Petrogenesis of Volcanic Rocks in the Khabr-Marvast Tectonized Ophiolite:Evidence for Subduction Processes in the South-Western Margin of Central Iranian Microcontinent

Abstract: The Late Cretaceous Khabr–Marvast tectonized ophiolite is located in the middle part of the Nain–Baft ophiolite belt, at the south-western edge of the central Iranian microcontinent. Although all the volcanic rocks in the study area indicate subduction-related magmatism (e.g. high LILE (large ion lithophile elements) / HFSE (high field strenght elements) ratios and negative anomalies in Nb and Ta), geological and geochemical data clearly distinguish two distinct groups of volcanic rocks in the tectonized association: (1) group 1 is comprised of hyaloclastic breccias, basaltic pillow lavas, and andesite sheet flows. These rocks represent the Nain–Baft oceanic crust; and (2) group 2 is alkaline lavas from the top section of the ophiolite suite. These lavas show shoshonite affinity, but do not support the propensity of ophiolite.     

Estimation of sediment load and erosion of different geological units: A case study from a basin of north-eastern Iran

Erosion of geological units and sediment load in rivers can be considered as the serious problems in recent decades.Increasing sediment loads generate major hazards for water resources development,particularly in terms of loss of reservoir storage due to sedimentation and siltation of water distribution systems.In this paper,the performance of four sediment rating curve (SRC) development methods was evaluated for the Shirin Darreh River(SDR) basin (1750 km2),located in North Khorasan Province,Iran.Data of flow discharge (Q) and suspended sediment flux (SSF)(Q-SSF pairs,N=957)and daily flow discharge,recorded by the Regional Water Company of North Khorasan (RWCNK) at the Qaleh-Barbar (QB) gauging site during 1989-2018were used.The flow discharge classification method performed best by meeting the desired criteria of most statistical indices,including normalized root mean square error (NRMSE),mean bias error (MBE),mean absolute error (MAE),index of agreement (d),and coefficient of determination (R~2).Based on the optimized method,the rate of suspended sediment transportation at the study site was estimated about2.7×10~6 ton year~(-1).Erodibility of the exposed formations in the study area was estimated based on a factorial scoring model (FSM).Three indices,focused on the outcrop and erodibility,were calculated for the geological units at sub-basin and total scales.Marl deposits are the most extensive geological unit in the three sub-basins and the maximum formation outcrop ratio (FOR) and participation in erosion (PCE)were obtained for these rocks at total scale.In fact,marl unit can be regarded as the main source to supply the suspended sediments in the study basin.     

Spatial crime distribution and prediction for sporting events using social media

ABSTRACT

Sporting events attract high volumes of people, which in turn leads to increased use of social media. In addition, research shows that sporting events may trigger violent behavior that can lead to crime. This study analyses the spatial relationships between crime occurrences, demographic, socio-economic and environmental variables, together with geo-located Twitter messages and their ‘violent’ subsets. The analysis compares basketball and hockey game days and non-game days. Moreover, this research aims to analyze crime prediction models using historical crime data as a basis and then introducing tweets and additional variables in their role as covariates of crime. First, this study investigates the spatial distribution of and correlation between crime and tweets during the same temporal periods. Feature selection models are applied in order to identify the best explanatory variables. Then, we apply localized kernel density estimation model for crime prediction during basketball and hockey games, and on non-game days. Findings from this study show that Twitter data, and a subset of violent tweets, are useful in building prediction models for the seven investigated crime types for home and away sporting events, and non-game days, with different levels of improvement.     

Assessment of reference evapotranspiration across an arid urban environment having poor data monitoring system

Estimation of reference evapotranspiration (ET₀) in urban areas is challenging but essential in arid urban climates. To evaluate ET₀ in an urban environment and non-urban areas, air temperature and relative humidity were measured at five different sites across the arid city of Isfahan, Iran, over 4 years. Wind speed and sunshine hours were obtained from an urban surrounding weather station over the same period and used to estimate ET₀. Calculated ET₀ was compared with satellite-based ET₀ retrieved from the MOD16A2 PET product. Although MODIS PET was strongly correlated with the Valiantzas equation, it overestimated ET₀ and showed average accuracy (r = 0.93–0.94, RMSE = 1.18–1.28 mm/day, MBE = 0.73–0.84 mm/day). The highest ET₀ differences between an urban green space and a non-urban area were 1.1 and 0.87 mm/day, which were estimated by ground measurements and MODIS PET, respectively. The sensitivity of ET₀ to wind speed and sunshine hours indicated a significant effect on cumulative ET₀ at urban sites compared to the non-urban site, which has a considerable impact on the amount of irrigation required in those areas. Although MODIS PET requires improvement to accurately reflect field level microclimate conditions affecting ET₀, it is beneficial to hydrological applications and water resource managers especially in areas where data is limited. In addition, our results indicated that using limited data methods or meteorological data from regional weather stations, leads to incorrect estimation of ET₀ in urban areas. Therefore, decision-makers and urban planners should consider the importance of precisely estimating ET₀ to optimize management of urban green space irrigation, especially in arid and semi-arid climates such as the city of Isfahan.     

