Quantification of multiple sources of uncertainty in hydrologic and climate modelling
Frameworks incorporating hydro-meteorologic and climate models are applied to examine potential impacts of climate change for the future time periods. The importance of analyzing these frameworks is underscored by different sources of uncertainty that contribute to the variability observed...
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sg-ntu-dr.10356-690442023-03-03T19:31:12Z Quantification of multiple sources of uncertainty in hydrologic and climate modelling Vallam, Pramodh Qin Xiaosheng School of Civil and Environmental Engineering DRNTU::Engineering::Environmental engineering Frameworks incorporating hydro-meteorologic and climate models are applied to examine potential impacts of climate change for the future time periods. The importance of analyzing these frameworks is underscored by different sources of uncertainty that contribute to the variability observed in the models’ simulations. The sources of uncertainty addressed in this thesis are the parametric, model, scenario, and the downscaling uncertainty. Incorporating robust methodologies, the uncertainty propagated by the hydrologic and climate models are analyzed. The SLURP hydrologic model is subject to a robust and modified parametric uncertainty analysis methodology. Different types of meteorological models are analyzed for their ability to simulate precipitation for a multi-site tropical location utilizing spatial, statistical, frequency and extreme value criteria. An integrated climate change impact analysis framework incorporating hydro-meteorologic models and a climate change weather generator is utilized to examine the scenario uncertainty. Finally, the downscaling uncertainty is analyzed by instrumenting different downscaling approaches. Doctor of Philosophy 2016-09-28T02:42:34Z 2016-09-28T02:42:34Z 2016 Thesis Vallam, P. (2016). Quantification of multiple sources of uncertainty in hydrologic and climate modelling. Doctoral thesis, Nanyang Technological University, Singapore. http://hdl.handle.net/10356/69044 en 221 p. application/pdf |
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DRNTU::Engineering::Environmental engineering Vallam, Pramodh Quantification of multiple sources of uncertainty in hydrologic and climate modelling |
description |
Frameworks incorporating hydro-meteorologic and climate models are applied to
examine potential impacts of climate change for the future time periods. The
importance of analyzing these frameworks is underscored by different sources of
uncertainty that contribute to the variability observed in the models’ simulations. The
sources of uncertainty addressed in this thesis are the parametric, model, scenario,
and the downscaling uncertainty. Incorporating robust methodologies, the uncertainty
propagated by the hydrologic and climate models are analyzed. The SLURP
hydrologic model is subject to a robust and modified parametric uncertainty analysis
methodology. Different types of meteorological models are analyzed for their ability to
simulate precipitation for a multi-site tropical location utilizing spatial, statistical,
frequency and extreme value criteria. An integrated climate change impact analysis
framework incorporating hydro-meteorologic models and a climate change weather
generator is utilized to examine the scenario uncertainty. Finally, the downscaling
uncertainty is analyzed by instrumenting different downscaling approaches. |
author2 |
Qin Xiaosheng |
author_facet |
Qin Xiaosheng Vallam, Pramodh |
format |
Theses and Dissertations |
author |
Vallam, Pramodh |
author_sort |
Vallam, Pramodh |
title |
Quantification of multiple sources of uncertainty in hydrologic and climate modelling |
title_short |
Quantification of multiple sources of uncertainty in hydrologic and climate modelling |
title_full |
Quantification of multiple sources of uncertainty in hydrologic and climate modelling |
title_fullStr |
Quantification of multiple sources of uncertainty in hydrologic and climate modelling |
title_full_unstemmed |
Quantification of multiple sources of uncertainty in hydrologic and climate modelling |
title_sort |
quantification of multiple sources of uncertainty in hydrologic and climate modelling |
publishDate |
2016 |
url |
http://hdl.handle.net/10356/69044 |
_version_ |
1759857207077240832 |