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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Main Authors: Chun Xia Liang, Floris F. van Ogtrop, R. Willem Vervoort
Format: Article
Language:English
Published: PeerJ Inc. 2019-08-01
Series:PeerJ
Subjects:
Online Access:https://peerj.com/articles/7523.pdf
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spelling 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
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AT florisfvanogtrop detectingtheimpactoflandcoverchangeonobservedrainfall
AT rwillemvervoort detectingtheimpactoflandcoverchangeonobservedrainfall
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