A spatial statistical analysis of the occurrence of earthquakes along the Red Sea floor spreading: clusters of seismicity     

Khalid Al-Ahmadi  Abdullah Al-Amri  Linda See 《Arabian Journal of Geosciences》2014,7(7):2893-2904

The aim of this study is to apply spatial pattern analysis techniques to a seismic data catalog of earthquakes beneath the Red Sea to try and detect clusters and explore global and local spatial patterns in the occurrence of earthquakes over the years from 1900 to 2009 using a geographical information system (GIS). The spatial pattern analysis techniques chosen for this study were quadrant count analysis, average nearest neighbor, global Moran’s I, Getis–Ord general G, Anselin Local Moran’s I, Getis–Ord Gi*, kernel density estimation, and geographical distributions. Each of these techniques was implemented in the GIS so that computations could be carried out quickly and efficiently. Results showed that (1) these techniques were capable of detecting clusters in the spatial patterns of the occurrence of the earthquakes; (2) both global and local spatial statistics indicate that earthquakes were clustered in the study area beneath the Red Sea; (3) earthquakes with higher magnitudes on the Richter scale were notably concentrated in the central and southern parts of the Red Sea where seismic activities were most active; and (4) earthquakes with moderate magnitudes on the Richter scale were particularly concentrated in the northern part of the Red Sea where there is an area of late-stage continental rifting comprised of a broad trough without a recognizable spreading center, although there were several small, isolated deep troughs. We conclude that the pattern analysis techniques applied to the seismic data catalog of earthquakes beneath the Red Sea could detect clusters in the occurrence of earthquakes from 1900 to 2009.  相似文献   

Spatial and temporal variations of physicochemical and heavy metal pollution in Ramganga River—a tributary of River Ganges,India     

Mohd Yawar Ali Khan  Khalid Muzamil Gani  Govind Joseph Chakrapani 《Environmental Earth Sciences》2017,76(5):231

The River Ganges being the most sacred river and lifeline to millions of Indians in serving their water requirements is facing excessive threat of pollution. Under various river management and conservation strategies for its protection, the assessment of water quality of its main tributary Ramganga River is lacking. This study focuses on assessment of physicochemical and heavy metal pollution of the Ramganga River by application of multivariate statistical techniques. Sampling of Ramganga River at sixteen sampling sites was carried out in three seasons (summer, monsoon and winter) of 2014. The collected water samples were analyzed for physicochemical parameters and heavy metals. Results from cluster analysis (CA) of the data divided the whole stretch of the river into three clusters as elevation from 1304 to 259 m as less polluted, from 207 to 154 m as moderately polluted and from elevation 154 to 139 m as high-polluted stretches with anthropogenic as main sources of pollution in high-polluted stretch. Principal component analysis of the seasonal dataset resulted in three significant principal components (PC) in each season explaining 72–8% of total variance with strong loadings (>0.75) of PC1 on fluoride (F^?), chloride (Cl^?), sodium (Na⁺), calcium (Ca²⁺), magnesium (Mg²⁺), bicarbonate (HCO₃ ^?), total dissolved solids and electrical conductivity. Temporal variation by one-way ANOVA (Analysis of Variance) showed significant seasonal variation was in the pH, chemical oxygen demand, biochemical oxygen demand, turbidity, HCO₃ ^?, F^?, Zn, cadmium (Cd) and Mn (p < 0.05). Turbidity showed approximately a twofold increase in monsoon season due to rainfall in the catchment area and subsequent flow of runoff into the river. Concentration of HCO₃ ^?, F^? and pH also showed similar increase in monsoon. The concentration of Zn, Cd and Mn showed an increasing trend in summers compared to monsoon and winter season due to dilution effect in the monsoon season and its lasting effect in winters.  相似文献