JWSS - Journal of Water and Soil Science

Groundwater is a vital resource for meeting drinking, agricultural, and industrial needs in arid and semi-arid regions of Iran. In this study, quantitative and qualitative changes in groundwater in the Garmsar Plain were modeled using GIS, MODFLOW, and MT3DMS software during the period 2011-2013. Spatial and climatic data were comprehensively processed and prepared in the GIS environment, and groundwater flow was simulated using the MODFLOW model, and water quality changes were analyzed using the MT3DMS model. After validation with field data from 2012 to 2013, the model showed acceptable accuracy with statistical indicators of mean absolute error (MAE) in the range of 0.4 to 0.5 meters and root mean square error (RMSE) between 0.5 and 0.6 meters. The modeling results showed that a 15% increase in water withdrawal led to a decrease in the water table of up to 8 meters, a constant withdrawal led to a decrease of 7 meters, and a 15% decrease in withdrawal led to a decrease of 5 meters in the water table. From a quality perspective, the decrease in withdrawal improved the quality of irrigation water but increased the concentration of some pollutants, which requires the development of effective management strategies to protect groundwater resources. The findings of this study illustrate the importance of sustainable exploitation and smart management of groundwater resources in the Garmsar Plain.

Urban floods and stormwater runoff are among the most significant environmental and social challenges in urban areas, caused by the accumulation of rainwater and the inadequacy of stormwater collection networks. The performance of the SewerGEMS software in analyzing rainfall events and evaluating the adequacy of the stormwater collection network in Shahrekord City under various conditions has been examined. Only two of the six observed rainfall events could be simulated. In the event of 06/11/1403 (Persian calendar), the observed peak discharge was approximately 1850 liters per second. In contrast, the simulated discharge for the two-sub-basin scenario was around 1750 liters per second, and for the eight-sub-basin scenario, about 1350 liters per second. The results of the two-sub-basin scenario are more reliable. In the event of 27/11/1403, the observed peak discharge was approximately 2000 liters per second, while the simulated discharge for the two-sub-basin scenario was around 1850 liters per second, and for the eight-sub-basin scenario, about 1400 liters per second. This demonstrates that the results for the two-sub-basin scenario are more accurate. The adequacy of the network was then evaluated for return periods of 2 years and 5 years. The results indicated that the stormwater collection network of Shahrekord is generally adequate; however, some areas, such as sections of the Bouali and 13 Aban canals, have deficiencies that lead to local flooding. Finally, recommendations such as identifying locations for artificial recharge basins and continuously monitoring and inspecting the canals, particularly before the rainy season, are proposed to improve the performance of the Shahrekord stormwater collection network and reduce flood-related risks.

Given the rising need for water consumption and the decrease in available water resources, improving water use efficiency appears essential. Using modern irrigation techniques and applying irrigation management based on current, accurate scientific principles will enhance irrigation efficiency. This study aimed to estimate evaporation and windfall losses using meteorological variables and measure these losses in the cities of Isfahan, Golpayegan, and Fereydounshahr under different weather conditions. Evaporation and windfall losses were examined at 3, 6, 9, 12, and 15 hours using two selected equations across three meteorological stations with seven years of weather data. Then, evaporation and windfall losses were estimated using two experimental methods (abbreviated as WD1 and WD2), a science-based method (named droplet size), and field measurements. Results showed that evaporation and windage losses calculated with the empirical equation WD1 were about 2% higher than the field measurement value, while WD2 was about 1.5% lower. The correction factors for WD1 were 0.54, 0.44, and 0.51 for Isfahan, Fereydounshahr, and Golpayegan, respectively, and for WD2, it was 1.62, 1.17, and 1.56, respectively. The differences in evaporation and windage losses at various times of day and months of the year were statistically significant at the 5% level.

