New magnitude scaling relations for earthquake early warning in the Alborz region,Iran

Rapid magnitude estimation relations for earthquake early warning systems in the Alborz region have been developed based on the initial first seconds of the P-wave arrival. For this purpose, a total of 717 accelerograms recorded by the Building and Housing Research Center in the Alborz region with the magnitude (M_w) range of 4.8–6.5 in the period between 1995 and 2013 were employed. Average ground motion period (\( \tau_{\text{c}} \)) and peak displacement (\( P_{\text{d}} \)) in different time windows from the P-wave arrival were calculated, and their relation with magnitude was examined. Four earthquakes that were excluded from the analysis process were used to validate the results, and the estimated magnitudes were found to be in good agreement with the observed ones. The results show that using the proposed relations for the Alborz region, earthquake magnitude could be estimated with acceptable accuracy even after 1 s of the P-wave arrival.     

Identification of Nutrients Critical Source Areas with SWAT Model under Limited Data Condition

Water Resources - The lack of long term observed data is the main challenge in many simulation-based studies for identification of nutrient critical source areas (CSAs). This study explored the...     

Hydrogeochemical evaluation and statistical analysis of groundwater of Sylhet,north-eastern Bangladesh

To investigate the hydrogeochemical characteristics of groundwater 23 shallow, 30 intermediate and 38 deep wells samples were collected from Sylhet district of Bangladesh, and analyzed for temperature, pH, Eh, EC,DO, DOC, Na^+, K^+, Ca²⁺, Mg²⁺, Cl^-, SO_4^2-, NO_3^-,HCO_3^-, SiO_2^-, Fe, Mn and As. Besides, 12 surface water samples from Surma and Kushiyara Rivers were also collected and analyzed to understand the influence into aquifers. Results revealed that, most of the groundwater samples are acidic in nature, and Na–HCO_3 is the dominant groundwater type. The mean value of temperature, EC,Na^+, K^+, Ca²⁺, Mg²⁺, Cl^-, NO_3^- and SO_4^2- were found within the range of permissible limits, while most of the samples exceeds the allowable limits of Fe, Mn and As concentrations. However, relatively higher concentration of Fe and Mn were found in deep water samples and reverse trend was found in case of As. The mean concentrations of As in shallow, intermediate and deep wells were 39.3, 25.3and 21.4 lg/L respectively, which varied from 0.03 to148 lg/L. From spatial distribution, it was found that Fe,Mn and As concentrations are high but patchy in northern,north-western, and south-western part of Sylhet region. The most influential geochemical process in study area were identified as silicate weathering, characterized by active cation exchange process and carbonate weathering, which thereby can enhance the elemental concentrations in groundwater. Pearson's correlation matrix, principal component analysis and cluster analysis were also employed to evaluate the controlling factors, and it was found that, both natural and anthropogenic sources were influencing the groundwater chemistry of the aquifers. However, surface water has no significant role to contaminate the aquifers,rather geogenic factors affecting the trace elemental contamination. Thus it is expected that, outcomes of this study will provide useful insights for future groundwater monitoring and management of the study area.     

Rehabilitation of earthquake damaged external RC beam‐column joints by joint enlargement using prestressed steel angles

The effectiveness of a rehabilitation method based on joint enlargement using prestressed steel angles to enhance the seismic behavior of damaged external reinforced concrete beam‐column joints was experimentally investigated. Three half‐scale joints having either non‐seismic or seismic reinforcement details were tested both before and after rehabilitation by applying lateral cyclic loading of increasing amplitudes. Two defects were considered for the two non‐seismic units, being the absence of transverse steel hoops and insufficient bond capacity of beam bottom steel reinforcing bars in the joint panel zone. The damaged specimens were rehabilitated by injecting epoxy grout into existing cracks and installing stiffened steel angles at the re‐entrant corners of the beam‐column joint, both above and below the beam, that were mounted and held in place using prestressed high‐tensile strength bars. The test results indicated that the seismic performance of the rehabilitated specimens in terms of strength, stiffness, and ductility was fully recovered and comparable with the performance of the seismically detailed specimen. Copyright © 2016 John Wiley & Sons, Ltd.     

