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Civil Engineering

UNLV Theses, Dissertations, Professional Papers, and Capstones

Colorado River Basin

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Full-Text Articles in Engineering

Multi-Resolution Spatio-Temporal Change Analyses Of Hydro-Climatological Variables In Association With Large-Scale Oceanic-Atmospheric Climate Signals, Kazi Ali Tamaddun May 2019

Multi-Resolution Spatio-Temporal Change Analyses Of Hydro-Climatological Variables In Association With Large-Scale Oceanic-Atmospheric Climate Signals, Kazi Ali Tamaddun

UNLV Theses, Dissertations, Professional Papers, and Capstones

The primary objective of the work presented in this dissertation was to evaluate the change patterns, i.e., a gradual change known as the trend, and an abrupt change known as the shift, of multiple hydro-climatological variables, namely, streamflow, snow water equivalent (SWE), temperature, precipitation, and potential evapotranspiration (PET), in association with the large-scale oceanic-atmospheric climate signals. Moreover, both observed datasets and modeled simulations were used to evaluate such change patterns to assess the efficacy of the modeled datasets in emulating the observed trends and shifts under the influence of uncertainties and inconsistencies. A secondary objective of this study was to …


Association Of Oceanic-Atmospheric Oscillations And Hydroclimatic Variables In The Colorado River Basin, Ajay Kalra May 2011

Association Of Oceanic-Atmospheric Oscillations And Hydroclimatic Variables In The Colorado River Basin, Ajay Kalra

UNLV Theses, Dissertations, Professional Papers, and Capstones

With increasing evidence of climatic variability, there is a need to improve forecast for hydroclimatic variables i.e., precipitation and streamflow preserving their spatial and temporal variability. Climatologists have identified different oceanic-atmospheric oscillations that seem to influence the behavior of these variables and in turn can be used to extend the forecast lead time. In the absence of a good physical understanding of the linkages between oceanic-atmospheric oscillations and hydrological processes, it is difficult to construct a physical model. An attractive alternative to physically based models are the Artificial Intelligence (AI) type models, also referred to as machine learning or data-driven …