Development of an Integrated Hydro-Climatic Systems Analysis Framework and its Application to the Athabasca River Basin, Canada
A Thesis Submitted to the Faculty of Graduate Studies and Research in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Environmental Systems Engineering at University of Regina. xvii, 311 p. Climate change has profound impacts on regional hydrological characteristics...
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Other Authors: | , , , , |
Format: | Thesis |
Language: | English |
Published: |
Faculty of Graduate Studies and Research, University of Regina
2016
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Subjects: | |
Online Access: | http://hdl.handle.net/10294/7620 http://ourspace.uregina.ca/bitstream/handle/10294/7620/Cheng_Guanhui_200287668_PHD_EVSE_Fall2016.pdf |
Summary: | A Thesis Submitted to the Faculty of Graduate Studies and Research in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Environmental Systems Engineering at University of Regina. xvii, 311 p. Climate change has profound impacts on regional hydrological characteristics in large unregulated continental river basins (LUCRiBs) such as the Athabaasca River Basin (ARB), Canada. A systematic analysis of these impacts is confronted with many challenges. For instance, the performances of general circulation models (GCMs) vary with many factors, e.g. climate variables, geographic locations, temporal scales, and evaluation measures. Mesoscale atmospheric features can barely be provided by coarse-resolution GCMs. Filling this gap by statistical downscaling is further challenged by redundant computations, resulting from spatial climatic similarities, and the complexities of data uncertainties, nonlinear correspondences, normality prerequisites, and multivariate dependencies. Climatic projection may lack a solid GCM-evaluation foundation and a high spatial resolution. These complexities in downscaling may also exist and be coupled with massive computations in integer optimization in hydrological simulation. Furthermore, an integration of these challenges would decrease the reliability of long-term streamflow forecastings for guiding socio-economic development and eco-environmental conservation over LUCRiBs such as the ARB under climate change. To fill the gap of few effective techniques, an integrated hydro-climatic systems analysis framework is developed and applied to the ARB. This framework includes six modules. (a) The multi-dimensional performances of CMIP5 GCMs and their ensemble are evaluated. (b) The climate over the ARB is classified by recursive dissimilarity and similarity inferences. (c) The spatial resolution of GCM is enhanced by recursive multivariate principal-monotonicity inferential downscaling based on (a) and (b). (d) High-resolution climatic projection under four ... |
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