by S Vishal Gupta, Imtiyaz A Parvez, Ankit, Prosanta K Khan & Rakesh Chandra
The Srinagar region of Kashmir Valley in North West Himalayas, covers more than 2 million inhabitants and is exposed to high seismic risk. In order to gain insight on potential site effects and subsurface structure of the region, we carried out an extensive high-resolution microtremor ambient noise survey at 429 locations. The acquired dataset was processed using the Horizontal to Vertical Spectral Ratio (HVSR) technique to map the resonance frequency, the thickness of sedimentary cover, and to identify areas prone to seismic amplification. We provide a spatial classification of the obtained HVSR curves in four types: (1) clear peak H/V curves relating the strong impedance contrast in the subsurface; (2) multiple peaks (or Broad) H/V curves corresponding to sloping internal stratification of sediments; (3) two peaks H/V curves related to two different impedance contrast existing in the subsurface; (4) flat H/V curves around and over hard rock outcroppings. The HVSR curves show the peaks in the range of 0.22 Hz to 9.96 Hz indicating heterogeneous and complex sedimentary cover in the region. Inversion of the HVSR curves gives the shear waves velocity distribution which highlights two distinct reflective surfaces in most of the areas. In addition, we also used the estimated fundamental frequency of various types of houses/buildings located in Srinagar city to assess the possibility of resonance in case of occurrence of any earthquake. This study adds a value to the region in earthquake engineering, seismic hazard and risk evaluation purpose for Srinagar and its suburbs.
by Kantha Rao Bhimala, V. Rakesh, K. Raghavendra Prasad & G. N. Mohapatra
Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data were analyzed to study the vegetation dynamics over different meteorological subdivisions in India for the period 2000–2016. Soil moisture (SM), rainfall (RF), and land use land cover (LULC) data were analyzed to identify the climatic and anthropogenic drivers that cause vegetation changes at the subdivision scale. Principal component analysis and MK (Mann-Kendall) test showed significant greening trend over semi-arid regions of Northwest India (NWI) and South India (SI) while slight browning trend seen over some of the subdivisions in Indo-Gangetic (IG) plains and Western Ghats (WG). It is found that the NDVI has superior correlation with soil moisture compared with rainfall and the croplands (CL) found to have significant increasing trend over the NWI and SI. Increasing trend in soil moisture over the NWI and SI may have contributed to increase in CL area and the greening trend. Over IG plains, the NDVI showed moderate correlation with SM and RF, and the greening trend (browning trend) in some regions can be attributed to increase in natural vegetation mosaic (decrease of CL). The NDVI has shown browning trend over the core monsoon regions of Madhya Pradesh (an increase of barren lands over west MP and decrease of CL over east MP) and Western Ghats (significant decrease of CL over Konkan and Goa). This study revealed that the soil moisture and LULC changes are the major driving factors for the vegetation changes over majority of the subdivisions in India.