hydraulic conductivity

Evaluation of drainage systems helps researchers and planners to examine the strengths and weaknesses of these systems and improve them in future plans. For this reason, in the present study, the performance of the drainage system implemented in the Gamboa irrigation and drainage network, located in the agricultural lands of Hamidieh city, was evaluated. In this research, she investigated the changes in water table level and salinity exit from the soil profile and measured the design indicators of underground drains. In order to read the water level fluctuations of the reservoir, observation wells were installed at intervals of 0.3, 0.8, 1.5, 2.5 and 15 meters and in the middle of the underground drains. The installation intervals of the observation wells between two drainage lines were 1/4L, 2/4L, 3/4L and 25 meters from the drain outlet. The results showed that The average hydraulic conductivity value in fields was 0.95 in reality and 0.89 m/day in design conditions, and the drainage coefficient value was 2.36 in reality and 2.6 mm/day in design conditions. Also, the examination of the proposed relationships for the design of the drainage system showed that Damm's relationship had the highest accuracy and Van Schilfgaard's relationship had the highest error in determining the water level. The control index of the depth of the ponding surface was between 0.82 and 1.11 and the control index of salinity exit from the soil was acceptable between -0.3 and -0.9. Product performance index was obtained in the range of (0.86-0.78). In total, after four years of the implementation of this drainage system, the productivity of wheat production increased by 62% from 2.55 tons per hectare to 4.1 tons per hectare compared to the conditions without drainage.

Oil pollution is recognized as one of the significant threat to soil fertility and plant production. Pollution caused by petroleum hydrocarbons, reduces the hydraulic conductivity of soils, leading to increased erosion and runoff, and decreased plant growth. One practical approach for remediating soils contaminated with petroleum hydrocarbons is using biosurfactant-producing microorganisms that can degrade these compounds. This study examined the efficacy of a microbial consortium comprising the bacterial strains Dietzia aerolata PS14B1, Kocuria salina PS12B2, and Mesobacillus harenae PS9D12 in altering the permeability coefficient of soil contaminated with high pollution (TPH). In the hydrocarbon growth and degradation test in the mineral base medium after seven days of incubation, the results showed that strains PS14B1, PS12B2, and PS9D12 were successful in reducing Total Petroleum Hydrocarbons (TPH) by 25.63%, 24.11%, and 22.83%, respectively, which was significantly different from the control (P<0.05).  The inoculation of the bacterial strains into the soil and subsequent 30-day incubation demonstrated a significant increase in soil hydraulic conductivity, from 1.18 cm h-1 to 9.12 cm h-1, compared to the control treatment (3.24 cm h-1). These findings suggest that the bacterial consortium holds potential for the sustainable remediation of oil-contaminated sites and the enhancement of soil permeability in polluted areas.

Soil is considered as one of the main factors in the production of agricultural products, To carry out this research, an area of ​​50,000 hectares is selected in Ghaderabad plain. Ghaderabad plain is one of the important and prone areas of Kerman province for the cultivation of crops, and the selection of a suitable planting pattern can be effective in the optimal use of water and soil resources. In order to carry out the project, soil samples were prepared up to a depth of 150 cm, and the necessary physical and chemical tests were performed on the samples. After completing the field operations and receiving the results of the laboratory analysis of the soil samples, it has been determined the type and amount of restrictions in each of the components of the land units and for each of the main uses. Finally, using Excel software, some characteristics of soil profiles such as hydraulic conductivity, percentage of lime, organic carbon and clay in cultivated and virgin lands were compared and the effect of land use change was evaluated. Examining the changes in the physical and chemical characteristics of the soil after the change of use can not only represent the effects and consequences of this transformation, but it can also be a guide in determining how to face this problem and prevent further degradation and destruction of the soil.

