مجله پژوهش آب ایران
پیاپی 44 (بهار 1401)

Tea is the most popular drink after water in the world and more and more people are consuming it every day. Therefore, it is necessary to increase the production of this product per unit area. Since in some months of the year the amount of rainfall does not meet the water requirement of the plant, to produce more product per unit area, Supply of water shortage with proper irrigation method is unavoidable.

In order to investigate the effect of different irrigation methods and irrigation levels on the yield and water use efficiency of Chinese hybrid cultivar tea plant (Camellia sinensis L.), an experiment was conducted as split plots based on randomized complete blocks design in three replications with three main treatments including permanent sprinkler irrigation (SI), local drip irrigation (DI) and strip drip irrigation (TDI), and three sub-treatments including without irrigation (I0), 50 (I1) and 100 (I2)% of crop water requirement in 1399 in the Research Station of Fashalam tea garden in Fooman region. In order to determine the physical and chemical properties of the soil in the study area, soil samples were taken from a depth of 0 to 20, 20 to 40 and 40 to 60 cm and were analyzed in the laboratory. In this experiment, the field capacity, permanent wilting point, bulk density and pH was determined and soil texture was measured by hydrometric method. The meteorological data required to calculate the water requirement of the tea plant were prepared from the Rasht agricultural meteorological station. The amount of rainfall during the irrigation period (May to November) in 2020 was equal to 307.197 mm, which was lower than the average rainfall of the last 30 years in the same irrigation period was 188.2 mm. The water requirement of the tea plant was calculated using the daily data of 30 years of Rasht agricultural meteorological station with penman monteith FAO method by software of CROPWAT 8.0, and then the daily water requirement of the plant by considering the water use efficiency of 80% in sprinkler irrigation system and 95% in the drip irrigation system was determined. Gross amount of irrigation water was determined based on plant water requirement, soil moisture holding capacity and water use efficiency in sprinkler and drip irrigation systems. The net amount of irrigation water in the treatment of the 50% of the plant water requirement was equal to 50% of the amount of the net irrigation water in the treatment 100% of the plant water requirement. The volume of water given to each plot at each irrigation period was measured using a water meter to the nearest tenth of a liter.

The results of the data variance analysis showed that the effect of irrigation methods, different levels of irrigation and their interaction on the yield of green and dry tea leaves and water use efficiency based on green and dry tea leaves were significant at the level of one percent probability. So that the average of the lowest green and dry leaf yield and water use efficiency based on green and dry leaves with 3846.90 and 1044/7 kg/ha, and with 1.23 and 1.33 kg/m3 in DI irrigation method and the highest of them with 7859.70 and 2129.6 kg/ha, and with 2.39 and 0.65 kg/m3 were observed in SI irrigation method which increased by 2.043 and 2.038, and 1.94 and 1.97 times in compared with DI irrigation method, respectively. Also, the lowest green and dry leaf yield and water use efficiency based on green and dry leaves with 1050.1 and 299.16 kg/ha, and 0.44 and 0.13 kg/m3 at I0 irrigation level, and the highest of them with 8947.20 and 2418.17 kg/ha, and 2.53 and 0.65 kg/m3 were observed at I2 irrigation level which increased by 8.52 and 8.08, and 5.75 and 5.00 times in compared with I0 irrigation level, respectively. The results of the interaction of irrigation methods at different levels of plant water requirement on green tea leaf yield showed that the highest yield with 13000 kg/ha was obtained in SI irrigation method with I2 irrigation level. Therefore, SI irrigation method with I2 irrigation level can be considered as optimum method to the tea green leaf production in the Fooman region.

Climate change affects the hydrological cycle, available water resources and water demand by changing temperature and precipitation. In this regard, predicting temperature and precipitation changes by the models of the Sixth Climate Change Assessment Report due to more accuracy in their outputs can be helpful to plan and manage water resources in the future. In addition, identifying appropriate models among these climate models will pave the way for future research into the effects of climate change. In order to achieve these objectives, the present study was conducted.

