Alteration Mapping for Porphyry Copper Exploration Using ASTER and QuickBird Multispectral Images,Sonajeel Prospect,NW Iran

The Sonajeel prospect is located in the Arasbaran belt which is one of the significant copper mineralization belts in NW Iran. There are mostly Eocene volcano-sedimentary rocks and Post Eocene intrusive units which are the source for mineralization in the area. ASTER multispectral images were used for delineation of alteration zones as a key feature of porphyry copper mineralization. Due to the need for geometric correction and ortho-rectification of the ASTER images, a high resolution QuickBird image with pixel width of about 60 cm (in PAN) was employed as a reference image in order to boost the rectification process. Ortho-rectification has been done by using digital elevation model which is created by topographic map in scale 1:1000. Potassic alteration as one of the essential alteration types in porphyry copper deposits, distributed mostly in the north of the Sonajeel prospect that determined by Thermal infrared bands processing. Phyllic and argillic alteration zones detected by creating relative absorption band-depth grids which are comparable to field observations. Moreover, silica rich areas which are remnants of hydrothermal circulation and form at the top of porphyry copper systems were detected for recognition of epithermal deposits (with 1 km distance from Sonajeel porphyry system). Finally, Remote Sensing results were compared by field evidences especially for determination of an epithermal system. Most parts of the alteration zones were observed of the surface confirmed with the remote sensing alteration (in average about 75% matched fittingly), displayed concentrations anomalous in the NE and NW parts of the studied area.     

Modelling of piping collapses and gully headcut landforms:Evaluating topographic variables from different types of DEM

The geomorphic studies are extremely dependent on the quality and spatial resolution of digital elevation model(DEM)data.The unique terrain characteristics of a particular landscape are derived from DEM,which are responsible for initiation and development of ephemeral gullies.As the topographic features of an area significantly influences on the erosive power of the water flow,it is an important task the extraction of terrain features from DEM to properly research gully erosion.Alongside,topography is highly correlated with other geo-environmental factors i.e.geology,climate,soil types,vegetation density and floristic composition,runoff generation,which ultimately influences on gully occurrences.Therefore,terrain morphometric attributes derived from DEM data are used in spatial prediction of gully erosion susceptibility(GES)mapping.In this study,remote sensing-Geographic information system(GIS)tech-niques coupled with machine learning(ML)methods has been used for GES mapping in the parts of Semnan province,Iran.Current research focuses on the comparison of predicted GES result by using three types of DEM i.e.Advanced Land Observation satellite(ALOS),ALOS World 3D-30 m(AW3D30)and Advanced Space borne Thermal Emission and Reflection Radiometer(ASTER)in different resolutions.For further progress of our research work,here we have used thirteen suitable geo-environmental gully erosion conditioning factors(GECFs)based on the multi-collinearity analysis.ML methods of conditional inference forests(Cforest),Cubist model and Elastic net model have been chosen for modelling GES accordingly.Variable's importance of GECFs was measured through sensitivity analysis and result show that elevation is the most important factor for occurrences of gullies in the three aforementioned ML methods(Cforest=21.4,Cubist=19.65 and Elastic net=17.08),followed by lithology and slope.Validation of the model's result was performed through area under curve(AUC)and other statistical indices.The validation result of AUC has shown that Cforest is the most appropriate model for predicting the GES assessment in three different DEMs(AUC value of Cforest in ALOS DEM is 0.994,AW3D30 DEM is 0.989 and ASTER DEM is 0.982)used in this study,followed by elastic net and cubist model.The output result of GES maps will be used by decision-makers for sustainable development of degraded land in this study area.     

Landslide susceptibility assessment by Dempster–Shafer and Index of Entropy models,Sarkhoun basin,Southwestern Iran

Landslides are natural disasters often activated by interaction of different controlling environmental factors, especially in mountainous terrains. In this research, the landslide susceptibility map was developed for the Sarkhoun catchment using Index of Entropy (IoE) and Dempster–Shafer (DS) models. For this purpose, 344 landslides were mapped in GIS environment. 241 (70%) out of the landslides were selected for the modeling and the remaining (30%) were employed for validation of the models. Afterward, 10 landslide conditioning factor layers were prepared including land use, distance to drainage, slope gradient, altitude, lithology, distance to roads, distance to faults, slope aspect, Topography Wetness Index, and Stream Power Index. The relationship between the landslide conditioning factors and landslide inventory maps was determined using the IoE and DS models. In order to verify the models, the results were compared with validation landslide data not employed in training process of the models. Accordingly, Receiver Operating Characteristic (ROC) curves were applied, and Area Under the Curve (AUC) was calculated for the obtained susceptibility maps using the success (training data) and prediction (validation data) rate curves. The land use was found to be the most important factor in the study area. The AUC are 0.82, and 0.81 for success rates of the IoE, and DS models, respectively, while the prediction rates are 0.76 and 0.75. Therefore, the results of the IoE model are more accurate than the DS model. Furthermore, a satisfactory agreement is observed between the generated susceptibility maps by the models and true location of the landslides.     