Design of irrigation and drainage networks requires accurate estimation of relevant parameters, which is made possible using new estimation methods. Important parameters useful in determining drain spacing include the depth of the hardpan and the hydraulic conductivity of the area. New interpolation methods based on geostatistics take into account spatial variations in variables, thereby reducing the inaccuracies of traditional methods. Therefore, this study uses geostatistical and Thiessen's polygon methods, which is a common method in drainage design, to estimate hardpan depth and hydraulic conductivity parameters for estimating drainage distance. The results show that simple kriging and universal kriging methods with determination coefficients of 0.83 and 0.89 and root mean square errors of 0.26 and 2.67 (meters) achieve the best results for determining the depth and permeability of impermeable layers, respectively. Also, the best fitted variogram respectively were calculated as an exponential variogram with zero nugget effect and 1.37 sill and a spherical variogram with a sill of 0.027 and 0.003 nugget effect. showed the strength of the spatial structure of the area and the full impact of the structured component on the variogram model of the parameters. Also, the results showed that the distance of drains is uniform and non-uniform condition at different depths of the installation of drains, in kiriging method were calculated less than thiessen method. And with taking into account areas with hydraulic conductivity of more than one meter per day, the difference between the two methods in estimating the distance of the drains increased to 11%.

Surface runoff is the main factor eroding soil which causes sheet and interrill erosion in gentle slopes. It started when water infiltration would be lower than rainfall intensity during rainfall event. Soil properties can vary amount and rate of surface runoff during rainfall. This study was carried out to investigate the role of soil properties in amount of surface runoff generation and its temporal variations in different soil textures. Eight soil textures placed in 1 m × 1.2 m plots were exposed under seven simulated rainfalls with 60 mm h-1 in intensity for 60 min. Runoff samples were collected for 5-min intervals during each event. Results indicated that various soil physicochemical properties are different among the soils. Surface runoff varied among the soils and the highest runoff (55.51 mm) was in clay, while sand didn’t produce any runoff during rainfall. Surface runoff production rate temporally increased during rainfall and reached to a pick after about 30-50 min. Time to pick was very short (30 min) in fine textured soils. The correlation analysis showed that surface runoff is significantly affected by sand, silt clay, bulk density, gravel, hydraulic conductivity, calcium carbonate, gypsum and ESP. With an increase in soil hydraulic conductivity, surface runoff was inversely differed. Linear regression analysis showed that sand percentage is the most important factor controlling surface runoff in semi-arid soils. Controlling surface runoff in the soils with lower percentage of sand as well as hydraulic conductivity is essential to prevent sheet and interrill erosion in semi-arid soils.

Nowadays, by increasing the water demand in different sectors, the withdrawal amount from groundwater resources is increasing leading to more drawdown of Markazi province aquifers. One of the most suitable methods for the optimal management of groundwater resources is the analysis of the behavior of aquifers in various conditions using mathematical models. The objective of this paper is to investigate the effects of withdrawal for agricultural and industrial consumptions on the groundwater level of the Shazand plain located in Markazi Province and the impact of a 20% increase in irrigation efficiency of farms in the case of the development of under pressure and low-consumption systems using the GMS numerical model.

First, the conceptual and numerical model of the Shazand aquifer was executed in the GMS software and calibrated in the steady state. Then, the model was recalibrated in a transient state for the statistical period from October 2015 to September 2019. To examine the reactions of the model to the changes of important and effective parameters, the sensitivity analysis of the model was performed and the model was verified for the statistical period of October 2019 to September 2021. Then, the changes in the groundwater level in the aquifer under two reference management scenarios and increasing irrigation efficiency were investigated and compared. In the reference scenario assuming the continuation of the current conditions and in the efficiency increase scenario assuming a 20% increase in irrigation efficiency, the simulation of changes in the groundwater level in the entire Shazand plain for the upcoming 20 years from October 2021 to September 2041 was carried out.

Based on the obtained results, the RMSE error value related to the steady state recalibration is about 0.7 meters and the average RMSE error value in the transient state in all months of simulation in two recalibration and validation periods is less than 0.6 meters, which shows the high accuracy of the model in simulating the groundwater level in the whole plain. The sensitivity analysis showed that the changes in specific yield and hydraulic conductivity parameters have the greatest effect on the fluctuations of groundwater in the whole plain. The results showed that in the reference scenario, the drop in the groundwater level at the end of the 20-year operation period is 3.95 meters. In the scenario of a 20% increase in efficiency, with the reduction of extraction from wells due to the increase in irrigation efficiency, the amount of drop will reach 2.76 meters, in which case the amount of drop will be mitigated by 1.2 meters.

