Soil infiltration rate is the major soil hydraulic property which can be affected by the soil physical characteristics and management practices. The use of land can affect various soil properties such as physical and hydraulic properties. Differences of the hydraulic soil characteristics such as infiltration rate in various land uses can affect their potential to runoff production as well as soil loss in the catchment. The knowledge of the physical and hydraulic characteristics of various land uses can help to better management of soil and water in the catchment. It is very essential in the semi-arid catchments where vegetation cover is generally poor, the soils are often instable against erosive factors especially when the rainfalls are consecutive and intensive. Therefore, this study was conducted to investigate the soil physical and hydraulic characteristics in the TahamChai catchment, in a semi-arid region, NW Zanjan. Various land uses consist of pastures, rainfed and irrigated lands can be observed in the catchment, which cover about 62%, 33%, and 5% of the catchment area, respectively. The pastures have been covered with poor vegetation and are intensively exhausted by over-grazing. Rainfed lands are mostly under winter wheat cultivation. Soil erosion and sedimentation were the major environmental problem in this catchment.
The maps of land use and slope gradient were provided for study area. A total of 20 sites were selected based on the surface area of each land use in the catchment located between 34 46-36 53 N latitudes and 48 17-48 37 E longitudes. The study area consisted of ten sites in the pasture, seven sites in the rainfed and three sites in the irrigated lands. The geographical positions of study sites were determined by a global positing system (GPS). Soil infiltration rates were measured by double rings method at three replications in each site. Variation of soil infiltration rate was determined for each land use. Soil samples were collected at three replications from each site to determine other physicochemical soil properties. Particle size distribution, bulk density, saturation percentage, aggregate mean weight diameter, organic matter, and equivalent calcium carbonate were determined using standard methods in the lab. Mean comparisons of infiltration rate along with other physicochemical soil properties among the land uses were done using the Duncan's parametric method. The Pearson’s correlation coefficients were used to determine the relationships between soil properties and soil infiltration rate.
Based on the results, no significant difference was observed between the land uses in particle size distribution. Soil infiltration rate showed different patterns among the land uses, so that significant difference was observed among them (p Pastures with poor vegetation cover appeared the lowest soil infiltration capacity as compared to other land uses in the catchment. Decreasing soil infiltration rate was associated with increasing bulk density in the area. It seems that overgrazing in the pastures increases soil bulk density and leads to decline the soil organic matter content as well as soil aggregation and aggregate stability. According to the results, pastures have the highest potential to runoff production and soil erosion rather than the other land uses (rainfed lands and irrigated lands). Therefore, maintaining vegetation cover and preventing over-grazing in the catchment is recommended to increase soil organic matter content and decrease soil compaction. These practices improve the hydraulic soil characteristics especially infiltration rate and in consequence decrease the catchment potential to runoff production and soil erosion.

In the network of floodwater spreading and artificial recharge system, deposition is the main obstacle of infiltration water in the soil and reaching of water to the groundwater. Soil infiltration reduction depends on suspended material, the infiltration rate, soil physical characteristics and quality of the floodwater spreading. Fine-grained sediment enters into the network during the flood; reduce the efficiency of these projects and in long time of operation to actually lose its effectiveness. The main objective of this study is the effect of sediment deposited on the variation of infiltration rate by the floodwater spreading. In this study, double rings with triangular surface soil infiltration rate were used and the relevant data were entered into the Excel software. The analysis and comparison of the effects of the floodwater spreading on soil infiltration rate in comparison to control was evaluated using the statistical method of factorial completely randomized design. The effects of floodwater spreading on soil infiltration rate were evaluated using the statistics factorial method in completely design. Duncan mean comparison test was applied to compare rate of infiltration on spreading area with ditches between them. It is necessary to mention that the control values in the first year were compared with the results of reminder years. In general, the analysis of variances show the difference between rates of infiltration in depth of soil is significant at level %5 but the level signiticant for floodwater is %1. There is no significant difference for interaction of these two factors.