Effect of ground motion selection methods on seismic collapse fragility of RC frame buildings

Variation in the seismic collapse fragility of reinforced concrete frame buildings predicted using different ground motion (GM) selection methods is investigated in this paper. To simulate the structural collapse, a fiber‐element modelling approach with path‐dependent cyclic nonlinear material models that account for concrete confinement and crushing, reinforcement buckling as well as low cycle fatigue is used. The adopted fiber analysis approach has been found to reliably predict the loss in vertical load carrying capacity of structural components in addition to the sidesway mode of collapse due to destabilizing P–Δ moments at large inelastic deflections. Multiple stripe analysis is performed by conducting response history analyses at various hazard levels to generate the collapse fragility curves. To select GMs at various hazard levels, two alternatives of uniform hazard spectrum (UHS), conditional mean spectrum (CMS) and generalized conditional intensity measure (GCIM) are used. Collapse analyses are repeated based on structural periods corresponding to initial un‐cracked stiffness and cracked stiffness of the frame members. A return period‐based intensity measure is then introduced and applied in estimating collapse fragility of frame buildings. In line with the results of previous research, it is shown that the choice of structural period significantly affects the collapse fragility predictions. Among the GM selection methods used in this study, GCIM and CMS methods predict similar collapse fragilities for the case study building investigated herein, and UHS provides the most conservative prediction of the collapse capacity, with approximately 40% smaller median collapse capacity compared to the CMS method. The results confirm that collapse probability prediction of buildings using UHS offers a higher level of conservatism in comparison to the other selection methods. Copyright © 2017 John Wiley & Sons, Ltd.     

SOM-DRASTIC: using self-organizing map for evaluating groundwater potential to pollution

Groundwater is considered as the most important water resource, especially in arid and semi-arid regions, so it is crucial to impede this source of water to be contaminated. One of the most common methods to assess groundwater vulnerability is DRASTIC method. However, the subjectivity existing in defining DRASTIC weights and ratings as well as inadaptability of the parameters involved in this method with special geology, hydrogeology, land use and climatic conditions have urged researchers to modify this method. In this paper, a new method combining a special type of the neural networks called Self-Organizing Map (SOM) and the traditional DRASTIC model resulting in the hybrid SOM-DRASTIC model is applied to modify and improve DRASTIC Model. The traditional DRASTIC method holds a summation among all negative effects of different factors contributing to vulnerability, while the proposed hybrid method is able of classifying the groundwater vulnerability and deriving the real relation existing between the DRASTIC parameters as the inputs and the vulnerability class as the output of the method. The vulnerability assessment process was performed on the Zayandeh-Rud river basin aquifers in Iran. The SOM-DRASTIC identified the northern parts of the study area as the most vulnerable areas with a drastically fractured structure, while the traditional DRASTIC ranked the western parts as the most vulnerable regions with a high rate of net recharge. The results demonstrate that the proposed method can be used by managers and decision-makers as an alternative robust tool for vulnerability-based classification and land use planning.     

Performance evaluation of WAVEWATCH III model in the Persian Gulf using different wind resources

The third-generation wave model, WAVEWATCH III, was employed to simulate bulk wave parameters in the Persian Gulf using three different wind sources: ERA-Interim, CCMP, and GFS-Analysis. Different formulations for whitecapping term and the energy transfer from wind to wave were used, namely the Tolman and Chalikov (J Phys Oceanogr 26:497–518, 1996), WAM cycle 4 (BJA and WAM4), and Ardhuin et al. (J Phys Oceanogr 40(9):1917–1941, 2010) (TEST405 and TEST451 parameterizations) source term packages. The obtained results from numerical simulations were compared to altimeter-derived significant wave heights and measured wave parameters at two stations in the northern part of the Persian Gulf through statistical indicators and the Taylor diagram. Comparison of the bulk wave parameters with measured values showed underestimation of wave height using all wind sources. However, the performance of the model was best when GFS-Analysis wind data were used. In general, when wind veering from southeast to northwest occurred, and wind speed was high during the rotation, the model underestimation of wave height was severe. Except for the Tolman and Chalikov (J Phys Oceanogr 26:497–518, 1996) source term package, which severely underestimated the bulk wave parameters during stormy condition, the performances of other formulations were practically similar. However, in terms of statistics, the Ardhuin et al. (J Phys Oceanogr 40(9):1917–1941, 2010) source terms with TEST405 parameterization were the most successful formulation in the Persian Gulf when compared to in situ and altimeter-derived observations.     

