The modeling of WATER movement through SOILs typically requires the functional representation of SOIL hydraulic PROPERTIES, such as the WATER retention curve. Among different WATER retention models, van Genuchten (VG) model is an appropriate one. The objectives of this study were to quantify relationships between the VG model parameters and SOIL physical PROPERTIES and to select equations that are useful for prediction of VG model for SOIL WATER retention curve. Fifty four SOIL samples were used for SOIL WATER characteristics determination by ceramic plate extractor, SOIL particle size determination by hydrometer method, SOIL bulk density and SOIL organic matter. Multiple regressions were used to determine the relationships between m and hp (SOIL WATER suction at reflection point of the SOIL WATER retention curve) and the aforementioned SOIL physical PROPERTIES. The results indicated that multiple regression models may be used to estimate, with acceptable accuracy, the WATER retention curve of VG type from SOIL sand content, bulk density and Organic matter percent. The proposed regression models were used for prediction of SOIL WATER retention curve for three different SOILs with an acceptable accuracy.

One of the crucial information, as input in modeling of hydrological processes, is relevant to SOIL moisture and especially the retention characteristic information available at catchment scale. This paper presents a method to relative approximation of these quantities shown. Accordingly, at the beginning, Determination and extraction of SOIL texture class's USDA method by Using SOIL texture class proposed by the Commission of the European Communities (CEC) (these method «CEC» has the 6 texture classes with codes 0 to 5) Was conducted. In continuation of these texture classes (texture classes USDA method) to estimate and AS a result in mapping the amount of field capacity and wilting point (for the whole country) is used. In these respect, the results showed that in general, the average range of SOIL moisture variations in texture classes by CEC method, for permanent wilting point is exceeded field capacity So that the changes for permanent wilting point than the average 6.77 to 10.9 and for the field capacity of 6.03 to 9.3 percent Is has the variations. Also in this study, according to expert opinion and utilizing scientific resources attempted to investigate the interaction between the effects of land use and slope of WATERshed in order to assess the information and the resulting the depth map of the surface layer of SOIL moisture retention. In this direction to assess and evaluate the applicability of the approach taken comply with the physics of the catchment, attempted to utilizing it (Effective depth map of the surface layer the SOIL moisture retention) along with wetting PROPERTIES Maps of field capacity and permanent wilting point that was achieved the National SOIL Map (the first stage of the research), In order to estimate and prepare a map of available moisture in areas of study there, Nishapur, Attaiyeh, Qaleh Meydan and Sabzevar as the regions chosen for study were used. The results indicate that the resulting map is proportional to the physics of the studied areas in order to achieve total available WATER and the role of the interaction basin slope, land use And well as the impact the moisture field capacity and permanent wilting point that was extracted from the SOIL map On Total available WATER is well evident. Accordingly, due to the integrated and comprehensive characteristics of moisture maps (field capacity and permanent wilting) for the whole country, this amount could be used as a primary domain of SOIL moisture characterized along with the method described in the effective depth of surface SOIL moisture retention on Hydrological modeling, particularly Understanding the phenomenon of a small amount of influence and power of WATER retention in the SOIL, the estimated components of WATER balance, etc. in order to prevent land degradation and SOIL and WATER resources management, to be used.

Quantitative description of infiltration process is crucial for many applications in hydrologic cycle. The direct measurement of infiltration is time consuming, expensive and often impractical because of the large spatial and temporal variability. Any indirect parametric estimation of this process would be quite useful. Although, the so-called pedotransfer functions (PTFs) are widely used as an indirect method to predict the SOIL hydraulic PROPERTIES, no attention has made to indirect estimation of infiltration. The objective of this study was to develop and verify some parametric PTFs to predict the infiltration process under three different land uses; namely pasture, wheat and fallow. For this purpose, 123 double ring infiltration data were collected. The parameters of four infiltration models were then obtained, using sum of least squares error method. Basic SOIL PROPERTIES of the two upper pedogenic layers such as initial WATER content, bulk density, particle-size distributions, organic carbon and gravel contents, CaC03 percent, field moisture capacity and penpanent wilting point WATER contents were measured for each sampling location. The parametric PTFs were then developed to predict the parameters of the infiltration models, using the step wise regression method. The accuracy of the derived PTFs was evaluated using MAMD, MRMSD, SDMRMSD and MPearson statistics. The results indicated that the PTFs derived for the land under fallow have the best performance on cumulative infiltration prediction. Under pasture, wheat and fallow land uses the derived PTFs for Philip, Horton and Kostiakov-Lewis models were the best predictor of infiltration, respectively.

