Ar-Ar Geochronology in a gneiss dome within the Zagros Orogénic Belt

Exhumation of the Tutak mantled gneiss dome without significant cooling has taken place in a doubly plunging anticline within the Sanandaj-Sirjan HP-LT metamorphic belt in the Zagros Thrust System of Iran. Reconstruction of structural evolution of the Tutak gneiss dome at the contact between Arabian and Iranian plates by ⁴⁰Ar/³⁹Ar geochronology exhibits history of the closure of Neo-Tethyan Ocean. There are two granites of different ages in the core of dome; the oldest corresponds to the central Iranian continental crust and was deformed at about 180 Ma. The younger granite was emplaced in the NE–SW transpression system. The timing of strain-related fabrics and exhumation history of the region illustrates the closure of Neo-Tethys and beginning of continent-continent collision at about 77 Ma, as constrained by a well defined plateau ⁴⁰Ar/³⁹Ar age obtained on biotite. Then, the biotite age corresponds to the second stage of emplacement of the Bendenow granite-gneiss which illustrating repeated orogenic events. Continuing deformation without interruption that by now has been created at about 77 Ma, was largely restricted to the transpression and high proportion of simple shear components relative to the pure shear components along the NE–SW.     

Stochastic Modeling of Groundwater Fluoride Contamination: Introducing Lazy Learners

While it remains the primary source of safe drinking and irrigation water in northwest Iran's Maku Plain, the region's groundwater is prone to fluoride contamination. Accordingly, modeling techniques to accurately predict groundwater fluoride concentration are required. The current paper advances several novel data mining algorithms including Lazy learners [instance-based K-nearest neighbors (IBK); locally weighted learning (LWL); and KStar], a tree-based algorithm (M5P), and a meta classifier algorithm [regression by discretization (RBD)] to predict groundwater fluoride concentration. Drawing on several groundwater quality variables (e.g., concentrations), measured in each of 143 samples collected between 2004 and 2008, several models predicting groundwater fluoride concentrations were developed. The full dataset was divided into two subsets: 70% for model training (calibration) and 30% for model evaluation (validation). Models were validated using several statistical evaluation criteria and three visual evaluation approaches (i.e., scatter plots, Taylor and Violin diagrams). Although Na⁺ and Ca²⁺ showed the greatest positive and negative correlations with fluoride (r = 0.59 and −0.39, respectively), they were insufficient to reliably predict fluoride levels; therefore, other water quality variables, including those weakly correlated with fluoride, should be considered as inputs for fluoride prediction. The IBK model outperformed other models in fluoride contamination prediction, followed by KStar, RBD, M5P, and LWL. The RBD and M5P models were the least accurate in terms of predicting peaks in fluoride concentration values. Results of the current study can be used to support practical and sustainable management of water and groundwater resources.     

Modification of the DRASTIC Framework for Mapping Groundwater Vulnerability Zones

The DRASTIC technique is commonly used to assess groundwater vulnerability. The main disadvantage of the DRASTIC method is the difficulty associated with identifying appropriate ratings and weight assignments for each parameter. To mitigate this issue, ratings and weights can be approximated using different methods appropriate to the conditions of the study area. In this study, different linear (i.e., Wilcoxon test and statistical approaches) and nonlinear (Genetic algorithm [GA]) modifications for calibration of the DRASTIC framework using nitrate (NO₃) concentrations were compared through the preparation of groundwater vulnerability maps of the Meshqin-Shahr plain, Iran. Twenty-two groundwater samples were collected from wells in the study area, and their respective NO₃ concentrations were used to modify the ratings and weights of the DRASTIC parameters. The areas found to have the highest vulnerability were in the eastern, central, and western regions of the plain. Results showed that the modified DRASTIC frameworks performed well, compared to the unmodified DRASTIC. When measured NO₃ concentrations were correlated with the vulnerability indices produced by each method, the unmodified DRASTIC method performed most poorly, and the Wilcoxon–GA–DRASTIC method proved optimal. Compared to the unmodified DRASTIC method with an R² of 0.22, the Wilcoxon–GA–DRASTIC obtained a maximum R² value of 0.78. Modification of DRASTIC parameter ratings was found to be more efficient than the modification of the weights in establishing an accurately calibrated DRASTIC framework. However, modification of parameter ratings and weights together increased the R² value to the highest degree.     

