Journal of New Approaches in Water Engineering and Environment

Abstract The limited capacity of water resources in our country requires their protection and optimal use in order to meet future water needs. Achieving these goals is only possible by preparing a balance of water resources and assessing their potential. The water balance indicates the water potential of an area. In this study, the balance for the years 2017-2018 was calculated based on water resources and consumption for the three study areas of Kashan, Moteh, and Golpayegan. The amount of the balance deficit was determined and confirmed with the latest balance sheet report for these three areas, which was approved by the Isfahan Regional Water Organization. The surface resources, including the river in Golpayegan, are the most important in this area. The agricultural sector has the highest consumption in all three areas and also has the highest groundwater consumption. Additionally, Golpayegan area has the highest groundwater discharge, resulting in a greater balance deficit in this area. The results show that the balance deficit for the statistical year in the three areas of Kashan, Moteh, and Golpayegan is -30, -0.61, and -40 million cubic meters, respectively. Finally, it is suggested that due to the balance deficit in these three study areas and the high depth of groundwater, the use of groundwater resources should be limited, and surface resources should be used by establishing more hydrometric stations, especially in the Golpayegan area.

Abstract Daily statistics of climatic elements spanning from 01/01/1378 to 12/29/1398, comprising a total of 7670 data points, were curated for simulation purposes. The Gamma test methodology was employed to discern the most effective combination of input variables for the machine learning models. This test serves to assess the impact of each independent variable on the dependent variable. Consequently, all of these variables were selected as inputs for the trio of models. The dataset was partitioned, allocating 70% (5370 data points) for training and 30% (2300 data points) for testing purposes. Utilizing this partitioned data, the tuning parameters of each model were optimized to yield the most favorable output. Model performance evaluation was conducted utilizing four metrics: Root Mean Square Error (RMSE), Mean Absolute Error (MAE), coefficient of determination (R2), and Developed Difference Ratio (DDR).
The analysis of the results indicates that all three models exhibit varying degrees of accuracy in predicting the ETO values, with the Gene Expression Programming (GEP) model demonstrating the highest accuracy and lowest error. Specifically, for the GEP model with a three-gene structure, the performance evaluation indices (RMSE, MAE, R2, and ETO(DDR)MAX) during the training phase were determined as (4.42, 0.98167, 0.2219, 2752), while during the testing phase, they were recorded as (8.54, 0.9907, 0.1515, 0.1985). Following the GEP model, the Support Vector Machine (SVM) and Artificial Neural Network (ANN) models ranked subsequently in the simulation process

Abstract Objective: The aim of the current study was to investigate the effect of wet and dry incidents on the quality and quantity of groundwater in Kalaleh city.

Methods: In this research, Standard Precipitation Index (SPI) was used to investigate the wet and dry incidents in a 15-year statistical period (2006-2021). Standardized water level index (SWI) and information from 10 Deep and semi-deep wells (2006-2021) were used to assessment the condition of groundwater level.Also, the qualitative parameters of 10 wells including K+, Na+, Mg2+, Ca2+, SO42- , Cl- , HCO3-, pH, SAR,TDS and EC were used. Excel and SPSS software were used for statistical analysis.Also,Pearson's correlation coefficient was used to investigate the effect of wet and dry incidents on the fluctuation level and quality factors of groundwater.

Results:Examining the drought situation in Kalaleh using SPI indicated that the most severe droughts occurred in 2007, 2011 and 2018and the wettest years occurred in 2006 and 2019.The results of the research showed that with the increase in the severity of Drought and Wet, the level of deep and semi-deep groundwater decreased and increased, respectively. Also,Correlation results between SWI and water quality showed that there is no significant correlation between any of the water quality variables and SWI. There was only a significant relationship between acidity and SPI.

Conclusions:The result of this research shows that the occurrence of periods of drought or wet in the studied area does not have significant effects on the quality of groundwater resources

