mohammad omidifard

Water infiltration into soil is one of the most important soil physical processes for hydrological and agricultural applications. It plays a key role in hydrological studies, water resource management, soil conservation, irrigation systems, drainage systems, and soil erosion control in watersheds. There are various equations for determining how water infiltrates into the soil. Some of these (e.g., Philip and Green-Ampt equations) are based on the physical properties of the soil and the results of solving the relationships governing water flow in the soil. The others (e.g., Kostiakov, Kostiakov-Lewis, Horton, and US Soil Conservation Service equations) are empirical relationships obtained from analyzing the curve between infiltration rate and time without any physical background. Using these relationships avoids the waste of time and high cost required to measure infiltration in the field, especially on a large scale. The coefficients of these equations, like other soil characteristics, depend on the soil type and conditions and are subject to spatial and temporal variations. Therefore, this research aimed to study the spatial variability and model of the spatial dependence of the coefficients of different theoretical and empirical infiltration equations in the calcareous soils of Bajgah, Shiraz.
 

Infiltration tests were carried out at 50 points of the studied soil using the single-ring method. Different infiltration equations, including Horton, Kostiakov, Kostiakov-Lewis, US soil conservation service (SCS), Green-Ampt, and Philip equations were fitted to the measured data, and the coefficients of the equations were determined. Preliminary statistical checks included determining the summary statistic (measure of location, measure of spread, and shape parameters of data distribution), checking the normality of the distribution of the infiltration coefficients data, and performing necessary transformations if required. To check the spatial dependency of the data, the experimental semivariogram of the data was calculated. Various theoretical models, including spherical, exponential, and Gaussian models, were fitted and the best semivariogram model and its characteristics were determined using statistical criteria. Coefficients at unmeasured points were also estimated using the normal kriging method and the inverse distance weighting (IDW) method with different weight powers. The evaluation of the estimation methods was also carried out using the jack-knife method and the appropriate estimation method was identified. Estimation of the coefficients at points without data and zoning was done using the appropriate estimation method. The statistical and geostatistical analyses mentioned above were carried out using the software packages Excel and GS+.

The coefficient of variation (CV) of the studied infiltration equation coefficients varied between 12.5 and 478%, with the highest and lowest CV for the coefficients “A” of the Kostiakov-Lewis equation and “b'” of the SCS equation. The isotropic spherical model was the best-fitted model to the semivariogram of the coefficients of the Kostiakov (K and b), Horton (c, m, and a), Philip (“A”), and Kostiakov-Lewis (b') equations. Whereas, the isotropic exponential model was the best-fitted model to the coefficients of the SCS (a and b), Philip (“S”), and  Kostiakov-Lewis (K and A) equations. The range of variation (the radius of influence) of the coefficients of the infiltration equations varied from 1.96 to 211 m, respectively, for the “K” coefficient of the Kostiakov equation and the coefficients of the Kostiakov-Lewis, “a” of Horton, “S” of Philip, and “b”' of SCS equations. Among the coefficients studied, the highest and lowest nugget effect (C0) to threshold (C+C0) ratio was obtained as 0.648 and 0.5, respectively. The spatial correlation class of the infiltration equation coefficients was moderate, and the maximum and minimum radius of influence were 211 and 6.4 m, respectively, which corresponded to the “S” coefficient of Philip, the coefficients of Kostiakov-Lewis, the “a” coefficient of Horton, and the “b” coefficient of the SCS equations. The most precise and the least precise estimates were related to the “A” coefficient of Philip, “b” of Kostiakov, and “b'” of Kostiakov-Lewis equations, respectively.

In this study, spatial variations of the coefficient of various infiltration relations were investigated and modeled, and estimation and zoning were performed using the best model. Results showed that the spatial dependence class of the coefficient of infiltration relations in the study area is medium, and also, the maximum and minimum radius of influence of 211 and 6.4 m are related to the coefficient S of the Philip and the coefficients of the Kostiakov-Lewis and the coefficient a of Horton and the coefficient b of the US Soil Conservation Service equations, respectively. In other words, this study suggests geostatistical methods and limited measurements to estimate the coefficients of the infiltration equations with reasonable precision and to save time and cost when zoning or estimating these coefficients at large scales. However, due to the weak and unsuitable spatial structure, the IDW method outperformed the kriging method in some cases in the studied area and its use can lead to more precise estimates. Therefore, in cases where the spatial structure of the desired feature is weak and inappropriate, methods such as Kriging that rely on strong spatial correlation are unsuitable, and in these cases, other alternative estimation methods, such as IDW which does not depend on the presence of strong and appropriate spatial structure in the data should be used.

This study aimed to understand the transition process of governors in the Islamic Republic of Iran.The study used a qualitative research approach and developed a grounded theory. Data were collected through semi-structured interviews with nine previous governors and reviewing three former governors' biographies.

