Study on infiltration rate based on primary particle size distribution data in arid and semiarid region soils

Soil particle size distribution (PSD) is used to estimate some soil processes, soil moisture characteristics, and infiltration rate (IR). Prediction of infiltration rate from soil texture data requires an accurate characterization of PSD. The objective of this study was to determine more important primary particle diameters that control IR. The experiments were conducted using double-ring method with constant head of 5 cm in 15 different soils and three replications. The range of measured IR for studied soils varied from 1.6 to 30.66 cm h^?1. The results indicated that the primary PSD had a significant influence on IR. In other words, most D _n fractions had significant positive effect on the final IR. Among different fractions, D ₃₀, D ₄₀, and D ₆₀ showed higher relationships with IR than the others. These diameters are attributed to particles with diameter of 0.05, 0.08, and 0.16 mm, respectively. The results also showed that increasing the percent of sand have intensified influence on increasing the final IR. Reversely, clay and silt contents showed negative effects on final IR. Furthermore, the CaCO₃ had a meaningful effect on the IR that showed the importance of lime in arid and semiarid regions. Finally, it is revealed that the role of texture was important, especially in behavior of infiltration, runoff, and production capability.     

A proposed geotechnical-based method for evaluation of liquefaction potential analysis subjected to earthquake provocations (case study: Korzan earth dam, Hamedan province, Iran)

During the earthquakes, a number of earth dams have had severe damages or suffered major displacements as a result of liquefaction, thus modeling by computer codes can provide a reliable tool to predict the response of the dam foundation against earthquakes. These modeling can be used in the design of new dams or safety assessments of existing ones. In this paper, on the basis of the field and laboratory tests and by combination of several software packages a seismic geotechnical-based analysis procedure is proposed and verified by comparison with computer model tests and field and laboratory experiences. Verification or validation of the analyses relies to the ability of the applied computer codes. By using the Silakhor earthquake (2006, M _s 6.1) as a basis in order to check the efficiency of the proposed framework, the procedure is applied to the Korzan earth dam of Iran which is located in Hamedan Province to analyze and estimate the liquefaction and safety factor. Design and development of a computer code by the authors which was named as the ??Abbas Converter?? with graphical user interface which operates as logic connecter function that can compute and model the soil profiles is the critical point of this study. The results confirmed and proved the ability of the generated computer code on the evaluation of soil behavior during earthquake excitations. Also, this code was able to facilitate this study better than previous ones have, taking over the encountered problem.     

Support vector machines and feed-forward neural networks for spatial modeling of groundwater qualitative parameters

The present study attempts to model the spatial variability of three groundwater qualitative parameters in Guilan Province, northern Iran, using artificial neural networks (ANNs) and support vector machines (SVMs). Data collected from 140 observation wells for the years 2002–2014 were used. Five variables, X and Y coordinates of the observation well, distance of the observation well from the shoreline, areal average 6-month rainfall depth, and groundwater level at the day of water quality sampling, were considered as primary input variables. In addition, nine qualitative variables were also considered as auxiliary input variables. Electrical conductivity (EC), sodium concentration (Na⁺), and sulfate concentration (SO₄ ^2?) of the groundwater in the region were estimated using ANNs and SVMs with different input combinations. The results showed that both ANNs and SVMs work well when the only primary input variable is the well location. The ANN yielded an RMSE of 1.03 mEq/l for SO₄ ^2?, 1.05 mEq/l for Na⁺, and 203.17 μS/cm for EC, using the X and Y coordinates of the observation wells in the study area. In the case of SVM, these values were, respectively, 0.87, 0.87, and 176.68. Considering the auxiliary input variables (pH, EC, and the concentrations of Na⁺, K⁺, Ca²⁺, Mg²⁺, Cl^?, SO₄ ^2?, and HCO₃ ^?) resulted in a significant decrease in the RMSE of both ANNs (0.22, 0.30, and 33.04) and SVMs (0.26, 0.34, and 36.23). Comparing these RMSE values with those of cokriging interpolation technique (0.59, 0.98, and 177.59) indicated that ANNs and SVMs produced more accurate estimates of the three qualitative parameters. The relative importance of auxiliary input variables was also determined using Gamma test. The output uncertainty of ANNs and SVMs were determined using p-factor and d-factor. The results showed that SVMs have less uncertainty than ANNs.     