Infiltration is one the most important parameters in surface irrigation which its accurate measurement is obvious. It could potentially affected by different parameters such as bed slope، discharge، cross section and roughness coefficient. In this research، Kostiakov-Louis equation (KLE) was employed using two-point method، in order to measure the soil infiltration rate. This study was carried out in research field of Shahrekord University، Shahrekord، Iran. A completely randomized block design was employed with three treatments and three replications. The effect of changes in furrow bed slope and shape is evaluated on the soil moisture distribution، soil infiltration rate and cumulative infiltration. Statistical analysis was performed using the LSD test. The results show that the lowest infiltration rate (0. 00052 cubic meters per minute) and cumulative infiltration value (0. 5 cubic meters per meter) were observed in variable furrow bed slope. The changes in the slope were significant (P<0. 01) on soil infiltration rate and soil basic infiltration rate (). There is no correlation between cross section variation and KLE parameters including k، a and (P<0. 01). The result shows that soil moisture distribution was more uniform in variable cross sections than other treatments

Proper design and management of irrigation systems requires knowledge of soil infiltration rate، which is in turn influenced by water salinity and sodicity. The objectives of this study were to investigate the spatial variability of irrigation water electrical conductivity (EC) and sodium adsorption ratio (SAR) and to map these parameters using geostatistical methods. The main objective was to predict the spatial distribution pattern of soil infiltration rate over the study area based on water salinity and sodicity. Water samples were collected from 76 observations wells in the Kerman Plain in 2008. The geostatistical methods used were ordinary and log-normal kriging. The performance of interpolation methods was evaluated through cross-validation with comparison criteria of root mean square error (RMSE) and mean absolute error (MAE). Geostatistical analysis showed that both EC and SAR had strong spatial correlations، and these fitted a spherical model. The cross-validation results are indicated that the two methods provided similar accuracy for estimating salinity and sodicity. Furthermore، it was evident from the kriged maps generated through both methods for EC and SAR that the estimation error maps produced were only slightly different. Therefore، whenever the aim is to produce only a map of spatial distribution of soil properties، ordinary kriging، which is mathematically simpler than other methods، is preferred. Soil infiltration rate distribution pattern was also predicted based on the kriged maps of EC and SAR، and، some approved standards. The results indicated that most of that area، including northern and western regions had good infiltration rates. The rest، which cover mostly the northeastern and southeastern of the study area، had moderate infiltration rates.

Soil infiltration is one of the most important factors in successful operation of floodwater spreading projects. The suspended particle in floodwater reduces the rate of soil infiltration. The objective of this research was firstly to monitor the variation of infiltration and secondly to determine the effective factors in decreasing the infiltration rate. In this research، three representative strips of the floodwater spreading network were selected. Each strip was divided into three rectangular areas، and by drawing rectangulars diameters، each rectangular area was further broken into 4 triangulars. The soil infiltration rate was measured in two steps at the center of each triangle during 2004 – 2005. In each step، 9 measurements were undertaken in each rectangle، implying totally 27 measurements were collected from each strip. Based on the obtained results، there was no significant difference between the infiltration rate at the strips over this two-year experiment. Also، there was no significant difference between the infiltration rate in the experimental strips compared to the control strips. Comparing the soil infiltration rate of the stripes in the first and second year showed that its values in the second year are less than the first year. Also، a significant difference at a 95% confidence level was observed in the infiltration rate of the first and second strips in two years.

Characterizing soil infiltration parameters is time consuming and costly. We carried out the current research to predict different parameters of soil infiltration using field/laboratory measured and remotely-sensed data. The investigated parameters included infiltration rates at different time intervals and the parameters of the three well-known infiltration models. We employed soil sampling and field measurements on late spring 2012 and acquired ETM+ data for the correspondent dates. We measured several soil properties as well as infiltration. Then, we developed several pedo-transfer functions (PTFs) from the collected field/laboratory measured and remotely sensed data to predict the intended infiltration parameters. Results showed that field/laboratory measured data were able to predict soil infiltration rates and parameters of the investigated models with reasonably high accuracies (E value up to 0.961). The results also revealed that, although there was no significant and robust relationship between soil surface reflectance and the investigated parameters, the developed PTFs had reasonable accuracies (E value up to 0.634) in estimating the intended infiltration parameters using soil characteristics (moisture content, soil separates, and organic carbon) which are predictable from remotely sensed data.

In order to evaluating effects of irrigation with saline-sodic water, we conducted three infiltration experiments in clay-loam soil in end-close furrow. We were using 5cm water depth every week, which had EC=12 ds/m and SAR=32. Experiments were done with volume-index method in end-close furrow in third, sixth and tenth irrigation. Therefore infiltration speed and cumulative infiltrations curves were fitted in different times with Kostiakov and Philip models. Results showed that great decrease in infiltration rate was happened since irrigation with saline-sodic water in experiment. Therefore infiltration rate decreased 40.6 and 68 percent from third irrigation to sixth and sixth to tenth irrigation, respectively. So using saline-sodic water can decreased infiltration rate up to 81 percent in 50 days. Evaluation of the simulation results of test data again Kostiakov &loese and Philip model data with RMSE and MBE parameters showed that these models could simulate soil infiltration rate changes good under the effect of irrigation with saline-sodic water. Also simulation accuracy was increased at the end of experience time than initial and mead time infiltration tests

