JWSS - Journal of Water and Soil Science

Phytoremediation is one of the best methods for cleaning heavy metal contaminated soils. In this method, tolerant plants with high absorption potential are used to clean up the pollutant. The purpose of this greenhouse study was to find the most suitable plants with the highest Zn translocation factor and shoot concentration. Soil samples were collected from zinc and lead Bama mine in Isfahan province, Iran. To compare the hytoextraction power, Heliantus annus.L., Thlaspi caerulescens, Trifolium pretense L. and Amaranthus retroflexus were planted in 8 kilogeram pots. The experiment was conducted in completely randomized design with three replications. After seventy days, plants root and shoot were harvested and Zn concentration was measured. The result showed that Thlaspi caerulescens had significantly higher root and shoot Zn concentration (3125 and 4041 mg kg-1, respectively). The highest bioaccumulation factor and translocation factor was observed in Thlaspi caerulescens. Based on this research, Thlaspi caerulescens was one of the suitable Zn hyper accumulators for cleaning up the Zn pollution.

The conventional application of nitrogen fertilizers via irrigation is likely to be responsible for the increased nitrate concentration in groundwater of areas dominated by irrigated agriculture. This requires appropriate water and nutrient management to minimize groundwater pollution and to maximize nutrient use efficiency and production. To fulfill these requirements, drip fertigation is an important alternative. Design and operation of drip fertigation system requires understanding of nutrient leaching behavior in cases of shallow rooted crops such as potatoes, which cannot extract nutrient from lower soil depth. This study deals with neuro-fuzzy modeling of nitrate leaching from a potato field under a drip fertigation system. In the first part of the study, a two-dimensional solute transport model (HYDRUS-2D) was used to simulate nitrate leaching from a sandy soil with varying emitter discharge rates and various amounts of fertilizer. The results from the modeling were used to train and validate an adaptive network-based fuzzy inference system (ANFIS) in order to estimate nitrate leaching. Radii of clusters in ANFIS were tuned and optimized by genetic algorithm. Relative mean absolute error percentage (RMAEP) and correlation coefficient (R) between measured and obtained data from HYDRUS were 0.64 and 0.99, respectively. Results showed that ANFIS can accurately predict nitrate leaching in soil. The proposed methodology can be used to reduce the effect of uncertainties in relation to field data.

Organic fertilizers affect soil chemical and physical properties, particularly chemical forms of zinc in soil solid phase and thereby improve soil Zn availability. The present field study was aimed to evaluate the effects of organic and chemical fertilizer (zinc sulfate) on different zinc fractions in soil solid phase of rhizosphere in two successive years in Rudasht Research Field, Isfahan. Treatments consisted of sewage sludge (5 and 10 t ha-1), cow manure (5 and 10 t ha-1), and ZnSO4 (40 Kg ha-1). The control had no added Zn. Three weeks after applying fertilizer treatments, Back Cross genotype of wheat was cultivated in each plot. Our results showed that the organic fertilizers increased Zn concentration in exchangeable fraction (EXCH-Zn), the organically bound Zn form (ORG-Zn), and Zn bound to iron and manganese oxides (FeMnOX-Zn). However, the changes in Zn fractions were dependent on the fertilizer type. Positive and significant correlation between EXCH-Zn, ORG-Zn, and FeMnOX-Zn, and the total Zn uptake by wheat indicated that these pools of Zn in solid phase are labile pools with a significant role in supplying Zn for plants.

In recent years, use of carbon-based adsorbents has increased in pollution reduction from aqueous solutions. Biochar is a carbon-rich porous material, with low costs, and environmentally friendly, which is prepared by pyrolysis of biomass. In this study, potential of rice husk biochar to desalinate irrigation water with EC of 5, 15 and 25 dS/m was investigated. The effect of pyrolysis temperatures of 400 (RHB4), 600 (RHB6) and 800 (RHB8) on selected physicochemical characteristics and their desalination power was considered. The results showed that pyrolysis temperature has a significant effect on biochar properties. RHB6 with 301.1 mg g-1 desalination capacity was more efficient than the other biochars. This adsorbent had maximum surface area (211 m2 g-1) and total pore volume (0.114 cm3 g-1). The results of this study could open new horizons to manage the agricultural wastes and simultaneously reduce the cost of irrigation water.