This research focuses on evaluating the efficiency of constructed wetlands in treating municipal wastewater using two plants: vetiver (Chrysopogon zizanioides) and common reed (Phragmites australis). Given the increasing pollution of water resources and water scarcity in Iran, the application of nature-based solutions (NBS), particularly constructed wetlands, is a crucial approach for effective wastewater management and treatment. This study concentrates on the wastewater from the treatment plant of Isfahan University of Technology and, over a period of six months, assesses the impact of four different treatments in a completely randomized design: 1) wetland planted with vetiver (V), 2) wetland planted with reed (N), 3) control wetland without plants (B), and 4) control wetland without plants but with a supporting substrate (P), on chemical parameters of wastewater and plants. The measured parameters include BOD₅, COD, nitrate, and phosphate. Results indicated the highest levels of BOD₅ and COD in the control treatments (without plants) and a significant reduction in these parameters in the treatments planted with vetiver and reed. The best removal performance for these two parameters was observed in the sixth month at a hydraulic retention time of 30 days, with reductions of 67% and 65% for BOD₅ and 85% and 84% for COD in the vetiver and reed treatments, respectively. In the sixth month, at a retention time of 15 days, nitrate levels decreased by 25% and 34% in the vetiver and reed treatments, respectively, and by 39% and 59% at 30 days retention time. These differences were statistically significant at the 5% level for both retention time and plant type. Phosphate reductions in the sixth month at 15-day retention were 65% and 81% in vetiver and reed treatments, respectively, and at 30 days, 82% and 87%, with these decreases being statistically significant for both retention times and plant types at the 5% level. Retention time results showed that the reduction of BOD₅ and COD is directly related to retention time, with longer retention times yielding higher removal percentages. Regarding nitrogen and phosphorus, the reed demonstrated the highest performance, effectively reducing these pollutants. The total nitrogen uptake in the shoots and roots of the reed after 30 days was 33.4 and 22.51 mg/kg dry plant matter, respectively, indicating the high capacity of the reed for nitrogen absorption from wastewater. This study demonstrates that planting vetiver and reed can serve as sustainable solutions for improving water quality and effective water resource management in Iran

The present study was conducted with the aim of quantitative and qualitative analysis of agricultural water consumption in Markazi Province, and calculated and examined water consumption at the level of 18 crops and 12 counties using the water footprint as a comprehensive indicator. A simultaneous study of the three components of the blue, green, and gray water footprint was conducted as an analytical tool to assess the amount and manner of water consumption. In this study, meteorological, agricultural, and input consumption data were used in the 2022-2023 crop year, and water footprint values were estimated in terms of units and totals by crop and county. The results showed that BWFU is strongly influenced by spatial factors (climate and precipitation) and plant characteristics (yield, crop type, and growth period). A difference of up to 98% in BWFU among different crops and a difference of more than 9 times in GWFU in rainfed compared to irrigated lands were observed. Also, GRWFU values exceeded BWFU for many crops, indicating a significant pollutant load from the use of chemical fertilizers. In addition to spatial factors and plant characteristics, the difference of 223 MCM between Saveh and Ashtian counties and the difference of 52.7 MCM between Shazand and Mahallat counties in BWF and GWF, respectively, indicate spatial differences in BWFU and cultivation area. Also, the difference in 1377 MCM between the GRWF of Arak and Ashtian counties is affected by the amount and type of fertilizer used, in addition to the cultivation area. In addition to improving performance, suggested management measures include reducing the cultivation area of high-consumption crops, expanding rainfed lands in high-rainfall areas, optimizing input consumption, and modifying the cultivation pattern in accordance with resources and climatic conditions in order to maintain the quantity and quality of water resources. Accordingly, the research results demonstrate the potential of the water footprint index in location-based and product-based analysis of water consumption and formulation of management responses.

