IRANIAN JOURNAL OF GEOPHYSICS
Year:2019 | Volume:12 | Issue:4 |Papers Count:11

Determination of affected area by seeding agents, the so-called target area, is an essential requirement for evaluation of cloud seeding projects. The most conservative and credible estimates of seeding effects were obtained from control matches drawn from outside the operational target within 2 hours of the time that each unit was seeded initially (DeFelice et al., 2014). A coupled modeling system consisting of the mesoscale WRF model and the Hybrid Single-Particle Lagrangian Integrated Trajectory Model (HYSPLIT), provides capability to simulate the transportation and dispersion of seeding materials and to characterize target area on the map. This study is devoted to sensitivity analysis of simulated dispersion patterns to several parameters including different configuration based on physical parameterizations used in WRF model, horizontal and temporal resolution of WRF and spatial resolution of HYSPLIT, to determine the most probable dispersion patterns. Since temperature and wind parameters are the most important parameters in cloud seeding operations, they are measured instantaneously at 1-second intervals at the flight height of the airplane during each flight and therefore, they are very valuable data to assess the performance of the WRF model in simulating these fields. Hence, at first the WRF model outputs such as temperature and wind are validated by data measured by the airplane. Results indicate that there is an acceptable agreement between field data and WRF outputs that are going to be used as input data for dispersion model. In this study, eight configurations of the WRF model based on different physical parameterization schemes are used for 34 flights in cloud seeding project in 2015 and HYSPLIT model is run by these types of input data and resulting target area are compared on the map. Then, HYSPLIT model is run for four selected seeding operations according to three temporal and two horizontal resolutions of input data in addition to three spatial resolutions of HYSPLIT model and the transport of seeding plumes is characterized on the geographical map. The results indicate that dispersion model is sensitive to all mentioned parameters. Also, in most cases, dispersion model results at the flight height of cloud seeding aircraft are significantly influenced by the input data provided by the WRF model. In addition, the dispersion model results are less sensitive to other parameters. Furthermore, when the spatial resolution of the HYSPLIT model is close to the horizontal resolution of the input meteorological data provided by the WRF model, affected area of seeding agents is more integrated and therefore there is a greater degree of certainty in determining the target area.

In this study, Simulated Annealing algorithm is applied on Rayleigh wave group velocities to image the density variations and shear and compressional wave velocities structure of the crust and upper-mantle of Makran subduction zone. Based on previous studies, surface wave dispersion measurements are primarily sensitive to seismic shear wave velocities. However, it has been proved that the sensitivity to compressional wave velocity is significantly smaller than the sensitivity to shear wave velocity. Also the sensitivity function for the density is smaller than the one for the shear wave velocity. Therefore, shear wave velocity variations are mainly the model parameters in surface wave dispersion analysis. Simulated Annealing is a probabilistic technique for finding the global optimum of a given function. It is especially useful to approximate global optimization in a large search space. The Simulated Annealing method like the Monte-Carlo method, samples the whole model space and can avoid getting stuck in local minima. To evaluate calculation efficiency and effectiveness of Simulated Annealing algorithm, two noise-free and two noisy (10% of white Gaussian noise) synthetic data sets are firstly inverted. Then, a real data from Makran region is inverted to examine the applicability and robustness of the proposed approach on real surface wave data. In next step, gravity data inversion was applied with a priori information based on surface wave analysis results to obtain Moho depth variations and crustal density structure. The reason for using gravity data set is that surface waves group velocity is sensitive to average velocity variations and has a good lateral sensitivity, whereas gravity anomaly is sensitive to depth variations of discontinuities and has a good vertical resolution. Our results show that the Moho depth across the Makran subduction zone increases from the Oman seafloor and Makran forearc setting to the volcanic arc. Generally, the crust in the western Makran is thicker than the eastern part and the maximum crustal thickness in the Makran region reaches 46 to 48 km below the Taftan-Bazman volcanos. The Moho map clearly depicts the western edge of the Makran subduction zone, where the Minab fault (representing the eastern edge of the Hormuz Straits) marks the boundary between the thick continental crust of the Arabian plate and the thin oceanic crust of the Oman Sea. Our results show clearly that the high-velocity slab of the Arabian plate subducts northwards beneath the low-velocity overriding lithosphere of Lut block in the western Makran and Helmand block in the eastern Makran.