At first Step, 138 and 113 meteorological stations were selected to study precipitation and temperature based on the appropriate location distribution in Iran, respectively. Then, monthly precipitation and temperature data of the historical period (1995-2014) were zoned in 30 basins of the country by Thiessen polygon method. In the next step, the results of simulation of precipitation and temperature of 10 CMIP6 models were extracted from website. Then, in order to equalize the time period of the base period of climate models with the observation period, the simulation results of models were used on a monthly basis.For each model, the position of network cells covering 30 basins of the country was determined and according to the percentage of the area of each cell in that basin, the average temperature and precipitation of GCM models were calculated at the level of each basin.Moreover, to increase the accuracy of the results of climatic models, the output of 10 climatic models in the historical period (2020-2039) were compared to observational data and were ranked based on KGE criteria. Then, the models were weighted based on the obtained rankings. In the next step, the forecasting results of climate models under three scenarios SSP126, SSP245 and SSP585 in the next period were obtained, after combining the output of the models based on their weight. Finally, the average changes in temperature and precipitation for the period of 2020-2039 compared to the historical period, were presented for all the basins.

The results of climate models ranking based on their ability in climate forecasting showed that the high score models are different depending on the variety climate in regions and their diversity in precipitation simulation is greater than temperature. So that, among 10 CMIP6 models, 6 high score models for simulation of precipitation and 4 high score models for temperature simulation in different parts of the country were determined. Furthermore, the results of climate forecasts indicate a change in precipitation from about +19 to -12% and an increase in temperature on average in the range of 0.1 to 0.6 degrees Celsius in different basins of the country over the next 20 years. Based on the average temperature changes of 20 next year, it can be seen that the northern regions of the country will experience more temperature increases than the southern regions of the country in the coming period. Increasing the temperature in the next period, while increasing evapotranspiration, will also increase water demand and consumption in different sectors. Therefore, it is necessary to develop policies to adapt to climate change in the agricultural, drinking and industrial sectors. Moreover, the western basins of the country will experience the greatest decrease in rainfall during this period. Due to the strategic location of some of these basins, both in terms of proximity to neighboring countries and in terms of dependence on agricultural activities to create food security and the lack of water resources, reduced rainfall can lead to several problems. Therefore, it is necessary to take measures to reduce water consumption, including changing consumption patterns and planning to compensate for economic losses and establish a balance between water supply and demand.

Water quality is one of the most important factors in healthy living and human life. In this sense, some of the water quality parameters should be controlled in maintaining the human health and welfare. In today’s industrial world, most of the global natural water sources, including those in Iran, contain impurities such as the TDS. Numerous factors that are includes include cations such as sodium ion (Na+), potassium ion (K+), calcium ion (Ca+2), and magnesium ion (Mg+2) and anions such as chloride ion (Cl-) and bicarbonate ion (HCO3- ) with sulphate ion (SO42-) affect the concentration of these parameters in natural water systems. The total dissolved solids (TDS) is one of its most important factors; Many water resources development programs will be implemented to identify these factors. Accurate prediction of water quality parameters is a basic need for water quality management, human health, public consumption and household consumption. In the last decades, artificial intelligence (AI) techniques have become viable and popular due to their advantages, and have been widely developed in solving a variety of environmental engineering and water quality engineering problems.

For the estimation of water quality parameters (WQPs), Singh et al. (2011) utilized the clustering method, or support vector clustering (SVC), to optimize surface water quality monitoring in the city of Lucknow, India. The overall view of the water quality index of their study area revealed that most of the study area come under highly to very highly polluted zones. Tan et al. (2012) predicted phosphorus values in China with the least square support vector regression (LSSVR) method. They compared the efficiency of the LSSVR method with neural networks of the radial basis function (RBF) and back-propagation (BP). Experimental results showed that the small sample case with noise, LSSVM method was better than multi-layer BP and RBF neural network and is able to better meet the requirements of water quality prediction. Liu et al. (2013) addressed WQPs prediction in aquaculture employing the GP and real-value genetic algorithm-SVM (RGA-SVR). They used the GA to modify the coefficients of the SVR method. The results showed the superiority of the RGA-SVR algorithm over other methods based on the root mean square error (RMSE) and mean absolute percentage error (MAPE). Ghavidel and Montaseri (2014) employed ANN, GEP, and ANFIS with grid partition as well as ANFIS with subtractive clustering (ANFIS-SC) to predict TDS values of the Zarinehroud basin, Iran. A comparison was made between the above AI approaches, and the results demonstrated the superiority of GEP over the other intelligent models. Abyane (2014) compared artificial neural network (ANN) with multivariate linear regression (MLR) for prediction of BOD and COD in the wastewater treatment plant. In their study, ANN could predict BOD and COD parameters with higher precision than MLR.