According to the results, the highest drop in the groundwater level in both reference and increase in efficiency scenarios in the central areas of the plain is 9.2 and 6.9 meters, respectively, and the lowest drop in the western areas of the plain is 1 and 0.5 meters, respectively. Considering that the agricultural sector has the greatest impact on the level drop in the aquifer in the central areas of the plain, it is better to focus management plans to control withdrawal from the aquifer, such as increasing efficiency or modifying the cultivation pattern, on this sector. In case of the implementation of systems under pressure and increasing efficiency in the plain, the amount of drawdown in the region will be mitigated to some extent, but the problem will not be solved and it is necessary to implement supplementary programs to cultivate high consumption plants instead of high consumption crops and in the industry sector instead of extracting groundwater, treated municipal wastewater should be used.

Drying a large area of ​​Lake Urmia is considered a serious environmental challenge for the region and the country. Therefore, the knowledge of the physical and mechanical characteristics of Lake Urmia bed material is necessary to do engineering activities to regenerate it. One of the major problems related to lake bed sediments is the effect of the high percentage of organic matter with low shear strength, high salt concentration, and solubility of some matters on soil behavior. In this article, after performing different field and laboratory tests to determine soil properties, the Guelph penetrometer (2800KI) was tested up to a distance of 1 km from the width of the lake and in different areas of the lake (Hyderabad in Naghadeh, Chichest in ​​Urmia and the ​​Urmia-Tabriz causeway). In these three areas of the lake, by digging 20 wells with a radius of 4 cm and a depth of 25-30 cm at different intervals in a zigzag pattern up to a length of 1 km towards the inside of the lake, hydraulic conductivity was measured using a Guelph permeameter in two hydraulic heads of 5 and 10 cm for each borehole with two replications. The study results showed that the hydraulic conductivity for the two areas of Hyderabad and Chichest of Urmia, on average, for loamy soils, mainly near the shore of the lake, was estimated to be 0.175 cm/h; 5.34 cm/h for layered sand and 1.89 cm/h for the ​​area around Urmia-Tabriz causeway.

Changing the amount of exploitation in order to increase productivity and reduce groundwater extraction in the plains of Iran has had a positive effect on water balance. Some management strategies, such as well relocation, have been able to reduce the effects of water table drawdown. Simulation of water resources systems has an effective role in studying the effects of drought and determining the temporal and spatial constraints of water management. Joint functions are tools that join or “couple” multivariate distribution functions to their one-dimensional univariate (marginal) distribution functions. The copula function is capable of exhibiting the structure of dependence between two or more random variables and has recently emerged as a practical and efficient method for modeling the general dependence in multivariate data. In addition, in the field of hydrogeological studies in recent years, a lot of research has been done to investigate some specific aspects of groundwater simulation such as exploitation optimization, artificial recharge, underground dam, quantitative and qualitative simulation of groundwater, economic studies of water supply and demand. In this paper, the framework of a probabilistic multivariate decision model based on long-term rainfall information and extraction of effective variables in aquifer recharge are considered. The relationships and constraints governing the severity and depth of precipitation with emphasis on the hydrodynamic characteristics of the aquifer and also the use of real-time information updating system, a decision model for the design of surface artificial recharge structure is developed and simulated. The main difference considered in this study in probabilistic rainfall planning as a long-term goal for the sustainability of water resources management is the description of special conditions and constraints of the aquifer. Rafsanjan plain located 110 km from Kerman has an unlimited aquifer with an area of 4108 km2. This plain is located between 252 ° 54 to ´34 ° 56 east longitude and 151 ° 29 to ´31 ° 31 north latitude at an altitude of 1400 to 3443 m above sea level and in the northeast of Kerman province. The three plains of Rafsanjan, Noogh and Anar are located in this area, which does not have a permanent river and is a source of water from the aquifer. About 620 million cubic meters (MCM) of groundwater is discharged annually by 1289 existing wells. According to long-term statistics, the volume of groundwater resources in the Rafsanjan area is estimated at about 430 MCM, with an annual overexploitation of 190 MCM. 8 locations were selected for the construction of surface artificial recharge structures that can collect rainfall and upstream runoff. It should be noted that the surface slope and hydraulic gradient are influential components in the movement and infiltration of water, which are estimated using the topographic map and water table. The volume of water demand based on groundwater exploitation annually has been estimated in the region of each point. Moreover, the priority of water supply is determined based on the population living in each area. Groundwater level simulation in Rafsanjan plain aquifer from 1997 to 2020 was performed using 35 active piezometer data. The first 17 years were used for calibration and the last 4 years for verification. Seasonal stress periods and daily time steps were considered for the calculations. The results showed that this method can be a managerial strategy for groundwater balancing in the event of seasonal and scattered rainfall. The aquifer transmissivity which reaches more than 400 m2/day, indicates the storage capacity and water movement. Bivariate frequency analysis showed that in a 100-year return period, there is a possibility of rainfall with a depth of about 115 mm or an intensity higher than 70 mm/day. This rainfall can increase the groundwater level by an average of 2 m in the center of the aquifer. Moreover, beneficiaries are able to reduce drought stresses and control their management significantly by performing optimal planning.

