Use this URL to cite or link to this record in EThOS:
Title: Building an eScience infrastructure for environmental science
Author: Chiang, G.-T.
Awarding Body: University of Cambridge
Current Institution: University of Cambridge
Date of Award: 2010
Availability of Full Text:
Full text unavailable from EThOS.
Please contact the current institution’s library for further details.
The objective of this project is to build an eScience/grid infrastructure suitable for use with environmental sciences and especially with hydrological science. The infrastructure allows a wide range of hydrological problems to be investigated and is particularly suitable for either computationally intensive or multiple scenario applications. To accomplish this objective, this project discovered the shortcomings of current grid infrastructures for hydrological science and developed missing components to fill this gap. In particular, there were three primary areas which needed work; firstly, integrating data and computing grids; secondly, visualization of geographic information from grid outputs; and thirdly, implementing hydrological simulations based on this infrastructure. A grid infrastructure, which consists of a computing and a data grid, has been built. In addition, the computing grid has been extended to utilize the Amazon cloud computing resources. Users can implement a complete simulation job life cycle form job submission, and data management to metadata management based on this infrastructure. In order to deal with the visualization and metadata within the grid, XMLization is used in this project. I developed a Writing Keyhole Markup Language (WKML), which is a Fortran library allowing enviornemntal scientists to visualize their model outputs in Google Earth. I have also developed a Writing Hydrological Markup Language (WHML) to describe the hydrological data. Finally, an XPath-based tool integrated with RMCS has been developed to extract metadata from XML files. A hydrological scientific pilot project tries to discover whether SHETRAN modelling could be used to predict hydrological behaviour at downstream. The outcomes proved that the SHETRAN synthetic Flood Frequency Curves (FFCs) suggest that simple short-term modelling can be extrapolated to estimate the impact on FFCs of changes in land use/management.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available