Due to complex characteristics of time series WQPs, a standalone model can hardly satisfy the estimation accuracy requirements. Therefore, the hybrid models combined with different single models will be an effective way to improve the WQPs estimation accuracy. This study proposes a new and accurate hybrid model for predicting WQP (i.e., TDS) using ions at Varand and Garmrood, two hydrometric stations of Tajan basin, Iran. The proposed WQP estimating framework was developed based on the combination of a data pre-processing algorithms (i.e., EEMD) with two AI-based models that was not addressed by the literature related to the WQPs modelling. Acceptance and reliability of proposed hybridized and standalone models (e.g., artificial neural networks (ANN), EEMD-ANN, support vector machine (SVM) and EEMD-SVM) using five performance criteria and visual diagrams were evaluated. Comparison of results between independent and hybrid models showed that EEMD data pre-processing algorithm can increase the performance of the hybrid SVM model for estimating the TDS quality parameter in both training and testing stages at both considered hydrometric stations. For example, the EEMD-SVM model with RMSE = 20.23 for the training phase and RMSE = 27.29 for the test phase at Varand station and RMSE = 45.26 for the training phase and RMSE = 40.06 for the test phase at Garmrood station has performed better than other hybrid and standalone models. In general, the proposed hybridized model of support vector machines based on EEMD data pre-processing algorithm can be proposed as a superior model to decision makers for planning and management in the field of river water quality detection and determination.

Due to the scarcity of fresh water resources, one of the main solutions to supply agricultural water resources is the use of unconventional water, including agricultural water drainage, saline water resources and effluents. In Khuzestan province, a total of about four billion cubic meters of drainage water is produced annually. The volume of water in the Karun Basin alone is about two billion cubic meters per year. One of the areas where sugarcane drainage has accumulated and is now a serious concern is the 35,000-hectare sugarcane wetland, located south of Ahwaz on the border with Iraq. Drainage production due to various activities, especially agriculture in Khuzestan province, is one of the serious problems. Sugarcane production and fish farming are the main producers of drainage in southwestern Khuzestan. In order to optimal use of sugarcane drainage, the effect of these waters on the quantitative and qualitative properties of cotton in the Cultivation and Sugarcane Industry of Mirza Kuchak Khan during 2018 and 2019 was investigated.

Experimental cultivation was performed in 8 lines of 30 meters with intervals of 60 x 20 cm. The field soil had a silty to loamy clay texture.. The experimental design was split-split plots with 3 replications. Three planting dates: February 28, March 29 and April 29 as the main plot, three irrigation treatments including sugarcane drainage, Karun river water, and intermittent irrigation with Karun water and drainage (combined) as a sub plot and three cotton cultivars included Golestan, Khorshid and Shayan were considered as sub-plots. The first planting date was 28th February, after plowing, disc and fertilizing. Thus, fuzzy seeds were disinfected using carboxin tiram fungicide and Gachu insecticide and then planted at appropriate depth according to field soil conditions. Irrigation planning was done based on measuring the percentage of soil moisture before irrigation and the depth of root development. Thus, in each irrigation regim, one day before the irrigation operation by measuring soil moisture to a depth of 100 cm, soil moisture deficiency is determined according to the depth of plant development by considering the maximum amount of management allowed deficit (MAD) equal to 60% of soil water holding capacity. In order to measure the yield components, five plants in each treatment were identified and measured on these plants. Cotton was harvested three times. Data were analyzed using MSTATC software and Duncan test. Finally, the best treatments were identified and introduced in terms of planting date, type of irrigation and cultivars that have better yields.