The decrease in rainfall, the increase in drought and the development of agriculture in recent years have led to an increase in the consumption of underground water and an increasing decline in water levels. In this study, using version 10 of GMS software, the condition of Qazvin Plain aquifer was modeled in two stable states for October 2017 and unstable from October 2017 to September 2018. The sensitivity analysis of the model was performed with respect to the parameters of hydraulic conductivity and specific yield, and these parameters were determined after calibration and validation of the model. The sensitivity analysis of the model with respect to the two mentioned parameters shows that the model is more sensitive to changes in hydraulic conductivity compared to changes in specific yield. The root mean square error in stable and unstable state was 0.84 and 1.06 m, respectively, and the absolute mean error was 0.66 and 0.75 m, respectively, which shows the high accuracy of the model simulation. The average value of hydraulic conductivity in the aquifer area was estimated as 14.06 m/day and specific drainage was 0.064. Then the underground water level in 6 scenarios of changing the irrigation systems (maintaining the existing situation, increasing the irrigation level under pressure, changing the systems to surface, changing the systems to rain, changing the systems to drip and irrigation with 100% efficiency) was simulated. The results showed that assuming that the underground water extraction is constant, in the surface irrigation scenario, the underground water level will be at its highest level with 30% return water and in drip irrigation conditions at its lowest level with 3.6% return water.

Increasing groundwater consumption and water table level leads to changes in hydrodynamic properties of the aquifer especially the parameters of hydraulic conductivity and specific yield. In this study, that was conducted in 2021 using GMS model version. 10 in Qazvin aquifer, the coefficients of hydraulic conductivity and specific yield of aquifer in three census periods of 2002, 2009 and 2018 after calibration and validation of the model in two cases steady and unsteady were determined and compared. The root mean square errors in the steady state  for the proposed periods were 0.86, 0.73 and 0.84 m, respectively, and in the unsteady state were 1.7, 0.93 and 1.06 m, respectively. That shows high accuracy of the model simulation. The average hydraulic conductivity in the aquifer was estimated for the years of 2002, 2009 and 2018 which was 19.13, 16.85 and 14.06 meters per day and the average specific yield was 0.078, 0.071 and 0.064, respectively. The results showed that over time and by decreasing the groundwater level, the parameters of hydraulic conductivity and specific yield decrease. Since 2015 due to the measures taken for balancing and artificial recharge plan, the slope rate of hydraulic conductivity has decreased from 0.38 to 0.31. Also the slope rate of special discharge has decreased from 0.00117 to 0.00078. The main reason for this decreasing trend can be the destruction of soil structure and effective reduction of porosity indicating the irreversibility of the aquifer to its previous state. Therefore, it is necessary to pay attention to these changes regarding the recharge of aquifers and return water from irrigation systems.

