JWSS - Journal of Water and Soil Science

Saturated hydraulic conductivity (K_s) is one of the most important soil physical characteristics that plays a major role in the soil hydrological behaviour. It is mainly affected by the soil structure characteristics. Aggregate size distribution is a measure of soil structure formation that can affect Ks. In this study, variations of K_s were investigated in various aggregate size distributions in an agricultural soil sample. Toward this aim, eight different aggregate size distributions with the same mean weight diameter (MWD= 4.9 mm) were provided using different percentages of aggregate fractions consisting of (< 2, 2-4, 4-8 and 8-11mm). The Ks values along with other physicochemical properties were determined in different aggregate size distributions. Based on the results, significant differences were found among the aggregate size distributions in K_s, particle size distribution, porosity, aggregate stability, electrical conductivity (EC), organic matter and calcium carbonate. The aggregate size distributions with a higher percentage of coarse aggregates (4-8 and 8-11 mm) also showed higher K_s as well as clay percentage. A positive correlation was also observed between Ks and clay, aggregate stability and EC, whereas sand showed a negative correlation with K_s. No significant correlations were found between K_s and silt, porosity and organic matter. Further, multiple linear regression analysis showed that clay and aggregate stability were the two soil properties controlling K_s in the aggregate size distributions (R²=0.80, p<0.01). Aggregate stability was recognized as the most important indicator for evaluating the K_s variations in various aggregate size distributions.

Nowadays, acid rain serves as one of the most serious environmental problems has affected many regions in the world. This phenomenon is characterized by many environmental impacts, such as soil contamination and degradation. Acid rain immediately affects soil, causing soil particles to breakdown and be dispersed; this is the first step to initiate the soil erosion. Therefore, in this study, the effect of different pH levels of acid rain (at different levels) on the soil splash was investigated under laboratory conditions using a rain simulator and a cup splash. In the experiments, acid rains, with the pH values of 3.75, 4.25, 5.25 and normal rains at three intensities of 40, 60 and 80 mmh^-1, were studied; finally, a number of 36 samples were taken for statistical analyses. SPSS 23 and EXCEL 2013 software and one way and two-way ANOVA were used for the statistical analysis at a confidence level of 95%. The results showed that at the intensities of 40 and 60 mmh^-1, the splash rate was significantly different in all pH treatments, and the acid rain with pH of 3.75 showed the highest splash rate. However, no significant difference was found at the rain intensity of 80 mmh^-1, despite the higher splash rate at the pH of 4.25 and 5.25 treatments. Also, the results of the comparison of the means showed that the soil splash rate was also increased with enhancing rain intensity. Finally, the two-way ANOVA test showed that the simultaneous interaction effects of the two factors of pH and rain intensity on soil splash was not significant.

Soil water retention curve (SWRC) reflects different states of soil moisture and describes quantitative characteristics of the unsaturated parts of the soil. Direct measurement of SWRC is time-consuming, difficult and costly. Therefore, many indirect attempts have been made to estimate SWRC from other soil properties. Using pedotransfer functions is one of the indirect methods for estimating SWRC. The aim of this research was to assess the effect of using soil particles percentage in comparison with the geometric characteristics of soil particles on the accuracy of the pedotransfer equations of SWRC and the critical point of it. Accordingly, 54 soil samples of Isfahan province from seven texture classes were used. The most suitable functions for estimating SWRC, parameters of van Genuchten and Brooks-Corey equations, and the critical point of SWRC were selected based on statistical indices. The results indicated that the pedotransfer equations fitted the SWRC data well and the outputs from them were in a good agreement with the independent (validation) SWRC data. The results revealed that using soil particles percentage (sand and clay), bulk density and organic matter content in the point estimation of SWRC was better than applying geometric properties of the soil particle diameter. On the other hand, in the estimation of parametric and critical point of SWRC, using the geometric properties of soil particle diameters resulted in more satisfactory results, as compared with using the soil particles percentage. The NRMSE values indicated that the accuracy of the pedotransfer equations in the lower matric head was greater than that of the higher matric head.

