JWSS - Journal of Water and Soil Science

Reflectance spectroscopy is a fast and safe method to predict soil physicochemical and biological properties in low cost ways. Traditional methods to determine soil properties require spending a lot of time and money so that farmers are generally reluctant to use the results of laboratory measurements in soil and water management. Reflectance spectroscopy in the spectral range of 400-2500 nm (VNIR) is an alternative method for estimating the soil properties. The aim of this study was to evaluate the results of laboratory spectrometer to estimate the concentration of Lead (Pb) and Nickel (Ni) in soils irrigated with water from treatment of urban sewage sludge of Rey city and finally to compare these results with the results of measurements of atomic absorption spectrometry. In this study, the Partial Linear Square Regression (PLSR) model was used to estimate the concentration of heavy metals and Residual Mean Square Error (RMSE) was used to evaluate the performance of this model. In this research, after spectral corrections related to elimination of the water absorption bands as well as elimination of the inefficient spectrum from heavy metals estimations, the methods of estimating these elements were studied through mathematical derivation of spectral values and also the acquisition of the continuum removal spectra. The results show that the estimated values from first derivate spectra are more consistent with the results of atomic absorption spectrometers.

Soil depth is a major soil characteristic commonly used in distributed hydrological modeling in order to present watershed subsurface attributes. It strongly affects water infiltration and accordingly runoff generation, subsurface moisture storage, vertical and lateral moisture movement, saturation thickness and plant root depth in the soil. The objective of this study is to develop a statistical model that predicts the spatial pattern of soil depth over the watershed from topographic and land cover variables derived from DEM and satellite image, respectively. A 10 m resolution DEM was prepared using 1:25000 topographic maps. Landsat8 imagery, OLI sensor (May 06, 2015) was used to derive different land cover attributes. Soil depth, topographic curvature, land use and vegetation characteristics were surveyed at 426 profiles within the four sub-watersheds. Box Cox transformations were used to normalize the measured soil depth and each explanatory variable. Random Forest prediction model was used to predict soil depth using the explanatory variables. The model was run using 336 data points in the calibration dataset with all 31 explanatory variables (18 variables from DEM and 13 variables from remote sensing image), and soil depth as the response of the model. Prediction errors were computed for validation data set. Testing dataset was done with the model soil depth values at testing locations (93 points). The Nash-Sutcliffe Efficiency coefficient (NSE) for testing data set was 0.689. The results showed that land use, Specific Catchment Area (SCA), NDVI, Aspect, Slope and PCA1 are the most important explanatory variables in predicting soil depth.

The use of plants and soil microorganisms is a promising technique for the phytoremediation of heavy metal-contaminated soils. This study was carried out in order to evaluate the soil microbial potential with four Cd concentration levels (0, 10, 30 and 100 mg kg-1); the study also addressed the inoculation of arbuscular mycorrhizal fungi (AMF) species (a mixture of Glomus species including G. intraradices, G. mosseae and G. fasciculatum) as well as plant growth promoting rhizobacteria (PGPR) (a mixture of Pseudomonas species including P. putida, P. fluorescens, and P. aeruginosa) with the Centaurea cyanus plant. The soil sample was spiked uniformly with Cd nitrate salt to create different Cd concentrations. The contaminated soils were then sterilized and subsequently inoculated with AMF and PGPR. The results indicated that with increasing the soil Cd concentration, colonization percent, abundance of rhizobateria, shoot biomass, and shoot relative biomass were significantly decreased, while the  proline content and the shoot Cd concentration were significantly increased (P≤0.05). The mean of Cd extracted in AMF and PGPR treatments was 1.8 and 2.8 and the translocation factor was 1.2 and 1.5 times higher, as compared to the corresponding control treatments, respectively. It could be concluded that microbial inoculation, in addition to improving plant growth, plays an important role in the Cd phytoremediation efficiency by plant.