Abstract Objective: Accurately measuring flow rates in open channels is one of the fundamental challenges in hydraulic engineering, playing a crucial role in water resource management and the design of hydraulic structures. This study aims to develop an accurate hydraulic model for estimating flow rates in Simple Modified Baffle Flumes (SMBF) through a combination of laboratory experiments and numerical simulations using Flow3D software.
Methods: Experiments were conducted in a rectangular channel with 27 different flow rates (ranging from 5 to 50 liters per second) and four contraction ratios (0.342, 0.467, 0.561, and 0.726). Numerical simulations were performed using the RNG turbulence model and the Volume of Fluid (VOF) method in Flow3D software. The numerical model was calibrated with experimental data, and its accuracy was evaluated using the Mean Absolute Relative Error (MARE) criterion.
Results: The findings indicated that by applying calibrated energy correction coefficients (K ranging from 0.95 to 1.05), the MARE was reduced to 4.85%, which represents a 2.47% improvement over previous methods. Increasing the contraction ratio from 0.342 to 0.726 led to a 32.5% increase in the Froude number and a 20% increase in turbulent kinetic energy.
Conclusions: This study presents an accurate numerical model and novel correction coefficients, providing an efficient and sustainable approach for optimizing the design of SMBF flumes and enhancing the accuracy of flow rate estimation. It is recommended that future studies investigate the effects of submerged flow and environmental parameters.

Abstract Developing construction projects and shortage of based materials have increased the necessity of using cheap and available materials. For this aims soil-cement has used for the last several decades, but there are limited studies on the effect of silica fume and curing temperature on the mixture. In this laboratory, study soil and water used were from upstream basin of Karkheh dam. Physical, mechanical and chemical tests for soil and water were performed according to the ASTM criteria. Different cylindrical samples of soil-cement-S.F mixtures at optimum moisture were made based on modified AASHTO method. Samples were cured at 27°C and 40°C in 7 and 14 days in humid room. Wetting and drying tests also compressive strength testes at 7, 14 and 28 days were performed. Statistical analysis of results with SAS software showed that the increase of cement, S.F, and special curing temperature enhanced strength and durability of the mixtures. According to the USBR criteria, all samples can be used in construction projects. Also, the research results showed that it is possible to construct watershed management dams using a mixture of soil-cement-microsilica at a cost of about 50% of stone, cement or concrete, which can be a dramatic development for the construction of watershed management dams in the future, and also the use of this mixture reduces environmental degradation and the use of soil at the dam construction site and also increases the speed of watershed management operations.

Abstract Soils containing a significant amount of clay are considered problematic soils in projects from the point of view of civil engineering, so it is necessary to improve these types of soils for the establishment of structures by using soil improvement materials. In this research, to investigate the effect of nano lime - calcium hydroxide Ca(OH)2 - and bagasse on the resistance characteristics of soils, an unconfined compressive strength test was conducted. To make the samples, the maximum dry weight and optimum moisture content were selected. The desired tests are performed on samples of clay, clay and nanolime mixture, clay and bagasse mixture, clay and lime mixture in 3, 5, and 7 weight percentages of dry soil, and a combination of both nanolime and sugarcane bagasse ash. It was done in specified percentages and a period of 7 and 28 days. The results of the experiments showed that the use of nano-lime and sugarcane bagasse ash and lime for soil stabilization increases soil resistance. In the unconfined compressive strength test, the samples stabilized with nanolime had a greater increase in strength compared to the samples stabilized with lime, and the highest amount of increase is related to the sample with a 5% additive in the 7-day curing period. Also, in the combined use of nanolime and sugarcane bagasse ash, compared to nanolime, the obtained resistance has decreased.

Abstract Objective:In order to examine the quality of water resources and their effects on human health, various indicators using physical and chemical parameters such as pH, EC,total hardness (TH),nitrate, etc.,determine the water quality and the risk from consuming contaminated water with a number, and the results are also interpreted qualitatively to make it easy for the general public to understand.
Methods: In this research,drinking water sources of Sahne city were sampled in the distribution network.These samples were collected from different areas of the city and transferred to the laboratory under standard conditions. pH,EC,total hardness (TH)and nitrate were measured for the collected samples. In order to check the condition of the samples in terms of these parameters in comparison with the existing standards, the average of these parameters was compared with the national standard of Iran and the WHO standard.
Results:According to the quality indicators, the results showed that the drinking water sources of Sahneh city have excellent quality and all the investigated parameters were within the standard ranges.However, EC in 62% of the samples, , pH in 13.79% of the samples, and TH in 10.34% of the samples, were higher than the standard. According to the IRCA index, the health risk in 13.79% of the samples was at the high risk level and in 13.79% at the medium risk level.
Conclusions: The amount of HQ index was obtained in the following age groups: infants > children > adolescents >adults,and infants are the most sensitive group to the non-carcinogenic risks of nitrates.