Infiltration is a significant process which controls the fate of WATER in the hydrologic cycle. The direct measurement of infiltration is time consuming, expensive and often impractical because of the large spatial and temporal variability. Artificial Neural Networks (ANNs) are used as an indirect method to predict the hydrological processes. The objective of this study was to develop and verify some ANNs to predict the infiltration process. For this purpose, 123 double ring infiltration data were collected from different sites of Iran.The parameters of some infiltration models were then obtained, using sum squares error optimization method.Basic SOIL PROPERTIES of the two upper pedogenic layers such as initial WATER content, bulk density, particle-size distributions, organic carbon, gravel content, CaCO3 percent and SOIL WATER contents at field capacity and permanent wilting point were obtained for each sampling point. The feedforward multilayer perceptron was used for predicting the infiltration parameters. Two ANNs types were developed to estimate infiltration parameters. The developed ANNs were categorized into two groups, type 1 and type 2 ANNs. For developing type 1 ANNs, the basic SOIL PROPERTIES of the first upper SOIL horizon were used as inputs, hierarchically. While for developing type 2 ANNs the basic SOIL PROPERTIES of the two upper SOIL horizons were used as inputs, using principal component analysis technique. Evaluation results of these two types ANNs showed the better performance of type 1 ANNs in predicting the infiltration parameters. Therefore, this type of ANNs was used for predicting the cumulative infiltration. The reliability test indicated that the developed ANNs for Philip model have the best performance to predict cumulative infiltration with a mean RMSE of 6.644 cm. The developed ANNs for Horton, Kostiakov-Lewis and Kostiakov have the next best ranks, respectively.

SOIL WATER characteristics curve (SWC), is one of the most important traits of every SOIL and is employed in many aspects of SOIL management such as irrigation, drainage, land reclamation, infiltration and erosion. Laboratory method to determine this curve is time consuming, costly, difficult and involves some errors. For this reason researchers have tried to estimate it with the help of mathematical and statistical models. One of these models has been suggested by Arya and Paris. The primary concept of this model has been developed on the basis of shape similarity between SWC and cumulative SOIL particle size distribution (PSD) curves. An experimental coefficient (a) have been employed in this model. Arya and Paris obtained the mean of 1.38 for a. Evaluating the generality of this value for SOILs of various physical PROPERTIES, particulary texture, was the main objective of this study. For this purpose, five SOIL series (Balestan, Arzanagh, Sharabian, Sarab and Gonbadan) were selected from the Sarab region in northwest of Iran. Within each series seven sites were specified and core (undisturbed) samples were taken from each site in triplicate. Composite disturbed samples also were taken. Percentage of SOIL particles, saturated WATER contents, SOIL bulk and densities and PSD curves were determined for all samples, and finally SWC curves were simulated by employing Arya and Paris model. The experimental SWC were also prepared using suction and pressure plate apparatus. Comparison of experimental SOIL WATER content at specified SOIL WATER potential with those predicted from the model indicated that a values ranged from 1.3 to 1.43. Within this range 1.3 seems justifiable for the most series and implies that the model with a=1.3 simulates SWC curves accurately enough. The generalization, however, may need more investigation.

In order to prevent land degradation and SOIL and WATER pollution, realizing the respective processes and quantifying their relationships is unavoidable. Infiltration process is one of the most important components of the hydrological cycle. On the other hand, the direct measurement of infiltration process is laborious, time consuming and expensive. In this study, the possibility of predicting cumulative infiltration in specific time intervals, using readily available SOIL data and Pedotransfer Functions (PTFs) was investigated. For this purpose, 210 double ring infiltration data were collected from different regions of Iran. SOIL texture ranged from loam to clay. Basic SOIL PROPERTIES of the two upper pedogenic horizons including initial WATER content, bulk density, particle-size distributions, organic carbon, gravel content, CaCO3 percent and SOIL WATER contents at field capacity and permanent wilting point were determined on each SOIL sample. The parametric PTFs were then developed to predict the cumulative infiltration at times 5, 10, 15, 20, 30, 45, 60, 90, 120, 150, 180, 210, 240, 270 minutes after the start of the infiltration test and the time of basic infiltration rate, using the stepwise regression method. The results of reliability test indicated that all derived PTFs underestimated the cumulative infiltration. Also, the obtained RMSEs at small times were lower than those obtained at the ending times of the infiltration process. EF statistic had positive values and increased with time increasing. The EF values indicated that the efficiency of the derived PTFs improved during the time increasing. Also, developed PTFs had a mean RMSD of 6.90 cm in ESTIMATING the cumulative infiltration curve. Results indicated that at the 1% probability level, the estimated cumulative infiltration curve can be accepted as one of the replicates of a reliable infiltration test.