The results showed that the highest yield with 1712 kg/ ha was related to the planting date of 28 Feb. Yield of the first planting date was 42% and 574% higher than the planting dates of 29 March (1204 kg/ha) and 29 April (254 kg/ha), respectively. The total yield of cotton on the date of 29 March was 374% higher than the date of 29 April. The highest percentage of early maturity was related to the first planting date, which was not significantly different from the second and third planting date. There was no significant difference in different dates in terms of early maturity. In terms of mean boll weight, the first planting date had a higher boll weight of 11.5 and 87.6% than the second and third planting dates, but the difference between the date of the first and second crops was not significant in terms of boll weight, but The difference between these two planting dates and the third planting date was statistically significant on boll weight. The number of bolls per plant on the date of the first crop was 35 and 147% higher than the date of the second and third planting date, respectively, while the date of the second planting date had 83% more bolls than the date of the third planting date. There was no significant difference between treatments in terms of lint percentage but the second planting date had a higher lint percentage. Among irrigation water quality treatments, the yield of irrigation treatment with Karun water and intermittent irrigation with Karun water and drainage (combined) were not significantly different. Karun water irrigation had 12% higher yield than drainage irrigation, while the yield of irrigation with Karun water was only 6% higher than combined irrigation, this difference was not statistically significant. Among cotton cultivars, the highest yield with 1159 kg /ha was related to Golestan cultivar, which was 16.8% higher than Shayan cultivar. Shayan cultivar is one of the cultivars in which high temperature caused the flowers to dry out. The reason for the decrease in yield of Khorshid and Shayan cultivars was more withering and falling flowers at higher temperatures than Golestan cultivar. Golestan cultivar was more tolerant to salinity and heat stress than the other two cultivars. For this reason, it had more yield than Khorshid and Shayan cultivars and it seems to be a suitable cultivar for Khozestan. The effect of irrigation water quality treatments on fiber quality properties was not significant so that the highest strength with 26.84 was related to the date of the first planting (Feb.28), which did not differ significantly from the date of the second planting (March 29).. The effect of planting date on fiber strength at the level of 1% was significant. There was a significant difference between cotton cultivars in terms of strength and micronair at the 5% level. Shayan cultivar had the highest strength compared to the other two cultivars. The fiber strength of Golestan and Khorshid cultivars was statistically the same. Among cotton cultivars, Shayan and Golestan cultivars were significantly different from Khorshid cultivar at 5% level and had the lowest micronair. According to the results of this study, the first planting date on Feb 28 and intermittent irrigation with Karun water and drainage (combined) and Golestan cultivar is recommended for Khuzestan region.

Evapotranspiration plays an imperative role in management of regional water resources, climate change and agricultural production. In this study efficiency of some data-driven techniques, including support vector machine (SVM), artificial neural networks (ANN) and its hybrid with wavelet transform (WANN), multi linear regression (MLR) and decision tree (DT) for predicting Evapotranspiration rates at Scottsbluff Station in Nebraska have been monitored. For this purpose, 5 meteorological parameters utilized as inputs for the models. Daily meteorological information, data used in this study, were between 2005 - 2013 years to train and test the models. In order to implement each of the models 8 scenarios were considered according to combination of input parameters. For evaluate performance of the studied techniques, three different statistical indices were used which included root mean square error (RMSE), correlation coefficient (R) and Nash-Sutcliffe coefficient (NSE). In addition, Taylor charts were used to test similarity between observation and prediction data. The results showed that at the Scottsbluff station, WANN8 (is the eighth scenario for the WANN model) according to the root mean square error (RMSE), correlation coefficient (R) and Nash-Sutcliffe equal to 0.097, 0.999 and 0.999 performed better than ANN, SVM, MLR and DT. The SVM and ANN models also showed excellent accuracy, and the DT and MLR models performed worse than the other models despite their acceptable accuracy. As a conclusion, the results of the present study were proved that WANN provides reasonable procedures for modeling Scottsbluff at the Scottsbluff station.