Climate change significantly affects the water use efficiency (WUE) and yield of field crops. This study evaluates the impacts of climate change on biological yield, grain yield, water consumption, and WUE of two barley genotypes, Goharan and Reyhan 03, under autumn and spring planting regimes using the CERES-Barley model within the Decision Support System for Agrotechnology Transfer (DSSAT) software. Data provided for model calibration and validation were sourced from the field experiments conducted at the Isfahan University of Technology research farm located in Najafabad, Iran. Meteorological data for the period of 2003 to 2016 were obtained from the Najafabad weather station, while future climate projections for 2020–2050 were generated using the MarkSim weather generator under the Representative Concentration Pathway (RCP) 8.5 scenario. Planting dates were analyzed within a ±35-day window relative to baseline dates of October 22 for autumn and March 3 for spring. The model demonstrated high accuracy in calibrating key traits, including days to anthesis, days to maturity, leaf area index, grain yield, and biological yield. Elevated temperatures associated with climate change reduced grain and biological yields across both planting seasons, with biological yield exhibiting a more pronounced decline, particularly under spring planting. During the 2040–2050 period, water consumption peaked at 387.5 mm for Goharan in autumn planting, while spring planting recorded a minimum of 239 mm for Reyhan 03. Delaying autumn planting by 20–25 days enhanced WUE, while planting earlier in the spring )10–20 days (improved WUE by exploiting cooler temperatures. Evapotranspiration increased by 399 mm in autumn but decreased by 267 mm in spring. The earlier-maturing Reyhan 03 genotype demonstrated smaller yield losses in spring planting due to climate change. The findings of this study suggest that programmed adjustments to planting dates may mitigate the adverse impacts of climate change on barley production, thereby enhancing sustainability.

Water scarcity has made the agricultural water footprint a critical measure for sustainable resource management, particularly in water-stressed regions such as Iran. This index depends on various factors, including climate, crop yield, dietary habits, and irrigation/agricultural efficiency, which can be estimated more rapidly using modeling approaches. The SSM-iCROP2 model is a simulation model that has been parameterized and evaluated for over 30 crop species in Iran and has been widely used in studies related to crop yield. Since sugar is a key energy source in the food basket, sugarcane occupies vast cultivated areas in the country. Sugarcane is primarily grown in Khuzestan province. This study aimed to apply the aforementioned model to estimate the blue and green water footprint of this strategic crop, using upscaling methods for both potential and farmer-managed conditions from 1992 to 2022. The results showed that the total water footprint of sugarcane (sum of blue, green, and gray water footprints) was 2,251 and 3,134 cubic meters per ton for potential and actual (farmer) conditions, respectively.

Rapid urbanization and the expansion of impervious surfaces in urban areas can cause a reduction in infiltration rate, which consequently increases the flash floods and surface runoff in cities. In recent years, the use of bio-infiltration systems has been considered as one of the most effective approaches based on low-impact development (LID) for sustainable urban runoff management. In this study, the performance of six types of biological infiltration basins was investigated to reduce the volume of runoff and improve surface water management in the eastern region of Qazvin city. First, 40 years of rainfall data (1983–2023) were collected from the Qazvin meteorological station, and Intensity–Duration–Frequency (IDF) relationships were developed for various return periods. Six design scenarios were modeled: bioretention basins with and without a drainage system; tree boxes with and without a drainage system; infiltration trenches; and permeable pavements. The dimensions of all systems were kept constant to focus solely on hydrological performance without the influence of size or shape. Overall, using HEC-GeoHMS, SWMM, and MIDS models together offered a detailed and accurate framework for analyzing the hydrological behavior of bioretention systems in urban runoff management. Results showed that the runoff coefficients for the sub-basins averaged 0.79, highlighting the dominance of impervious surfaces in the area. These values were used as inputs for the MIDS model to simulate the six different bioretention scenarios. The results indicated that the permeable pavement scenario had the greatest effect on annual runoff reduction (about 728,555 m ³), while the bioretention cell with a drainage system had the lowest performance. SWMM results, based on DEM-derived sub-catchment data, showed low soil infiltration and high impervious surface coverage. These conditions highlighted the importance of bioretention systems in reducing urban flooding. Overall, the study demonstrates that well-planned bio-retention and other green infrastructure can decrease peak flows, increase time of concentration, and improve urban hydrological and environmental conditions.

This study aimed to optimize the site selection of artificial groundwater recharge zones in the Yazd-Ardakan watershed (covering an area of 116,765 hectares) to address challenges such as water scarcity, severe groundwater depletion, and annual rainfall below 100 mm. The research integrated Geographic Information Systems (GIS) and Multi-Criteria Decision-Making (MCDM) methods. Seventeen influential criteria, including elevation, slope, land use, geology, soil type, climate, distance from faults, and isothermal lines were analyzed using ArcGIS 10.5. Criteria weighting was performed using the Best-Worst Method (BWM), and layer integration was achieved through the Weighted Linear Combination (WLC) approach. Results indicated that slope (weight: 0.203), elevation (correlation >0.75), and land use (correlation ≈0.5) had the highest impact on zone suitability, while climate and isothermal lines were less influential. The final suitability map (900×900 m resolution) revealed that central and southern plain areas with slopes <2%, permeable alluvial formations, flat topography, and optimal distance from faults were prioritized for artificial recharge. Sensitivity analysis identified eight key criteria (correlation >0.5), and by eliminating 53% of non-essential parameters, an efficient framework for sustainable water resource management was established. This study not only contributes to raising groundwater levels, improving soil fertility, and preserving local ecosystems but also offers a practical solution for water crisis management in arid regions. 
 