Management of organic and inorganic treatments may have positive or negative effects on soil quality, plant growth and human nutrition. The objectives of this study were to determine the effects of organic and inorganic zinc fertilizer application on soil quality indicators and wheat yield. This research was conducted at Agricultural Research Station Roudasht, Isfahan, Iran. Sewage sludge and cow manure (5 and 10 t/ha), ash rubber (1 t/ha), powder rubber (200 kg/ha), ZnSO4 (40 kg/ha) were applied and wheat was cultivated. Soil samples were collected at tilling and harvest stages. After taking samples and measurements of the soil parameters, we determined the critical limits for each category and class rating for the each soil parameters, and the soil quality index was calculated. The results showed sewage sludge and rubber ash were significantly effective in increasing soil bioavailable Zn compared to other treatments. Application of sewage sludge and cow manure at 10 ton/ha improved soil quality. The expanded soil quality index can help better understand the effect of fertilizers on soil. A positive and significant relationship between soil quality indicators and Zn uptake and wheat yields was also observed. Our results indicate that addition of 10 t/ha sewage sludge as fertilizer can significantly improve soil quality, supplying the necessary amount of Zn for wheat growth.

In this work, the effect of raw and modified bentonite and zeolite with trivalent iron on the stabilization of water-soluble and adsorbed arsenic in a calcareous soil was studied. Raw and modified bentonite and zeolite were added to the soil in different weights in a completely randomized block design with three replications and kept to field capacity soil moisture content of 80% for 8 weeks. The concentrations of water-soluble and adsorbed arsenic, water-soluble and absorbed phosphorus in soil and soil pH were measured. Treatments significantly affected the mobility of arsenic and phosphorus in soil. Raw zeolite and bentonite in different levels increased arsenic mobility (about 107 to 325 % and 259 to 350% respectively). Despite the change in surface properties of zeolites modified with iron, this treatment at different levels increased arsenic mobility in soils by about 124 to 246%. Bentonite modified with iron had the greatest effect on reducing arsenic mobility in soil (about 91%). Phosphate mobility was similar to arsenic in different treatments.

With the advent of advanced geographical informational systems (GIS) and remote sensing technologies in recent years, topographic (elevation, slope, and aspect) and vegetation attributes are routinely available from digital elevation models (DEMs) and normalized difference vegetation index (NDVI) at different spatial (watershed, regional) scales. This study explores the use of topographic and vegetation attributes in addition to soil attributes to develop pedotransfer functions (PTFs) for estimating soil saturated hydraulic conductivity in the rangeland of central Zagros. We investigated the use of artificial neural networks (ANNs) in estimating soil saturated hydraulic conductivity from measured particle size distribution, bulk density, topographic attributes, normalized difference vegetation index (NDVI), soil organic carbon (SOC), and CaCo3 in topsoil and subsoil horizon. Three neural networks structures were used and compared with conventional multiple linear regression analysis. The performances of the models were evaluated using spearman’s correlation coefficient (r) based on the observed and the estimated values and normalized mean square error (NMSE). Topographic and vegetation attributes were found to be the most sensitive variables to estimate soil saturated hydraulic conductivity in the rangeland of central Zagros. Improvements were achieved with neural network (r=0.87) models compared with the conventional multiple linear regression (MLR) model (r=0.69).

Transport of fluoride and consumption of groundwater with excess fluoride concentrations poses a health threat to millions of people around the world. The objective of this study was to simulate transport of fluoride (F) using HYDRUS-1D model. The study was conducted in lysimeters at Lavark research station site in Isfahan. The treatments consisted of two concentrations of F (157 and 315 mg kg-1). The duration of the study was 125 days. Some of soil physical and chemical properties, soluble F and total F concentration were determined during the study. The results showed the transport of F in calcareous soil profiles. This may be due to the high pH and desorption of F ion as a result of repulsion by the more negatively charged soil surfaces. The highest concentration of total F and water soluble F were observed in the 10 cm surface soil layer. The concentration of F decreased with increased soil depth. The correlation coefficient was significant between the water soluble fluoride and the total fluoride (1% level). Also, the difference between the observed t- value and a critical value on the t distribution is statistically insignificant. It showed that the model simulated successfully water soluble F concentration in the soil profile.

