Remote sensing based evaluation of uncertainties on modelling of streamflow affected by climate change

Assessment of the impacts of land-use and climate change on streamflow is vital to develop climate adaptation strategies. However, uncertainties in the climate impact study framework could lead to changes on streamflow impact. The aim of this study is to assess the uncertainties on Digital Elevation...

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Main Author:	Tan, Mou Leong
Format:	Thesis
Language:	English
Published:	2016
Subjects:	G70.39-70.6 Remote sensing
Online Access:	http://eprints.utm.my/id/eprint/78612/1/TanMouLeongPFFGHT2016.pdf
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id	my-utm-ep.78612
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spelling	my-utm-ep.786122018-08-29T07:53:02Z Remote sensing based evaluation of uncertainties on modelling of streamflow affected by climate change 2016-02 Tan, Mou Leong G70.39-70.6 Remote sensing Assessment of the impacts of land-use and climate change on streamflow is vital to develop climate adaptation strategies. However, uncertainties in the climate impact study framework could lead to changes on streamflow impact. The aim of this study is to assess the uncertainties on Digital Elevation Model (DEM), Satellite Precipitation Product (SPP) and climate projection on the modelling of streamflow affected by climate changes. These uncertainties are evaluated and reduced independently. The climate projection uncertainty is addressed through the modification of the Quantifying and Understanding the Earth System - Global Scale Impacts (QUEST-GSI) methodology. Twenty-six modified QUEST-GSI climate scenarios were used as climate inputs into the calibrated Soil and Water Assessment Tool (SWAT) model to evaluate the impacts and uncertainties of climate change on streamflow for three future periods (2015-2034, 2045-2064 and 2075-2094). The selected study areas are the Johor River Basin (JRB) and Kelantan River Basin (KRB), Malaysia. The Shuttle Radar Topography Mission (SRTM) version 4.1 (90m resolution) DEM and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks – Climate Data Record (PERSIANN-CDR) SPP which show a better performance were selected for the SWAT model modification, calibration and validation. The results indicated that the modified SWAT model could simulate the monthly streamflow well for both basins. Land-use and climate changes from 1985 to 2012 reduced annual streamflow of the JRB and KRB by 5% and 4.2%, respectively. In future, the annual precipitation and temperature of the JRB / KRB are projected to increase by -0.4-10.3% / 0.1-11.2% and 0.6-3.2oC / 0.8-3.3oC, respectively, and that this will lead to an increase of annual streamflow by 0.5-13.3% / 4.4-18.5%. This study showed that satellite data play an important role in providing input data to hydrological models. 2016-02 Thesis http://eprints.utm.my/id/eprint/78612/ http://eprints.utm.my/id/eprint/78612/1/TanMouLeongPFFGHT2016.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:98235 phd doctoral Universiti Teknologi Malaysia, Faculty of Geoinformation and Real Estate Faculty of Geoinformation and Real Estate
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	G70.39-70.6 Remote sensing
spellingShingle	G70.39-70.6 Remote sensing Tan, Mou Leong Remote sensing based evaluation of uncertainties on modelling of streamflow affected by climate change
description	Assessment of the impacts of land-use and climate change on streamflow is vital to develop climate adaptation strategies. However, uncertainties in the climate impact study framework could lead to changes on streamflow impact. The aim of this study is to assess the uncertainties on Digital Elevation Model (DEM), Satellite Precipitation Product (SPP) and climate projection on the modelling of streamflow affected by climate changes. These uncertainties are evaluated and reduced independently. The climate projection uncertainty is addressed through the modification of the Quantifying and Understanding the Earth System - Global Scale Impacts (QUEST-GSI) methodology. Twenty-six modified QUEST-GSI climate scenarios were used as climate inputs into the calibrated Soil and Water Assessment Tool (SWAT) model to evaluate the impacts and uncertainties of climate change on streamflow for three future periods (2015-2034, 2045-2064 and 2075-2094). The selected study areas are the Johor River Basin (JRB) and Kelantan River Basin (KRB), Malaysia. The Shuttle Radar Topography Mission (SRTM) version 4.1 (90m resolution) DEM and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks – Climate Data Record (PERSIANN-CDR) SPP which show a better performance were selected for the SWAT model modification, calibration and validation. The results indicated that the modified SWAT model could simulate the monthly streamflow well for both basins. Land-use and climate changes from 1985 to 2012 reduced annual streamflow of the JRB and KRB by 5% and 4.2%, respectively. In future, the annual precipitation and temperature of the JRB / KRB are projected to increase by -0.4-10.3% / 0.1-11.2% and 0.6-3.2oC / 0.8-3.3oC, respectively, and that this will lead to an increase of annual streamflow by 0.5-13.3% / 4.4-18.5%. This study showed that satellite data play an important role in providing input data to hydrological models.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Tan, Mou Leong
author_facet	Tan, Mou Leong
author_sort	Tan, Mou Leong
title	Remote sensing based evaluation of uncertainties on modelling of streamflow affected by climate change
title_short	Remote sensing based evaluation of uncertainties on modelling of streamflow affected by climate change
title_full	Remote sensing based evaluation of uncertainties on modelling of streamflow affected by climate change
title_fullStr	Remote sensing based evaluation of uncertainties on modelling of streamflow affected by climate change
title_full_unstemmed	Remote sensing based evaluation of uncertainties on modelling of streamflow affected by climate change
title_sort	remote sensing based evaluation of uncertainties on modelling of streamflow affected by climate change
granting_institution	Universiti Teknologi Malaysia, Faculty of Geoinformation and Real Estate
granting_department	Faculty of Geoinformation and Real Estate
publishDate	2016
url	http://eprints.utm.my/id/eprint/78612/1/TanMouLeongPFFGHT2016.pdf
_version_	1747818028259606528

Remote sensing based evaluation of uncertainties on modelling of streamflow affected by climate change

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