Nowadays, the Beerkan computational algorithms (BESTslope and BESTsteday) are known as the suitable indirect methods for estimating soil saturated hydraulic conductivity (Ks) and sorptivity (S), as well as the scale parameter (hg) in van Genuchten soil water retention equation through the data collected in the Beerkan infiltration experiment and other required data. The purpose of this study was to compare these algorithms in estimating Ks and S, as well as the soil water content corresponding to the suctions of 33 kPa, 100 kPa, 200 kPa, 300 kPa and 1500 kPa. For this purpose, a total of 40 Beerkan infiltration experiments were carried out in Sistan dam research field. From all Beerkan experiments, 30 tests in loam and sandy loam textures having a relative error less than 5.5% (Er <5.5%) were selected for further analysis. The statistical criteria RMSE, ME and ωr2 were used to compare the measured and estimated water content values at each suction. The results showed that the BESTsteday algorithm, which had a more simple calculating process than the main algorithm (i.e. BESTslope), could provide the Ks and S values and the soil water content of the near field capacity with an acceptable accuracy. The model performance in estimating water content corresponding to the 1500 kpa suction head (i.e. _θfc) was not acceptable for both algorithms. Moreover, the relative error of estimating soil water content (Er(_h,θ)) was decreased gradually by an increase in clay %.

One of the management practices to reduce the harmful effects of chemical fertilizers and to protect soil and water resources is applying a combination of organic and chemical fertilizers that can better than using them separately. Therefore, in order to understand and identify the effectiveness of this management practice, it is necessary to examine runoff and sediment production. This study was carried out in an agricultural sloping land located in the North of Iran, near Sari city. For this purpose, runoff measurement plots of 1 × 5 m were set up under natural rainfall based on a randomized block experimental design. Soil samples were measured at 0-10 and 10-20 cm depths. In this study, parameters such as runoff (volume, nitrate content, sediment yields), soil physical features (porosity and infiltration coefficient), and soil chemical properties (EC, OC, N, CEC, pH) were measured. The results showed that among soil chemical and physical properties, just N, EC and pH significantly influenced the Municipal Solid Waste Compost. A PCA was carried out, showing that these treatments explained 74.35% of the total variance of the results. Accordingly, it could be stated that using soil and water conservation management practices can rapidly significantly improve the soil properties in the sloping lands.

Location of soil moisture sampling in irrigation management is of special importance due to the spatial variability of soil hydraulic characteristics and the development of root system. The objective of this study was determination of the suitable location for soil moisture sampling in drip-tape irrigation management, which is representative of the average moisture in the soil profile (θ_avg) as well. For this purpose, soil moisture distribution (θ_ij) at the tassel stage of maize and one irrigation interval (68-73 day after plant) were measured at the end of season. The results showed more than 70% length of the root of plant was located in 30 cm of the soil depth. By accepting ±10% error in relation to the averaged soil moisture, some region of soil profile was determined which was in the acceptable error range and also near the averaged soil moisture (0.9θ_avg<θ_Rec<1.1θ_avg). By overlapping θ_Rec in one irrigation interval, the appropriate location for soil moisture sampling was the horizontal distance from drip-tape line to 20 cm and the depth of 10-20 cm from the soil surface. To determine the appropriate place for soil moisture sampling, the development of root system and the maximum concentrated root length density in the soil profile extracting the maximal soil moisture should be taken in to account, parallel with the averaged soil moisture.

