Artificial neural network inversion of magnetic anomalies caused by 2D fault structures

A new approach is proposed to interpret magnetic anomalies caused by 2D fault structures. This approach is based on the artificial neural network inversion, utilizing particularly modular neural network algorithm. The inversion process is implemented to estimate the parameters of 2D fault structures where it has been verified first on synthetic models. The results of the inversion show that the parameters derived from the inversion agree well with the true ones. The analysis of noise has been studied in order to investigate the stability of the approach where it has been tested for contaminated anomalies with 5 and 10 % of white Gaussian noise. The results of the inversion provide satisfactory results even with contaminated signals.The validity of the approach has been demonstrated through real data taken from New South Wales, Australia. A comparable and satisfactory agreement is shown between the inversion results of the neural network and those from techniques published in literatures.     

Impact of model complexity and multi-scale data integration on the estimation of hydrogeological parameters in a dual-porosity aquifer

This study investigates the impact of model complexity and multi-scale prior hydrogeological data on the interpretation of pumping test data in a dual-porosity aquifer (the Chalk aquifer in England, UK). In order to characterize the hydrogeological properties, different approaches ranging from a traditional analytical solution (Theis approach) to more sophisticated numerical models with automatically calibrated input parameters are applied. Comparisons of results from the different approaches show that neither traditional analytical solutions nor a numerical model assuming a homogenous and isotropic aquifer can adequately explain the observed drawdowns. A better reproduction of the observed drawdowns in all seven monitoring locations is instead achieved when medium and local-scale prior information about the vertical hydraulic conductivity (K) distribution is used to constrain the model calibration process. In particular, the integration of medium-scale vertical K variations based on flowmeter measurements lead to an improvement in the goodness-of-fit of the simulated drawdowns of about 30%. Further improvements (up to 70%) were observed when a simple upscaling approach was used to integrate small-scale K data to constrain the automatic calibration process of the numerical model. Although the analysis focuses on a specific case study, these results provide insights about the representativeness of the estimates of hydrogeological properties based on different interpretations of pumping test data, and promote the integration of multi-scale data for the characterization of heterogeneous aquifers in complex hydrogeological settings.     

Evidence for the occurrence of hydrogeochemical processes in the groundwater of Khoy plain,northwestern Iran,using ionic ratios and geochemical modeling

Rapid population growth, industrialization, and agricultural expansion in the Khoy area (northwestern Iran) have led to its dependence on groundwater and degradation of groundwater quality. This study attempts to decipher the major processes and factors that degrade the groundwater quality of the Khoy plain. For this purpose, 54 groundwater samples from unconfined and confined aquifers of the plain were collected in July 2017 and analyzed for major cations and anions (Na, K, Ca, Mg, HCO₃, SO_4, and Cl), minor ions (NO₃ and F), and Al. Magnesium and bicarbonate were identified as the dominant cation and anion, respectively. Several ionic ratios and geochemical modeling using PHREEQC indicated that the most important hydrogeochemical processes to affect groundwater quality in the plain were weathering and dissolution of evaporitic and silicate minerals, mixing, and ion exchange. There were smaller effects from evaporation and anthropogenic factors (e.g., industries). Results showed that the high salinity of the groundwater in the northeast area of the plain was due to the high solubility of the evaporitic minerals, e.g., halite and gypsum. Reverse ion exchange and the contribution of mineral dissolution were more significant than ion exchange in the northeastern part of the plain. Elevated salinity of the groundwater in the southeast was attributed mostly to reverse ion exchange and somewhat to evaporation.     

APG:A novel python-based ArcGIS toolbox to generate absence-datasets for geospatial studies

One important step in binary modeling of environmental problems is the generation of absence-datasets that are traditionally generated by random sampling and can undermine the quality of outputs.To solve this problem,this study develops the Absence Point Generation(APG)toolbox which is a Python-based ArcGIS toolbox for automated construction of absence-datasets for geospatial studies.The APG employs a frequency ratio analysis of four commonly used and important driving factors such as altitude,slope degree,topographic wetness index,and distance from rivers,and considers the presence locations buffer and density layers to define the low potential or susceptibility zones where absence-datasets are gener-ated.To test the APG toolbox,we applied two benchmark algorithms of random forest(RF)and boosted regression trees(BRT)in a case study to investigate groundwater potential using three absence datasets i.e.,the APG,random,and selection of absence samples(SAS)toolbox.The BRT-APG and RF-APG had the area under receiver operating curve(AUC)values of 0.947 and 0.942,while BRT and RF had weaker per-formances with the SAS and Random datasets.This effect resulted in AUC improvements for BRT and RF by 7.2,and 9.7％from the Random dataset,and AUC improvements for BRT and RF by 6.1,and 5.4％from the SAS dataset,respectively.The APG also impacted the importance of the input factors and the pattern of the groundwater potential maps,which proves the importance of absence points in environmental bin-ary issues.The proposed APG toolbox could be easily applied in other environmental hazards such as landslides,floods,and gully erosion,and land subsidence.     

An effective stress-based DSC model for predicting the coefficient of lateral soil pressure in unsaturated soils

Acta Geotechnica - In this study, an analytical model is developed to establish a framework for predicting the coefficient of lateral soil pressure in unsaturated soils. To this end, the disturbed...     