Predictive value of Keetch-Byram Drought Index for cereal yields in a semi-arid environment

The study examines the potential of urban roofs to reduce the urban heat island (UHI) effect by changing their reflectivity and implementing vegetation (green roofs) using the example of the City of Vienna. The urban modelling simulations are performed based on high-resolution orography and land use data, climatological observations, surface albedo values from satellite imagery and registry of the green roof potential in Vienna. The modelling results show that a moderate increase in reflectivity of roofs (up to 0.45) reduces the mean summer temperatures in the densely built-up environment by approximately 0.25 °C. Applying high reflectivity materials (roof albedo up to 0.7) leads to average cooling in densely built-up area of approximately 0.5 °C. The green roofs yield a heat load reduction in similar order of magnitude as the high reflectivity materials. However, only 45 % of roof area in Vienna is suitable for greening and the green roof potential mostly applies to industrial areas in city outskirts and is therefore not sufficient for substantial reduction of the UHI effect, particularly in the city centre which has the highest heat load. The strongest cooling effect can be achieved by combining the green roofs with high reflectivity materials. In this case, using 50 or 100 % of the green roof potential and applying high reflectivity materials on the remaining surfaces have a similar cooling effect.     

A GIS‐based multi‐criteria seismic vulnerability assessment using the integration of granular computing rule extraction and artificial neural networks

This study proposes multi‐criteria group decision‐making to address seismic physical vulnerability assessment. Granular computing rule extraction is combined with a feed forward artificial neural network to form a classifier capable of training a neural network on the basis of the rules provided by granular computing. It provides a transparent structure despite the traditional multi‐layer neural networks. It also allows the classifier to be applied on a set of rules for each incoming pattern. Drawbacks of original granular computing (GrC) are covered, where some input patterns remained unclassified. The study was applied to classify seismic vulnerability of the statistical units of the city of Tehran, Iran. Slope, seismic intensity, height and age of the buildings were effective parameters. Experts ranked 150 randomly selected sample statistical units with respect to their degree of seismic physical vulnerability. Inconsistency of the experts' judgments was investigated using the induced ordered weighted averaging (IOWA) operator. Fifty‐five classification rules were extracted on which a neural network was based. An overall accuracy of 88%, κ = 0.85 and R² = 0.89 was achieved. A comparison with previously implemented methodologies proved the proposed method to be the most accurate solution to the seismic physical vulnerability of Tehran.     

A long-term trend in precipitation of different spatial regions of Bangladesh and its teleconnections with El Niño/Southern Oscillation and Indian Ocean Dipole

A long-term (1948 to 2012) trend of precipitation (annual, pre-monsoon, monsoon, and post-monsoon seasons) in Bangladesh was analyzed in different regions using both parametric and nonparametric approaches. Moreover, the possible teleconnections of precipitation (annual and monsoon) variability with El Niño/Southern Oscillation (ENSO) episode and Indian Ocean Dipole (IOD) were investigated using both average and individual (both positive and negative) values of ENSO index and IOD. Our findings suggested that for annual precipitation, a significant increasing monotonic trend was found in whole Bangladesh (4.87 mm/year), its western region (5.82 mm/year) including Rangpur (9.41 mm/year) and Khulna (4.95 mm/year), and Sylhet (10.12 mm/year) and Barisal (6.94 mm/year) from eastern region. In pre-monsoon, only Rangpur (2.88 mm/year) showed significant increasing trend, while in monsoon, whole Bangladesh (3.04 mm/year), Sylhet (7.17 mm/year), and Barisal (6.94 mm/year) showed similar trend. In post-monsoon, there was no significant trend. Our results also revealed that the precipitation (annual or monsoon) of whole Bangladesh and almost all of the spatial regions did not show any significant correlation with ENSO events, whereas the average IOD values showed significant correlation only in monsoon precipitation of western region. The individual positive IODs showed significant correlation in whole Bangladesh, western region, and its two divisions (Rajshahi and Khulna). So, in the context of Bangladesh climate, IOD has the more teleconnection to precipitation than that of ENSO. Our findings indicate that the co-occurrence of ENSO and IOD events may suppress their influence on each other.

     

Changing patterns in rainfall extremes in South Australia

Theoretical and Applied Climatology - Daily rainfall records from seven stations in South Australia, with record lengths from 50 to 137 years and a common period of 36 years, are...