The aim of this study was to evaluate the spatial distribution of soil infiltration using geostatistics methods in a regional scale on 400 hectares of Mansour Abad Plain, in Larestan region, Fars Province. Sampling and parameters measurement were done for 78 points in a regular grid with a distance of 100*100 meters; for these variables, the best variogram model between linear, exponential, Gaussian and spherical models with the highest R2 and the lowest error was determined using GS+ and ArcGIS software. In this study, soil infiltration (cm/min) using the double ring method and some other soil properties including soil electrical conductivity (dS/m), pH, saturation percentage (%SP), particle size percentage (sand, silt and clay), and calcium (meq/lit), magnesium (meq/lit), sodium (meq/lit) were measured and determined. The spatial distribution of Kostiakov and Philip models parameters and theri zoning were determined using the geostatistic method. The results showed that, among different soil properties, the final infiltration rate had a high degree of variability in the study area, and the decision was based on the usual averaging methods, which could have a lot of error. Among applied infiltration models, Kostiakov model and Philip model were the best empirical and physical infiltratin models, respectively, in the studied area. The best semivariogram model for the steady state infiltration rate was Philip model, with the coeficients of S and A, and a coefficient of Kostiakove model was gaussian; for the b coefficient, Kostiakove model was exponential. Spatial structure of the final infiltration rate, a and b coefficients of Kostiakove model, and S and A coefficients of the Philip model, was strong. The best interpolation method for the final infiltration rate was cokriging with the cofactor of silt percentage, for the S coefficient of Philip model was inverse distance weighting (IDW); for a and b coefficients of Kostiakove model, kriging and IDW were suitable, respectively.

A significant amount of the oil meal is produced annually in the oil industry. Oil meal addition into the soil can improve the soil organic matter and micronutrients concentration. This study was conducted to investigate the effect of olive, sesame and black cumin meal (0, 2 and 5 g 100g^-1 soil) on the soil Cu, Zn and Fe concentration in saline and non-saline soils by a greenhouse experiment. The soil basal respiration, organic carbon, carbohydrate and DTPA extractable Cu, Zn and Fe concentration were measured after 60 days of incubation. The results showed that the greatest organic carbon and carbohydrate content were observed in olive and black cumin treatments and the lowest was observed in the sesame treatment. Using oil meal in the soil improved the micronutrient concentration, as compared to the control treatment. Sesame meal had the greatest effect on the DTPA extractable Cu and Zn concentration increment. The DTPA extractable Fe concentration was the highest in the sesame treatment and the lowest in the black cumin one. In addition, salinity decreased the DTPA extractable Fe and Zn concentration, as compared to the non-saline soil. As the conclusion, oil meal incorporation in to the soil improved the soil organic carbon and micronutrient concentration. However, their effect depends on the meal quality and soil salinity.

Due to unsuitable soil physical conditions, calcareous soils, and the existence of a huge amount of sulfur in the country, the study of sulfur effects on the soil structure and other soil properties is necessary. Therefore, the effects of different rates of sulfur including: 0, 750, 1500 and 3000 kg/ha, when accompanied by Halothiobacillus neapolitanus bacteria, on the soil properties in the corn-wheat rotation in two years were investigated. Parameters of soil pH, EC, sulphate, organic carbon, soil structure and wheat yield were measured. For the quantification of soil structure and quantity evaluation of sulfur effect on the soil structure, with measuring the aggregate size distribution, the mean weight diameter (MWD) and geometric mean diameter (GMD) of the aggregate indices, and the amounts of fractal dimension were determined. The r results indicated that with the progress of the experiment and further application of sulfur along with thiobacillus bacteria, aggregation and aggregate stability were increased. The effect of sulfur treatments on MWD and GMD was significant; based on quantification indices, it had 28 percent positive effect on the soil structure. Sulfur with 3 percent reduction of fractal dimension had a significantly positive effect on the soil structure. Application of sulfur decreased a small amount of soil pH and increased 12 percent of the soil EC and 40 percent of the soil sulphate. So soil structure improvement and reclamation of soil physical condition can be very effective on the soil conservation and sustainability of the production resources and the conservation of environment.

