Repository logo
 

Spatio-temporal rainfall estimation and nowcasting for flash flood forecasting.

dc.contributor.advisorPegram, Geoffrey Guy Sinclair.
dc.contributor.authorSinclair, Scott.
dc.date.accessioned2011-01-21T11:59:49Z
dc.date.available2011-01-21T11:59:49Z
dc.date.created2007
dc.date.issued2007
dc.descriptionThesis (Ph.D.Eng.)-University of KwaZulu-Natal, Durban, 2007.en_US
dc.description.abstractFloods cannot be prevented, but their devastating effects can be minimized if advance warning of the event is available. The South African Disaster Management Act (Act 57 of 2002) advocates a paradigm shift from the current "bucket and blanket brigade" response-based mind set to one where disaster prevention or mitigation are the preferred options. It is in the context of mitigating the effects of floods that the development and implementation of a reliable flood forecasting system has major significance. In the case of flash floods, a few hours lead time can afford disaster managers the opportunity to take steps which may significantly reduce loss of life and damage to property. The engineering challenges in developing and implementing such a system are numerous. In this thesis, the design and implement at ion of a flash flood forecasting system in South Africa is critically examined. The technical aspect s relating to spatio-temporal rainfall estimation and now casting are a key area in which new contributions are made. In particular, field and optical flow advection algorithms are adapted and refined to help predict future path s of storms; fast and pragmatic algorithms for combining rain gauge and remote sensing (rada r and satellite) estimates are re fined and validated; a two-dimensional adaptation of Empirical Mode Decomposition is devised to extract the temporally persistent structure embedded in rainfall fields. A second area of significant contribution relates to real-time fore cast updates, made in response to the most recent observed information. A number of techniques embedded in the rich Kalm an and adaptive filtering literature are adopted for this purpose. The work captures the current "state of play" in the South African context and hopes to provide a blueprint for future development of an essential tool for disaster management. There are a number of natural spin-offs from this work for related field s in water resources management.en_US
dc.identifier.urihttp://hdl.handle.net/10413/2247
dc.language.isoenen_US
dc.subjectTheses--Civil engineering.en_US
dc.subjectNowcasting (Meteorology)
dc.subjectPrecipitation forecasting.
dc.subjectFlood forecasting.
dc.titleSpatio-temporal rainfall estimation and nowcasting for flash flood forecasting.en_US
dc.typeThesisen_US

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Sinclair_Scott_2007.pdf
Size:
14.84 MB
Format:
Adobe Portable Document Format

License bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.86 KB
Format:
Item-specific license agreed upon to submission
Description: