Historical tsunami in the Makran Subduction Zone off the southern coasts of Iran and Pakistan and results of numerical modeling

Tsunami hazard in the Makran Subduction Zone (MSZ), off the southern coasts of Iran and Pakistan, was studied by numerical modeling of historical tsunami in this region. Although the MSZ triggered the second deadliest tsunami in the Indian Ocean, among those known, the tsunami hazard in this region has yet to be analyzed in detail. This paper reports the results of a risk analysis using five scenario events based on the historic records, and identifies a seismic gap area in western Makran off the southern coast of Iran. This is a possible site for a future large earthquake and tsunami. In addition, we performed numerical modeling to explain some ambiguities in the historical reports. Based on the modeling results, we conclude that either the extreme run-up of 12–15 m assigned for the 1945 Makran tsunami in the historical record was produced by a submarine landslide triggered by the parent earthquake, or that these reports are exaggerated. The other possibility could be the generation of the huge run-up heights by large displacements on splay faults. The results of run-up modeling reveal that a large earthquake and tsunami in the MSZ is capable of producing considerable run-up heights in the far field. Therefore, it is possible that the MSZ was the source of the tsunami encountered by a Portuguese fleet in Dabhul in 1524.     

Seismic and well logging interpretation for evaluation of the lower Bahariya reservoir,southwest Qarun (SWQ) Field,Gindi Basin,Egypt

This paper focuses on seismic and well log interpretations for evaluating the sandstones of the Cenomanian Bahariya Formation in the southwest Qarun Field, Gindi Basin, northern Western Desert of Egypt. The seismic profiles display a clear anticlinal structure intersected by reverse faults in the study area. This faulted anticline has been interpreted to be one of the Syrian arc system folds formed by Upper Cretaceous tectonic inversion, which resulted from the NW movement of the African Plate relative to Laurasia. This anticline has been recommended as a target for exploration by the present work as it may represent a structural trap for hydrocarbon accumulation. The sandstones of the Lower Bahariya Formation in the southwest Qarun Field display good reservoir characteristics. The interpretation of the available well log data for the SWQ-21 and SWQ-25 wells for the Lower Bahariya Formation reflects a good reservoir quality for oil production in its topmost part. This reservoir possesses low S_W (<50%), high porosity (16%), low S_W/S_XO and low BVW (<0.09) which all reflect a high potential for oil production.     

The relationship among environmental variables,jellyfish and non‐gelatinous zooplankton: A case study in the north of the Gulf of Oman

Processes underlying the temporal and spatial variations observed in the distribution of jellyfish and non‐gelatinous zooplankton in the Gulf of Oman are not well understood. This information gap is clearly a major issue in controlling the harmful blooms of jellyfish and non‐gelatinous zooplankton. Samples of jellyfish and non‐gelatinous zooplankton were collected from six stations in Chabahar Bay and three stations in Pozm Bay within four seasons. At each station, environmental variables were also recorded from bottom and surface water. A total of 83 individuals of medusae representing four species of Scyphozoa (i.e., Cyanea nozakii, Chrysaora sp., Pelagia noctiluca, Catostylus tagi) and species of Hydrozoa (i.e., Diphyes sp., Rhacostoma sp., Aequorea spp.) were observed in the study area. A total of 70,727.25 individuals/m^?3 of non‐gelatinous zooplankton dominated by copepods and cladocerans were collected in nine stations within the four seasons. The results of a RELATE analysis yielded no significant association between species composition for jellyfish and non‐gelatinous zooplankton. Among environmental variables, water transparency, nitrite concentration, water depth and temperature were better associated with the total variation in jellyfish species composition than with that of non‐gelatinous zooplankton. Dissolved oxygen, pH, and phosphate concentration were significant environmental variables associated with the variation in the spatial and temporal distribution patterns of non‐gelatinous zooplankton assemblages. Although some jellyfish species (i.e., Rhacostoma sp., Pelagia noctiluca, Catostylus tagi) occur independently of non‐gelatinous zooplankton assemblages, other jellyfish (i.e., Chrysaora sp., Aequorea spp., Cyanea nozakii, Diphyes sp.) are strongly correlated with non‐gelatinous zooplankton assemblages.     