The thermal maturity of sedimentary basins as revealed by magnetic mineralogy

The thermal evolution of sedimentary basins is usually constrained by maturity data, which is interpreted from Rock-Eval pyrolysis and vitrinite reflectance analytical results on field or boreholes samples. However, some thermal evolution models may be inaccurate due to the use of elevated maturities measured in samples collected within an undetected metamorphic contact aureole surrounding a magmatic intrusion. In this context, we investigate the maturity and magnetic mineralogy of 16 claystone samples from Disko-Svartenhuk Basin, part of the SE Baffin Bay volcanic margin. Samples were collected within thermal contact metamorphic aureoles near magma intrusions, as well as equivalent reference samples not affected by intrusions. Rock-Eval pyrolysis (T_max), and vitrinite reflectance (Ro) analysis were performed to assess the thermal maturity, which lies in the oil window when 435°C ≤ T_max ≤ 470°C and 0.6%–0.7% ≤ Ro ≤ 1.3%. In addition, we performed low- (<300K) and high-temperature (>300K) investigations of isothermal remanent magnetization to assess the magnetic mineralogy of the selected samples. The maturity results (0.37% ≤ Ro ≤ 2%, 22°C ≤ T_max ≤ 604°C) show a predominance of immature to early mature Type III organic matter, but do not reliably identify the contact aureole when compared to the reference samples. The magnetic assemblage of the immature samples consists of iron sulphide (greigite), goethite and oxidized or non-stoichiometric magnetite. The magnetic assemblage of the early mature to mature samples consists of stoichiometric magnetite and fine-grained pyrrhotite (<1 μm). These results document the disappearance of the iron sulphide (greigite) and increase in content of magnetite during normal burial. On the other hand, magnetite is interpreted to be the dominant magnetic mineral inside the contact aureole surrounding dyke/sill intrusions where palaeotemperatures indicate mature to over-mature state. Interestingly, the iron sulphide (greigite) is still detected in the contact aureole where palaeotemperatures exceeded 130°C. Therefore, the magnetic mineralogy is a sensitive method that can characterize normal burial history, as well as identify hidden metamorphic contact aureoles where the iron sulphide greigite is present at temperatures beyond its stability field.     

A study of crude oil‐degrading bacteria from mangrove forests in the Persian Gulf

Mangroves are coastal ecosystems, found in tropical and subtropical regions around the world. They are found in the transitional zones between land, sea, and rivers. Petroleum hydrocarbons are the most common environmental pollutants, and oil spills pose a great hazard to mangroves forests. This research was focused on the isolation and characterization of crude oil‐degrading bacteria from mangrove ecosystems at the Persian Gulf. Sixty‐one crude oil‐degrading bacteria were isolated from mangrove samples (plant, sediment, and seawater) that enriched in ONR7a medium with crude oil as only carbon source. Some screening tests such as growth at high concentration of crude oil, bioemulsifier production, and surface hydrophobicity were done to select the most efficient strains for crude oil degradation. Molecular identification of strains was carried out by amplification of the 16S rRNA gene by PCR. The results of this study were indicated that the quantity of crude oil‐degrading bacteria was higher in the root of mangrove plants compare to other mangrove samples (sediment and seawater). Also, identification results confirmed that these isolated strains belong to Vibrio sp. strain NW4, Idiomarina sp. strain BW32, Kangiella sp. strain DP40, Marinobacter sp. strain DW44, Halomonas sp. strain BS53, and Vibrio sp. strain DS35. The application of bioremediation strategies with these bacteria can reduce crude oil pollution in this important marine environment.     

Isolation, distribution and evaluation of cytotoxic and antioxidant activity of cultivable actinobacteria from the Oman Sea sediments

Screening bioactive natural products from bacteria is a determinative step in the drug discovery programs. The present study aim to isolate actinobacteria from the Oman Sea sediments for determining the effects of different culture media and treatments on the yield of the isolation process, and measure the DPPH radical scavenging and Artemia cytotoxic activity of culture extracts of the actinobacterial isolates. A total of 290 actinobacterial isolates were collected from 14 sediment samples. Heat treatment(40.68%) and M_4 medium(29.31%) exhibited the maximum isolation rates of actinobacteria. Streptomyces isolates were dominantly distributed in all of the investigated stations according to 16 S rRNA gene sequencing. The distribution pattern of Streptomyces followed a depth-dependent frequency trend, whereas the members of rare genera including Micromonospora, Nocardia Actinoplanes, Nocardiopsis, Saccharopolyspora and Crossiella were distributed in deeper stations. Approximately,25% of the examined isolates could scavenge 90% of 10~(–4) mol/L DPPH solutions at 1 250 μg/mL final concentration of their ethyl acetate culture extracts. Furthermore, the most potent extracts could scavenge DPPH radicals with IC50 ranges from 356.8 to 566.4 μg/mL. Brine shrimp cytotoxicity tests showed that 38.88% of the examined culture extracts exhibited LC_(50) lower than 1 000 μg/mL against the Artemia cells. Moreover, the most potent culture extracts exhibited LC_(50) range from 335.4 to 534.4 μg/mL. Phylogenetic analysis by 16 S rRNA gene sequence revealed that the OS 005, OS 263 and OS 157 closely related to Streptomyces djakartensis, Streptomyces olivaceus and Nocardiopsis dassonvillei respectively. These results suggested the widespread distribution of the antioxidant and cytotoxic producing actinobacteria in the Oman Sea sediments, which could be considered as promising candidates for the discovery of microbial bioactive compounds.     

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.