Impact of local site conditions on portfolio earthquake loss estimation for different building types

This article presents a sensitivity analysis investigating the impact of using high-resolution site conditions databases in portfolio earthquake loss estimation. This article also estimates the effects of variability in the site condition databases on probabilistic earthquake loss ratios and their geographical pattern with respect to structural characteristics of different building types. To perform the earthquake loss estimation here, the OpenQuake software developed by Global Earthquake Model is implemented in Clemson University’s supercomputer. The probabilistic event-based risk analysis is employed considering several notional portfolios of different building types in the San Francisco area as the inventory exposure. This analysis produces the stochastic event sets worth for 10,000 years including almost 8000 synthetically simulated earthquakes. Then, the ground motion prediction equations are used to calculate the ground motion per event and incorporate the effect of five site conditions, on amplifying or de-amplifying the ground motions on notional building exposure locations. Notional buildings are used to account for various building characteristics in conformance with the building taxonomy represented in HAZUS software. The HAZUS damage functions are applied to model the vulnerability of various structural types of buildings. Finally, the 50-year average mean loss and probabilistic loss for multiple values for probability of exceedance (2, 10, 20, and 40%) in 50 years are calculated, and the impact of different site condition databases on portfolio loss ratios is investigated for different structural types and heights of buildings. The results show the aggregated and geographical variation of loss and loss ratio throughout the region for various site conditions. Comparing the aggregated loss and loss ratio, while considering different databases, represents normalized differences that are limited to 6% for all building taxonomy with various heights and for all PoEs. However, site-specific loss ratio errors are significantly greater and in some cases are more than 20%.     

Flood hazard mapping using synthesis hydraulic and geomorphic properties at watershed scale

The occurrence of natural phenomena such as floods has caused serious consequences for human societies. The simulation of flood hazard maps and its depth in a river is one of the most complex processes in hydrology. In fact both geomorphological and hydraulic procedures for deriving the flood hazard maps and depth are imperfect at watershed scale. In this study, a combination of both procedures, using a probabilistic approach is used. Flood inundation maps for 2-, 10-, 25-,50- and 100-return period floods using flood routine within HEC-RAS in combination of Arc-GIS and topographic wetness index (TWI) map were produced. TWI threshold was identified using a maximum likelihood method in order to produce flood prone areas and calibrated over the reach of Zirab City. The correlation between TWI threshold and the flood depth was carried out and simple linear regression developed for various return periods. The resulting regression model is used in order to create flood hazard maps with various return periods at watershed scale.     

Inversion of surface gravity data for 3-D density modeling of geologic structures using total variation regularization

We develop an inversion procedure using the total variation (TV) regularization method as a stabilizing function to invert surface gravity data to retrieve 3-D density models of geologic structures with sharp boundaries. The developed inversion procedure combines several effective algorithms to solve the TV regularized problem. First, a matrix form of the gradient vector is designed using the Kronecker product to numerically approximate the 3-D TV function. The piecewise polynomial truncated singular value decomposition (PP-TSVD) algorithm is then used to solve the TV regularized inverse problem. To obtain a density model with depth resolution, we use a sensitivity-based depth weighting function. Finally, we apply the Genetic Algorithm (GA) to select the best combination of the PP-TSVD algorithm and the depth weighting function parameters. 3-D simulations conducted with synthetic data show that this approach produces sub-surface images in which the structures are well separated in terms of sharp boundaries, without the need of a priori detailed density model. The method applied to a real dataset from a micro-gravimetry survey of Gotvand Dam, southwestern Iran, clearly delineates subsurface cavities starting from a depth of 40 m within the area of the dam reservoir.     

Geochemical Anomaly and Mineral Prospectivity Mapping for Vein-Type Copper Mineralization,Kuhsiah-e-Urmak Area,Iran: Application of Sequential Gaussian Simulation and Multivariate Regression Analysis

Natural Resources Research - In this paper, sequential Gaussian simulation (SGS) and number–size (N–S) fractal modeling were used for copper geochemical anomaly mapping in the western...     

Steady two-layer vortices on the beta-plane

Monopolar vortices are studied in the framework of the quasigeostrophic two-layer equations. Steady, eastward-travelling vortex solutions with a baroclinic vertical structure and closed streamlines in both layers are obtained' by perturbation analysis. The radial profile is essentially arbitrary in the region of closed streamlines. Westward-travelling vortices with a similar structure radiate barotropic waves, and are therefore unsteady. The propagation velocity of the vortices is essentially determined by the ‘hetonic’ mechanism, i.e. by the horizontal shift between the upper and lower-layer vortices. Their dynamics are studied qualitatively, and it is concluded that eastward-travelling vortices are stable, whereas those travelling westward are unstable.     

Normalized residual displacement spectra for post-mainshock assessment of structures subjected to aftershocks

Residual displacement, as a significant measure of structural inelasticity, is effectively used in post-earthquake seismic assessment of structures. This demand can be considered for seismic evaluation of structures under multiple earthquakes. This study introduces a simple and novel index to predict the residual displacement of mainshock-damaged structures against subsequent aftershock. The proposed index is defined as a ratio between residual displacement of damaged structures against aftershock and peak inelastic displacement of intact structures under mainshock. In this study, constantstrength spectra based on the index are developed considering the effects of important structural characteristics and also significant seismic parameters. Moreover, analytical equations are presented to predict the proposed index for bi-linear single-degree-of-freedom(SDOF) systems considering both the effects of positive and negative polarities of aftershock. Furthermore, an equation is suggested to estimate the peak inelastic displacement of intact systems under mainshock, which is required to compute the index.