One of the important elements in mechanized irrigation is to know the relation between suction force (matric force) and soil moisture, which is referred to as moisture curve. The shape and coefficients of this curve are influenced by the texture and structure of the soil and can change with soil structure modification.  The most important goals of this study were to evaluate the effect of using zeolite on water holding capacity and coefficients of moisture curve patterns of two sandy and loamy soil texture, the effect of using zeolite on the shape and soil moisture curve coefficients based on various models, some of them so far in Iran, zeolite was added to soils at levels of consumption (2, 5 and 10%). The moisture content of each soil was determined at various points in 12 points using a Dicagon machine.  Soil moisture curve coefficients using software and fittings of six Brooks and Corey models, Kosugi, Durner, Fredlund and Xing,  VanGenuchten and Seki. The results indicate that in all models, the parameter value increases with the use of zeolite and increase the level of use. Water storage capacity also increases with the use of zeolite.  Other results showed that the best model for estimating the moisture curve of laryngeal and sandy soils of the Darren model is weakest and the weakest models in the lush soils of the broccoli model and Kasughi model and in the sandy soil of the Brooksouli model Blindness and model-gnuchten Shand.

In this study, the effect of some soil parameters on the life forms and total aboveground net primary production (ANPP) in meadow rangelands in Fandoghlou region of Namin county in Ardabil Province were investigated. ANPP in 180 plots of 12 by harvesting and weighting method were measured. Eighteen soil samples were collected along transects. Some physical and chemical attributes of the soil were measured by standard methods. The relationship between these parameters and ANPP was performed using multivariate regression (enter) method. To determine the effects of important soil parameters on ANPP variation, principal component analysis (PCA) was used. The results of regression analysis showed that electrical conductivity (EC), magnesium (Mg), spreadable clay (WDC), volumetric moisture content (VM), organic carbon (OC), soluble potassium (KS), exchangeable potassium (Kexch), sodium (Na) and phosphorus (P) were the effective parameters on the life forms and total ANPP (p<0.01). The accuracy of obtained equations for grasses, forbs and total ANPP were calculated 79, 76 and 70%, respectively. Moreover, results of PCA showed that soil parameters justify 84.52 percent of total ANPP variation and in comparison, with regression results with 28% it provides better results.

The using of soil conditioners to water and soil conservation is essential and also, the effect study of soil moisture on the soil conservation process and its role on changing runoff, soil erosion and sediment yield is necessary for understanding and simulating the hydrologic response of soil. Therefore, the present study was carried with the aim of investigating the effect of biochar with amount of 1.6 t ha-1 on the components of  time to runoff, runoff volume, runoff coefficient, soil loss and sediment concentration in different soil moisture including air-dried, 15, 20 and 30 percent with three replications in plot scale. The results showed that after application of biochar conditioner, time to runoff compared with control treatment at soil moistures of air-dried of 15, 20 and 30 percent happened later 66.66, 186.6, 150.5, and 475.47 respectively. The results also showed that the runoff volume at soil moistures of air-dried of 15, 20 and 30 percent decreased 44.49, 55.65, 36.47 and 41.08 percent, respectively, and the runoff coefficient reduced 55.71, 66.39, 48.44 and 37.82 percent, respectively. The adding biochar caused the decreasing soil loss with rates of 91.19, 85.055, 85.63 and 88.066 percent, respectively, and the sediment concentration with amounts of 84.19, 66.53, 76.57 and 79.59 percent, respectively. Also the results showed that the changes of soil moisture had the significant effect on changing the time to runoff, runoff volume, and soil loss and sediment concentration in level of 99 percent.

Use of the curve gradient of the Soil Water Retention Curves (SWRC) in the inflection point (S Index) is one of the main indices for assessing the soil quality for management objectives in agricultural and garden lands. In this study Anneling Simulated – artificial neural network (SA-ANN) hybrid algorithm was used to identify the most effective soil features on estimation of S Index in Jiroft plain. For this purpose, 350 disturbed and undisturbed soils samples were collected from the agricultural and garden lands and then some physical and chemical soil properties including Sand, Silt, Clay percent, Electrical Conductivity at saturation, Bulk Density, total porosity, Organic Mater, and percent of equal Calcium Carbonate were measured. Moreover, the soil moisture amount was determined within the suctions of 0, 10, 30, 50, 100, 300, 500, 1000, 1500 KP using pressure plate. Then, the determinant features influencing the modeling of S Index were derived using SA-ANN hybrid algorithm. The results indicated that modeling precision increased by reducing the input variables. According to the sensitivity analysis, the Bulk Density had the highest sensitivity coefficient (sensitivity coefficient=0.5) and was identified as the determinant feature for modeling the S Index. So, since increasing the number of features does not necessarily increase the accuracy of modeling, reducing input features is due to cost reduction and time-consuming research.

