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Full-Text Articles in Meteorology
Estimating Annual Precipitation For The Colorado River Basin Using Oceanic-Atmospheric Oscillations, Ajay Kalra, Sajjad Ahmad
Estimating Annual Precipitation For The Colorado River Basin Using Oceanic-Atmospheric Oscillations, Ajay Kalra, Sajjad Ahmad
Civil and Environmental Engineering and Construction Faculty Research
Estimating long-lead time precipitation under the stress of increased climatic variability is a challenging task in the field of hydrology. A modified Support Vector Machine (SVM) based framework is proposed to estimate annual precipitation using oceanic-atmospheric oscillations. Oceanic-atmospheric oscillations, consisting of Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), Atlantic Multidecadal Oscillation (AMO), and El Niño–Southern Oscillation (ENSO) for a period of 1900–2008, are used to generate annual precipitation estimates with a 1 year lead time. The SVM model is applied to 17 climate divisions encompassing the Colorado River Basin in the western United States. The overall results revealed that …
Association Of Oceanic-Atmospheric Oscillations And Hydroclimatic Variables In The Colorado River Basin, Ajay Kalra
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 …