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Masters Degrees (Environmental Hydrology)

Permanent URI for this collectionhttps://hdl.handle.net/10413/6589

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Browsing Masters Degrees (Environmental Hydrology) by Author "Bollaert, M. J."

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    Development of a geographic data model for hydrological modelling.
    (2006) Bollaert, M. J.; Clark, David John.
    Hydrology is a multi-disciplinary science, and therefore derives data from diverse sources, with the data often of a spatio-temporal nature. A recent trend has been to combine these data with GIS, due to the data’s geographic origin, and inherently requires an abstraction of reality in order to deal with the multitude of data that would otherwise result. Consequently, data models have been developed for this purpose, and these require a generalisation of processes and variables, while offering a simplified structure for their storage. The purpose of this study was to develop a data model for the storage and dissemination of hydrological variables and associated data used in hydrological modelling. Data would be of a spatial and temporal nature, and thus the design of the new data model needed to provide for this. A number of existing geographic data models were therefore reviewed, including the geodatabase model. This data model and the object-relational database model upon which it was built, were ascertained as being the most suitable for the study, and were therefore included in the design of the new data model. The related Arc Hydro data model was subsequently reviewed, since it offered an established means by which to model geographic features associated with surface hydrology. Following this, an investigation into time series storage methods was carried out, as it was important that the new data model be able to store large time series datasets in an efficient manner. Thus a number of methods were identified and evaluated as to their advantages and disadvantages. A new data model was thereby conceived, using the geodatabase as its foundation, and was developed in order to offer efficient storage of hydrological data. The data model developed was subsequently tested by populating it with data from the Quaternary Catchments database which supports the ACRU model. Finally, additional functionality was added to the data model, in the form of export options.