Landfill sites are one of the most important sources of contaminant entry to the environment. In this research, the concentrations of Cu, Pb, Ni, Cd, and organic compound BPA in Hamadan landfill were evaluated to determine the status of its burial environment in 2014. Seven water samples (2 samples from spring and 5 samples from well), 2 leachate samples and 15 soil samples were collected from Hamadan landfill. Evaluation of the concentrations of Cu, Pb, Ni, Cd and the organic compound BPA was done by atomic absorption and gas chromatography with mass spectrometry. The concentrations of metals (Cu, Pb, Ni and Cd) in water samples (wells and springs) Pb <Cu <Cd <Ni, the leachate samples Cu <Pb <Ni <Cd and finally, the soil samples Cd <Cu <Pb <Ni, were obtained, respectively. Water samples (wells and springs), only in a 7W handheld water well sample (the nearest to the buried well) related to BPA 22.35 (μg /l) composition, waste leachate samples for the concentrations of BPA, 103.3 (μg /l), and soil samples for the combined concentration of BPA 5.52 (ng /g) were obtained. High concentrations of Ni, Pd and Cd and high concentrations of BPA in the samples of leachate composition, soil samples of landfill, and the 7W handheld water well samples were due to the high volume of electronic waste and plastic waste.
 

With the increase of population, the optimal use of water resources is necessary. This study was carried out to evaluate the impact of different levels of irrigation on the yield, yield components and water productivity of corn using single and double row drip irrigation systems (Tubes type). . The experiment was conducted in a split plot design based on the randomized complete block design (RCBD) with three replications in 2012 in Hajiabad, Hormozgan Province. The treatments were comprised of three levels of irrigation as the main plot (100, 80 and 60% water requirement) and two patterns of irrigating water pipe installation (normal and every other row) as a sub-plot of the design. The results showed that irrigating with the 80 percent water requirement, in comparison with full irrigation, increased the total yield by 1.4%, the seed weight by 1.8%, the number of seeds per row by 8.7%, and the number of seed row per maize by 13%. In spite of yield superiority in the pattern of normally irrigating water pipe installation (10055.56 kg ha-1), against every other row installation (9366.67 kg ha-1), water productivity was more in every other row installation (1.089 kg m-3). Therefore, partial root-zone drying   was recommended by the irrigation of    the 80% plant water requirement for the maize in the region.

Salinity adversely affects crops metabolism and yield. The present work was conducted to evaluate the singular and interaction influences of Arbuscular mycorrhizal (AM) fungi and brassinolide, as an active group of (brassinosteroids) BRs, on some physiological parameters of wheat plants to cope with salt stress14-day old mycorrhizal (Glomus mosseae) and non- mycorrhizal wheat (Triticum aestivum L.). Plants were foliar sprayed with 0 and 5 µM epibrassinolide 3 times once every two days. Then, each group was treated with 0 and 150 mM NaCl once every 3 days for 10 days. After salt treatment, some plants were harvested to estimate the leaf reducing sugar and glycine betaine contents. After the final growth, all wheat plants were harvested to measure some yield parameters. Synergistic influence of brassinolide and AM fungi was observed in protein and 1000-grain weight. It seemed that this was rooted in the increased accumulation of reducing sugars and glycine betaine, both helping to maintain osmotic potential in cells under high salinity in soil.

In this study, the distribution of heavy metals pollution including arsenic, antimony, nickel, copper, cadmium, cobalt, bismuth, lead and zinc in the stream sediments of Zarshuran- Aghdarreh area was investigated by using statistical techniques and the geometric integration of each sample basin. For this purpose, the degree of pollution in 154 stream sediment samples was analyzed and the distribution maps for enrichment factors were prepared by using a combination technique, pixel estimation, and statistical and geostatistical methods. The results of calculating the enrichment factors indicated that the higher enrichment was related to arsenic, antimony, bismuth, cadmium and lead. Furthermore, the concentration of zinc, copper, lead, arsenic, antimony, cadmium and bismuth in the stream sediment samples was higher than the global average. Application of the principal component analysis on the data led to the recognition of 9 main components for the dataset; the first 5 were components with eigen values greater than 1 and a cumulative percentage more than 85%. Arsenic, antimony, cadmium, lead and zinc in the first component, cobalt in the second component, bismuth in the third component, copper in the fourth component and nickel in the fifth component had the highest values.