Nonparametric Geostatistical Simulation of Subsurface Facies: Tools for Validating the Reproduction of,and Uncertainty in,Facies Geometry

Delineation of facies in the subsurface and quantification of uncertainty in their boundaries are significant steps in mineral resource evaluation and reservoir modeling, which impact downstream analyses of a mining or petroleum project. This paper investigates the ability of nonparametric geostatistical simulation algorithms (sequential indicator, single normal equation and filter-based simulation) to construct realizations that reproduce some expected statistical and spatial features, namely facies proportions, boundary regularity, contact relationships and spatial correlation structure, as well as the expected fluctuations of these features across the realizations. The investigation is held through a synthetic case study and a real case study, in which a pluri-Gaussian model is considered as the reference for comparing the simulation results. Sequential indicator simulation and single normal equation simulation based on over-restricted neighborhood implementations yield the poorest results, followed by filter-based simulation, whereas single normal equation simulation with a large neighborhood implementation provides results that are closest to the reference pluri-Gaussian model. However, some biases and inaccurate fluctuations in the realization statistics (facies proportions, indicator direct and cross-variograms) still arise, which can be explained by the use of a single finite-size training image to construct the realizations.

     

Monitoring hawksbill turtle nesting sites in some protected areas from the Persian Gulf

Iranian nesting populations of the critically endangered hawksbill turtle(Eretmochelys imbricate) are some of the most important in the Indian Ocean. In this study, four of the most important hawksbill nesting grounds in the Persian Gulf, situated within three Iranian marine protected areas, were surveyed during nesting season,including Nakhiloo, Ommolgorm and Kharko Islands and the mainland beaches of the Naiband Marine-Coastal National Park(NMCNP). We present GIS maps of these key nesting grounds and describe sand texture of key nesting zones, along with conservation recommendations. About 9.2(28.3%) out of 32.5 km of all shores surveyed in this study were used by nesting hawksbill turtles follows: Nakhiloo: 1.4 km(52% of potential nesting area);Ommolgorm: 1.94 km(40%); Kharko: 3.4 km(28%), and NMCNP: 2.46 km(18.9%). The average nesting density was calculated as 131 nests/km at Nakhiloo, 76 nests/km at Ommolgorm, 7 nests/km at Kharko, and 15 nests per km at NMCNP. Highest nesting density was observed in Nakhiloo and Ommolgorm. It is thought that high hawksbill nesting density in these islands seems likely a result of limiting adequate nesting shores rather than the size of population, and also low density in Kharko and NMCNP more related to past and current pressures and low population density. With the exception of Ommolgorm Island, sands at the nesting grounds were well sorted.Grain size indicated that female hawksbill turtles in the Iranian Persian Gulf nest in sands that are generally mixed, with mean grain size ranging from coarse sands(0.4Φ;～0.5–1 mm) to fine sands(2Φ;～0.25 mm). We provide and discuss conservation recommendations and suggestions for future.     

Reliability and sensitivity analysis of wedge stability in the abutments of an arch dam using artificial neural network

In this study, the seismic stability of arch dam abutments is investigated within the framework of the probabilistic method. A large concrete arch dam is considered with six wedges for each abutment. The seismic safety of the dam abutments is studied with quasi-static analysis for different hazard levels. The Londe limit equilibrium method is utilized to calculate the stability of the wedges in the abutments. Since the finite element method is time-consuming, the neural network is used as an alt...