Soil water content is the most effective factor associated with the hydrophobic and hydrophilic changes in a soil. Water repellency in soils, is not a permanent feature; it can be reached in the dry season and reduced or eliminated in the wet season It can be said that in terms of moisture, there is a critical region that is defined as the threshold moisture content, where in lower moisture, the soil is repellent and in higher moisture, the soil is wet able. The purpose of this study was to investigate soil moisture variations on degree of hydrophobicity and determine the amount of threshold water content in soil samples of wetland around Shahr-e-Kord. In this study, some samples of Shahr- e-Kord wetland were investigated. After determining the initial moisture content of the soil, the soil hydrophobicity conditions were determined by determining the time of water droplet penetration (WDPT). Soil moisture variations were carried out using soil wetting and drying method, and in each step the soil hydrophobicity conditions were tested. Reducing water content in soil samples, led to a change in the degree of hydrophobicity in hydrophobic samples, in one soil hydrophilic soil sample, Reducing water content changed hydrophilic soil to hydrophobic soil. The threshold water content was also observed up to a maximum of 54% volumetric water content at a given point. Based on this, the higher moisture content of the threshold at this point indicates the higher soil potential for runoff generation. Soil analysis showed that soil organic matter had a positive correlation with threshold water content.

Furrow irrigation is the most common method of surface irrigation. However, the accurate estimation of the soil water infiltration equation is the most important challenge for evaluating this method of irrigation. In this study, a fast and simple method that is named soil intake families and presented by USDA-NRCS (RSIF), evaluated for estimation of the Kostiakove-lewis infiltration equation parameters based on soil information. Also, this method was developed based on irrigation condition and considering soil characteristics (D-RSIF). Two treatments including constant and variable inflow discharge were tested with 4 repetitions and different irrigation phases including advance, storage and recession were simulated by developed Zero-Inertia model using RSIF and D-RSIF methods. The results showed that using the zero- inertial model, the difference between simulated advance times and simulated runoff were significant at 5% level for D-RSIF and RSIF methods. For variable inflow discharge, the error of estimating runoff volume was 10%, 6%, 12% and 41% for RSIF, D-RSIF, multilevel calibration and two-point methods respectively. Also, the irrigation scheduling error, based on soil physics characteristics (RSIF) was 14% that means consuming water more than required.

Rainfall erosion is the first type of water erosion on the land which is affected by various factors such as land use change and previous rainfall. This study was carried out to investigate the influence of previous rainfalls on the process of rainfall erosion in two marl soils (pasture and that changed to agriculture) under the simulated rainfall. Toward this goal, aggregate samples with the diameters of 6 to 8 mm were randomly collected from the marl areas in the west of Zanjan. Soil aggregates were packed into 48 boxes with the dimension of 30×40 cm to examine the effects of eight rainfall durations with three replications. Eight simulated rainfalls with the duration of 0, 7, 14, 21, 28, 35, 42 and 49 min and a constant intensity of 40 mm h^-1 were used in the experiment. The soils were exposed to another simulated rainfall with 40 mm h^-1 in terms of intensity for 15 min to study the rainfall erosion processes. The results showed that the aggregate breakdown was significantly affected by the previous rainfalls in the pasture soil (P<0.01), while there was no significant difference among the previous rainfalls in the case of agriculture soil.  Soil compaction and particles splash were significantly affected by previous rainfalls (P<0.05). Aggregate breakdown and particles splash were 1.41 and 1.31 times bigger than their values in the pasture soil. This study, therefore, revealed that the land use change in the mal areas increases the soil vulnerability to rainfall erosion processes. The rate of rainfall erosion processes in each rainfall event depends on the amount of previous rainfall. Increasing aggregate break down and soil water content by the previous rainfall could significantly influence the splash erosion rate in a marl soil.

