Crystalline basement and fold complex of the Volga-Ural, Pericaspian, and Fore-Caucasus petroliferous basins

3D models of apparent magnetization and density of rocks allow us to provide insights into the deep structure of the Volga-Ural, Pericaspian, and Fore-Caucasus petroliferous basins. In the Volga-Ural Basin, some Riphean rifts reveal close spatial relations to Paleoproterozoic linear zones, presumably of the rift nature as well. The structure of the Paleoproterozoic Toropets-Serdobsk Belt is interpreted in detail. Rocks with petrophysical properties inherent to basic volcanics are established in the pre-Paleozoic basement of the marginal zone of the Pericaspian Basin. These rocks locally spread beyond the boundary escarpment and may be regarded as a part of the Riphean plume-related basaltic province. It is shown that the Pericaspian Basin was formed on the place of a triple junction of Riphean rifts: the Sarpa and Central Pericaspian oceanic branches and the continental branch of the Pachelma Aulacogen. The drastically different petrophysical properties of the basement beneath Baltica and the Astrakhan Arch indicate that this arch is an element of the large terrane that was attached to Baltica in the Vendian. The suture along which the Astrachan Terrane is conjugated with the basement of the central and southern segments of the Karpinsky Ridge is traced beneath the Paleozoic complex. A system of northwest-verging thrust faults formed during the collision between Scythia and Eurasia is mapped in the basement of the junction zone between the Karpinsky Ridge and Scythian Platform (Terrane). According to geological data, this event took place in the Early Paleozoic.     

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.     

Temporal Structures of the North Atlantic Oscillation and Its Impact on the Regional Climate Variability

In this study, the temporal structure of the variation of North Atlantic Oscillation （NAO） and its impact on regional climate variability are analyzed using various datasets. The results show that blocking formations in the Atlantic region are sensitive to the phase of the NAO. Sixty-seven percent more winter blocking days are observed during the negative phase compared to the positive phase of the NAO. The average length of blocking during the negative phase is about 11 days, which is nearly twice as long as the 6-day length observed during the positive phase of the NAO. The NAO-related differences in blocking frequency and persistence are associated with changes in the distribution of the surface air temperature anomaly, which, to a large extent, is determined by the phase of the NAO. The distribution of regional cloud amount is also sensitive to the phase of the NAO. For the negative phase, the cloud amounts are significant, positive anomalies in the convective zone in the Tropics and much less cloudiness in the mid latitudes. But for the positive phase of the NAO, the cloud amount is much higher in the mid-latitude storm track region. In the whole Atlantic region, the cloud amount shows a decrease with the increase of surface air temperature. These results suggest that there may be a negative feedback between the cloud amount and the surface air t.emperature in the Atlantic region.     

Sulfoarsenide complexes of gold in hydrothermal solutions in the formation of gold ore deposits (thermodynamic modeling)

The composition and conditions of the formation of gold sulfoarsenide complexes were studied by means of the solution of inverse problems of physicochemical modeling on the basis of the SELEKTOR software, with the computer analysis of the experimental data on Au dissolution in the presence of orpiment at 200–300°C and 1 kbar pressure. It was shown that sulfoarsenide complexes of gold formed in sulfurous-arsenious metalliferous hydrothermal solutions quantitatively prevailed in acidic and near-neutral solutions in the presence of As. The stability of the H₂AuAsS ₃ ⁰ sulfoarsenide complex and of its AuAsS ₂ ⁰ deprotonated analogue depends on the concentration of arsenic in the system, just as the ratio of sulfoarsenide and hydrosulfide complexes of gold. The productive metalliferous generations of sulfides in pyrite-arsenopyrite parageneses are deposited involving gold sulfoarsenides.     

Atmospheric modulation of surface heat fluxes at Ocean Weather Station P on a decadal time‐scale

Abstract

A 30‐year record (1951–1980) of surface heat fluxes at Ocean Weather Station P in the northeastern Pacific Ocean (50°N, 145°W) was examined for differences in the interdecadal variation between fail and winter. During the latter part of the 1950s and the early 1960s, the winter surface heat flux from the ocean to the atmosphere diminished significantly whereas the fall heat flux increased slightly This difference in the modulation of the winter heat flux from the fall heat flux during this period appears to be caused by the presence of an atmospheric circulation anomaly resembling that of the Pacific/North America (PNA) low‐frequency variability mode during the winter season.     

Application of wavelet-artificial intelligence hybrid models for water quality prediction: a case study in Aji-Chay River,Iran

The accuracy of Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS), wavelet-ANN and wavelet-ANFIS in predicting monthly water salinity levels of northwest Iran’s Aji-Chay River was assessed. The models were calibrated, validated and tested using different subsets of monthly records (October 1983 to September 2011) of individual solute (Ca²⁺, Mg²⁺, Na⁺, SO₄ ^2? and Cl^?) concentrations (input parameters, meq L^?1), and electrical conductivity-based salinity levels (output parameter, µS cm^?1), collected by the East Azarbaijan regional water authority. Based on the statistical criteria of coefficient of determination (R²), normalized root mean square error (NRMSE), Nash–Sutcliffe efficiency coefficient (NSC) and threshold statistics (TS) the ANFIS model was found to outperform the ANN model. To develop coupled wavelet-AI models, the original observed data series was decomposed into sub-time series using Daubechies, Symlet or Haar mother wavelets of different lengths (order), each implemented at three levels. To predict salinity input parameter series were used as input variables in different wavelet order/level-AI model combinations. Hybrid wavelet-ANFIS (R² = 0.9967, NRMSE = 2.9 × 10^?5 and NSC = 0.9951) and wavelet-ANN (R² = 0.996, NRMSE = 3.77 × 10^?5 and NSC = 0.9946) models implementing the db4 mother wavelet decomposition outperformed the ANFIS (R² = 0.9954, NRMSE = 3.77 × 10^?5 and NSC = 0.9914) and ANN (R² = 0.9936, NRMSE = 3.99 × 10^?5 and NSC = 0.9903) models.     

A Spectral Analysis Based Methodology to Detect Climatological Influences on Daily Urban Water Demand

Urban water demand (UWD) is highly dependent on interacting natural and socio-economic factors, and thus a wide range of data analysis and forecasting methods are required to fully understand the issue. This study applies, for the first time, the continuous wavelet transform to determine changes in the temporal pattern of UWD and its potential meteorological drivers for three major Canadian cities: Calgary, Montreal, and Ottawa. This analysis is complemented by Fourier and cross-spectral analysis to determine inter-relationships and the significance of the patterns detected. The results show that the annual (365 days) cycle provides the most consistent and significant relationship between UWD and meteorological drivers. Wavelet analysis shows that UWD is only sensitive to air temperature in the summer months when mean daily temperatures are greater than 10 to 12 °C. For the three cities studied, the UWD increases by between 10 ML (Montreal) and 50 ML (Calgary) per day with every 1 °C increase in air temperature. In an area with low precipitation (Calgary), there is an inverse relationship between UWD and precipitation during summer months. Wavelet transform and Fourier analysis also detected a 7-day cycle in UWD, particularly in the more industrialized city of Montreal, which is related to the working week. In general, applying the season dependent linear relationships between UWD and temperature is suggested as perhaps being more appropriate and potentially successful for forecasting, rather than continuous complex nonlinear algorithms that are designed to explain variability in the entire UWD record.