Arbuscular mycorrhizal fungi (AMF) are widespread endosymbionts in terrestrial ecosystems and their exudates have important effects on soil properties. A greenhouse experiment was conducted with six AMF treatments including four exotic species inoculums (Funneliformis mosseae ,Claroideoglomus claroideum  and Rhizophagus irregularis and a mixed isolate of three species), one mixed native AMF species treatment and a sterilized soil (control) with four salinity levels (1, 5, 10 and 15 dS m^-1). AMF increased the soil (EEG) and total (TG) extractable glomalin, and also the hot water (HWC) and diluted acid (DAC) extractable carbohydrates compared to control treatment in all salinity levels. The native AMF species had the greatest effects on EEG, TG, HWC and DAC at 10 and 15 dS m^-1. Soil EEG and TG concentrations were higher in the mixed exotic AMF treatment than in each AMF species. The greatest glomalin concentration was related to F. mosseae at 1, 5 and 15 dS m^-1 but at 10 dS m^-1 the greatest glomalin concentration was related to C. claroideum. The greatest carbohydrate concentration was related to F. mosseae at 1 and 5 dS m^-1 but at 15 dS m^-1 significant differences were observed among the three AMF species. Our results showed that there is an interaction between salinity and different AMF species, and a combination of them determines the function of AMF.

The sorption and desorption of fluoride by soil can play an important role in the transport of fluoride in soil. The study was conducted on the soil from Isfahan University of Technology research station site (two depths of 0-30 and 30- 60 cm). Fluoride sorption reactions were examined by equilibrating 0, 2.5, 5, 10, 25, 50 and 100 mg L^-1 NaF solution with soils for 23 hr. The desorption experiments were performed using 0.03 mol L^-1 NaCL solutions immediately following the completion of sorption experiments. The sorption isotherms of F were well described by the Langmuir and Freundlich models. The n values for Freundlich isotherm were 0.57 and 0.55 for two depths of the studied soil, respectively. The k_F values for Freundlich isotherm were 0.026 and 0.025 mg ^(1-n) Lⁿ g^-1 for two depths, respectively. Maximum monolayer sorption capacities (q _max) were obtained to be 0.4 and 0.35 mg g^-1 for 1 and 2 layers of the studied soil, respectively. The desorption isotherms of F were well described by the Freundlich model. The fitted model parameters’ (k_F and n) values for desorption branches were larger than these values for sorption branches. Also, the results showed a positive hysteresis (n_desrb sorb and k_desorb >K_sorb). It seems fluoride sorption to be reversible.

Petroleum pollution is an important environmental issue in most of the countries especially those have an oil industry. This study was conducted to investigate the effect of petroleum pollution on soil water repellency and its relation to soil structural stability in Bakhtiardasht area, Isfahan. Polluted and adjacent non-polluted locations were selected to be representative in the green space around the Isfahan Oil Refinery. Soil water repellency was assessed using water drop penetration time (WDPT) in the polluted locations. Soil sample with least aggregates disturbance were collected and selected soil physical and chemical properties were measured. Soil structural stability was evaluated using the wet-sieving method and mechanically dispersible clay (MDC) structural stability indices of mean weight diameter (MWD) and geometric weight diameter (GMD) of aggregates and MDC were then calculated. Results showed that the positive effect of petroleum pollution on the MWD and GMD become significant. Negative impact of petroleum pollution on MDC was also significant. Increment of total petroleum hydrocarbons (TPHs) increased the soil water repellency. A positive correlation was observed between soil water repellency and GMD. However, TPHs concentrations greater than 6.4% decreased the MWD and GMD presumably due to anionic repulsion between clay particles and hydrocarbon functional groups. Although greater water repellency increased soil structural stability in the polluted locations when compared to control locations, however, diminished water retention of polluted soil has created an unfavorable condition for the green space in the area.

Heavy metals are known to have deleterious effects on human health. The main route of human exposure to heavy metals is the daily intake of food. This study was designed to investigate the heavy metal concentrations (Cu, Zn, Mn, Fe, Cr, Ni and Cd) in soil and major food crops (wheat, potato and corn) and estimate the health risks of metals to humans via soil and the crops consumed in Hamedan Province, using the total non-cancer hazard quotient. Daily metal intakes were estimated for three receptor groups and then compared with health guideline values. The non-cancer risk estimations showed that chromium, manganese, cadmium, zinc, Iron, Nickel and copper have oral Hazard Quotient values less than a value of one. The Hazard Index values were greater than 1 for all age groups, suggesting that adults and children in the study area may experience a potential non-cancer risk due to diet of heavy metal via wheat, corn and potato consumption and soil ingestion. Consumption of plant foods particularly wheat was found to be the major route of human exposure to heavy metal. The soil ingestion route is also important.