Abstract Unconventional types of water include brackish water, upstream agricultural land drainage, and treated wastewater could be used in pressurized irrigation systems,. Therefore, in this study, an experiment was conducted in the form of completely randomized split plots with 8 treatments and three replications in Gorgan University of Agricultural Sciences and Natural Resources from autumn 2019 to spring 2020 for canola. The effect of quality or type of irrigation water (W) on two levels, type of irrigation system (T) on two levels and method of irrigation fertilizer (F) on both levels on the yield of rapeseed parameters was tested. The results showed that the simple effects of irrigation fertilizer (irrigation fertilizer (F1), no irrigation fertilizer (F2)) in well water (w1) and wastewater (w2) in surface (T1) and subsurface (T2) drip irrigation system in The 1% probability level depends on the amount of dry matter, number of branches, number of pods (pods) and yield.The results also showed that the use of Gorgan treated effluent and drip irrigation on canola performance parameters (at a probability level of 5%) were not significant. Irrigation fertilizer on 1000-seed weight at 5% level is not significant. Also the simple effects of water type treatment and irrigation method and all interactions of water type effect on irrigation (WF), water type effect on dripper type (WT), fertilizer effect, dripper type (FT), water type effect on irrigation fertilizer type dripper (WFT) at the 5% probability level was not significant on all canola yield parameters.

Abstract Objective: Using a water injection system with counter and transverse jets against the flow passing over an ogee spillway after a sudden expansion reduces pressure fluctuations and turbulence along the channel, resulting in flow uniformity and consequently controlling asymmetric jumps.
Methods: In this research, the hydrodynamic flow parameters in a channel were investigated using a combination of a transverse jet at angles of 30, 45, and 90 degrees at two heights of 35 and 45 cm from the channel bed, and the simultaneous use of a counter jet with 5 fixed jets and a total discharge of 4 liters per second, with three Froude numbers of 4.7, 7.8, and 9.5.
Results: The jet injection time, the βL parameter (a parameter similar to the Boussinesq coefficient in the momentum equation) in the S jump exhibits less turbulence and dispersion compared to the T jump, indicating that the use of a transverse jet injection system can act as a flow dissipater, leading to flow uniformity. It also causes a significant reduction in the flow momentum (βL.Vm²) at the sudden expansion section from the beginning to the end of the channel.
Conclusions: The use of a transverse and counter jet system with varying angles can significantly reduce turbulence and channel erosion, control asymmetric hydraulic jumps, and uniformize the flow velocity distribution along the channel.

Abstract The escalating demand for water resources in recent decades has driven intensified groundwater extraction, resulting in declining aquifer levels and deteriorating water quality. In coastal regions, this phenomenon has exacerbated saltwater intrusion into freshwater aquifers. This study aims to simulate the groundwater flow dynamics of the Qalgachi coastal aquifer and assess the extent of saline water intrusion using a solute transport model. The groundwater flow system was quantitatively modeled using the GMS software, while the MT3DMS numerical code was employed to simulate solute transport and evaluate the migration of the saline water front. A solute transport model was calibrated using chloride concentration data derived from 16 groundwater samples collected across the study area. The transient flow model demonstrated robust performance during calibration and validation phases, as evidenced by a strong correlation between simulated and observed hydraulic head values, with RMSE below 1.14 m. This confirms the model’s reliability for simulating groundwater flow and contaminant transport. Hydraulic analysis revealed a negative water balance, indicating a sustained depletion of aquifer storage. The solute transport model highlights that excessive groundwater abstraction has induced a cone of depression, triggering saline water intrusion from the lake’s coastal interface into the aquifer. The encroachment of saline water extends up to 2.3 km inland. In several monitoring wells, EC and chloride concentrations have reached critical levels of 9,700 μS/cm and 2389 mg/L, respectively, confirming significant contamination due to saltwater intrusion. These findings underscore the urgent need for sustainable groundwater management strategies to mitigate further aquifer degradation.

Abstract Water Quality Index (WQI) is an index that assesses water quality using a set of physical, chemical, biological, and microbiological parameters in the water environment. WQI is determined using 12 different parameters including magnesium, calcium, sodium, potassium, chloride, sulfate, nitrate, bicarbonate, electrical conductivity of water, total dissolved solids, water hardness, and acidity. These parameters were measured twice a year in the months of Khordad and Mehr from 1387 to 1400 in the sample wells of the study area. The WQI is calculated by combining and weighting these 12 parameters to determine the quality of water for the wells. In this study, two well-known models of artificial neural networks, including Multilayer Perceptron (MLP) and Radial Basis Function (RBF), are employed and evaluated for the desired objective. The findings of this study demonstrate that by reducing the number of parameters to 8, the artificial neural network can estimate the water quality index with very high accuracy, with a correlation coefficient of 0.99 and a root mean square error (RMSE) of 0.02. Additionally, the MLP provides better results compared to the RBF. The quality of groundwater in the area of Dehgolan County is generally very good and good. However, the quality of groundwater in the area of Qorveh County, with movement from the western side of the County towards the east and southeast, changed from very good to very bad, respectively.