Tillage and puddling are important operations of paddy field. Puddling is an important and common method in bed preparation for rice seedling cultivation in paddy lands, which is done with rotavator. To investigate the changes in soil physical and hydraulic parameters, an experiment was conducted as a split plot based on a randomized complete block design with three replications in Ghaemshahr, Iran. In this study, the rice field was under two main treatments, T1 (without tillage) and T2 (with tillage) and four sub-treatments of passing the rotavator, P1 (once), P2 (twice), P3 (three times) and P4 (four Times). Different levels of puddling on the paddy field with loam texture were applied and the parameters of infiltration, hydraulic conductivity, gravimetric water contents and dry soil bulk density were measured. Also, at the end of the cultivation season, 1000-grain rice weight was calculated for each treatment. The results showed that in both parameters of permeability and hydraulic conductivity, the T2 treatments had the lowest amount of infiltration and hydraulic conductivity. Also, in both parameters, with increasing the intensity of puddling, the rate of infiltration and hydraulic conductivity decreased significantly.  By applying tillage and increasing the intensity of puddling, a decreasing trend in the bulk density and an increasing trend in soil water content were observed. So that, the tillage treatment with high puddling (P4) had the maximum weight moisture (28.67 %). Different tillage methods did not show any effect on the weight of 1000-grains rice. In contrast, different puddling treatments had a significant effect on the weight of 1000-grains rice and in high puddling treatment the highest weight of 1000-grains rice (28.38 g) was observed showing the positive effect of high levels of puddling on this parameter. Finally, it can be concluded that tillage and puddling reduce water loss and thus increase water productivity in the rice cultivation.

In groundwater modeling, to input the hydraulic conductivity parameter, the aquifer is usually divided into some zones and for each zone a value is considered for this parameter. However, the field measurements of this parameter are performed only in some places, and therefore its generalization to other areas is associated with uncertainty. The aim of this study was to investigate the uncertainty of the hydraulic conductivity parameter in modeling the aquifer of Qom plain. For this purpose, using the MODFLOW groundwater model, the model of this aquifer was constructed and calibrated in a steady state simulation with a value of RMSE = 2.95 m for computed groundwater levels. Then the model was run using Null Space Monte Carlo to identify areas of hydraulic conductivity that calibrate the model with the same error rate as the original model. The results showed that there are eight other different zones of hydraulic conductivity that if used, the model will still be calibrated with the same error rate. The highest standard deviation of the hydraulic conductivity parameter for these eight zones was about 28 meters per day in the central and northern areas of the aquifer and the lowest standard deviation was less than 1 meter per day that occurred in the southern and eastern areas of the aquifer. This means high uncertainty of the hydraulic conductivity parameter in the central and northern areas and less uncertainty in the southern and eastern areas. Given that no significant relationship was found between the amount of uncertainties of hydraulic conductivity and the location of piezometers, so it can be concluded that increasing the number of piezometers in the model does not help to reduce the uncertainties of the hydraulic conductivity parameter and therefore more measurements of this parameter in different parts of the aquifer is needed.

Due to the vulnerable nature of earthen dams , all factors affecting the stability of these dams should be studied. Consecutive wetting and drying of the earthen dam core is one of the important factors that can affect the physical and mechanical parameters of the dam core. These changes increase the subsequent risks such as leakage, piping and subsidence. This is especially happen in arid and semi-arid regions such as Iran. Various researches have been done in this field and some of these researches have provided suitable mathematical models for their data, but because the results of each research related to the studied soil are specific to the same study, these models can be unusable for other data. In the present study, after collecting 866 laboratory data from 23 researches, the effect of wetting and successive drying of clay dam cores on physical-mechanical parameters was investigated and multivariate mathematical relationships between physical-mechanical parameters and number of wetting and drying were investigated. This study showed that the effect of wetting and drying on mechanical parameters is very important and should be considered in the analysis of embankment dam structures.

