The 485-km-long coastline of Odisha, a state in the northeastern part of the Indian peninsula, is potentially vulnerable to several disaster events that take place frequently. In addition to threats due to natural hazards, these coastal regions also face immense population and developmental pressures. The increase in the intensity and frequency of cyclones and accelerated sea level rise related to increased sea surface temperature have led to flooding, coastal erosion and shoreline retreat causing damage to coastal ecosystems and resources in these regions. In recognition of these risks, the present work demonstrates a GIS-based approach to assess the vulnerability of the 187-km stretch from Puri to Konark out of the total 485-km coastline using analytical hierarchy process (AHP). The present study focuses on computation of integrated coastal vulnerability index which is an integration of physical vulnerability index, geotechnical vulnerability index and social vulnerability index using AHP taking nine risk variables into consideration. An attempt has been made to demonstrate the state-of-the-art microzonation of the coastal stretch between Puri and Konark based on the vulnerability indices using geographical information system.
Geotechnical engineers, nowadays, are able to examine many problems in much greater depth with the help of advanced hardware and software. Again, the engineers have started to depend less on sophisticated software and hardware with the availability of cloud computing services. Here, only the cloud computing system interface software needs to be run simply like a web browser. In view of the inherent risk and variability associated with geotechnical engineering, the geotechnical modelling tools usually resort to statistical and numerical techniques to take care of uncertainties in the key problem parameters. With the advent of cloud computing, geotechnical engineering needs computer technology not only for analysis and mathematical modelling, but also for recording, storing, retrieving, processing, visualizing and displaying of important geotechnical data much efficiently. The present paper broadly reviews the role of cloud computing as well as system identification and parameter identification integrated with cloud computing in geotechnical engineering.
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