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Full-Text Articles in Meteorology

Evaluating Changes And Estimating Seasonal Precipitation For Colorado River Basin Using Stochastic Non-Parametric Disaggregation Technique, Ajay Kalra, Sajjad Ahmad May 2011

Evaluating Changes And Estimating Seasonal Precipitation For Colorado River Basin Using Stochastic Non-Parametric Disaggregation Technique, Ajay Kalra, Sajjad Ahmad

Civil and Environmental Engineering and Construction Faculty Research

Precipitation estimation is an important and challenging task in hydrology because of high variability and changing climate. This research involves (1) analyzing changes (trend and step) in seasonal precipitation and (2) estimating seasonal precipitation by disaggregating water year precipitation using a k-nearest neighbor (KNN) nonparametric technique for 29 climate divisions encompassing the Colorado River Basin. Water year precipitation data from 1900 to 2008 are subdivided into four seasons (i.e., autumn, winter, spring, and summer). Two statistical tests (Mann-Kendall and Spearman’s rho) are used to evaluate trend changes, and a rank sum test is used to identify the step change in …


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 …