One of the main reasons for bridge failure is the local scour around the pier. Pier groups are popular in the structural designs due to economical and geotechnical reasons. The mechanism of scouring at the pier groups is more complicated than the single one. In this study, the scour around group piers in the sandy soil and a mixture of sand and clay in some relative compaction equal to 90% and the optimum moisture was studied. The arrangement of the group piers was 1pier * 3pier and 3pier * 1pier along and transverse of the flow direction, respectively, at the interval space of D, 2D and 2.5D intervals. The effect of the Bentonite clay content was investigated. Finally, by using Kaolinite clay, the effect of the clay mineral was studied. The results showed that the scouring depth was different not only in cohesive and non- cohesive soils, but also according to the type of the clay mineral. The use of 10% bentonite clay mixed with sand reduced scour more than 90%, as compared to the sandy soil. On the other hand, using 15% of kaolin in the similar conditions reduced scour depth by only a 34%, in comparison to the sandy soil.

Soil erosion and its consequences are important factors in forest road network management. Cutslopes are the most important source of making sediment among different parts of the forest roads structure. For this research, a new and bare road in district No. 2, series No. 5 of NekaChoob forest, was selected; then the study data was measured. The study design was a completely randomized design in 10 plots with the size of 2 m² along 500 meters of road with the 8 natural rainfall events. The results of the Pearson correlation showed that among soil properties, the contents of the liquid limit at the 5% confidence level and the plastic limit at the 1% confidence level had positive correlations with runoff and soil loss. Also, organic matter at the 1% confidence level and the contents of the sand at the 5% confidence level had negative correlations with runoff and soil loss. With increasing the soil moisture and bulk density, runoff and soil loss were enhanced. The results of the multivariate model showed that soil loss could be estimated using the Plastic Limit and sand percentage variables with a the correlation coefficient of 0.948.

Soil moisture is one of the most important factors that can affect productivity in ecosystems in arid and semiarid regions. The aim of this study was to investigate soil moisture and vegetation changes in the Isfahan province at the seasonal scale. For this purpose, MODIS Land Surface Temperature (LST) and NDVI data were used to calculate the TVDI index, and the rate of soil moisture content was also measured at several soil depths including 5, 10, 20, 30 cm. in the growing season. Seasonal changes of LST and NDVI indices were also studied in different climate regions ranging from humid to hyperarid. The results showed that the changes in NDVI and LST in this region were different, depending on the climate type and soil conditions; the LST and its changes mostly depended on the amount of vegetation cover NDVI changes based on the plant phenology in humid regions, which was were greater than that in arid and semi-arid climates. Soil moisture monitoring indicated that the relationships between TDVI and different soil depths varied based on the seasonal conditions. In the early growing season, the soil moisture at the depth of 0-5 cm had a higher correlation with TVDI, but in the middle of growing season, the deeper soil moisture (10-30 cm) showed the highest correlation. Therefore, the findings of this research indicated the importance of the growing season, soil conditions and vegetation percentage and types in the soil moisture studies by using satellite data.

Soil is one of the most important natural resources of countries in which erosion occurs. In this research, the effect of soil characteristics on the amount of erosion at the suborder level was studied. For this purpose, 77 soil samples (0-30 cm) were prepared and the parameters were determined in the laboratory. The semi-variograms of soil parameters and their spatial distribution maps were prepared with GS⁺ and GIS, respectively. The study area was divided into work units by combining land use and geology maps and water erosion was estimated at each unit by the EPM method. By drilling profiles in different parts of study area, soil suborders were determined by Soil Taxonomy and the average values of parameters in each suborder was estimated. The principle components analysis (PCA) was then used for data analysis. The results showed that three parameters of silt, organic carbon and electrical conductivity could account for 30.384% as the first main component; clay, sand and vegetation could explain 11.189% as the second main component; and slope and height covered 15.330% as the third main component; in total, 63.805% percent of erosion variation could be justified by three main components. The lowest and highest amounts of erosion (69.12 and 343.57 m³/km², respectively) were estimated in Xeralfs and Fluvents suborders. The erosion class of suborders at the study area was determined to be “few” and “medium”.