Water is the source of life and the main building block of the universe, which is also the most consumed beverage in the world. Water contains various ions, such as nitrate, nitrite, fluoride, sulfate, chloride, calcium, magnesium, etc. Further, the type and amount of species in water might affect water quality and human health. Today, the high amount of nitrate in drinking water is one of the main public concerns in the health section. Therefore, World Health Organization (WHO) and National Standard Organization of Iran have set the permissible nitrate levels in drinking water at 45 and 50 mg/L, respectively. Nitrate removal from drinking water is necessary to ensure the supply of safe water and prevent the spread of various diseases affected by high amounts of nitrate. In the human body, nitrate has reduced to nitrites that are combined with hemoglobin, which then leads to the making of methemoglobin, which is deadly for babies. Long exposure to nitrate and nitrite leads to the formation of the carcinogenic compound nitrosamine. On the other hand, nitrate affects the size and function of the thyroid gland. Based on the initial quality of water, the level of application scale, the conditions of access to materials and equipment, the cost of the method, and the Type of application of water consumption, different methods are used for nitrification.To investigate the methods used to reduce or remove nitrate ions from water, a comprehensive study was conducted on the basis of reports and research of various scientists in the last two decades. The collected reports were categorized and the characteristics of each method were precisely evaluated separately. Then, the advantages and disadvantages of each method were compared with other methods presented. The most important methods for nitrate reduction are as follows: Ion exchange, Reverse osmosis, Adsorption, Electrodialysis, Chemical, and Biological method. Each of these techniques has its own advantages and disadvantages and different factors, such as economic explanation, industrial application, efficiency, selectivity, and lack of polluting the environment determine the selective method.Among the various methods, the ion exchange method is an effective, simple, relatively low-cost method to reduce the amount of nitrate in water that has good efficiency, especially for low volume water sources. This method involves passing water containing nitrate through a resin bed consisting of anion exchange resins in which the nitrate ion is exchanged with anions such as chloride and has a removal efficiency of more than 90%. In addition to salts and ions, the reverse osmosis method can remove suspended solids, organic matter, colloids, bacteria, and viruses. Generally, reverse osmosis units in the pressure range of 300 to 1500 psi might remove nitrate ions from water. In addition to the mentioned method, ease of execution and uncomplicated design have made adsorption a cost-effective method for nitrate removal. Furthermore, various chemical processes, including electrochemical reduction methods, are used to remove nitrate ions. In these methods, common reducing agents such as active metals, ammonia, borohydride, formate, hydrazine, hydroxylamine, hydrogen, and iron are used.The electrodialysis method purifies water by selectively removing undesirable ions through a semipermeable membrane. In this method, the reduction of nitrate concentration strongly depends on the applied current. The results showed that the optimal current of 20 volts and a concentration of 500 mM electrolyte leads to a significant increase in nitrate removal.The biological method of nitrate reduction is based on the use of nitrate-free microbes, which uses nitrate as the final electron receptor, organic and inorganic materials as electron donors, and energy sources as a way to maintain microbial growth. Bio nitrification is of two types: heterotrophic and autotrophic. The heterotrophic nitrification method is more economical than the autotrophic method on a larger scale and has the possibility of reducing nitrate to nitrogen gas with higher selectivity.The need to reduce or eliminate nitrate from drinking water to prevent various diseases in humans is an important factor in studying and updating nitrate removal techniques. In this study, an attempt was made to offer a variety of methods for nitrate removal, their mechanism, examples of studies, reflecting the properties, and finally, a brief comparison of methods, to provide a basis for studies to introduce and innovate in nitrate reduction techniques. An appropriate understanding of the features of the methods used will save time and cost, improve results, and observe the standards of the World Health Organization. After reviewing and comparing the studied methods, it would be stated that Ion exchange, Reverse osmosis and Electrodialysis are more efficient, compared with other methods, to remove nitrate from drinking water. High efficiency, being user-friendly, environmental considerations, and using at industrial scale are among the most favorable and common properties of these methods.

Wastewater treatment of steel industries as one of the most important and water-consuming industries is of high important, especially in terms of wastewater reuse. One of the most important and newest methods for industrial wastewater treatment is the coagulation and flocculation method, in which the efficiency of the process can be greatly improved by controlling various factors such as temperature, pH, retention time and coagulation concentration. In this study, the efficiency of polyaluminum chloride in removing the turbidity of simulated hot-rolled effluent of a steel plant was evaluated in the presence of independent variables of pH, stirring time, temperature, oil concentration and suspended solids. The experiments were performed by Design expert 8 software. To do so, the central composite design method was applied as the most common type of design in the response procedure method. The results showed that increasing the polyaluminum chloride coagulant to about 5 mg / l increases the turbidity removal efficiency, thus reducing the turbidity to less than NTU 20, which is a standard for water turbidity used in the rolling process. Increasing the temperature from 27 to 55 degrees has slightly enhanced the turbidity removal efficiency. According to the test design results, the best turbidity removal efficiency from the studied effluent (51 to 62%) was achieved at polyaluminum chloride of 1 mg / l, the amount of suspended solids of 1500 mg / l and the stirring time of 30 seconds. In this case, the range of turbidity removal efficiency was. The results showed that pH, temperature and oil content had the lowest effectiveness. Overall, the results of the present study indicate that the optimal addition of polyaluminum chloride to the effluent improves the effluent turbidity removal.

