Modelling for Science, for a better future - some recent outcomes
A Preliminary Study on Rainfall Pattern before and after the January 26, 2001 Bhuj Earthquake (Mw 7.7) over Kachchh Region of Western Peninsular, India.
by Parul C. Trivedi, H. P. Joshi and Imtiyaz A. Parvez
Under the influence of great debate on relation between earthquake and rainfall, some scientists have carried out detailed study and now commonly accepted that heavy rainfall can trigger earthquake at the faults or fractures depending upon the local geology. Here, an attempt is made to check relation between earthquake and rainfall with different scientific approaches. We have attempted to critically examine the relation between the Bhuj earthquake-aftershocks sequence and the rainfall pattern over the region as large earthquake (Mw 7.7) has occurred on January 26, 2001 in Kachchh region of western peninsular shield of India and the aftershocks are being reported till the date. We have analyzed rainfall data for 20 years, i.e. 10 years before and 10 years after the main shock of January 26, 2001, recorded by three meteorological observatories in the Kachchh region. We have studied annual total rainfall for two decades, annual rainfall departures from the climate normals, number of rainy days and number of heavy rainfall days during the period for all the three meteorological observatories of Kachchh region. We have found significant increase in all the measured rainfall parameters i.e. annual total rainfall, number of rainy days and number of heavy rainfall days over the Kachchh region during last decade i.e., from 2001 to 2010 after the main shock. Numbers of negative departures have been decreased during the last decade compared to previous decade. Thus rainfall pattern over Kachchh region is being changed. This increase in rainfall activity over Kachchh region may have been influenced by large earthquake and continuing aftershock activities over the region.
Source: http://www.scirp.org/journal/PaperInformation.aspx?paperID=49858&
Ultra-high Resolution Global Model Climate Change Projection for India: Towards a Data Intensive Paradigm
by K. Rajendran, A. Kitoh, S. Sajani
Global warming will precariously affect agricultural production and the livelihood of farmers by unpredictably changing the abundance of rainfall and extreme events (Rajendran et al. 2013), which exhibits strong variation of rainfall. Hydropower generation and water availability are some of the other concerns that depend on rainfall variation. Thus, identification of recent climate trends and projection of future climate change are crucial for agro-economic states. As we build strong observational networks and monitor climate indicators, parallel efforts in dynamical modelling should also be practised. Since the special nature of the geographical orientation of the country with low-altitude coastlines and highly elevated mountains at the north, numerical models employed for projections should have sufficiently high spatial resolution to resolve these details. An ultra-high resolution global general circulation model (GCM) at 20-km resolution jointly developed by Meteorological Research Institute (MRI), Japan, and Japan Meteorological Agency (JMA) is used to investigate the future projection of climate change patterns for India. Analysis of four-dimensional multivariable global dataset at ultra-high resolution of 20-km and century time scale for climate change projections and for deriving inferences is highly data intensive and requires high-performance computing with huge memory, visualisation and storage. The projections are determined through time-slice integrations of the model which has shown marked fidelity in representing the present-day climate of India in all seasons especially the mean summer monsoon rainfall over India. Projected future scenario shows coherent and significant enhancement in summer rainfall over most parts of India along with significant reduction in rainfall along the southern parts of the Western Ghats.
The Role of Microzonation in Estimating Earthquake Risk
by Imtiyaz A. Parvez & Philippe Rosset
This chapter is dedicated to understanding the role of seismic zonation and microzonation, as well as understanding seismic risk analysis and mitigation strategy. The merits and demerits of various approaches to estimating earthquake hazard are discussed in terms of whether it is probabilistic, deterministic, or neodeterministic. The importance of geotechnical, geomorphological, and geological databases for seismic microzonation has been highlighted along with various techniques available to characterize site conditions. A variety of tools currently in use illustrate the basic principles of microzonation mapping at different scales. The main parameters involved in earthquake loss assessments and evaluating the influence of soil conditions on these estimates are discussed using QLARM, an advanced seismic risk estimation tool, for a few case histories.
source: http://www.sciencedirect.com/science/article/pii/B9780123948489000110
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