Application of the coral health chart to determine bleaching status of <Emphasis Type="Italic">Acropora downingi</Emphasis> in a subtropical coral reef

The ‘Coral Health Chart’ has become a popular tool for monitoring coral bleaching worldwide. The scleractinian coral Acropora downingi (Wallace 1999) is highly vulnerable to temperature anomalies in the Persian Gulf. Our study tested the reliability of Coral Health Chart scores for the assessment of bleaching-related changes in the mitotic index (MI) and density of zooxanthellae cells in A. downingi in Qeshm Island, the Persian Gulf. The results revealed that, at least under severe conditions, it can be used as an effective proxy for detecting changes in the density of normal, transparent, or degraded zooxanthellae and MI. However, its ability to discern changes in pigment concentration and total zooxanthellae density should be viewed with some caution in the Gulf region, probably because the high levels of environmental variability in this region result in inherent variations in the characteristics of zooxanthellae among “healthy” looking corals.     

Impacts of Methane on Carbon Dioxide Storage in Brine Formations

In the context of geological carbon sequestration (GCS), carbon dioxide (CO₂) is often injected into deep formations saturated with a brine that may contain dissolved light hydrocarbons, such as methane (CH₄). In this multicomponent multiphase displacement process, CO₂ competes with CH₄ in terms of dissolution, and CH₄ tends to exsolve from the aqueous into a gaseous phase. Because CH₄ has a lower viscosity than injected CO₂, CH₄ is swept up into a ‘bank’ of CH₄‐rich gas ahead of the CO₂ displacement front. On the one hand, this may provide a useful tracer signal of an approaching CO₂ front. On the other hand, the emergence of gaseous CH₄ is undesirable because it poses a leakage risk of a far more potent greenhouse gas than CO₂ if the cap rock is compromised. Open fractures or faults and wells could result in CH₄ contamination of overlying groundwater aquifers as well as surface emissions. We investigate this process through detailed numerical simulations for a large‐scale GCS pilot project (near Cranfield, Mississippi) for which a rich set of field data is available. An accurate cubic‐plus‐association equation‐of‐state is used to describe the non‐linear phase behavior of multiphase brine‐CH₄‐CO₂ mixtures, and breakthrough curves in two observation wells are used to constrain transport processes. Both field data and simulations indeed show the development of an extensive plume of CH₄‐rich (up to 90 mol%) gas as a consequence of CO₂ injection, with important implications for the risk assessment of future GCS projects.     

PM10 Source Apportionment in Ahvaz,Iran, Using Positive Matrix Factorization

Source apportionment of particulate matter <10 µm in diameter (PM₁₀), having considerable impacts on human health and the environment, is of high priority in air quality management. The present study, therefore, aimed at identifying the potential sources of PM₁₀ in an arid area of Ahvaz located in southwest of Iran. For this purpose, we collected 24‐h PM₁₀ samples by a high volume air sampler. The samples were then analyzed for their elemental (Al, As, B, Ba, Be, Ca, Cd, Co, Cr, Cu, Fe, Hg, K, Mg, Mn, Na, Ni, Pb, Se, Si, Sn, Sr, Li, Ti, V, Zn, Mo, and Sb) and ionic (NH, Cl^?, NO, and SO) components using inductively coupled plasma optical emission spectrometry and ion chromatography instruments, respectively. Eight factors were identified by positive matrix factorization: crustal dust (41.5%), road dust (5.5%), motor vehicles (11.5%), marine aerosol (8.0%), secondary aerosol (9.5%), metallurgical plants (6.0%), petrochemical industries and fossil fuel combustion (13.0%), and vegetative burning (5.0%). Result of this study suggested that the natural sources contribute most to PM₁₀ particles in the area, followed closely by the anthropogenic sources.     

