Earthquake ground-motion prediction equations for northern Iran

Natural Hazards - Earthquake ground-motion prediction equations for soil and rock sites in northern Iran have been developed based on stochastic models and Bayesian updating. Due to a lack of...     

Coastal Wave Height Prediction using Recurrent Neural Networks (RNNs) in the South Caspian Sea

The prediction of wave parameters has a great significance in the coastal and offshore engineering. For this purpose, several models and approaches have been proposed to predict wave parameters, such as empirical, soft computing, and numerical based approaches. Recently, soft computing techniques such as recurrent neural networks (RNN) have been used to develop sea wave prediction models. In this study, the RNN for wave prediction based on the data gathered and the measurement of the sea waves in the Caspian Sea, in the north of Iran is used for this study. The efficiency of RNNs for 3, 6, and 12 hourly and diurnal wave prediction using correlation coefficients is calculated to be 0.96, 0.90, 0.87, and 0.73, respectively. This indicates that wave prediction by using RNNs yields better results than the previous neural network approaches.     

An assessment of groundwater salinization in Haryana state in India using hydrochemical tools in association with GIS

Unplanned abstraction of groundwater due to various land use land cover activities and variations in monsoonal rainfall have greatly affected the availability and quality of groundwater resources in semi-arid regions of India. In the present study, a study of the hydrogeochemical characteristics of groundwater was undertaken in the Sonipat district of Haryana in India together with the use of stable isotope (δ¹⁸O and δD) measurements and GIS analysis. A total of 53 groundwater samples were collected from seven blocks of the district, and 14 water quality parameters and stable isotopes (δ¹⁸O and δD) were analysed to infer hydrogeochemical processes taking place in the area. The integration of hydrochemistry with GIS is very helpful to understand the factors governing in the area. The majority of the samples showed Na–Cl type of hydrochemical facies. The trilinear plot for major cations and anions in groundwater indicates dominance of sodium, calcium, chloride and bicarbonate ions. Nitrate plumes in the groundwater appear to be migrating in groundwater from the central and south-western parts of the area towards the urbanized areas. A total of 64% of the samples exceed the maximum permissible limit of 1.5 mg/L given by WHO for fluoride. Besides natural sources such as silicate and carbonate weathering, ion exchange, and reverse ion exchange, the leaching of surficial salts and untreated industrial wastes along with unregulated abstraction are contributing to poor groundwater quality in the study area. An assessment of saturation indices has shown that groundwater in the area is unsaturated with respect to anhydrite, halite and gypsum suggesting significant contribution of Ca²⁺, Mg²⁺ and other ions in the groundwater. A scatter plot of δ¹⁸O versus Cl also suggests mixing of saline water with fresh groundwater.     

Trend analysis of hydroclimatological variables in Urmia lake basin using hybrid wavelet Mann–Kendall and Şen tests

This paper investigates monthly, seasonal, and annual trends in rainfall, streamflow, temperature, and humidity amounts at Urmia lake (UL) basin and analyzes the interaction between these variables and UL’s water level fluctuation during the 1971–2013 period. Two new methods including nonparametric hybrid wavelet Mann–Kendall test and ?en’s methodology have been used to determine potential trends in the variables and their dominant periods. The results showed significant decreasing trends in the water level and streamflow series, moderate decreasing trend in the rainfall and relative humidity series, and increasing trends in the observed temperature data. The 8- , 12-month, and 2-year periods were detected as the dominant periods of the variables in monthly, seasonal, and annual timescales, respectively. The results from the interaction analysis revealed that the main factor influencing the water level at UL is decreasing trend in the streamflow series. Both the monthly series of UL’s water level and the streamflow series of the stations indicated two start points of significant decreasing trend in 1973 and 1998. Furthermore, a comparative analysis among the applied methods indicated a good agreement between the results of hybrid wavelet Mann–Kendall test and ?en’s trend analyzing method.     

Prediction of river flow using hybrid neuro-fuzzy models

The complex nature of hydrological phenomena, like rainfall and river flow, causes some limitations for some admired soft computing models in order to predict the phenomenon. Evolutionary algorithms (EA) are novel methods that used to cover the weaknesses of the classic training algorithms, such as trapping in local optima, poor performance in networks with large parameters, over-fitting, and etc. In this study, some evolutionary algorithms, including genetic algorithm (GA), ant colony optimization for continuous domain (ACO_R), and particle swarm optimization (PSO), have been used to train adaptive neuro-fuzzy inference system (ANFIS) in order to predict river flow. For this purpose, classic and hybrid ANFIS models were trained using river flow data obtained from upstream stations to predict 1-, 3-, 5-, and 7-day ahead river flow of downstream station. The best inputs were selected using correlation coefficient and a sensitivity analysis test (cosine amplitude). The results showed that PSO improved the performance of classic ANFIS in all the periods such that the averages of coefficient of determination, R², root mean square error, RMSE (m³/s), mean absolute relative error, MARE, and Nash-Sutcliffe efficiency coefficient (NSE) were improved up to 0.19, 0.30, 43.8, and 0.13%, respectively. Classic ANFIS was only capable to predict river flow in 1-day ahead while EA improved this ability to 5-day ahead. Cosine amplitude method was recognized as an appropriate sensitivity analysis method in order to select the best inputs.     