Groundwater quality is one of the most important aspects of hydro geochemistry, which discusses the chemical description of water, the spatial distribution of various chemical structures, the suitability of water for various purposes such as drinking, agriculture and industry. The purpose of this study is to investigate the characteristics and factors affecting the water quality of springs from the west of Rasht and in this regard, classification of springs based on the major anions and cations, to determine the quality of water in the region in terms of variables Physicochemical BOD, PH, Eh, Ec, TDS, major cations and anions and some trace elements, study of possible effects of geological units on the water quality of springs in the study area, detecting of physicochemical properties and quality of spring water in terms of drinkability, the study of water contamination in the study area based on the microbial indicators of Total Coliforms and Fecal ColiForm. Study areas is part of the Alborz zone and is situated between of 49˚ 17’ to 49˚ 30’ of Eastern longitudes and 37˚ 12’ to 37˚ 20’.

After Sampling, samples were sent to Rasht Science and Technology Park Laboratory for evaluating of physicochemical properties, measuring the concentration of anions and major cations, total hardness, heavy metals, total dissolved solids (TDS) and biochemical oxygen (BOD), acidity (pH), electrical conductivity (EC) and microbial studies. Element concentrations measured by atomic absorption spectrophotometry method using graphite furnace. Evaluation of the concentration of anions was conducted by titration and potentiometry. Aq.QA software according to the standard (WHO 2011) was used to analyze the data and the type of water and its quality. The quality of drinking water was assessed using Schoeller (1995), metal index (MI), and heavy metal pollution index (HPI). After evaluating the amounts of ions and chemical compounds in the water, we need to monitor and classify these amounts. Qualitative diagrams such as Piper, Stiff plotted by Aq-Qa software were used. Piper diagram is used for geochemical evaluation of groundwater flow system. The position of hydrogeochemical data of springs in the western region of Rasht on the Piper diagram indicates the presence of three different hydrogeochemical types including (Ca-Cl) type in Abbas Ali Faraj Poor spring, (Ca-HCO3) type in Abkar springs, Agha Seyed Javad tomb and Nazar Mhaleh spring and (Ca-SO4) type in the spring of Mohammad Ali Abbast. Due to the predominant type of water in the region, which is calcium bicarbonate and the predominant element in all springs (calcium), these waters have a constant hardness and the concentration of alkaline earth cations (Ca2 +) and weak acid anions (HCO3-) in them is higher than strong acid anions (SO4-). The Stiff diagram is used to assess water quality changes in a place and over a period of time. According to the Stiff diagram, the groundwater of the region is in the groups of calcium bicarbonate (M2, M5, M4 springs), calcium sulfate (M3 spring) and calcium chloride (spring M1), respectively. One of the criteria for classifying water in terms of drinking is the Schoeller classification. According to Schoeller classification in Abbas Ali Faraj Pour and Mohammad Ali springs water class (except for calcium which is bad) in all cases is in the good to acceptable range, and Abkar spring is in the category of unsuitable (for calcium) but in all other cases is in the category of good and acceptable, and the springs of Agha Seyed Javad tomb and Nazar Mahaleh (except for calcium which is drinkable in emergency situations) are in the good and acceptable category in terms of drinking. According to the Gibbs diagram, West Rasht springs are mainly located in the area where the rock process is predominant. This represents the interaction between the chemistry of the rock and the chemistry of the rainwater that has penetrated into the ground. To determine the level of pollution of water resources in terms of the presence of heavy metals, the Metal Index (MI) is used to assess the ability to drink and the Heavy Metal Pollution Index (HPI) to examine the effect of heavy elements on human health. According to the results, all MI springs are less than one and so drinkable. By calculating the Heavy Metal Contamination Index (HPI), none of the studied sources are contaminated with heavy metals.

