Hydrogeological assessment of the Tabarteh fault zone by physicochemical analysis and multivariate statistical methods

Hydrogeologically, faults may impede, conduit, exert no influence, or may play a combination of these roles on groundwater flow. The object of this paper is to study the hydrogeological role of the Tabarteh fault, which is located on the border of Zagros and Central Iran tectonic zones in an alluvial aquifer. The recorded data of water table levels, chemical parameters, and discharge rate of wells, in addition to geological maps and geophysical results, were collected and evaluated. The outcrop of travertine in limited areas and the emergence of a few small springs within the alluvium show a barrier role of the fault in the groundwater flow. The spatial analysis of chemical components, head time series, and groundwater flow direction assessment demonstrated that the fault acts as both a barrier and a non-barrier in different sections. The multivariate statistical methods of cluster and discriminant analyses also confirm the dual role of the fault.     

Monitoring and prediction of land use/land cover changes using CA-Markov model: a case study of Ravansar County in Iran

Human‐induced land use/land cover (LULC) changes are among the most important processes that shape the dynamics of the earth’s surface. This phenomenon, which is occurring at an astonishing rate, and its consequential environmental impacts have become an important area of research for scientists.Therefore, a wide range of methods and models have been developed to detect and predict these alterations, among which cellular automata (CA) models such as the CA‐Markov model, due to their affinity to geographic information system (GIS) and remote sensing (RS), are appropriate for detailed resolution modelling and simulating dynamic spatial processes. In Iran, the district of Ravansar has undergone severe LULC changes recently, thus to take the necessary precautions, decision‐makers need to predict and determine the extent of these changes. In this study, using spatial analysis methods the LULC changes in Ravansar were investigated from 1992 to 2015. Subsequently, the CA‐Markov model was applied to simulate the spatial pattern changes of LULC until 2030. Our results indicated that from 1992 to 2015, this region has witnessed a noticeable increase in the areas of the built‐up and agricultural lands (both aquatic and non‐aquatic), resulting in the decrease of the gardens, range, and bare lands. The simulated LULC map showed that this trend will continue due to more urbanization and development of agricultural areas.     

Local site effect of a clay site in Shiraz based on seismic hazard of Shiraz Plain

Propagation of seismic waves through soil layers would drastically change the frequency content and amplitude-based features of ground motions at the surface. These alterations are known as seismic site effects. Computation of site effects of high-populated areas such as large cities is of great importance (e.g., it is used in development of seismic microzonation of a region). Shiraz is one of the most populous cities of Iran and is located in a high seismic hazardous region. A representative clay site in this city is selected to assess local site effects. The time series and random vibration theory procedure in the frequency domain are implemented to analyze the aforementioned site. Furthermore, the nonlinear dynamic soil behavior is simulated by the equivalent linear method and the nonlinear method via DEEPSOIL program. Three types of soil column uncertainties such as shear wave velocity, modulus reduction, and damping ratio of soil layers as well as depth of underlying rock half-space (D _bed) are considered herein. The mean amplification and standard deviation of natural logarithm of amplification factors are computed for a variety of analysis types. The results of the current study show that the computed mean and standard deviation of amplification factor in ln units by considering only V _S uncertainty are in good agreement with the corresponding ones by considering V _S and modulus reduction and damping ratio variabilities simultaneously for the studied site. Furthermore, it seems that the effect of bedrock depth in definition of spectral shapes of the Iranian seismic building code should be taken into account.     

Hydrodynamic Tidal Model of the Persian Gulf Based on Spatially Variable Bed Friction Coefficient

The aim of this study is to develop a two-dimensional hydrodynamic tidal model for the Persian Gulf (PG2017) using 2D-MIKE21 software. The advantages of present study is accounting for the spatial variation of bed friction coefficient besides a precise bathymetry together with a 23-year of combined records of satellite altimetry data. We found that the bed friction coefficient has a significant effect on sea level changes in the region under our modeling consideration. Since the tidal behavior in the northern part of the Qeshm Island is significantly different from the other parts of the Persian Gulf, to present a more accurate hydrodynamic tidal model, the Gulf is divided into two regions where the bed friction coefficient is modeled separately for each region. The root mean square value of the differences between the amplitude of dominant constituents; M2, S2, K1, and O1 derived from the PG2017 model and that of 98 altimetry and coastal tide gauge stations are respectively equal to 1.6, 1.9, 2.8, and 1.3?cm. Moreover, comparing the PG2017 model efficiency with the FES2014, OSU12, EOT11a, DTU10, and Admiralty models shows that the PG2017 model has an improvement of 22.1%, 47.2%, 43.2%, 44.2%, and 57.6% in terms of relative error, respectively.     

Statistical analysis of surface urban heat island intensity variations: A case study of Babol city,Iran