Hydraulic conductivity of soils is one of the most important parameters in designing soil structures, water, and environmental resources management. Hydraulic conductivity in the soil varies with the size of their particles. Several studies by different researchers on fine-grained soil hydraulic conductivity and coarse-grained soils are done. In some studies, the methods and materials used to reduce soil hydraulic conductivity. On the other hand, nanoclays are nanoparticles of layered mineral silicates. Depending on chemical composition and nanoparticle morphology, nano clays are organized into several classes such as montmorillonite, bentonite, kaolinite, hectorite, and halloysite(Majeed and Taha, 2013). Organically modified nanoclays (organoclays) are an attractive class of hybrid organic-inorganic nanomaterials with potential uses in polymer nanocomposites, as rheological modifiers, gas absorbents, and drug delivery carriers(Abbasi et al, 2016).Plate-like montmorillonite is the most common nanoclay used in materials applications. Montmorillonite consists of ~ 1 nm thick aluminosilicate layers surface-substituted with metal cations and stacked in ~ 10 µm-sized multilayer stacks. Depending on the surface modification of the clay layers, montmorillonite can be dispersed in a polymer matrix to form a polymer-clay nanocomposite. Within the nanocomposite individual, nm-thick clay layers become fully separated to form plate-like nanoparticles with a very high (nm × µm) aspect ratio.In this study, the effect of different amounts of montmorillonite nano clay (0.25, 0.5, 0.75, and 1%) on the hydraulic conductivity in three different densities (85, 90, and 95%) of sandy and clay soils have been investigated experimentally.

The aim of this study was to investigate the effects of the Garmsiry water transfer project (97 MCM per year from Sirvan River) on the behavior of the Mehran aquifer. For this purpose, the Groundwater Modeling System (GMS 7.1), which is one of the most suitable tools to simulate the groundwater level, was used. To develope the GMS model, input data including; aquifer boundary, Digital Elevation Model (DEM), bedrock level, groundwater level, groundwater withdrawal from wells, hydraulic conductivity, and groundwater recharge layers were prepared by ArcGIS 10.4. These layers were used to conceptual model construction using the MODFLOW codes in GMS interface. For steady and transient state calibration, and validation of the model, groundwater level changes resulting from the model are compared with piezometric measurements for the period Oct-2016, 2016-2017, and 2017–2018, respectively. The results showed a good accuracy in calibration and validation model, respectively, between the simulated and observed groundwater levels (ME=0.12, RMSE=0.84) and (ME=0.57, RMSE=1.4). Three scenarios including, 10, 15, and 20 percent of agricultural water return were conducted to evaluate the effects of Garmsiry water transfer project. The results showed that the groundwater level of Mehran aquifer will be increased 1.43, 2.22, and 3 meter per year in scenarios 1 to 3, respectively. This issue is very important along with the low storage coefficient of the Mehran plain aquifer, and can be a warning for severe drainage problems in the near future. The results of this study showed that the central and southern parts of the plain would have drainage problems less than ten years after the operation of the irrigation network.

As one of the main indicators of soil quality, structure is related to hydraulic parameters which plays a significant role in predicting and estimating them (Pachepsky et al., 2008). Mohawesh et al, (2017) stated that hydraulic properties are key factors in the movement of water and the transport of pollutants, and the soil structure has a significant effect on the storage and movement of water in the soil. Tension infiltrometer is an effective tool to measure infiltration rate and the flow of water into pores using suctions less than 0 cm, where the macro and meso pores have highest rate of hydraulic activities for water and solution transportation. The measurement of hydraulic conductivity in different suctions is important for characterizing different aspects of unsaturated and near-saturated water in the soil. Although the hydraulic properties of the soil have been investigated from different aspects and by different methods, the role of soil structure specifically from comparison viewpoints of different types of structures and their effects on hydraulic properties has not yet been studied. The aim of this study was to measure and evaluate the hydraulic properties and quantitative parameters describing the water conductive active pores using tension infiltrometer in near-saturated condition of different soil structures.

Prediction of bacteria transport to groundwater is very important to prevent water resources from coliform bacteria pollusion. The objective of this study was to investigate the effectiveness of microbially induced calcium carbonate precipitation (MICCP) in preventing the transport of Escherichia coli as an indicator coliform. For the MICCP process, the sand sample was poured into PVC tubes (with inside diameter of 4.8 and height of 14.92 cm) and incubated for 3 days in the presence of Sporosarcina pasteurii. After the stablishment of steady-state flow, 0.1 pore volume of Escherichia coli suspension (108 CFU/mL) was added to the sand column and the leaching was followed with distilled water. The column effluent was sampled in 0.1 to 5 pore volume. After leaching, the sand column was sliced into five sections (~3 cm), and the number of E. coli trapped in each slice was measured using the plate count method in EMB agar culture medium. Leaching was also carried out in control sand column. The effect of MICCP treatment and its interaction with pore volume was significant (p<0.05) on Escherichia coli count in effluent. The effect of depth and its interaction with MICCP treatment were significant (p<0.05) on E. coli residuals and bioprecipitated calcium carbonate in the column. Overall, the role of biopreciptated calcium carbonate was significant in bacteria filtration, as it decreased the sand column hydraulic conductivity and reduced the number of E. coli in column effluents.