The position of hydrogeochemical data of springs in the western region of Rasht on the piper diagram indicates the presence of three different hydrogeochemical types including type (Ca-Cl), (Ca-HCO3) and type (Ca-SO4) in the studied springs. The amount of TDS in the spring of Mohammad Ali Abbast (M3) is the lowest and the spring of the tomb of Agha Seyed Javad (M4) is the highest. According to the Stiff diagram, the groundwater of the region is abundant in the groups of calcium bicarbonate (and calcium sulfate and calcium chloride, respectively). According to Schoeller diagram, all the studied springs are in good to acceptable range in terms of drinking (except for calcium). Except for springs M1 and M5 with BOD more than 5 ppm (water purity is doubtful), other springs with BOD less than 5 ppm comply with Schoeller and 1053 standard of Iran and WHO and are pure water. Except for spring M3, which is free of coliforms due to fecal coliform feces, all other four springs have fecal origin water pollution and all springs have bacteria originating from sewage and are placed in unsatisfactory water class. According to Iranian standards, all springs are within the permitted range, but according to WHO, Abkar spring, except for chlorine ions, comply with other cases, and other springs comply with WHO standards and are within the permitted range.

Adding organic residues as biochar to the soil to improve its physical, chemical and biological properties is a new approach in the management of plant residues and organic wastes. Biochar is a carbon-rich porous material that has recently been added to soil as a modifier. Adding biochar to the soil, besides carbon sequestration in the soil, has many positive agronomic and environmental effects. In the studies, the researchers paid the most attention to the amount of biochar added to the soil. The aim of this study was to investigate the impact of wheat straw, vermicompost and apricot wood in different amounts and particle sizes on the average water infiltration rate and field saturated hydraulic conductivity.

Wheat straw, vermicompost and apricot wood were prepared at 330 °C. The effect of the mentioned biochars in the amounts of 0.5%, 1.5% and 3% and particle sizes of 0-0.5, 0.5-1 and 1-2 mm were evaluated in a factorial experiment with a randomized complete block design with three replicate. A control plot was also considered in each block.

The results showed that the effect of the studied treatments on iave and Kfs was significant. The iave had a significant increase in biochar treatments with medium and high amounts and large particle size compared to the control. Changes in biochar type, biochar amount and biochar particle size had a significant effect on iave and Kfs. The interaction effects of biochar type and biochar particle size, biochar type and biochar amount and biochar particle size and also biochar type and biochar amount in iave change contributed to 25.75%, 16.73% and 15.96%, respectively. In Kfs changes, the main effect of biochar amount and the interaction effects of the type of biochar and the amount of biochar and the size of biochar particles and also the amount of biochar and the size of biochar particles contributed 31.93%, 21.93% and 10.78%, respectively. In the studied biochars, depending on the type of biochar, the interaction effect of the amount of biochar and the size of biochar particles on the average infiltration rate was not the same. Among the treatments of wheat straw biochar, the amount of 3% and particle size of 1-2 mm, has the highest iave, which was not significantly different from the treatment of wheat straw at 3% and particle size of 0.5-1-1 mm. In vermicompost treatments in the amount of 1.5% and particle size of 1-2 mm particle size, the highest iave was observed, which was significantly different from the other values and particle size in that biochar. Among all treatments, the highest iave was in vermicompost biochar with an amount of 1.5% and a particle size of 1-2 mm. However, in apricot wood biochar, the highest average water infiltration rate was observed in the amount of 0.5% and particle size of 0.5-1. There was no significant difference with the average water infiltration rate in the amount of ٪ 1.5 and particle size of 0.5-1 mm of this type of biochar In all treatments, the highest iave (0.2615 m hr-1) was in vermicompost biochar with an amount of 1.5% and particle size of 1-2 mm. Comparison of the Kfs means in each biochar showed that in the wheat straw biochar treatments the highest Kfs is in the amount of 0.5% and particle size is 0.5-1 mm. At amounts of 1.5% and 3% of wheat straw biochar, the field saturated hydraulic conductivity of soil decreased with increasing biochar particle size. In vermicompost biochar, the highest Kfs was observed in the amount of 0.5% and particle size of 0.5-1 mm. In apricot wood biochar, the highest Kfs was in the amount of 0.5% and the particle size was 0-0.5 mm, which was not significantly different from Kfs in the amount of 1.5% and the particle size of 0.5-1 mm. In this type of biochar the lowest Kfs observed in the amount of 3% and particle size 0.5-0 mm. between all treatments, the highest Kfs (0.00256 cm sec-1) was observed in wheat straw biochar with an amount of 0.5% and a particle size of 0-0.5 mm. To obtain the desired result from the addition of biochar on the hydraulic properties of the soil, biochar should be designed with the appropriate amount and size of biochar particles.

