A statistical distribution for modelling rainfall with promising application in crop science

Poster

Lennox, Sarah, Dunn, Peter K., Power, Brendan and De Voil, Peter. 2004. "A statistical distribution for modelling rainfall with promising application in crop science." Fischer, Tony, Turner, Neil, Angus, John, McIntyre, Lynne, Robertson, Michael, Borrell, Andrew and Lloyd, David (ed.) 4th International Crop Science Congress (ICSC 2004): New Directions for a Diverse Planet. Brisbane, Australia 26 Sep - 01 Oct 2004 Gosford, Australia.
Paper/Presentation Title

A statistical distribution for modelling rainfall with promising application in crop science

Presentation TypePoster
AuthorsLennox, Sarah (Author), Dunn, Peter K. (Author), Power, Brendan (Author) and De Voil, Peter (Author)
EditorsFischer, Tony, Turner, Neil, Angus, John, McIntyre, Lynne, Robertson, Michael, Borrell, Andrew and Lloyd, David
Journal or Proceedings TitleProceedings of the 4th International Crop Science Congress
Year2004
Place of PublicationGosford, Australia
ISBN1920842209
Web Address (URL) of Paperhttp://www.cropscience.org.au/icsc2004/poster/2/6/1273_lennoxs.htm
Conference/Event4th International Crop Science Congress (ICSC 2004): New Directions for a Diverse Planet
Event Details
4th International Crop Science Congress (ICSC 2004): New Directions for a Diverse Planet
Event Date
26 Sep 2004 to end of 01 Oct 2004
Event Location
Brisbane, Australia
Abstract

The finding of an accurate and reliable rainfall model has been the point of much discussion in previous research and has promising input applications in areas such as crop growth, hydrological systems and simulation studies. In the past it has been necessary to model rainfall as two separate processes: rainfall occurrence (whether the period is dry/wet) and rainfall amounts (rainfall amount observed during a wet period). As the rainfall process involves both discrete (rainfall = 0 mm) and continuous parts (rainfall >0 mm), two separate models have previously been fitted and the information from the two models combined in order to provide a summary of the rainfall model. The Tweedie distribution however is able to combine both aspects to provide one complete rainfall process. This results in a more accurate, reliable and practical model that can then be incorporated into other areas such as crop growth systems.

KeywordsTweedie distribution, Generalized Linear Model (GLM), precipitation, crop model simulation
ANZSRC Field of Research 2020300403. Agronomy
Public Notes

Note that M. Robertson is an co-Editor of this work. Copyright The Authors © 2004.

Individual authors retain copyright in the papers for the 4th International Crop Science Congress.
Reproduction and the making available of this material for personal or non-commercial purposes is authorised, on condition that:attribution is given to the copyright owner;
no official connection is claimed; the material is made available without charge or at cost; and the material is not subject to inaccurate, misleading or derogatory treatment.

Byline AffiliationsDepartment of Primary Industries, Queensland
Department of Mathematics and Computing
Department of Primary Industries and Fisheries, Queensland
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