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41.
S. M. Talha Qadri Md. Aminul Islam M. R. Shalaby Khaista Rehman Khattak S. H. Sajjad 《Arabian Journal of Geosciences》2017,10(12):267
The Attock Basin is situated close to the northwest of Pakistan. Recent seismic event of October 2015 (7.5Mw) near the Pakistan Afghanistan border has proved that the area of interest is seismically active and triggered a series of aftershocks of magnitude even greater than 6.5Mw. This seismic activity has posed danger to the future of the people and infrastructure especially to the northwestern part of the country. Therefore, site response analysis is essential for estimating local site conditions in response to seismic events. Ambient noise recordings were made at 50 sites within urban and semi-urban settlements in the Attock Basin to analyze the site response of the small but densely populated basin. At each of these sites, the fundamental frequency of the soft sediments (f 0), the amplitude (A 0) of corresponding H/V spectral ratios, the thickness of soft sediment (H) lying over competent lithology, and the soil vulnerability index (K g) were studied. Results were correlated with sparsely available borehole data to enhance the credibility of the study conducted for microzonation and predicting the site response to earthquake seismicity in the Attock Basin. The soil vulnerability index was found to range from moderate to high. Results clearly showed that the study area exhibits low to moderate fundamental frequency with greater soft sediment thicknesses distributed throughout the study area. Moreover, higher impedance contrasts were found at most of the sites within the central part of the Attock Basin, thus reflecting a moderate to high susceptibility of damage in those regions in response to seismic events. 相似文献
42.
Quantitative analyses of groundwater flow and transport typically rely on a physically‐based model, which is inherently subject to error. Errors in model structure, parameter and data lead to both random and systematic error even in the output of a calibrated model. We develop complementary data‐driven models (DDMs) to reduce the predictive error of physically‐based groundwater models. Two machine learning techniques, the instance‐based weighting and support vector regression, are used to build the DDMs. This approach is illustrated using two real‐world case studies of the Republican River Compact Administration model and the Spokane Valley‐Rathdrum Prairie model. The two groundwater models have different hydrogeologic settings, parameterization, and calibration methods. In the first case study, cluster analysis is introduced for data preprocessing to make the DDMs more robust and computationally efficient. The DDMs reduce the root‐mean‐square error (RMSE) of the temporal, spatial, and spatiotemporal prediction of piezometric head of the groundwater model by 82%, 60%, and 48%, respectively. In the second case study, the DDMs reduce the RMSE of the temporal prediction of piezometric head of the groundwater model by 77%. It is further demonstrated that the effectiveness of the DDMs depends on the existence and extent of the structure in the error of the physically‐based model. 相似文献
43.
Amir Hossein Hakimhashemi Jeoung Seok Yoon Oliver Heidbach Arno Zang Gottfried Grünthal 《Journal of Seismology》2014,18(3):671-680
The M w 3.2-induced seismic event in 2006 due to fluid injection at the Basel geothermal site in Switzerland was the starting point for an ongoing discussion in Europe on the potential risk of hydraulic stimulation in general. In particular, further development of mitigation strategies of induced seismic events of economic concern became a hot topic in geosciences and geoengineering. Here, we present a workflow to assess the hazard of induced seismicity in terms of occurrence rate of induced seismic events. The workflow is called Forward Induced Seismic Hazard Assessment (FISHA) as it combines the results of forward hydromechanical-numerical models with methods of time-dependent probabilistic seismic hazard assessment. To exemplify FISHA, we use simulations of four different fluid injection types with various injection parameters, i.e. injection rate, duration and style of injection. The hydromechanical-numerical model applied in this study represents a geothermal reservoir with preexisting fractures where a routine of viscous fluid flow in porous media is implemented from which flow and pressure driven failures of rock matrix and preexisting fractures are simulated, and corresponding seismic moment magnitudes are computed. The resulting synthetic catalogues of induced seismicity, including event location, occurrence time and magnitude, are used to calibrate the magnitude completeness M c and the parameters a and b of the frequency-magnitude relation. These are used to estimate the time-dependent occurrence rate of induced seismic events for each fluid injection scenario. In contrast to other mitigation strategies that rely on real-time data or already obtained catalogues, we can perform various synthetic experiments with the same initial conditions. Thus, the advantage of FISHA is that it can quantify hazard from numerical experiments and recommend a priori a stimulation type that lowers the occurrence rate of induced seismic events. The FISHA workflow is rather general and not limited to the hydromechanical-numerical model used in this study and can therefore be applied to other fluid injection models. 相似文献
44.
45.
Mohammad Hadi Moeini Amir Etemad-Shahidi Vahid Chegini Iraj Rahmani 《Ocean Dynamics》2012,62(5):785-797
The main goal of this study is to develop an efficient approach for the assimilation of the hindcasted wave parameters in
the Persian Gulf. Hence, the third generation SWAN model was employed for wave modeling forced by the 6-h ECMWF wind data
with a resolution of 0.5°. In situ wave measurements at two stations were utilized to evaluate the assimilation approaches.
It was found that since the model errors are not the same for wave height and period, adaptation of model parameter does not
result in simultaneous and comprehensive improvement of them. Therefore, an approach based on the error prediction and updating
of output variables was employed to modify wave height and period. In this approach, artificial neural networks (ANNs) were
used to estimate the deviations between the simulated and measured wave parameters. The results showed that updating of output
variables leads to significant improvement in a wide range of the predicted wave characteristics. It was revealed that the
best input parameters for error prediction networks are mean wind speed, mean wind direction, wind duration, and the wave
parameters. In addition, combination of the ANN estimated error with numerically modeled wave parameters leads to further
improvement in the predicted wave parameters in contrast to direct estimation of the parameters by ANN. 相似文献
46.
Amir Shah Ruddin Md Shah Mashhor Mansor Shahrul Anuar Mohd Shah Che Salmah Mohd Rawi Abu Hassan Ahmad Ibrahim Jaafar 《湿地科学》2008,6(1):34-44
A survey was carried out at the largest rice cultivation area in Peninsular Malaysia,the Muda rice agroecosystem.The main objective of this study was to document the overall biodiversity associated with this unique agroecosystem by using a combination of sampling techniques in order to record different groups of fauna and flora.The total number of biota recorded and identified from the rice field ecosystem during the study period consisted of 46 species of zooplankton,81 species of aquatic insects,5 species of rodents,7 species of bats,87 species of birds,11 species of fishes and 58 species of weeds.A long-term study should be carried out as more species are expected to be recorded when more of the Muda rice agroecosystem area has been sampled to obtain sufficient information on the Muda rice agrobiodiversity. 相似文献
47.
Ali Haghizadeh Safoura Siahkamari Amir Hamzeh Haghiabi Omid Rahmati 《Journal of Earth System Science》2017,126(3):39
With regard to the lack of quality information and data in watersheds, it is of high importance to present a new method for evaluating flood potential. Shannon’s entropy model is a new model in evaluating dangers and it has not yet been used to evaluate flood potential. Therefore, being a new model in determining flood potential, it requires evaluation and investigation in different regions and this study is going to deal with this issue. For to this purpose, 70 flooding areas were recognized and their distribution map was provided by ArcGIS10.2 software in the study area. Information layers of altitude, slope angle, slope aspect, plan curvature, drainage density, distance from the river, topographic wetness index (TWI), lithology, soil type, and land use were recognized as factors affecting flooding and the mentioned maps were provided and digitized by GIS environment. Then, flood susceptibility forecasting map was provided and model accuracy evaluation was conducted using ROC curve and 30% flooding areas express good precision of the model (73.5%) for the study area. 相似文献
48.
Estimation of enterococci input from bathers and animals on a recreational beach using camera images
John D. Wang Helena M. Solo-Gabriele Amir M. Abdelzaher Lora E. Fleming 《Marine pollution bulletin》2010,60(8):1270-6769
Enterococci, are used nationwide as a water quality indicator of marine recreational beaches. Prior research has demonstrated that enterococci inputs to the study beach site (located in Miami, FL) are dominated by non-point sources (including humans and animals). We have estimated their respective source functions by developing a counting methodology for individuals to better understand their non-point source load impacts. The method utilizes camera images of the beach taken at regular time intervals to determine the number of people and animal visitors. The developed method translates raw image counts for week days and weekend days into daily and monthly visitation rates. Enterococci source functions were computed from the observed number of unique individuals for average days of each month of the year, and from average load contributions for humans and for animals. Results indicate that dogs represent the larger source of enterococci relative to humans and birds. 相似文献
49.
We collected Vimba vimba throughout the spawning season (mid April to mid June, 2007) in Gorgan Bay (south-western Iran) and investigated its age,
growth, and reproductive traits. The maximum age was 5+ years. Both sexes grew allometrically (positive for males: b=3.140 9 and negative for females: b=2.791 4). The von Bertalanffy growth functions were described by the formulae L
t
=32.565(1-e−0.184(t+0.530)) for males and L
t
=35.950(1-e−0.179(t+0.529)) for females. The overall sex ratio was balanced, but males were predominant in the smaller size classes and females in the
larger size classes. Based on the gonadosomatic index (GSI) values, spawning appears to occur between late April and late
May in the bay. The highest mean GSI was 6.44 for males in early May and 20.36 for females in late April. Absolute fecundity
varies from the minimum of 5 436 eggs for age 3+ fish to the maximum of 36 141 eggs for age 5+ fish. Fecundity was also positively correlated with fish size (length and weight). Egg diameter ranged from 1.05 to 1.70
mm in the mean of 1.42 mm. There was no correlation between female size and ova diameter. 相似文献
50.
Amir H. Hosseini Clayton V. Deutsch Kevin W. Biggar Carl A. Mendoza 《Stochastic Environmental Research and Risk Assessment (SERRA)》2010,24(5):735-749
The spatial distribution of residual light non-aqueous phase liquid (LNAPL) is an important factor in reactive solute transport
modeling studies. There is great uncertainty associated with both the areal limits of LNAPL source zones and smaller scale
variability within the areal limits. A statistical approach is proposed to construct a probabilistic model for the spatial
distribution of residual NAPL and it is applied to a site characterized by ultra-violet-induced-cone-penetration testing (CPT–UVIF).
The uncertainty in areal limits is explicitly addressed by a novel distance function (DF) approach. In modeling the small-scale
variability within the areal limits, the CPT–UVIF data are used as primary source of information, while soil texture and distance
to water table are treated as secondary data. Two widely used geostatistical techniques are applied for the data integration,
namely sequential indicator simulation with locally varying means (SIS–LVM) and Bayesian updating (BU). A close match between
the calibrated uncertainty band (UB) and the target probabilities shows the performance of the proposed DF technique in characterization
of uncertainty in the areal limits. A cross-validation study also shows that the integration of the secondary data sources
substantially improves the prediction of contaminated and uncontaminated locations and that the SIS–LVM algorithm gives a
more accurate prediction of residual NAPL contamination. The proposed DF approach is useful in modeling the areal limits of
the non-stationary continuous or categorical random variables, and in providing a prior probability map for source zone sizes
to be used in Monte Carlo simulations of contaminant transport or Monte Carlo type inverse modeling studies. 相似文献