Reuse of wastewater as an important and constant water resource for agriculture that as the world's largest water consumption has gained incredible attention. Wastewater contains a large number of microorganisms of which some can lead to microbial pollution for the environment. There are different management ways to reduce soil surface pollution such as using subsurface drip irrigation and some amendments. Subsurface drip irrigation could reduce the movement of pathogens in the soil. Moreover, Biochar is a carbon material that has gained more attention for removing various pollutions in soil. So, it is necessary to investigate water movement and distribution in conjunction with using tools and methods for preserving water in water scarcity situation and reducing subsequent problems of wastewater use in the soil. The main objectives of this study were (i) to assay the effect of irrigation management, different flow rates, and adding biochar into the soil on water distribution, under subsurface drip irrigation; and (ii) to validate the HYDRUS model for modeling distribution of water and its movement in different conditions in subsurface drip irrigation. The study was conducted in outdoor glasses’ lysimeters (70×60×17 cm) in the research farm of Shahrekord University, Shahrekord. First, the lysimeters' walls were treated with grease in order to prevent preferential flow along the walls. Then, the lysimeters were filled with air-dried clay loam soil. The dripper was installed at the depth of 20 cm below the soil surface. Treatments included two discharge drippers (Q2 and Q4), three levels of maximum allowable depletion (MAD) (30, 50, and 70%), and three application rates of biochar (0, 0.5, and 1%). Three irrigations were done for each lysimeter based on the defined MAD by polluted water containing fecal coliform bacteria. The soil moisture content in lysimeters was measured using a moisture meter device at different times including 1, 2, 4, 6, 8, 10, and 24 hr after ceasing irrigation. Also, the HYDRUS-2D/3D was applied for simulating water movement and soil moisture content in various treatments under subsurface drip irrigation. Water distribution and moisture content depends on flow rate and soil hydraulic properties. In the current study, the biochar was an amendment that changed moisture distribution in soil due to creating various soil hydraulic properties, and it was more effective than MAD. Additionally, biochar affected the soil water content of a clay loam soil at various matric suctions especially between saturated content and field capacity. However, the moisture content at the permanent wilting point of any biochar rates did not change significantly. The horizontal direction of the wetting front in treatments mixed with biochar was smaller than the control. Treatments with a smaller discharge rate (2 l h-1) created the higher wetted area; because those treatments delivered the total amount of irrigation water in a long time so water had enough time to distribute in soil, in comparison with treatments with higher discharge rate (4 l h-1). Also, the irrigation interval in the biochar amended soils was higher than the counterparts. For all times, a higher soil water content around the dripper was observed at a higher discharge rate. Also for all times and both discharge rates, downward soil water movement was greater than upward soil water movement because capillary forces are small compared with gravity forces, and it can be the main point for soil and human health. It should be mentioned that the amount of moisture in soil surface in treatments mixed with 0.5 and 1 % biochar was less than 0% biochar; however, there is no significant difference between all treatments. The lowest and highest moisture content on the soil surface was observed in Q2B1 and Q4B0 treatments, respectively. MAD 30% with reducing irrigation interval, decreased the moisture fluctuations in soil surface than MAD 50 and 70%. Moreover, HYDRUS-2D/3D has an acceptable ability in simulating spatial-temporal changes in moisture under subsurface drip irrigation. The R2 and RMSE ranged from 0.62 to 0.78 and 0.037 to 0.053, respectively. Overall, the addition of biochar into the soil can reduce the risk of soil surface pollution resulting from using wastewater due to less moisture in the soil surface in arid and semi-arid regions with water scarcity. The porous structure of biochar improves water holding capacity and decreases evaporation from soils. Also creating a bigger saturated zone, using drippers with high flow rates can be suitable for short root plants.