Abstract Objective: It is possible to determine the optimal performance of systems using the simulation-optimization models. The surface irrigation in the form of low-pressure irrigation, is one of the modern irrigation methods, and is supported by the government by receiving free credits.
Methods: In this research, a new calibration- simulation- optimization model was developed for furrow irrigation. In this model, the SCS method was used to calibrate parameters of the SCS infiltration equation from infiltration test data. The SCS method was used for hydraulic simulation of surface irrigation (furrow design). The PSO meta-heuristic algorithm solver (particleswarm) was used for optimization. Finally, in this model, the simulation is done after the simulation-optimization of furrow irrigation. To optimize the hydraulic objective function, including the minimization of the linear combination of three performance indicators, the decision variables of flow rate, length and slope were used.
Results: Comparing the results of the SCS infiltration equation with the calibrated parameters with observed infiltration values, with R2=0.99, CRM=-0.002 and NRMSE=0.7%, indicated the proper performance of the calibration. The simulation results in three experimental fields showed over-irrigation with runoff losses, which led to an inappropriate objective function. Although the design reduced the losses by reducing the flow rate and closing the end. After that, optimization with options such as flow rate reduction, length increase and slope reduction, caused reduction (improvement) of the objective function from 1.22 to 0.24 for field 1, from 0.8 to 0.27 for field 2, and from 0.22 to 0.11 for field 3.

Abstract Objective: Soil moisture plays a significant role in agricultural production and climate dynamics. Given the increasing impact of climate change, this study aims to evaluate the capability of two selected CMIP6 models—ACCESS-CM2 and MPI-ESM1-2-LR—in simulating surface soil moisture and project this variable under two SSP scenarios (SSP1-2.6 and SSP5-8.5). This research addresses an important gap in projecting this variable in Qazvin Province.

Methods: Monthly surface soil moisture data from the ERA5-Land reanalysis database were used for the baseline period. The outputs of the two models were bias-corrected using the Linear Scaling (LS) method. To evaluate model performance, statistical indices such as RMSE, MAE, and the Pearson correlation coefficient were applied. Climate projections for the near future (2021–2040) were conducted under two SSP scenarios.
Results: The highest soil moisture levels occurred from January to April and from October to December, while the lowest values were observed in the central and southeastern regions. The ACCESS model outperformed the MPI model in representing spatial patterns, particularly in mountainous areas. The results indicated that under the SSP1-2.6 scenario, surface soil moisture would increase in winter, whereas a decrease or slight change was observed in summer. Under the SSP5-8.5 scenario, a more severe decline (up to 35%) occurred in summer and early autumn.
Conclusion: The findings suggest that soil moisture will decrease during warmer months due to climate change, potentially affecting irrigation management, drought monitoring, and agricultural crop yields.

Abstract Objective: An experiment was conducted with the aim of identifying and analyzing some of the secondary compouds and evaluating the allelopathic potential of the invasive weed of Commelina communis on germination, physiological, biochemical and antioxidant activity of a reference plant sensitive to the allelochemicals of Lepidium sativum.
Material and methods: This experiment was conducted as a factorial based on the completely randomized design with three replications in 2023. Different parts of C. communis weed at four levels i.e. root, stem, leaf and flowering branch were as the first factor and different concentrations of the extracts obtained from each of the parts were as the second factor. To extract the samples, first, 5 g of the plant powder of each part (weight) was mixed with 100 ml of distilled water as solvent (volume), separately. Then, different concentrations of 25, 50, 75 and 100% were prepared from the obtained extract (base solution) with the help of distilled water. Distilled water was used as control treatment.
Results: According to the results, the percentage and rate of germination, length of root and shoot, dry weight of root, shoot and seedling, content of chlorophyll a, b, total and carotenoids pigments, proline and soluble sugars, total phenols, total flavonoids and antioxidant activity of L. sativum were affected by the aqueous extract of parts and concentrations of C. communis and their interaction effect. So that the content of total chlorophyll pigment and subsequently the growth of Lepidium sativum seedlings significantly increased in concentrations of 25 and 50%