In a geophysical inversion process, the observed data is transformed to the meaningful properties of earth. For inversion of petrophysical properties, we need a rock physics model that links the petrophysical properties to the elastic properties of rock. The more accurate the model, the more reliable the results. There are a variety of procedures in which can invert petrophysical properties of earth through seismic data. Those procedures include experimental and empirical methods (In these methods, seismic data is assumed to be a function of some special petrophysical features of a zone), statistical methods and theoretical methods such as Biot model. Such theoretical method predicts elastic properties of rocks such as velocities and quality factors as functions of physical properties of rock and fluid. Here, we use BISQ (Biot-Squirt flow) model for inversion of petrophysical properties of reservoir rock. The BISQ describes seismic wave propagation in a fluid saturated poroelastic medium. This model consists of both Biot and squirt flow models and its accuracy is confirmed by several researchers versus other models. The model is developed for several anisotropic media too. Biot model relates the attenuation of seismic wave to parallel motion of fluid in a solid frame; while, the squirt flow model relates it to local motion of fluid. It is proven that both mechanisms exist during seismic wave propagation and BISQ model is correct for both of them, simultaneously. In a petrophysical properties inversion process, there are two vital elements. First one, as described before, is using a rock physical model and the other one is mathematical method by which we solve an optimization problem that minimizes misfit between observed and predicted data. Here, we choose PNGA (Parallel Niche Genetic Algorithm) because of nonlinearity of BISQ model. Moreover, PNGA as an evolutionary algorithm, has capability of dealing with multi-objective optimization problems. We apply the mentioned method on both synthetic and real data. The inversion results show acceptable correlation with the used quantities in generation of synthetic and well logs.

Solar radiation is one of the important parameters that affects on many soil and water processes such as evaporation, snow melting and plant growth. Considering the importance of the amount of radiation in the the application of solar energy and the many problems in recording this parameter and the success of intelligent models in predicting complex parameters, it is reasonable to use ANFIS and ANN models to predict the radiation parameter. In this study, using a large database on a wide period which contained a set of meteorological and geographical data such as latitude, longitude, months of the year, the average temperature, the sunshine duration, relative humidity and the average of the monthly global solar irradiation, the performance of two techniques, artificial neural network and Active Neuro-Fuzzy Inference System, was investigated for the next 12 months in the Yazd station. Sensitivity analysis of different climate parameters such as maximum temperature, average temperature, sunshine hours, relative humidity, solar radiation and evaporation, showed that they were important factors in predicting of solar radiation. Then, the two models were analyzed with different combinations of data. After ensuring the performance of the two models in the testing phase and achieving the best results with the highest efficiency and lowest error rate in the prediction of solar radiation, only by entering the most effective climatic parameters of 2005, the solar radiation value of 2006 was forecasted, and the predicted values were compared with actual values. The results of this study showed that both methods have the ability to simulate the amount of solar radiation. High values of the correlation coefficient and low error, confirm the reliability of the results. According to the results, although the highest correlation coefficient was obtained using artificial neural network, the results of both models were satisfactory in two stages of testing and evaluation and are estimated to be close to each other. In total, artificial neural networks with a correlation coefficient of 0. 91 and RMSE and MAE rates of 0. 19 and 0. 08, respectively, produced less error in predictions in comparison with fuzzy-neural networks. Also, the BIAS value is-0. 30, which shows a small negative overstimation in the data. Finally, the composition of sunny hours, average temperature, maximum temperature as the optimal combination was identified. In addition, it was determined that sunny hours and average temperatures are the most effective parameters in prediction of solar radiation, while relative humidity has the least effect on it.