Polynomial chaos expansion and response surface method for nonlinear modelling of reference evapotranspiration

The feasibility of polynomial chaos expansion (PCE) and response surface method (RSM) models is investigated for modelling reference evapotranspiration (ET₀). The modelling results of the proposed models are validated against the M5 model tree and multi-layer perceptron neural network (MLPNN) methods. Two meteorological stations, Isparta and Antalya, in the Mediterranean region of Turkey, are inspected. Various input combinations of daily air temperature, solar radiation, wind speed and relative humidity are constructed as input attributes for the ET₀. Generally, the modelling accuracy is increased by increasing the number of inputs. Including wind speed in the model inputs considerably increases their accuracy in modelling ET₀. Mean absolute error (MAE), root mean square error (RMSE), agreement index (d) and Nash-Sutcliffe efficiency (NSE) are used as comparison criteria. The PCE is the most accurate model in estimating daily ET₀, giving the lowest MAE (0.036 and 0.037 mm) and RMSE (0.047 and 0.050 mm) and the highest d (0.9998 and 0.9999) and NSE (0.9992 and 0.9996) with the four-input PCE models for Isparta and Antalya, respectively.     

Probabilistic analysis of soil‐structure interaction effects on the seismic performance of structures

This paper revisits the phenomenon of dynamic soil‐structure interaction (SSI) with a probabilistic approach. For this purpose, a twofold objective is pursued. First, the effect of SSI on inelastic response of the structure is studied considering the prevailing uncertainties. Second, the consequence of practicing SSI provisions of the current seismic design codes on the structural performance is investigated in a probabilistic framework. The soil‐structure system is modeled by the sub‐structure method. The uncertainty in the properties of the soil and the structure is described by random variables that are input to this model. Monte Carlo sampling analysis is employed to compute the probability distribution of the ductility demand of the structure, which is selected as the metrics for the structural performance. In each sample, a randomly generated soil‐structure system is subjected to a randomly selected and scaled ground motion. To comprehensively model the uncertainty in the ground motion, a suite of 3269 records is employed. An extensive parametric study is conducted to cover a wide range of soil‐structure systems. The results reveal the probability that SSI increases the ductility demand of structures designed based on the conventional fixed‐based assumption but built on flexible soil in reality. The results also show it is highly probable that practicing SSI provisions of modern seismic codes increase the ductility demand of the structure. Copyright © 2016 John Wiley & Sons, Ltd.     

Earthquake relocation in the Central Alborz region of Iran using a non-linear probabilistic method

In this study, we calculate accurate absolute locations for nearly 3,000 shallow earthquakes (≤20 km depth) that occurred from 1996 to 2010 in the Central Alborz region of northern Iran using a non-linear probabilistic relocation algorithm on a local scale. We aim to produce a consistent dataset with a realistic assessment of location errors using probabilistic hypocenter probability density functions. Our results indicate significant improvement in hypocenter locations and far less scattering than in the routine earthquake catalog. According to our results, 816 earthquakes have horizontal uncertainties in the 0.5–3.0 km range, and 981 earthquakes are relocated with focal-depth errors less than 3.0 km, even with a suboptimal network geometry. Earthquake relocated are tightly clustered in the eastern Tehran region and are mainly associated with active faults in the study area (the Mosha and Garmsar faults). Strong historical earthquakes have occurred along the Mosha and Garmsar faults, and the relocated earthquakes along these faults show clear north-dipping structures and align along east–west lineations, consistent with the predominant trend of faults within the study region. After event relocation, all seismicity lies in the upper 20 km of the crust, and no deep seismicity (>20 km depth) has been observed. In many circumstances, the seismicity at depth does not correlate with surface faulting, suggesting that the faulting at depth does not directly offset overlying sediments.     

Characterization of spatial patterns in river water quality using chemometric pattern recognition techniques

This study employed three chemometric data mining techniques (factor analysis (FA), cluster analysis (CA), and discriminant analysis (DA)) to identify the latent structure of a water quality (WQ) dataset pertaining to Kinta River (Malaysia) and to classify eight WQ monitoring stations along the river into groups of similar WQ characteristics. FA identified the WQ parameters responsible for variations in Kinta River's WQ and accentuated the roles of weathering and surface runoff in determining the river's WQ. CA grouped the monitoring locations into a cluster of low levels of water pollution (the two uppermost monitoring stations) and another of relatively high levels of river pollution (the mid-, and down-stream stations). DA confirmed these clusters and produced a discriminant function which can predict the cluster membership of new and/or unknown samples. These chemometric techniques highlight the potential for reasonably reducing the number of WQVs and monitoring stations for long-term monitoring purposes.