Improving the understanding of rainfall distribution and characterisation in the Cathedral Peak catchments using a geo-statistical technique

Authors

  • F Morris Centre for Water Resources Research, University of KwaZulu-Natal, Private Bag X01, Scottsville 3209, South Africa
  • ML Warburton Toucher Centre for Water Resources Research, University of KwaZulu-Natal, Private Bag X01, Scottsville 3209, South Africa
  • A Clulow Centre for Water Resources Research, University of KwaZulu-Natal, Private Bag X01, Scottsville 3209, South Africa
  • S Kusangaya Centre for Water Resources Research, University of KwaZulu-Natal, Private Bag X01, Scottsville 3209, South Africa
  • C Morris Agricultural Research Council-Animal Production Institute (ARC-API), c/o School of Life Sciences, University of KwaZulu-Natal, Private Bag X01, Scottsville 3209, South Africa
  • H Bulcock Centre for Water Resources Research, University of KwaZulu-Natal, Private Bag X01, Scottsville 3209, South Africa

DOI:

https://doi.org/10.4314/wsa.v42i4.19

Keywords:

Cathedral Peak, rainfall variability, regression-Kriging, mountainous areas

Abstract

The characterisation of rainfall variability, spatially and temporally, is essential for hydrological and ecological analyses. Inherently, this variability is distinctly more obvious in mountainous areas compared to lowlands. The objective of this study was to ascertain if the use of the regression-Kriging technique would provide improved estimates and understanding of the rainfall distribution across the Cathedral Peak catchments in the Drakensberg escarpment region, South Africa. Findings showed longitude and altitude to be the overall best predictors of the distribution of rainfall for the annual period, wet season and dry season, with longitude explaining 72% and altitude explaining 26% of the rainfall variability for mean annual precipitation, 73% and 26% for the wet season and 50% and 22% for the dry season, respectively. The combination of both longitude and altitude showed a larger coefficient of determination, of 0.73, 0.74 and 0.51, for the annual, wet season and dry season, respectively. Long-term mean annual rainfall patterns showed an overall strong directional distribution from west to east with a distinct pattern observed during the dry season. It was concluded that regression-Kriging is a useful alternative method for characterising rainfall distribution as well as prediction errors for mountainous areas.

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Published

2016-10-25

Issue

Vol. 42 No. 4 October (2016): Water SA

Section

Research paper

License

Copyright (c) 2022 F Morris, ML Warburton Toucher, A Clulow, S Kusangaya, C Morris, H Bulcock

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

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The content of this journal is licensed under a Creative Commons Attribution Licence.  Users are permitted to read, download, copy, distribute, print, search or link to the full texts of the articles in this journal under the terms of this Licence, without asking prior permission from the publisher or the author, provided the source is attributed. Copyright is retained by the authors.

How to Cite

F Morris (2016) “Improving the understanding of rainfall distribution and characterisation in the Cathedral Peak catchments using a geo-statistical technique”, Water SA, 42(4 October). doi:10.4314/wsa.v42i4.19.