The persistent scattering interferometry (PSI) technique is a valuable tool in displacements' monitoring of earth's surface. The persistent scattering interferometry (PSI) based on persistent scatterrer (PSInSAR) is one of the techniques used to reduce constraints (temporal and spatial incoherency). It is based on persistent scatterer and monitor displacement of only the pixels with timely-constant properties of scatterer. In order to detect and monitor landslides,  two time series SAR data sets including PALSAR ascending images from 2007 to 2010 and ASAR images from 2003 to 2010 with C-band and L-band wavelength were applied, respectively. Also, the PSI technique was implemented in a landslide near Noghol village, Padena, Semirom of Isfahan province. The results revealed  that both PALSAR and ASAR data set were efficient in identifying Noghol landslide. The results obtained  from ASAR and PALSAR images processing (with the values of 1253 mm and 1578 mm in two stages of time 4 and 7 years, respctively) were compared. The obtained vertical displacement's rate of the landslide by using ASAR data was more suitable because of its descending orbit. However, PALSAR images that indetified  more persistent scatterrer points were better in the  detection of the  landslide area. The results of GPS and PSInSAR techniques revealed that landslide displacement values and aspect were the same, confirming 135 centimeters of displacement to the  west aspect. Finally, a combination of radar data in two different passes provided the possibility of monitoring the mechanism of landslide and its movement direction.

The aim of this study was to evaluate the effect of increasing DEM spatial resolution on the assessment of the morphometric characteristics of waterways, as well as analysis and modeling of it by using RS and GIS techniques. In this study, which was carried out in the south of Darab city DEM 90 m (as one of the most usable data in waterway modeling), increase spatial resolution of DEM attraction algorithm in neighboring pixels with two models including: touching and quadrant neighboring models to estimate the value of sub-pixels. After manufacturing output images for sub pixels in 2, 3 and 4 scales with different neighborhoods, the best scale with the most appropriate type of neighborhood was determined using ground control points (270 points); then, the values of RMSE were calculated for them. The results showed that with using the Attraction model, the accuracy of the output of images was improved and the spatial resolution of them was increased. Among scales with different neighborhoods, 3 scales and quadrant neighboring model exhibited the most accuracy by the lowest value of RMSE for the DEM 90 meter. Evaluation of waterways morphometric features showed that DEM extracted from attraction algorithm had more ability and accuracy in waterways extraction, Extraction of morphometric complications, and information in the study area.

In recent years, with the excessive use of underground water resources in the Malayer Plain, the water level has dropped sharply and underground water resources, which serve as the main source of water supply for the agricultural sector and drinking, the city is facing a serious risk. Because of the relevance of each of the fields with other agricultural fields around, this study was done to show the potential effect of this problem on the welfare. So, in this study, the special econometric method was employed. The purpose of this study was to analyze the welfare of farmers and how it is affected by the exploitation of underground water resources. For this purpose, by using social welfare function, the effect of change in the value of groundwater level of social welfare producers was addressed. The necessary information was collected from 119 questionnaires carried out in 2015 .Moran's I statistics showed that the results of special regression method were better than those of Ols. The results of this study indicates a decline in the welfare loss of groundwater level and the continuation of the harvest of underground water resources would lead to a reduction in access to water and reduced production. The rate of change in return for the welfare of the reduction of every meter of underground water level to cultivate wheat and potatoes was 6983 and 7634 million Rials, respectively.

In the recent decades, dams have paradoxically been considered as a constraint and or a driving force of surface water conservation. On the other hand, dams have had a number of socio-economic and environmental impacts, the main reason for conducting the current case study on Shah-Qasem Dam in Yasouj, Iran, was to employ the survey field research through a questionnaire to assess the rural peoples’ viewpoint; this was done in four villages of the Southern Sar’roud County. Based on the (Cochran) formula, 192 individuals were relatively selected from each village. According to the findings, the most important impact of the dam was mainly economical (the average impact was between 2.37 and 3.7), whereas the least one was environmental (the average impact was between 1.81 and 3.54). Also, the results of the hypotheses’ analyses by means of 2 and Wilcoxon showed the following results: rise of the villages’ income, increase of the cultivated farms, increase in the employed individuals, enhancement of the cultivated crops, the regions production rising, improved tourism, lack of people’s participation in the decision making process, and reaming of the same plant varieties in the area, as compared with the pre-dam era. It is worth considering, however, that based on the statistical population used, this study was concerned mainly with the short benefits of the dam, rather than its long-term destructive ones.

Flow pattern around the bridge piers includes water surface profile, velocity profile, shear velocity, shear stress distribution, etc. In this research, the effects of the base shape along with scale effects on the flow pattern around the rectangular bridge piers were numerically calculated through "Fluent Software", using Horizontal Velocity Distribution (Vx) and Vertical Velocity Distribution (Vy) criteria. The results showed that in studying the horizontal component of velocity (Vx) for the rectangular bridge piers, the vortices activity radius was 8 times of the length of the pier, and the minimum channel width for vortices activity was 16 times of the length of the Bridge pier; also, the minimum channel length in front of the pier was 4 times of the length of the pier and behind which, it was 25 times more than the bridge pier. Finally, the minimum channel length for the vortexes activity was calculated to be 29 times more than the bridge pier length. Furthermore, for the vertical component of velocity, the flow pattern around the base of the bridge cannot be an appropriate parameter for checking the effects of the length and width of the channel.