Most processes of SOIL and WATER in the field occur in unsaturated conditions. In the field, It’s possible to estimate SOIL hydraulic PROPERTIES by measurement of SOIL WATER content and SOIL WATER pressure head in different times, using inverse method. In the other hand, it’s difficult, time consuming and costly to measuring SOIL WATER content and WATER pressure head simultaneously. So, in this paper, the possibility of predicting SOIL hydraulic PROPERTIES by measurement of SOIL WATER content or WATER pressure head separately were studied. To do this job, ESHPIM2, an inversion approach computer model, has been used. In this model, SOIL hydraulic parameters are optimized to reach the minimum value of objective function (Summation of squared differences between measured and predicted SOIL WATER content or WATER pressure head) using genetic algorithm. SOIL hydraulic parameters of four SOIL series at Agricultural College of Shiraz University were studied in three cases. In the first case, the ESHPIM2 model with the objective function based on measuring the SOIL WATER pressure head and in the second case, the ESHPIM2 model with the objective function based on measuring the SOIL WATER content are used. Moreover, in the third case, SOIL hydraulic parameters are estimated by measuring SOIL WATER content and SOIL WATER pressure simultaneously. The results show that SOIL hydraulic parameters are predicted more appropriately by measuring SOIL WATER pressure head than SOIL WATER content in studied SOILs by inverse method using ESHPIM2 model.

SOIL Saturated Hydraulic conductivity is one of the most important SOILs physical PROPERTIES, which has particular importance in studying and modeling the movement of WATER and salts in porous media. Because these methods are expensive and time consuming. Therefore, it seems necessary to estimate saturated hydraulic conductivity using of fast, low-cost methods with acceptable accuracy. In this research, geostatistical and response surface methods were used to estimate the hydraulic conductivity of SOIL saturation, the data was prepared from 135 SOIL profiles related to SOIL science and land reform studies of Ardabil Agricultural Jihad Organization in Fatah Ali Plain area. The main factor included saturated hydraulic conductivity, SOIL texture, bulk density, porosity, degree of saturation, and field capacity were considered as secondary factors. Among the geostatistical methods, ordinary cokriging had the best fit and the best fitted variogram in this method was the exponential model with zero nugget effect and 156 of sill range. That showed the strength of the spatial structure of the region and the full impact of the spatial structure on region variogram.  In the ordinary cokriging method, the estimation accuracy was estimated with the regression coefficient (R2=0.93) and (RMSE=3.21). In the response surface model, the best saturated hydraulic conductivity model based on the effective variables, was quadratic model with regression coefficient of 0.94 and the adequacy of accuracy of 49.2 was estimated, to determine the maximum hydraulic conductivity assuming the change of other effective parameters in the range of measured values, a target with desirability of 0.67 was obtained. This goal calculated the hydraulic conductivity of the SOIL at 8.9 (%) clay and 86 (%) sand, equal to 57.15 (mm/hour). Therefore, both methods are highly accurate in determining the hydraulic conductivity of SOIL saturation, but the response surface method (RSM) was more accurate.

The measurement of SOIL parameters for unsaturated SOIL constitutive models needs extensive laboratory tests. For most practical problems, it has been found that approximate SOIL PROPERTIES are adequate for analysis. Thus empirical procedures to evaluate unsaturated SOIL parameters would be valuable. The SOIL-WATER characteristic curve (SWCC) can be used to estimate various parameters, which describe unsaturated SOIL behavior. The SWCC is a relationship between SOIL suction and some measure of the WATER content. It can be measured or predicted based on the SOIL index PROPERTIES. Estimation based on the index PROPERTIES is highly desirable due to its simplicity and low cost.In this paper, a new model is presented for predicting the SWCC based on the SOIL index PROPERTIES and Van Genuchten equation. Comparisons show that the SWCC predicted by this model is ill a good agreement with the experimental results.

Dynamic cone penetration (DCP) test is used more in pavement design and construction, and less for subsurface geotechnical investigation and clay core dam. In the present article, evaluating geotechnical parameters of Sanandaj’s clay in the western region of Iran using the DCP test was taken into account. Accordingly, 6 trial pits with maximum depths of 15 m were excavated manually in various sites of Sanandaj on clay SOILs (CL). During the excavation process, 3 series of DCP tests were carried out and repeated in the pits after excavating every one meter. The SOIL samples for the selected sites were also obtained for the laboratory tests including WATER content, grain size, Atterberg limits, and triaxial compression tests. Based on the results of the experiments, the DCP test was repeatable (CoV<30%). The relationships between Dynamic Penetration Index (DPI), liquid index (LI), undrained shear strength (Cu) and dry density (gd) of the clay SOIL were also obtained with a high coefficient of determination (R2>83%). Using the DCP test, geotechnical PROPERTIES of the clay (CL) can be investigated rapidly and inexpensively