The study found that governors in the Islamic Republic of Iran experience confusion between institutional fields during the transition process. To overcome this confusion, governors employ tactics to discover institutional fields, develop communication channels, build connections with individuals within these fields, and exert influence over these fields. The governor's cultural and social capital are contextual aspects that play a role in this process. There are also intervening elements that are outside the governor's control, such as the public's perception of the government, the governor's legal standing and authority, the competence of the interior minister, and the province's degree of development.The study's findings provide a model for the transition process that can be used to support new governors in their transition to the governorate. The model emphasizes the importance of discovering institutional fields, developing communication channels, building connections with individuals within these fields, and exerting influence over these fields. The findings highlight the importance of contextual aspects and intervening elements that are outside the governor's control. The study's results may be useful in enhancing the performance of governors during their transition process and improving the governance of provinces in the Islamic Republic of Iran.

After coup d'etat of 1953 in Iran, Iran's relations with the United States entered a new phase and continued until the Shah's departure from Iran on 9th Jan. 1979, and perhaps shortly thereafter that. Meanwhile, many contracts were signed to commerce  military items between the two countries. But with the end of friendly relations between the two countries and the subsequent signature of Algiers Accords and the establishment of Iran-United States Claims Tribunal, allegations of breach of these contracts formed the basis for a case filed by Iran in the tribunal which is still pending. Given the lack of governing law in these contracts, it is important to determine their governing law which is subject to determination of their legal nature. Thus, this paper seeks to determine legal nature of arms and military equipment contracts between the United States and Iran by conducting analytical research. Given the five reasons as a strong sign of the existence of treaty elements in these contract, it can be concluded that the contracts in question are in fact treaty under the in the sense of Vienna Convention on the Law of treaties.

Saturated hydraulic conductivity and the other hydraulic properties of soils are essential vital soil attributes that play role in the modeling of hydrological phenomena, designing irrigation-drainage systems, transportation of salts and chemical and biological pollutants within the soil. Measurement of these hydraulic properties needs some special instruments, expert technician, and are time consuming and expensive and due to their high temporal and spatial variability, a large number of measurements are needed. Nowadays, prediction of these attributes using the readily available soil data using pedotransfer functions or using the limited measurement with applying the geostatistical approaches has been receiving high attention. The study aimed to determine the spatial variability and prediction of saturated (Ks) and near saturated (Kfs) hydraulic conductivity, the power of Gardner equation (α), sorptivity (S), hydraulic diffusivity (D) and matric flux potential (Фm) of a calcareous soil.
Material and The study was carried out on the soil series of Daneshkadeh located in the Bajgah Agricultural Experimental Station of Agricultural College, Shiraz University, Shiraz, Iran (1852 m above the mean sea level). This soil series with about 745 ha is a deep yellowish brow calcareous soil with textural classes of loam to clay. In the studied soil series 50 sampling locations with the sampling distances of 16, 8 , and 4 m were selected on the relatively regular sampling design. The saturated hydraulic conductivity (Ks), near saturated hydraulic conductivity (Kfs), the power of Gardner equation (α), sorptivity (S), hydraulic diffusivity (D) and matric flux potential (Фm) of the aforementioned sampling locations was determined using the Single Ring and Droplet methods. After, initial statistical processing, including a normality test of data, trend and stationary analysis of data, the semivariograms of each studied hydraulic attributes were calculated in various directions and their surface semivariograms were also prepared to determine the isotropic or anisotropic behavior of each studied soil attributes. Since all of studied soil hydraulic attributes were isotropic variables, therefore, the omnidirectional semivariograms were calculated and different theoretical models were fitted to them. The best fitted semivariogram models were determined using the determination coefficient, R2, and the residual sum of the square, RSS. The parameters of the best fitted models to the experimental semivariograms were also determined. The prediction of study hydraulic attributes was carried out using the parameters of semivariogram models by applying the ordinary Kriging approach. Predictions were also carried out using the Inverse Distance Weighing approach. The results of predictions were compared to each other using the Jackknifing evaluation approach and the suitable prediction method was determined and zoning was performed using the results of introducing prediction method. All of the semivariogram calculations and modeling, prediction of zoning of study hydraulic attributes were performed using the GS 5.1 software packages.
Results indicated that all of the studied soil hydraulic attributes belonged to the weak to moderated spatial correlation classes and the spherical model was the best fitted model for their semivariograms (except for Kfs and D that their best semivariogram models were exponential). The sill of all semivariograms ranged between 0.0003 to 0.419 for the S and Kfs, respectively. The nugget effects and the Range parameter of all semivariograms were located between 0.00015 to 0.108 for the S and Фm, and 211 to 6.4 m for Ks and D, respectively. Results also indicated that 3.5 and 50% of total variation of D and Ks was spatially structured and the other was random, respectively. The spatial correlation classes of near saturated soil hydraulic conductivity and soil hydraulic diffusivity were week, whereas, the spatial correlation classes of the other studied soil hydraulic attributes were moderate. Results revealed that the Inverse Distance Weighting method was the most suitable approach for the prediction of all studied soil hydraulic attributes in the present study. Comparison of the calculated statistical evaluation measures (i.e. Determination coefficient, R2, Mean residual error, MRE, mean square error, MSE, Normalized mean square error, NRMSE and geometric mean error ratio, GMER) and the final determined order of precision showed that the most and the least accurate predictions were obtained for Ks and Фm, respectively.
It is suggested in the cases that we need to map the hydraulic attributes or need their quantities in a large number; geostatistical prediction be performed using the limited measurements to reduce the needed time and costs.