Regionalization is one of the useful tools for carrying out effective analyses in regions lacking data or with having only incomplete data. One of the regionalization methods widely used in the hydrological studies is the clustering approach. Moreover, another effective factor on clustering is the degree of importance and participation level for each of these attributes. In this study, it was tried to use a broad range of attributes to compare their performance in regionalization. Then, according to the importance and role of each attribute in regionalization, the appropriate weight for each of the attributes in each category was determined using the principal component analysis (PCA) method, and the effect of this weighting in forming the homogenous regions was investigated by the Ward's clustering method. In this regard, the maximum 24-hour rainfall data of 63 meteorological stations located in Urmia Lake Basin (ULB) was used in this study during a time period of 30 years (1979-2008). Furthermore, seven categories of attributes were defined in order to regionalize the rainfall. The results showed that by considering different attributes and combining them with each other, a different clustering is obtained in each category in terms of the number of clusters and stations. Among seven categories of attributes, it was found that the geographical and climatic-geographical categories of attributes showed a more appropriate clustering over the ULB. Additionally, the weighting of attributes could have more effect on improving homogeneity and forming the independent clusters in most cases in terms of the scattering of station and how to locate over the basin.

Quantitative description of the spatial variability of soil hydraulic characteristics is crucial for planning, management and the optimum application. Field measurement of infiltration is very expensive, time-consuming and laborious. Soil structure also important effects on water infiltration in the soil. The objectives of this study were to determine the spatial variability of water infiltration, to select the most appropriate infiltration model, to calculate the parameters of relevant models, and to quantify the soil structure by using the fractal geometry. Infiltration parameters were estimated by using some physical soil properties, as well as fractal parameters, in this research. To achieve these purposes, 161 sites were selected and their infiltration was measured by using the constant head double-ring infiltrometers method in a systematic array of 500*500 m. The observed infiltration data from all examined sites were fitted to three selected infiltration models. Soil bulk density (BD), soil water content, soil particle size distribution, soil aggregate size distribution (ASD), organic carbon content (OC), saturation percentage (SP), soil pH and electrical conductivity (EC) were also measured in all 161 sites. For the quantitative assessment of soil structure, the aggregate size distribution, fractal parameters of the Rieu and Sposito model as well as the mean weight diameters (MWD) and geometric mean diameter (GMD) were also obtained. The obtained results indicated that the infiltration rates of the studied areas had generally low basic infiltration rates (1.1-31.1 cm hr^-1) for most sites with the average of 6.69 cm hr^-1. According to all obtained results and based on the least-square method, the Philip model was selected as the best performing model to account for infiltration. The aggregate size distribution demonstrated a fractal behavior, and the infiltration parameters could be significantly correlated with the fractal parameters and other soil physical properties.

Channels and surface water are ways for the transfer of pollutants to the environment and human. When any pollutant is spilled into the channel, the pollutant concentrations are decreased after the travel. Reducing the distance is an engineering expedient. To reduce the distance, mixing in water should be increased. Thus, the main goal of the present study was to investigate the effect of the triangular vane on transverse mixing used for control bank erosion. Experiments were carried out in an 80cm width flume. The vane, which was triangular, was made of Plexi-glass with a 30% width of the flume length, 15cm height and 50cm far from the tracer injection. Salt solution was used as the soluble tracer. The experiment was carried out to investigate the effect of the triangular vane for two conditions: with and without vane. The transverse mixing (e_z) and complete mixing length were estimated for the two conditions of with and without vane. The results showed with installing the triangular vane, the transverse mixing was increased up to 2.5 and the length of mixing was decreased by 60%, as compared with the tests of no vane.