One of the key factors in agricultural production is the availability of sufficient and usable nutrients for plant growth, and among these, nitrogen plays a particularly important role. The waste of nitrogen fertilizers due to the low efficiency of using fertilizers has caused environmental problems such as pollution of surface and groundwater by nitrate or ammonium. In this study, the influence of fertigation as a combination of urea, ammonium nitrate, natural zeolite of Semnan (CP), and modified zeolite by surfactant (SMZ) in the reduction of waste and manure fertilizer was evaluated. Two separate experiments with a completely randomized design with three replications were used for loam soil columns. Treatments consisted of four levels of zeolite application (0, 4, 8, and 16 g/Kg) and a fertilization level with a concentration of 60 mg per liter nitrate applied at three fertigations during six irrigations. In the first part of the study, the role of nitrogen fertilizers in fertigation as a combination of urea and ammonium nitrate (UAN) for ordinary soil was examined to reduce the concentration of nitrate and ammonium in the drainage water, and the results were compared with one of the fertigation applications. The results showed that the loss of fertilizer in the form of nitrate was reduced by 40 percent for the UAN treatment during the first period of fertigation. Since the results of the first part of the experiment showed that the concentration of ammonium nitrate does not reduce to the same level as drinking water, in the second part of the experiment, the soil amendments were used. The measured nitrate removal showed that the highest nitrate removal belonged to the soil mixed with 16 g/kg of modified zeolite in the surface layer of soil (SM16) treatment, and it was equivalent to 90 percent. The highest ammonium removal belonged to the soil mixed with 16 g/kg of natural zeolite in the surface layer of soil (CP16) treatment, and it was 85 percent. Therefore, the use of fertigation as a combination of nitrogen fertilizers with soil amendments for conditions where there is a potential for groundwater pollution by nitrate leaching is recommended.

Accurate monitoring of water surface dynamics in semi-arid regions poses challenges due to uncertainties regarding the optimal spectral index and sensor selection for effective water resource management. This study assessed the comparative performance of nine spectral water indices across the Landsat-8 and Sentinel-2 platforms to identify the best index-sensor combinations for monitoring semi-arid reservoirs. Utilizing the Google Earth Engine cloud computing platform, 181 satellite images were processed for Golestan Dam in northeastern Iran, comprising 107 Landsat-8 scenes from 2013 to 2023 and 74 Sentinel-2 scenes from 2018 to 2024. After applying atmospheric corrections using the LEDAPS and Sen2Cor algorithms, nine spectral indices (NDWI, MNDWI, ANDWI, AWEI, WI2015, WI1, WI2, LSWI, and NDTI) were calculated and evaluated against the WI2 reference through RMSE, R², and Nash-Sutcliffe efficiency metrics. MNDWI showed superior performance for Sentinel-2 (RMSE=21.42 ha, R²=0.998, NS=0.996), while ANDWI was optimal for Landsat-8 (RMSE=54.54 ha, R²=0.977, NS=0.976). Time-series analysis revealed a 35% reduction in mean annual reservoir area, decreasing from 7.28 km² in 2014 to 4.72 km² in 2021. Consistent seasonal patterns were observed, with spring maxima (9.33 km² in March) and autumn minima (3.35 km² in September) evident across both sensors. A high inter-sensor correlation (r = 0.933) supports the potential for multi-sensor integration in comprehensive monitoring efforts. The LSWI and NDTI indices displayed systematic overestimation due to interference from soil moisture and vegetation, making them unsuitable for quantifying water area. These findings highlight the sensor-dependent nature of optimal index selection, recommending MNDWI-Sentinel-2 pairing for short-term monitoring and ANDWI-Landsat-8 for long-term trend analysis in the management of semi-arid reservoirs.

