Impact assessment of rainfall-vegetation on sedimentation and predicting erosion-prone region by GIS and RS

Water reservoirs are facing universal sedimentation problems worldwide. Land covers, whether natural or manmade, eventually change, and the vegetation cover and rainfall have a great effect on the sediment load. Traditional techniques for analysing this problem are time-consuming and spatially limit...

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Main Authors: Alam, M., Hussain, R.R., Islam, A.B.M.S.
Format: Article
Published: Taylor & Francis Open 2016
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Online Access:http://eprints.um.edu.my/18184/
https://doi.org/10.1080/19475705.2014.942387
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spelling my.um.eprints.181842017-11-09T02:44:52Z http://eprints.um.edu.my/18184/ Impact assessment of rainfall-vegetation on sedimentation and predicting erosion-prone region by GIS and RS Alam, M. Hussain, R.R. Islam, A.B.M.S. TA Engineering (General). Civil engineering (General) Water reservoirs are facing universal sedimentation problems worldwide. Land covers, whether natural or manmade, eventually change, and the vegetation cover and rainfall have a great effect on the sediment load. Traditional techniques for analysing this problem are time-consuming and spatially limited. Remote sensing (RS) provides a convenient way to observe land cover changes, and geographic information system (GIS) provides tools for geographic analysis. This study demonstrates a GIS-based methodology for calculating the impact of vegetation and rainfall on the sediment load using remotely sensed data. Moderate resolution imaging spectroradiometer data were used to observe temporal changes in the vegetation-cover area of the watershed surface. The total drainage area for the reservoir was calculated from shuttle radar topographic mission data. The annual rainfall amount was used to compute the annual available rainwater for the watershed, and the impact of the annual available rainwater on the vegetation-covered area was determined. In addition, areas that were adding sedimentation to the reservoir were identified. An inverse relationship between the rainfall and vegetation cover was observed, clearly showing the triggering of erosion. Taylor & Francis Open 2016 Article PeerReviewed Alam, M. and Hussain, R.R. and Islam, A.B.M.S. (2016) Impact assessment of rainfall-vegetation on sedimentation and predicting erosion-prone region by GIS and RS. Geomatics, Natural Hazards and Risk, 7 (2). pp. 667-679. ISSN 1947-5705 https://doi.org/10.1080/19475705.2014.942387 doi:10.1080/19475705.2014.942387
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic TA Engineering (General). Civil engineering (General)
spellingShingle TA Engineering (General). Civil engineering (General)
Alam, M.
Hussain, R.R.
Islam, A.B.M.S.
Impact assessment of rainfall-vegetation on sedimentation and predicting erosion-prone region by GIS and RS
description Water reservoirs are facing universal sedimentation problems worldwide. Land covers, whether natural or manmade, eventually change, and the vegetation cover and rainfall have a great effect on the sediment load. Traditional techniques for analysing this problem are time-consuming and spatially limited. Remote sensing (RS) provides a convenient way to observe land cover changes, and geographic information system (GIS) provides tools for geographic analysis. This study demonstrates a GIS-based methodology for calculating the impact of vegetation and rainfall on the sediment load using remotely sensed data. Moderate resolution imaging spectroradiometer data were used to observe temporal changes in the vegetation-cover area of the watershed surface. The total drainage area for the reservoir was calculated from shuttle radar topographic mission data. The annual rainfall amount was used to compute the annual available rainwater for the watershed, and the impact of the annual available rainwater on the vegetation-covered area was determined. In addition, areas that were adding sedimentation to the reservoir were identified. An inverse relationship between the rainfall and vegetation cover was observed, clearly showing the triggering of erosion.
format Article
author Alam, M.
Hussain, R.R.
Islam, A.B.M.S.
author_facet Alam, M.
Hussain, R.R.
Islam, A.B.M.S.
author_sort Alam, M.
title Impact assessment of rainfall-vegetation on sedimentation and predicting erosion-prone region by GIS and RS
title_short Impact assessment of rainfall-vegetation on sedimentation and predicting erosion-prone region by GIS and RS
title_full Impact assessment of rainfall-vegetation on sedimentation and predicting erosion-prone region by GIS and RS
title_fullStr Impact assessment of rainfall-vegetation on sedimentation and predicting erosion-prone region by GIS and RS
title_full_unstemmed Impact assessment of rainfall-vegetation on sedimentation and predicting erosion-prone region by GIS and RS
title_sort impact assessment of rainfall-vegetation on sedimentation and predicting erosion-prone region by gis and rs
publisher Taylor & Francis Open
publishDate 2016
url http://eprints.um.edu.my/18184/
https://doi.org/10.1080/19475705.2014.942387
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score 13.15806