Catchment prioritization in terms of natural disaster intensity as well as prevention and control practices plays a main role in the natural resources and watershed management. In this study, a total of 24 sub-catchments in the Zohreh-Jarrahi basin were prioritized according to their morphometric parameters and using the mixed model of TOPSIS-Multivariate regression. A total of 12 morphometric parameters including constant component of channel maintenance, drainage density, ruggedness number, infiltration index, stream power index, stream frequency, slope, drainage texture rate, relief rate, form factor, bifurcation ratio and topography wetness index, in addition to rainfall, were studied and scored. Parameters were weighted by using multivariate regression and the spatial distribution of the observed flood events. TOPSIS model was used for the prioritization process. The results obtained from the weighting analysis showed that the ruggedness number, slope and rainfall had the highest effect on flooding in the study area with the score of 0.068, 0.024, and 0.016, respectively. According to the prioritization results, sub-catchments of Seidoon, Emamzadeh Jafar, and Takht Deraz, which had the minimum distance to the positive optimum (0.0028, 0.0029, and 0.0029, respectively) and the maximum distance to the negative optimum (0.0097, 0.0098 and 0.0095, respectively), showed the highest flooding intensity with the score of 0.7745, 0.7690 and 0.7625, respectively. In order to validate the results, prioritization results were compared to the observed flood events. Validation results also indicated the efficiency of the mixed model in delineation of catchments prone to flooding. Three sub-catchments of Seidoon, Emamzadeh Jafar and Takht Deraz were observed to have the highest number of observed flood events, thereby showing the high effectiveness of the model and also, the role of the morphometric parameters in flooding.

Land use/cover maps are the basic inputs for most of the environmental simulation models; hence, the accuracy of the maps derived from the classification of the satellite images reduces the uncertainty in modeling. The aim of this study was to assess the accuracy of the maps produced by machine learning based on classification methods (Random Forest and Support Vector Machine) and to compare them with a common classification method (Maximum Likelihood). For this purpose, the image of the OLI sensor of Landsat 8 for the study area (Sattarkhan Dam’s basin in the Eastern Azerbaijan) was used after the initial corrections. Five land uses including urban, irrigated and rain-fed agriculture, range and water body were considered. For conducting the supervised classification, ground truth data were used in two sets of educational (70% of the total) and test (30%) data. Accuracy indexes were used and the McNemar test was employed to show the significant statistical difference between the performances of the methods. The results indicates that the overall accuracy of Support Vector Machine, Random Forest, and Maximum Likelihood methods was 96.6, 90.8, and 90.8 %, respectively; also the Kappa coefficient for these methods was 0.93, 0.81 and 0.83, respectively. The existence of a significant statistical difference at the 95% confidence between the performances of the Support Vector Machine algorithm and the other two algorithms was confirmed by the McNemar test.

Flood discharge estimation with different return periods is one of important factors for water structures design and installation. On the other hand, a lot of rivers existing in Iran watersheds have no complete and accurate hydrometric data. In these cases, one of the suitable solutions to estimate peak discharges with different return periods is the regional flood analysis. In this research, 55 hydrometric stations were used. For this purpose, at first, peak discharges in different return periods were estimated using the EasyFit software. Then, the effective variables on the peak discharges were collected and the input variables of the models were selected by using gamma test with the help of the WinGamma software. Finally, data modeling was performed using the support vector machine, artificial neural networks and nonlinear multivariate regression techniques. Quantitative and qualitative assessment of the results using various indices including Nash-Sutcliffe Efficiency Coefficient (NSC) showed that SVM modeling method had the most accuracy in comparison to the other two modeling methods to predict the peak discharges in the Namak Lake Watershed.

Long-term use of treated wastewaters for irrigation adds compounds and/or ions to soils which might alter the soil physical, hydraulic and mechanical properties. Soil mechanical properties are closely linked with the plant growth. This study was conducted to investigate the effect of short-, mid- and long-term applications of the treated wastewater of Mobarake Steel Company in Isfahan on the soil penetration resistance and shear strength in the company green space. Soil penetration resistance and shear strength were measured using a pocket penetrometer and in situ shear box, respectively. The results showed that soil penetration resistance (i.e. soil hardness) at both dry and wet conditions significantly was increased upon short-, mid- and long-term applications of wastewater; 19 years of the application of wastewater resulted in the highest soil penetration resistance at wet condition, but the well water did not significantly affect it. Surface crust in the non-irrigated locations increased the soil penetration resistance, but the irrigated sealed soils were not significantly different from the virgin soil in terms of dry and wet penetration resistances. For the soil shear strength parameters, wastewater, well water and surface crust did not significantly affect soil cohesion (c), they but significantly affected the angle of internal friction (φ). Overall, soil shear strength parameters were not greatly affected by the irrigation water treatments because of the dominant effect of the soil fractions (texture and gravel content) and the microstructure.