The urban heat island is considered as one of the most important climate change phenomena in urban areas, which can result in remarkable negative effects on flora, concentration of pollutants, air quality, energy and water consumption, human health, ecological and economic impacts, and even on global warming. The variation analysis of the surface urban heat island intensity (SUHII) is important for understanding the effect of urbanization and urban planning. The objective of this study was to present a new strategy based on the Shannon’s entropy and Pearson chi-square statistic to investigate the spatial and temporal variations of the SUHII. In this study, Landsat TM, ETM+, OLI and TIRS images, MODIS products, meteorological data, topographic and population maps of the Babol city, Iran, from 1985 to 2017, and air temperature data recorded by ground recorder devices in 2017 were used. First, Single-Channel algorithm was used to estimate land surface temperature (LST), and the maximum likelihood classifier was employed to classify Landsat images. Then, based on LST maps, surface urban heat island ratio index was employed to calculate the SUHII. Further, several statistical methods, such as the degree-of-freedom, degree-of-sprawl and degree-of-goodness, were used to analyse the SUHII variation along different geographic directions and in various time periods. Finally, correlation between various parameters such as air temperature, SUHII, population variation and degree-of-goodness index values were investigated. The results indicated that the SUHII value increased by 24% in Babol over different time periods. The correlation coefficient yielded 0.82 between the values of the difference between the mean air temperature of the urban and suburbs and the SUHII values for the geographic directions. Furthermore, the correlation coefficient between the population variation and the degree-of-goodness index values reached 0.8. The results suggested that the SUHII variation of Babol city had a high degree-of-freedom, high degree-of-sprawl and negative degree-of-goodness.     

Monthly suspended sediment load prediction using artificial intelligence: testing of a new random subspace method

ABSTRACT

The predictive capability of a new artificial intelligence method, random subspace (RS), for the prediction of suspended sediment load in rivers was compared with commonly used methods: random forest (RF) and two support vector machine (SVM) models using a radial basis function kernel (SVM-RBF) and a normalized polynomial kernel (SVM-NPK). Using river discharge, rainfall and river stage data from the Haraz River, Iran, the results revealed: (a) the RS model provided a superior predictive accuracy (NSE = 0.83) to SVM-RBF (NSE = 0.80), SVM-NPK (NSE = 0.78) and RF (NSE = 0.68), corresponding to very good, good, satisfactory and unsatisfactory accuracies in load prediction; (b) the RBF kernel outperformed the NPK kernel; (c) the predictive capability was most sensitive to gamma and epsilon in SVM models, maximum depth of a tree and the number of features in RF models, classifier type, number of trees and subspace size in RS models; and (d) suspended sediment loads were most closely correlated with river discharge (PCC = 0.76). Overall, the results show that RS models have great potential in data poor watersheds, such as that studied here, to produce strong predictions of suspended load based on monthly records of river discharge, rainfall depth and river stage alone.     

Optimal water and waste load allocation in reservoir–river systems: a case study

In this paper, a new methodology is developed for optimization of water and waste load allocation in reservoir–river systems considering the existing uncertainties in reservoir inflow, waste loads and water demands. A stochastic dynamic programming (SDP) model is used to optimize reservoir operation considering the inflow uncertainty, and another model called PSO-SA is developed and linked with the SDP model for optimizing water and waste load allocation in downstream river. In the PSO-SA model, a particle swarm optimization technique with a dynamic penalty function for handling the constraints is used to optimize water and waste load allocation policies. Also, a simulated annealing technique is utilized for determining the upper and lower bounds of constraints and objective function considering the existing uncertainties. As the proposed water and waste load allocation model has a considerable run-time, some powerful soft computing techniques, namely, Regression tree Induction (named M5P), fuzzy K-nearest neighbor, Bayesian network, support vector regression and an adaptive neuro-fuzzy inference system, are trained and validated using the results of the proposed methodology to develop real-time water and waste load allocation rules. To examine the efficiency and applicability of the methodology, it is applied to the Dez reservoir–river system in the south-western part of Iran.     

Relative contributions of crust and mantle to generation of Oligo-Miocene medium-K calc-alkaline I-type granitoids in a subduction setting—a case study from the Nabar Pluton,central Iran

The Nabar pluton with the age of Oligo-Miocene located northwest of Isfahan, the Urumieh-Dokhtar magmatic belt, is composed of gabbro, gabbro diorite, diorite, quartz diorite, tonalite, and quartz monzonite. These rocks contain plagioclase, quartz, alkali-feldspar, magnesiohornblende, actinolite, tremolite-hornblende, actinolite-hornblende, anthophyllite, biotite, and Na-poor pyroxene. Application of the Al-in-hornblende barometry indicates pressures of 2–2.15 kbar, whereas the clinopyroxene barometry shows a pressure of 5 kbar. The temperature (i.e., 750–800°C) is estimated using the amphibole-clinopyroxene thermometry in a dioritic sample. Magmatic water content was greater than 10% at the time of formation of dioritic rocks in the Nabar pluton. Based on chemistry of mafic minerals and geochemical data, the Nabar plutonic complex comprises medium-K, calc-alkaline, and I-type granitoid. The rocks are characterized by enrichment of lithophile elements (LILEs) and depletion of high-field-strength elements (HFSEs). The Nabar rocks have weak concave-upward rare earth element (REE) patterns, suggesting that amphibole played a significant role in their generation during magma segregation. Low (Al₂O₃/(FeO + MgO + TiO₂) and (Na₂O + K₂O)/(FeO + MgO + TiO₂) ratios, and the patterns of trace and rare earth elements suggest that these rocks formed along a destructive plate margin and were derived from a lower crustal source. The magma probably formed by partial melting of lower crustal protoliths (amphibolites). Lower crust contamination with magma derived from partial melting of the upper mantle has an important role in the formation of this intrusive body, and a fractional crystallization of melts in higher crustal levels generated this spectrum of rock types. Mantle-derived gabbroic magmas emplaced into the lower crust are the most likely heat sources for partial melting.     

Extraction of velocity pulses of pulse-like ground motions using empirical Fourier decomposition

Journal of Seismology - Pulse-like ground motions may have only a distinct strong pulse or multiple pulses within the velocity time-history. These intrinsic pulses are hidden in low-frequency...