Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Publication
- Publication Type
Articles 1 - 4 of 4
Full-Text Articles in Physical Sciences and Mathematics
Hydroclimatic Forecasting In The Western United States Using Paleoclimate Reconstructions And Data-Driven Models, Christopher Allen Carrier
Hydroclimatic Forecasting In The Western United States Using Paleoclimate Reconstructions And Data-Driven Models, Christopher Allen Carrier
UNLV Theses, Dissertations, Professional Papers, and Capstones
This thesis investigated climate variability and their associated hydrologic responses in the western United States. The western United States faces the problem of water scarcity, where the management and mitigation of available water supplies are further complicated by climate variability. Climate variability associated with the phases of oceanic-atmospheric oscillations has been shown to influence streamflow and precipitation, where predictive relationships have led to the possibility of producing long-range forecasts. Based on literature review, four oceanic-atmospheric oscillation indices were identified in having the most prominent influence over the western United States including the El Niño - Southern Oscillation (ENSO), Pacific Decadal …
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 …
Improving Ensemble Streamflow Prediction Using Interdecadal/Interannual Climate Variability, Kenneth W. Lamb
Improving Ensemble Streamflow Prediction Using Interdecadal/Interannual Climate Variability, Kenneth W. Lamb
UNLV Theses, Dissertations, Professional Papers, and Capstones
The National Weather Service’s (NWS) river forecast centers provide long-term water resource forecasts for the main river basins in the U.S. The NWS creates seasonal streamflow forecasts using an ensemble prediction model called the Extended Streamflow Prediction (ESP) software. ESP creates runoff volume forecasts by taking the current observed soil moisture and snowpack conditions in the basin and applying them to historical temperature and precipitation scenarios. The ESP treats every historic input year as a likely scenario of future basin conditions. Therefore improving the knowledge about how long-term climate cycles impact streamflow can extend the forecast lead time and improve …
Using Oceanic-Atmospheric Oscillations For Long Lead Time Streamflow Forecasting, Ajay Kalra, Sajjad Ahmad
Using Oceanic-Atmospheric Oscillations For Long Lead Time Streamflow Forecasting, Ajay Kalra, Sajjad Ahmad
Civil and Environmental Engineering and Construction Faculty Research
We present a data-driven model, Support Vector Machine (SVM), for long lead time streamflow forecasting using oceanic-atmospheric oscillations. The SVM is based on statistical learning theory that uses a hypothesis space of linear functions based on Kernel approach and has been used to predict a quantity forward in time on the basis of training from past data. The strength of SVM lies in minimizing the empirical classification error and maximizing the geometric margin by solving inverse problem. The SVM model is applied to three gages, i.e., Cisco, Green River, and Lees Ferry in the Upper Colorado River Basin in the …