Application of gravity and magnetic methods for the crustal study and delineating associated ores in the western limb of Hazara Kashmir Syntaxis,Northwest Himalayas,Pakistan

The present geophysical study deals with the ores and crustal demonstration of southeastern Hazara and its adjoining areas of Azad Jammu and Kashmir, Pakistan, on the basis of terrestrial gravity and magnetic data. Tectonically, the study area lies in the Lesser Himalayas as well as to an extent in the sub-Himalaya, more specifically in the western limb of Hazara Kashmir Syntaxis. In this study, 567 gravity and 508 magnetic stations have been measured with CG-5 gravimeter and proton precession magnetometer, respectively. The collected data have been processed by applying standard corrections and then different types of maps were prepared. The ores in the area have been delineated by the qualitative interpretation of residual Bouguer anomaly and reduction to pole total magnetic intensity maps, whereas regional structures are demarcated by the Bouguer anomaly and regional Bouguer anomaly maps. The positive contour closures on the residual Bouguer anomaly map indicate the iron ore and phosphate, whereas negative contour closures are the effects of low-density material which consists of gypsum and soapstone. The pole-reduced total intensity map also shows the negative and positive contour closures almost in the same localities and confirms the residual Bouguer anomaly map. The geological model computed on the basis of Bouguer anomaly demarcated a series of faults between different rock units in the study area. The Kashmir Boundary Thrust cuts the western limb of Hazara Kashmir Syntaxis near the apex in the north of Muzaffarabad and marks the boundary between Murree Formation and carbonates of Abbottabad Formation. The gravity model also suggests that the thickness of the crust increases towards the northeast.     

Wavelet-Hilbert transform-based simulation of pulse-like ground motion

In nonlinear dynamic structural analysis, a suite of pulse-like ground motions is required for the performance-based design of structures near active faults. The dissimilarity in the amplitude and frequency content of the earthquake time series referred to nonstationary properties in temporal and spectral, respectively. An approach is proposed based on the nonstationary properties of the far-field records and the seismological information in an event for simulating pulse-like records. The pulse-like earthquake time history is estimated via the superposition of the residual part of the earthquake with the estimated pulse. The wavelet-based Hilbert transform is utilized to characterize the nonstationary properties, the instantaneous amplitude, and frequencies of far-field records to model residual part. The effects of near-fault and pulse are estimated based on the seismological properties of the region. The validation of the procedure is indicated by comparing simulated time-series, response spectra, and Arias intensity with recorded pulse-like records in two different earthquakes in California; the M_w 6.7 1994 Northridge and the M_w 6.5 1979 Imperial valley.

     

Identification of wet-prone regions over Northwest Himalaya using high-resolution satellite seasonal estimates

Natural Hazards - The present study aims to evaluate four satellite estimates, namely CMORPH v0.x, PERSIANN-CDR, TMPA-V7 and TMPA-V7-RT, over four seasons (during 2003–2017) against ground...     

The occurrence of NADPH-ferrihemoprotein reductase in Corbula caribea, from a natural oil seep at La Brea, Trinidad

Corbula caribea is the most common non-polychaete macrofaunal organism identified at a large natural oil seep at La Brea in south Trinidad. It is hypothesized that these animals may possess (NADPH-ferrihemoprotein reductase) a component of the Mixed Function Oxygenase system (MFO), which may allow them to ameliorate the potentially deleterious effects resulting from exposure to the high levels of petroleum hydrocarbons within this environment. This study was designed to determine whether organisms from the seep site showed greater enzyme activity when compared to organisms from a non-seep reference site. NADPH-ferrihemoprotein reductase activity was determined by incubating 10 microm cryostat sections with nitro-blue tetrazolium. The reaction product was determined by visual assessment and quantified by measuring the relative mean stain intensity. The intense staining, indicative of enzyme activity was evident in the digestive epithelia of seep animals. Observations indicated that organisms from the seep showed more intense staining, indicating greater enzyme activity, when compared to animals from a non-seep reference site. The relative stain intensity of NADPH-ferrihemoprotein reductase determined for organisms from the seep was 61.30. This was significantly higher than the stain intensity determined for organisms from the non-seep reference site (7.11). This supported visual assessments, which suggested that the seep organisms showed higher enzyme activity than organisms from the non-seep site. The results suggest that NADPH-ferrihemoprotein reductase may be present in Corbula caribea from the seep site and not in those from the non-seep site. It is possible that this enzyme may contribute to these animals ability to tolerate chronic exposure to petroleum hydrocarbons and offer then a selective advantage for survival the seep environment.