Prediction of River Stage-Discharge Process Based on a Conceptual Model Using EEMD-WT-LSSVM Approach

Water Resources - This study proposed a hybrid pre-processing approach along with a conceptual model to enhance the accuracy of river discharge prediction. In order to achieve this goal, Ensemble...     

Simulating monthly streamflow using a hybrid feature selection approach integrated with an intelligence model

ABSTRACT

Streamflow prediction is useful for robust water resources engineering and management. This paper introduces a new methodology to generate more effective features for streamflow prediction based on the concept of “interaction effect”. The new features (input variables) are derived from the original features in a process called feature generation. It is necessary to select the most efficient input variables for the modelling process. Two feature selection methods, least absolute shrinkage and selection operator (LASSO) and particle swarm optimization-artificial neural networks (PSO-ANN), are used to select the effective features. Principal components analysis (PCA) is used to reduce the dimensions of selected features. Then, optimized support vector regression (SVR) is used for monthly streamflow prediction at the Karaj River in Iran. The proposed method provided accurate prediction results with a root mean square error (RMSE) of 2.79 m³/s and determination coefficient (R² ) of 0.92.     

Forecasting Daily Seepage Discharge of an Earth Dam Using Wavelet–Mutual Information–Gaussian Process Regression Approaches

Because of their sensitive structure, earth dams might face failure due to seepage phenomenon. In order to prevent such failure, some equipment like piezometers are installed in the body or foundation of earth dams. This study investigated the importance of piezometer installation level in dam body or foundation using mutual information–wavelet–Gaussian process regression. 27 Piezometers in three section along with reservoir level were employed to predict one-step-ahead seepage discharge of Zonouz earth dam. The daily data of 1 year of piezometer level and reservoir level were collected for this purpose. In order to find the best possible input combination, three groups of modeling scenarios were defined using piezometers and reservoir level time series. As some input combinations had more than two variables, decomposed time series were imposed into mutual information (MI) tool in order to decrement input variables and find the most correlated input–output features. Afterward, mentioned features were imposed into optimized Gaussian process regression (GPR) to be predicted. Different kernels were selected as core tool of GPR, but results demonstrated the capability of radial basis function (RBF) kernel. GPR–RBF structure were optimized using cross-validation technique. Results indicated that input combination including piezometer level and reservoir level of section II, especially piezometer 203 time series led to the best result among all scenarios.     

Structural Evolution and Halokinesis of Khaje Salt Diapir,North‒West of Iran

Geotectonics - The northeastern part of the Tabriz, Khaje area has been studied to determine the relationship between the orientation of local structures and regional tectonics, and the influence...     

Analysis of the stress regime and tectonic evolution of the Azerbaijan Plateau,Northwestern Iran

The increasing number of earthquakes in recent decades in Northwestern Iran and the determination of the epicenters of these events makes possible to estimate accurately the changing tectonic regime using the Win-Tensor inversion focal mechanism program. For this purpose focal mechanism data were collected from various sources, including the Centroid Moment Tensor catalog (CMT). The focal mechanism and fault slip data were analyzed to determine change in the stress field up to the present day. The results showed that two stages of brittle deformation occurred in the region. The first stage was related to Eocene compression in NE–SW direction, which created compressional structures with NW–SE strike, including the North and South Bozgush, south Ahar and Gushedagh thrust belts. The second brittle stage began in the Miocene with NW–SE compression and caused developing thrusts with N–S trends that were active presently. These stress regimes were created by the counter-clockwise rotation of the Azerbaijan plateau caused by movement on strike slip faults and continuous compression between the Arabian plate, the south Caspian basin and the Caucasus region. Pliocene-Quaternary activity of the Sabalan and Sahand volcanoes as well as recent earthquakes occurred as a result of this displacement and rotational movement. The abundance of hot springs in the Ardebil, Hero Abad and Bostanabad areas also bore witness to this activity.