Detecting the impact of land cover change on observed rainfall
Analysis of observational data to pinpoint impact of land cover change on local rainfall is difficult due to multiple environmental factors that cannot be strictly controlled. In this study we use a statistical approach to identify the relationship between removal of tree cover and rainfall with dat...
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doaj-e3eb15506eb842799df561b5d14e10032020-11-24T21:21:26ZengPeerJ Inc.PeerJ2167-83592019-08-017e752310.7717/peerj.7523Detecting the impact of land cover change on observed rainfallChun Xia Liang0Floris F. van Ogtrop1R. Willem Vervoort2School of Life and Environmental Sciences, Sydney Institute of Agriculture, The University of Sydney, New South Wales, AustraliaSchool of Life and Environmental Sciences, Sydney Institute of Agriculture, The University of Sydney, New South Wales, AustraliaSchool of Life and Environmental Sciences, Sydney Institute of Agriculture, The University of Sydney, New South Wales, AustraliaAnalysis of observational data to pinpoint impact of land cover change on local rainfall is difficult due to multiple environmental factors that cannot be strictly controlled. In this study we use a statistical approach to identify the relationship between removal of tree cover and rainfall with data from best available sources for two large areas in Australia. Gridded rainfall data between 1979 and 2015 was used for the areas, while large scale (exogenous) effects were represented by mean rainfall across a much larger area and climatic indicators, such as Southern Oscillation Index and Indian Ocean Dipole. Both generalised additive modelling and step trend tests were used for the analysis. For a region in south central Queensland, the reported change in tree clearing between 2002–2005 did not result in strong statistically significant precipitation changes. On the other hand, results from a bushfire affected region on the border of New South Wales and Victoria suggest significant changes in the rainfall due to changes in tree cover. This indicates the method works better when an abrupt change in the data can be clearly identified. The results from the step trend test also mainly identified a positive relationship between the tree cover and the rainfall at p < 0.1 at the NSW/Victoria region. High rainfall variability and possible regrowth could have impacted the results in the Queensland region.https://peerj.com/articles/7523.pdfLand Cover ChangeStatistical analysisRainfall changeLand cover Rainfall InteractionEmpirical dataAustralia |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Chun Xia Liang Floris F. van Ogtrop R. Willem Vervoort |
spellingShingle |
Chun Xia Liang Floris F. van Ogtrop R. Willem Vervoort Detecting the impact of land cover change on observed rainfall PeerJ Land Cover Change Statistical analysis Rainfall change Land cover Rainfall Interaction Empirical data Australia |
author_facet |
Chun Xia Liang Floris F. van Ogtrop R. Willem Vervoort |
author_sort |
Chun Xia Liang |
title |
Detecting the impact of land cover change on observed rainfall |
title_short |
Detecting the impact of land cover change on observed rainfall |
title_full |
Detecting the impact of land cover change on observed rainfall |
title_fullStr |
Detecting the impact of land cover change on observed rainfall |
title_full_unstemmed |
Detecting the impact of land cover change on observed rainfall |
title_sort |
detecting the impact of land cover change on observed rainfall |
publisher |
PeerJ Inc. |
series |
PeerJ |
issn |
2167-8359 |
publishDate |
2019-08-01 |
description |
Analysis of observational data to pinpoint impact of land cover change on local rainfall is difficult due to multiple environmental factors that cannot be strictly controlled. In this study we use a statistical approach to identify the relationship between removal of tree cover and rainfall with data from best available sources for two large areas in Australia. Gridded rainfall data between 1979 and 2015 was used for the areas, while large scale (exogenous) effects were represented by mean rainfall across a much larger area and climatic indicators, such as Southern Oscillation Index and Indian Ocean Dipole. Both generalised additive modelling and step trend tests were used for the analysis. For a region in south central Queensland, the reported change in tree clearing between 2002–2005 did not result in strong statistically significant precipitation changes. On the other hand, results from a bushfire affected region on the border of New South Wales and Victoria suggest significant changes in the rainfall due to changes in tree cover. This indicates the method works better when an abrupt change in the data can be clearly identified. The results from the step trend test also mainly identified a positive relationship between the tree cover and the rainfall at p < 0.1 at the NSW/Victoria region. High rainfall variability and possible regrowth could have impacted the results in the Queensland region. |
topic |
Land Cover Change Statistical analysis Rainfall change Land cover Rainfall Interaction Empirical data Australia |
url |
https://peerj.com/articles/7523.pdf |
work_keys_str_mv |
AT chunxialiang detectingtheimpactoflandcoverchangeonobservedrainfall AT florisfvanogtrop detectingtheimpactoflandcoverchangeonobservedrainfall AT rwillemvervoort detectingtheimpactoflandcoverchangeonobservedrainfall |
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