Grid computing technology for hydrological applications

Advances in e-Infrastructure promise to revolutionize sensing systems and the way in which data are collected and assimilated, and complex water systems are simulated and visualized. According to the EU Infrastructure 2010 work-programme, data and compute infrastructures and their underlying technologies, either oriented to tackle scientific challenges or complex problem solving in engineering, are expected to converge together into the so-called knowledge infrastructures, leading to a more effective research, education and innovation in the next decade and beyond. Grid technology is recognized as a fundamental component of e-Infrastructures. Nevertheless, this emerging paradigm highlights several topics, including data management, algorithm optimization, security, performance (speed, throughput, bandwidth, etc.), and scientific cooperation and collaboration issues that require further examination to fully exploit it and to better inform future research policies. The paper illustrates the results of six different surface and subsurface hydrology applications that have been deployed on the Grid. All the applications aim to answer to strong requirements from the Civil Society at large, relatively to natural and anthropogenic risks. Grid technology has been successfully tested to improve flood prediction, groundwater resources management and Black Sea hydrological survey, by providing large computing resources. It is also shown that Grid technology facilitates e-cooperation among partners by means of services for authentication and authorization, seamless access to distributed data sources, data protection and access right, and standardization.

@Article{LPHIKRT12,
  author       = {Lecca, G. and Petitdidier, M. and Hluchy, L. and Ivanovic, M. and Kussul, N. and Ray, N. and Thieron, V.},
  title        = {Grid computing technology for hydrological applications},
  journal      = {Journal of Hydrology},
  number       = {1-2},
  volume       = {403},
  pages        = {186--199},
  year         = {2012},
  publisher    = {Elsevier},
  keywords     = {Computational hydrology; Environmental data; Grid computing; e-Infrastructure; Water resources management},
  issn         = {00221694},
  doi          = {10.1016/j.jhydrol.2011.04.003},
  url          = {https://publications.crs4.it/pubdocs/2012/LPHIKRT12},
}