Heavy metals in dust can directly enter to the human body through ingestion and inhalation. They can pollute the water and soil resources via atmospheric precipitation and accumulate in the plant tissues and then enter human body through water and food. This research aimed to study the heavy metals concentration in dust in Kermanshah province and to identify their sources. 49 samples of dust were collected in the cities of Kermanshah, Songhor, Gilangharb, Ghasre-Shirin, Sahneh, Sarpolzahab, Kangavar, Paveh and Javanrood during the spring 2013. The concentration of Zn, Cu, Ni, Cr, Mn and Fe were determined using an atomic absorption spectrometer following the sample extraction with a mixture of HCL and HNO₃ (3:1 ratio). The average concentrations of Zn, Cu, Ni, Cr, Mn and Fe were 182.3, 48.6, 115.3, 73.9, 428.1 and 23161 mg kg^-1, respectively. Correlation, cluster and principal component analyses were used to identify probable natural and anthropogenic sources of contaminants, and the enrichment factor was used to identify probable effects of human activity on the concentration of heavy metals. The results indicated that metal concentrations, except for Fe and Mn, were higher in comparison with the world soils. Zn, Cu, Ni and Cr are mainly of anthropogenic origin, while Fe and Mn are mainly of natural origin. Zn and Cu are mainly of traffic sources and partly of industrial sources, and Ni and Cr are mainly derived from industrial sources, combustion processes, combined with traffic sources. The analysis of EF revealed moderate enrichment for Mn and Cr, and significant enrichment for Zn, Cu and Ni. Based on the results of this study, more attention should be paid to identifying and controlling the sources of contaminants such as heavy metals in dust in order to prevent their associated pollution.

Pollutants are considered the disturbing factors of environment, and among them the heavy metals are more important considering their non-degradability and physiological effects on organisms in low concentrations. The goal of this research was to investigate the effect of industrial landuse on Cd and Pb concentrations in surface soils of the southwest Isfahan. According to satellite images and topographic maps (1:50000) of the study area, soil samples (depth: 0–20 cm) were collected using random sampling. A total of 38 surface soil samples were obtained from industrial areas (lowest distance = 1480 m) in the area of 73481 ha. Total concentrations of Cd and Pb in the digested solution were measured by Atomic Absorption Spectrophotometry (AAS). Using Arc GIS, the spatial distribution patterns and Cd and Pb variography of samples were analysed and finally the best models of spatial distribution of heavy metals were achieved. The primary results showed that the mean concentrations of Cd, and Pb of surface soil samples in industrial areas were 1.8 to 31.5 mg Kg^-1 higher than the world’s mean values, respectively. Although the mean concentrations of Cd and Pb were respectively 8 to 700 mg Kg^-1 lower than the standard of Iranian Department of Environment for industrial landuse.

Nitrogen use efficiency is relatively low in irrigated rice fields because of rapid N losses from ammonia volatilization, the nitrification, surface runoff, and leaching in the soil-flood water system. Since the plant N represents the total N supply of all sources, plant N status will be a good indicator of N availability to crops at any given time. Leaf colour chart (LCC) is a simple portable diagnostic tool, to determine the timing of N top dressing. LCC was developed to increase the N use efficiency at irrigated rice fields. A field experiment was carried out to compare the effect of N split application and LCC on the grain yield and agronomic and recovery efficiency of Fajr variety in 2009. The experiment was conducted in a randomized complete block design with 12 treatments in 3 replications on Fajr cultivar. Twelve treatments included control treatments (without nitrogen fertilizer) and 45, 90, 135 kg N ha^-1 for three times each and two treatments included LCC treatments 4 and 5. As a result, all treatments showed significant (p=0.05) grain yield increase in comparison to control. Increased yield was observed up to 135 kgN/ha (55.2%). Grain yield of LCC treatments was higher than split treatments. LCC treatment 5 had higher AE, RE, PE, PFP and IE than LCC 4 and fixed – 135 at the less N rate in all fields. Therefore, the results of different fertilizer treatments showed that the LCC treatment 5 with maximum grain yield, agronomic, physiological, internal and relative efficiency factors can be considered as the best management method for using nitrogen fertilizer and preventing from excess use of nitrogen fertilizer in Fajr cultivar.