Prediction of Land Subsidence Under Cyclic Pumping Based on Laboratory and Numerical Simulations

In this study subsidence due to groundwater withdrawal was investigated. Kerman Province in Iran is struggling with land subsidence problem due to extensive groundwater withdrawal mainly for farming. The rate and type of groundwater withdrawal has very important impact on settlement rate. In this research, effective parameters on land subsidence caused by groundwater withdrawal were determined by laboratory tests. Sampling had done up to depth of 300 m mainly with remolded specimens from Shams-abad, Nouq plain in Kerman province. Similar to the field preconsolidation pressure was applied on specimens in the laboratory. Rate of applied stress on prepared specimens was similar to effect of oscillation of groundwater level. In order to model the actual soil behavior in the laboratory, one-dimensional consolidation device (odometer) was adopted for testing. In these tests, the effect of loading caused by seasonal oscillation of groundwater table is considered by means of cyclic loading in the testing which has great effect on rate of settlements. The results of tests show that when the water table level periodically increases and decreases the amount of settlement decrease, comparing with the case when the groundwater table drop to a constant level. In order to predict the further effects of groundwater level oscillation and actual field condition on land subsidence, a finite element model based on Biots’ three-dimensional consolidation theory was developed. After calibration of finite element model with laboratory tests, this model was used for prediction the effect of groundwater level oscillation on actual field conditions.     

Using inverse modeling and hierarchical cluster analysis for hydrochemical characterization of springs and Talkhab River in Tang-Bijar oilfield,Iran

Hierarchical cluster analysis (HCA) and inverse modeling (PH REdox EQuilibrium (in C language) (PHREEQC)) were simultaneously useful approaches in interpreting surface water hydrochemistry within Talkhab River in the Tang-Bijar oilfield, Iran, where large uncertainties exist in the understanding of the water quality system. Q-mode HCA applied to the data revealed three major surface water associations distinguished on the basis of the major causes of variation in the hydrochemistry. The three water groups were classified as upstream waters (group 1: Ca–SO₄), intermediate waters (group 2: Ca–SO₄–Cl), and downstream waters (group 3: Na–Cl). Geochemical reaction models were constructed using PHREEQC to establish the reactions associated with the different mineral phases through inverse modeling. The hydrochemical compositions of the water groups and the mass balance calculations indicate that the dominant processes and reactions responsible for the hydrochemical evolution in the system are (1) dissolution of evaporites, (2) precipitation of carbonate minerals, (3) silicate weathering reactions, (4) limited mixing with saline water, and (5) ion exchange.     

Prospectivity modeling of porphyry copper deposits: recognition of efficient mono- and multi-element geochemical signatures in the Varzaghan district,NW Iran

Acta Geochimica - The Varzaghan district at the northwestern margin of the Urumieh–Dokhtar magmatic arc, is considered a promising area for the exploration of porphyry Cu deposits in Iran. In...     

Geochemical Aspects of Hypogene Hydrothermal Alteration Zones in the Chol‐qeshlaghi Area,NW Iran: Constrains on REEs

Chol-qeshlaghi altered area lies in the northwestern part of the post-collisional Urumieh-Dokhtar magmatic arc, NW Iran. Pervasive silicic, argillic, phyllic and propylitic altered zones appears to be intimately affiliated to the fluids derivative of upper Oligocene Khankandi granodiorite. This paper is dedicated to the identification of geochemical characteristics of hydrothermal alterations, focusing on the determination of the mass gains and losses of REEs, to gain significant insights regard...