The water crisis and climatic conditions in Iran have necessitated prioritizing low water-demand crops in agricultural investment policies. Quinoa, as a pseudo-cereal with relatively low water requirements, can be considered a suitable alternative to water-intensive crops. This study was conducted to investigate the comparative advantage of quinoa production compared to water-intensive crops under water-scarce conditions in Isfahan Province. To assess comparative advantage, two indicators—Domestic Resource Cost (DRC) and Social Cost-Benefit Ratio (SCB)—were employed. Data were collected through questionnaires and governmental sources, and shadow prices of inputs and outputs were utilized in the analyses. The statistical population consisted of quinoa producers. The results indicated that quinoa possesses a comparative advantage in Isfahan Province. The breakeven yield of this crop was estimated at 653 kg/ha, meaning that production above this level indicates the existence of a comparative advantage. Furthermore, the maximum allowable water consumption to maintain this advantage was estimated at 15,792 m³/ha; water consumption exceeding this amount eliminates the comparative advantage of quinoa cultivation. Additionally, the economic water productivity of quinoa was evaluated to be higher than that of other common crops in the region. Overall, considering comparative advantage of quinoa and its higher water productivity compared to common water-intensive crops, this product has the necessary potential to be included in the cropping pattern of Isfahan Province. However, recommendations for complete substitution require targeted and multidimensional policy interventions at technological, marketing, and policy-making levels, as well as conducting complementary research on the analysis and development of the quinoa value chain and market, investigating consumer behavior, designing targeted supportive policies for the transition period, and conducting a more comprehensive analysis of the comparative advantage of other products.

Scour is a major challenge in river engineering, as it causes bridge failures during flood events and leads to significant economic losses. This study aims to estimate the normalized scour depth (Dse/Dp) around pile groups by examining relevant hydrodynamic and geometric parameters. A dataset comprising 299 laboratory measurements collected from various sources was assembled and divided into training and testing subsets. As machine learning inputs, several models were employed, including Artificial Neural Networks (ANN), Support Vector Regression (SVR), Extreme Gradient Boosting (XGBoost), and a meta-ensemble learning model (Stacking). Hyperparameter tuning was performed using the Grid search method to achieve optimal regression performance. Model performance evaluation indicated that the ANN and SVR models achieved coefficients of determination of R² = 0.87 and R² = 0.91, respectively. The XGBoost model outperformed these approaches, yielding R² = 0.94 with an RMSE of approximately 0.28. Ultimately, the stacking ensemble model, by integrating the outputs of the base learners, demonstrated the highest predictive accuracy with R² = 0.96 and an RMSE of 0.11, representing an improvement of approximately 15% compared to ANN and 7% compared to XGBoost. Overall, the findings highlight that ensemble machine learning models—particularly the Stacking approach—provide a robust and efficient framework for predicting scour depth around pile groups and for capturing the complex flow behaviors in hydraulic systems.

Greenhouse gas emissions and achieving acceptable water and energy efficiency are among the most important challenges facing the agricultural sector. The objective of the current research was to investigate the indicators of water physical and economic productivity and energy of wheat in Khorasan Razavi Province. To evaluate these indicators, a questionnaire was used in this research. A total of 200 questionnaires, including 50 for each city, were distributed, and the amount of input consumption and production was collected. The results showed that the physical productivity of water in the plains of Mashhad, Torbat Jam, Taybad, and Bakharz was 0.57, 0.72, 0.7, and 0.46 kg/m3, respectively. Also, the results showed that the highest Energy efficiency and energy productivity were 2.18 and 0.148 kg/MJ, respectively, for the Taybad Plain, and the highest specific energy was 10.92 MJ/kg for the Bakharz Plain. The highest (1539/68 kg/ha) and lowest (964/79 kg/ha) greenhouse gas emissions were obtained in the Mashhad and Taybad plains, respectively. The overall results showed that crop yield in relatively arid areas such as Torbat-e Jam and Taybad is higher than in semi-arid areas with higher altitudes, similar to Mashhad and Bakhrez.