundwater quality; So that the calculated WQI for most of the sampling wells showed a positive correlation with time (increasing trend), which indicates the deterioration of groundwater quality in this area. In the entire study period, the highest and lowest WQI values were 101 and 354, respectively. Piper diagram analysis showed that the hydrochemical quality of the beginning of the study period changed from better quality calcium-bicarbonate facies to worse quality sodium-chloride facies at the end of the study period. Based on the Wilcox index, most of the samples were distributed in the C3S2 to C4S4 ranges in all study periods. This classification indicates waters with high to very high electrical conductivity (C3 and C4) and medium to very high sodium absorption ratio (S2 to S4). This study emphasizes the need to implement targeted management strategies to control pollutant sources and manage the exploitation of groundwater resources. https://idj.iaid.ir/article_247428.html Given the intensifying water scarcity crisis and the increasing use of urban wastewater in the agricultural sector, farmers’ adherence to health-related practices has become crucial for protecting human health, environmental sustainability, and food security. The present study aimed to analyze the determinants of farmers’ health behaviors regarding the use of urban wastewater for irrigating agricultural crops in Kermanshah County, Iran. The theoretical framework of the study was based on the Health Belief Model (HBM). This research was applied in terms of purpose and descriptive-correlational in terms of methodology. The statistical population consisted of all farmers using urban wastewater for agricultural irrigation in Kermanshah County. Data were collected through a researcher-developed questionnaire. The validity of the instrument was confirmed by a panel of experts, and its reliability was verified using Cronbach’s alpha coefficient. Data were analyzed using SPSS software. The findings revealed that the constructs of the Health Belief Model explained 30.4% of the variance in farmers’ health behaviors. Furthermore, the results of regression analysis indicated that self-efficacy and perceived barriers had positive and statistically significant effects on farmers’ health behaviors. The findings suggest that enhancing farmers’ confidence in their ability to implement health-related practices and increasing their awareness of the challenges and risks associated with wastewater use can contribute to the improvement of health behaviors. Based on the results, it is recommended that educational and extension programs focus on strengthening farmers’ self-efficacy, improving practical skills, and increasing awareness of the health and environmental consequences of wastewater use. In addition, addressing structural factors and providing institutional support alongside educational interventions can play a significant role in promoting farmers’ health behaviors. https://idj.iaid.ir/article_247479.html The Soil wetting pattern is a key factor in the optimal design and management of surface and subsurface drip irrigation systems, and its accurate characterization plays a decisive role in determining appropriate emitter and lateral spacing. In this study, the performance of several widely used wetting bulb estimation models, including Schwartzman, Amin and Ekhmaj, Karimi, Kandelous, and Al-Ogaidi, was evaluated and compared using laboratory experimental data. Experiments were conducted in a transparent rectangular physical model with dimensions of 3 m × 0.5 m × 1 m, using three soil textures (light, medium, and heavy). Emitters were installed at four depths (soil surface, 15, 30, and 45 cm) and operated at three discharge rates of 2.4, 4, and 6 L h⁻¹ over irrigation durations of 2 and 6 hours. Comparison between measured and simulated values indicated that the Al-Ogaidi model provided higher accuracy in predicting both horizontal and vertical wetting front distributions compared with the other models. The mean RMSE values for horizontal wetting front distribution in surface drip irrigation at a discharge of 4 L h⁻¹ were 0.071, 0.032, and 0.034 for clay, loam, and sandy soils, respectively, while the corresponding values for vertical distribution were 0.017, 0.019, and 0.072. The superior performance of this model can be attributed to its simultaneous consideration of a comprehensive set of soil physical and hydraulic parameters, enabling a more realistic representation of the complex processes governing water movement and distribution in porous media. Overall, the results demonstrate that multi-parameter empirical models can serve as efficient tools for improving design accuracy, enhancing management practices, and increasing the overall efficiency of surface and subsurface drip irrigation systems.