Infiltration is one of the most important soil physical variables and basic data in rainfall–runoff models for water loss determination in watersheds. Its measurement is، however، time consuming and costly. For this reason، soils infiltration rates determination by different models is always a serious concern to researchers. In this research، a single event precipitation was measured using rainfall simulator during a 90-minute rainfall for determination of the best infiltration equation in watershed scale. The parameters of five infiltration models namely Kostiakov، Green-Ampt، Horton، NRCS and Philip، were estimated by sum of squared error optimization for four different land uses and three soil textures of sandy clay loam، loam، and sandy loam. The cumulative infiltration rates estimated from the different models were compared using eight different statistics. The results showed that the Kostiakov and NRCS models had the highest priority score and the most permanent trend for accurate estimating of cumulative infiltration rate in different land uses whereas the Horton model was situated in the next position. Overall، the empirical models (Kostiakov، NRCS and Horton models) had the more realistic efficiency than the physical models (Green-Ampt and Philip models).

Biological soil crusts (BSCs(result from an intimate association between soil particles and cyanobacteria، algae، fungi، lichens and mosses in different proportions، which live on the surface، or immediately in the uppermost millimeters of soil. Biological soil crusts، are important from the ecological view point and their effects on the environment، especially in rangeland، and desert ecosystems. These effects have encouraged researchers to have a special attention to this components of the ecosystems. The present study carried out in Qara Qir rangeland of Golestan province، Iran، to investigate the effects of BSCs on Soil saline-sodic properties. In the study area، four sites were selected which included sections with and without BSCs. Soil sampling was carried out in each section for depths of 0-5 and 5-15 cm، with four replication. The gathered data from soil samples were analyzed by nested plot. Results showed that BSCs than non-BSCs، significantly decrease the amount of soil acidity، calcium carbonate and soil saline-sodic properties such as electrical conductivity، sodium، calcium and magnesium concentration، sodium adsorption ratio، and exchangeable sodium percentage at both depths. In general، it can be concluded that BSCs enhance soil infiltration rate and available water content، that together their bioaccumulation properties، leads to decreasing soil saline-sodic properties. Potassium concentration did not differ among areas covered by BSCs and without BSCs. But infiltration rate and available water content were increased significantly in two mentioned depths on sites covered with BSCs than without BSCs. In general، it can be concluded that BSCs enhance soil infiltration rate and available water content، that together their bioaccumulation properties، leads to decreasing soil saline-sodic properties.

Infiltration plays an important role in surface and subsurface hydrology and it is a key factor in the rainfall and runoff equations. The use of new approaches that have no limitations of common theoretical and empirical methods to determine infiltration relationships, will minimize the necessity of time consuming and costly experiments to determine permeability values and will make it possible to estimate the functional values. In this regard, in the present study the amount of soil permeability was estimated in Behshahr plain of Galougah located in Mazandaran province, using Fuzzy Inference System (FIS), Fuzzy Clustering Algorithm (FCA) and Nero-Fuzzy (ANFIS); so that, initial soil moisture content, soil organic matter content and soil lime content were considered as input parameters, and final soil infiltration rate was considered as output parameters of the models. Finally, the results obtained by the three mentioned modes were compared to the observed values by single-ring approach. According to the achieved results, Nero-Fuzzy approach with a mean deviation of 0.0042 cm/min, BIAS value of 0.6754 cm/min, Root-Mean-Square Error of 1.2096 cm/min and correlation coefficient of 0.9233 showed the most appropriate performance to estimate soil infiltration rate among the studied models; while, Fuzzy Clustering Algorithm with a mean deviation of 0.0075 cm/min, BIAS value of 2.1165 cm/min, Root-Mean-Square Error of 2.0244 cm/min and correlation coefficient of 0.8776, and Fuzzy Inference System with a mean deviation of 0.0161 cm/min, BIAS value of 2.5042 cm/min, Root-Mean-Square Error of 2.4533 cm/min and correlation coefficient of 0.8167 were placed in the next ranks respectively. Also, the highest correlation between observed and estimated values was seen in Nero-Fuzzy model (R2=0.85), and the two other studied models including Fuzzy Clustering Algorithm (R2=0.77) and Fuzzy Inference System (R2=0.66) are at the next ranks respectively. At the end of this research providing more data of soil physical and chemical characteristics as well as permeability amounts has been recommended in order to more accurate estimation of the studied models.