Iran is seismically a very active region. Earthquakes with high magnitudes occur every year in Iran, averagely. Therefore, dynamic response analysis is one of the most important issues in evaluating the soil behavior. In seismic response analysis method of earth layers, deformation issues during earthquakes are important. Two methods exist for dynamic analysis: equivalent linear method and nonlinear method. If seismic motion is weak, shear strain of alluvium will be less than 10-4 percent and earth layer behavior will be elastic. For strains greater than 10-4 percent, soil behavior will be nonlinear; then nonlinear and equivalent linear methods should be used. In large shear strain that soli behavior is completely nonlinear, the problem should be solved at time domain, step by step. Difference between nonlinear and equivalent linear method depends on soil nonlinear behavior. Ground response can be analyzed with 1D, 2D and 3D modeling. These methods have different capabilities in terms of problem and wave geometry modeling, also to the solution of equation of motion. 1D ground response analysis is used for horizontal structures that boundaries between their layers are distinct, but inclined surfaces, nonlinear ground, heavy and rigid buried structures, walls and tunnels need 2D and sometimes 3D analysis. In other words, while one of the two soil profile dimensions (surface or sub-surface dimension) is much bigger than the other one, transmission synthesis is acceptable. Nonlinear behavior of soil can be modeled as equivalent linear or nonlinear medium by 1D, 2D or 3D methods. Equivalent linear method is popular between engineers, due to its relative simplicity and its simple and clear parameters. Using accelerometers, geotechnical boreholes and equivalent linear and nonlinear analysis, acceleration spectra can be compared. DEEPSOIL software can analyze the alluvium. It is based on direct and continuous solution of equation of transmitted waves and calculates responses of a system with homogenous and viscoelastic layers to shear waves. DEEPSOIL is a one dimensional ground response analyzing software which is able to examine the defined layers by both of linear and nonlinear analysis methods. Urmia city has experienced many large and moderate earthquakes in last years. According to Iranian standard 2800, the design base acceleration in this city is 0. 25g. For studying the Urmia bedrock, two borehole data of the city with depth at 16 and 24 meters were used and some appropriate accelerograms were selected and scaled for matching with design spectra. These accelerograms were scaled with the same form spectrum, but they had different maximum acceleration (0. 2g, 0. 25g, 0. 3g, 0. 35g, 0. 4g, 0. 45g and 0. 5g). Using DEEPSOIL software with capability of nonlinear and equivalent linear analysis, acceleration spectra were compared. The aim of this study is to compare the results of the alluvial analysis with linear and non linear dynamics in estimating the amplification coefficient and the amount of amplification of the waves in then earthquake event Therefore, in order to evaluate the nonlinear behavior of soil, Equivalent linear and non linear analysis in time domain were performed on one-dimensional models of subsurface layer using borehole data in Urmia. The results of the two analyzes were compared with each other. By comparing spectral accelerations at the Earth's surface during different periods with corresponding values on seismic bed rock, the amplification coefficient is presented in different periods. The results show that in the range of 0. 1 to 1 second, the greatest amplification and the greatest difference were present between the two analyzes. In conclusion, we conclude that both Equivalent linear and nonlinear linear methods can be successfully used to analyze the one-dimensional ground response. The method of applying and interpreting each of these methods requires information about the assumptions of the Ground floor, the manner in which each method operates, the recognition of its constraints, and none of them can be considered decisively and precisely. However, the accuracy of these methods decreases with changes in soil conditions, uncertainty in soil characteristics and the empirical data dispersion, with a large number of input parameters based on them.