Soil saturated hydraulic conductivity (Ks) can be estimated from surrogate data such as soil texture, bulk density and organic carbon and CaCO3 contents using regression (Reg-PTFs) and artificial neural networks (ANN-PTFs) pedotransfer function (PTF). Saturated hydraulic conductivity was measured by falling head method in 100 soil samples that obtained from Ardabil plain, Iran. After performing physicals and chemicals analysis on soil samples, the data were divided into two sets of training (80 samples) and validation data (20 samples). Regression models were created by SPSS software, stepwise method and neural networks models were created by Neurosolution software. Statistics criteria such as coefficient of determination (R2), root mean square deviation (RMSE) and Akaike information Criterion (AIC) were determined. Input variables in the best regression models were sand, silt and bulk density. The best neural network models were obtained from the input variables that include bulk density, geometric mean and standard deviation of soil particle size distribution. The values for R2 and RMSE in training and testing data set for the Reg-PTF were 0.53, 0.074 and 0.51, 0.052 and for the ANN-PTF they were 0.84, 0.04 and 0.73, 0.06, respectively. In this research all independent variables such as bulk density, particle density, CaCO3, geometric mean and standard deviation of the particle size distribution included as inputs for development of Reg-PTFs and ANN-PTFs. The amount of R2 and RMSE for training and testing data set equal 0.87, 0.036 and 0.58, 0.076, respectively. Results showed that the ANN-PTF (R2= 0.84) performs better than the Reg-PTF (R2= 0.53) in this case. It was also found that when all independent variables were used as inputs in the neural ANN-PTF the values of R2 and RMSE (0.87 and 0.036) have been improved in the training data set.

The water movement in the aquifer is studied using the basic equations of flow, i.e. Darcy, continuity and mass survival equations, which are differently analyzed in the case of confined and unconfined aquifers. In these equations, hydrodynamic coefficients and other characteristics of the aquifer are used. Therefore, the determination of hydrodynamic coefficients of aquifer is necessary for groundwater studies. The most important characteristics of the aquifer i.e. hydrodynamic coefficients can be determined across the aquifer using modeling. If the aquifer model is properly provided, it can be a useful tool for better recognition of aquifer characteristics and also predicting the impact of different management plans on the water resources of the region. In this study, groundwater modeling was performed to determine the hydrodynamic coefficients in the unconfined aquifer of Kermanshah plain using GMS 7.1 software. The results showed that the amount of hydraulic conductivity in the Kermanshah plain aquifer varies from 0.1 to 30 meter per day and the amount of specific yield varies from 0.02 to 0.4. The amounts of computed water table by the model and the observed water table in the piezometers have high correlation and the root mean square error value is always less than one, which indicates the acceptable accuracy of the model for simulating the aquifer status.

This research was carried out to consider the effects of recreational human trampling on some soil physical and hydraulic properties in Fandoghloo Forest Park of Ardabil. A completely randomized design was conducted with three treatments of no trampling, moderate trampling and intensive trampling at five replicates.Water infiltration into soil under unsaturated condition was measured at the matric suctions (h) of 2, 5, 10 and 15 cm using tension infiltrometer. The infiltration data was modeled using Wooding method and then saturated hydraulic conductivity (Ks) and macroscopic capillary length (λc) using Gardner equation were calculated. The results showed that although trampling levels could not significantly affect the unsaturated hydraulic conductivity and soil sorptivitiy at different levels h, Ks and λc,but intensive recreational human trampling significantly decreased organic carbon (68.62%), total porosity (25.42%), field capacity moisture (46.81%), permanent wilting point moisture (51.72%) and final infiltration rate at h=15 cm (50%) and increased bulk density (46.07%) and soil penetration resistance (75.57%) in relation to the no trampling treatment; as a result, intensive recreational human trampling reduced physical and hydraulic quality of the forest soil.