The harvesting of renewable energy sources has become increasingly important to take account of the gradual decline of fossil fuel reserves and the environment degradation associated with the use of fossil fuels. Wind energy, as one of the most well-known renewable energy sources, has been extensively harnessed across the world (Shu et al., 2015). Utilization of energy from wind has gained appreciable momentum and is being widely disseminated for displacement of oil-produced energy, and eventually to reduce the catastrophic effects of fossil fuel energy on environment (Shaahid et al., 2014). Using of wind energy depends on precise prediction of wind properties in areas with no measurement; thus, this paper aimed to evaluate wind potential predictions presented by WAsP software in mountainous areas such as Kermanshah province. In this study, wind potential was estimated around four synoptic stations where there are SANA wind stations and then predicted and observed wind properties were compared for evaluation of accuracy. Wind data of synoptic stations in Sarpolzahab, Sonqor, Eslamabad, and Kermanshah was used for prediction of wind properties in SANA stations in Kerend, Sounqour, Mahidasht, and Hajiabad sites, respectively. The measurements were used in 40 m AGL (for all cases) and 80 m AGL (for Kerend and Sounqour sites). Using WAsP and ArcGIS software, wind atlas and then mean wind speed and mean wind power density maps were prepared in 10, 40 and 80 m AGL and a relatively limited area (15 to 35 km long) around each station. Then, using measurements in SANA stations and parameters such as mean wind speed, mean wind power density, most probable and maximum energy-carrying wind speed, the accuracy of estimates was assessed. The results showed that predicted wind properties were acceptable in Kerend, Hajiabad and Sounqour at 40 m AGL, but they were somewhat different in Mahidasht which is due to the long distance in complex terrain. As well, estimates were not so good at 80 m AGL in Sounqour. In other words, the log law of Wortman was not able to predict wind properties precisely at high height in complex terrain. However, paired sample T test result revealed there is no significant difference between predicted and observed values. Wind potential assessment showed that highlands and ridge mountains (with more than 2000 m height) are areas with high wind power density (>700 W/m2). Mean wind speed in lower regions was calculated 4 to 6 m/s and wind power density was calculated 100 to 300 W/m2 around Kermanshah, Eslamabad and Sonqor stations. The calculated wind speed and wind power density for Sarpolzahab area were 2 to 4 m/s and less than 200 W/m2, respectively. These values in this area are lower than other stations.

Natural frequency of soils is one of the important factors in the study of vulnerability to earthquakes. In areas characterized by soft sediments, the maximum amplitude of ground motion is common that leads to enhanced seismic hazard and risk. Zanjan city is located in northwest of Iran with high risk of earthquake hazard according to Building and Housing Research Center (BHRC). So, investigation of site effect, beside other parameters, in earthquake vulnerability is considerable. To map natural frequency of soil in Zanjan, microtremor horizontal-to-vertical spectral ratio (HVSR) method has been conducted. Specially, we used Nakamura’ s method on ambient noise records. We employed 3-component medium band Guralp seismometer. Ambient noise was recorded in 41 sites in a pre-designed profile. At each site, noise was recorded for at least one hour long. Geopsy software was used for data processing. Evaluation of the gathered data was examined following the recommended guidelines of SESAME (Site EffectS assessment using AMbient Excitations) project. The results of this study represent that there is one amplification peak in most stations. Considering the first peaks, the natural frequency of soil decreases from north to south in the city. The decrease of natural frequency represents an increase in the thickness of soil layer. In some sites, in west and center of the city, parallel to the Zanjanrud river, there are two peaks in spectral ratio. The second peak was always more than 3 Hz. The second peak is related to a shallow thin and low velocity sedimentary layer. To evaluation of results, the data for standard penetration test of boreholes was collected and shear wave velocity was estimated. Using the shear wave velocity obtained from the boreholes, we estimated the thickness of soil from the measured natural frequency of soils employing quarter wavelength law. The estimated thickness of soil shows the presence of a thin sedimentary layer with high velocity in the north of Zanjan. The bedrock slope becomes steeper by moving towards south and flattens within the basin. Inside the basin, the natural frequency is less than 1 Hz and the thickness of the sediments increases to about hundreds of meters. In general, the results of this study investigate one step for seismic hazard assessment and risk qualification of this urban area where great damages can be attained in case of strong earthquakes. Hence, these results should be taken into consideration before establishing the new urban constructions in the area of study.

Today, smartphones are well equipped with various sensors such as accelerometers, magnetometers and GPS devices. The smartphones that are installed on the ground and may not experience a considerable slipping, may effectively be used as a large network of low to moderate seismometers. This smartphone-based seismic network can efficiently serve for producing shake maps, earthquake risk and hazard assessment and analysis, and earthquake crisis management. In this article, an Android application is developed by Java-programming in Android Studio IDLE to record and save three components of acceleration data that are sensed by smartphone accelerometers, and send them to a local server. The feasibility of smartphone accelerometers are then investigated for developing any future smartphone-based seismic networks especially for earthquake engineering applications. For this purpose, several important criteria such as recorded acceleration data (for the three components), peak ground accelerations (PGA), peak ground velocities (PGV), peak ground displacements (PGD), as well as Fourier and response spectra and Arias intensities are derived for two test smartphones and a reference professional Gü ralp accelerometer. The effect of smartphone slipping with respect to the ground during the earthquake data recording is also investigated. Harmonic oscillations with different frequencies and Bam earthquake movements are simulated by a shaking table that is designed and manufactured in the Earthquake Research Center (EQRC), Ferdowsi university of Mashhad. The above mentioned criteria derived from the recorded seismic data for the two test mobile sets are compared with those of reference Gü ralp accelerometer. The results show that the frequency range provided by the seismic data recorded by smartphone accelerometers is efficiently enough for any earthquake engineering application (0. 1 to 10~20 Hz), especially for short to medium buildings. The accuracy of such devices are well enough to record seismic movements produced by nearly severe earthquakes with magnitudes > 5 at epicentral distances < 200 km. It is also shown in this article that small relative movements of mobile sets on their base may have little effect on seismic criteria and may not harmfully deviate the results. Sensitivity of the test mobiles to trigger earthquakes with magnitudes > 4. 5 at epicentral distance of 10 km is also investigated. As a whole, application of smartphone accelerometers seems to be strongly justified for developing any seismic data aimed at earthquake engineering applications and earthquake crisis management. The EQRC team is now developing its smartphone– based seismic network on small to moderate scales and is testing different protocols for an efficient data transfer.

On Sunday, November 12, 2017, a strong earthquake with local magnitude of Mn7. 3 occurred in the border region between Iran and Iraq in vicinity of the Sarpol-e Zahab town. Unfortunately, this catastrophic event caused many causalities, thousands of injured and vast amounts of damage to the buildings, houses and infrastructures in the epicentral area. The earthquake epicenter was located about 10 km south of Ezgeleh in the Zagros seismotectonic zone. This earthquake was recorded by 113 stations of Iran Strong Motion Network (ISMN) across the country. The nearest station to the epicenter of the earthquake was Sarpol-e Zahab (SPZ) station at a distance of about 39 km. In this research, the source parameters of the earthquake including the seismic moment (M0), the moment magnitude (M) and the corner frequency (fc) were estimated using two methods of Andrews (1986) and inversion of the displacement spectra based on the Brune source model in the frequency domain using ISMN strong motion data. Additionally, the frequency independent quality factor (Q), the source radius (r) (considering a hypothetical circular source), and the stress drop of the earthquake ( σ ) were calculated. The above mentioned values were calculated based on two time windows: the S-wave window and the whole trace window for both methods. The moment magnitude of the event is M7. 4 based on the displacement spectra inversion for the whole trace window and M7. 3 based on the S-wave window. The estimated value for both windows using the Andrews (1986) method is M7. 3. The estimated M values are in excellent agreement with the reported values. The calculated corner frequencies are from 0. 13 to 0. 17 Hz and the estimated source radii of the event using both methods are in the 9-11. 5 km range. Moreover, the estimated stress drops are in the range of 376 to 572 bar. Ultimately, the strong ground motion parameters were investigated. Using a band-pass filter, all recordings were filtered and their acceleration, velocity and displacement time histories along with their response spectra were extracted, then the peak ground acceleration (PGA), velocity, and displacement of this earthquake were estimated. The PGA recorded at SPZ station on horizontal and vertical components (uncorrected data) are about 684, 554 and 385 cm/s2, respectively. Interestingly, there are two clear packets of energy in the recorded time histories of the Sarpol-e-Zahab, Kerend and some other stations that possibly indicate two sequential failures or two simultaneous seismic events. Considering the magnitude of the event, comparison of the observed values of maximum ground acceleration and velocity with the predicted values by ground motion predication equations presented by Boore et al. (2014), suggests that these equations are appropriate for the region.