Estimating annual precipitation for the Colorado River Basin using oceanic-atmospheric oscillations
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...
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ftuninevadalveg:oai:digitalscholarship.unlv.edu:fac_articles-1082 2023-05-15T17:34:24+02:00 Estimating annual precipitation for the Colorado River Basin using oceanic-atmospheric oscillations Kalra, Ajay Ahmad, Sajjad 2012-06-22T07:00:00Z application/pdf https://digitalscholarship.unlv.edu/fac_articles/83 https://digitalscholarship.unlv.edu/cgi/viewcontent.cgi?article=1082&context=fac_articles English eng Digital Scholarship@UNLV https://digitalscholarship.unlv.edu/fac_articles/83 https://digitalscholarship.unlv.edu/cgi/viewcontent.cgi?article=1082&context=fac_articles Civil & Environmental Engineering and Construction Faculty Publications Meteorology North America – Colorado River Watershed Ocean-atmosphere interaction Precipitation forecasting Rainfall probabilities Atmospheric Sciences Climate Environmental Engineering Environmental Sciences Water Resource Management article 2012 ftuninevadalveg 2023-01-16T16:24:13Z 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 the annual precipitation in the Colorado River Basin is significantly influenced by oceanic-atmospheric oscillations. The long-term precipitation predictions for the Upper Colorado River Basin can be successfully obtained using a combination of PDO, NAO, and AMO indices, whereas coupling AMO and ENSO results in improved precipitation predictions for the Lower Colorado River Basin. The results also show that the SVM model provides better precipitation estimates compared to the Artificial Neural Network and Multivariate Linear Regression models. The annual precipitation estimates obtained using the modified SVM modeling framework may assist water managers in statistically understanding the hydrologic response in relation to large scale climate patterns within the Colorado River Basin. Article in Journal/Newspaper North Atlantic North Atlantic oscillation University of Nevada, Las Vegas: Digital Scholarship@UNLV Pacific |
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Open Polar |
collection |
University of Nevada, Las Vegas: Digital Scholarship@UNLV |
op_collection_id |
ftuninevadalveg |
language |
English |
topic |
Meteorology North America – Colorado River Watershed Ocean-atmosphere interaction Precipitation forecasting Rainfall probabilities Atmospheric Sciences Climate Environmental Engineering Environmental Sciences Water Resource Management |
spellingShingle |
Meteorology North America – Colorado River Watershed Ocean-atmosphere interaction Precipitation forecasting Rainfall probabilities Atmospheric Sciences Climate Environmental Engineering Environmental Sciences Water Resource Management Kalra, Ajay Ahmad, Sajjad Estimating annual precipitation for the Colorado River Basin using oceanic-atmospheric oscillations |
topic_facet |
Meteorology North America – Colorado River Watershed Ocean-atmosphere interaction Precipitation forecasting Rainfall probabilities Atmospheric Sciences Climate Environmental Engineering Environmental Sciences Water Resource Management |
description |
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 the annual precipitation in the Colorado River Basin is significantly influenced by oceanic-atmospheric oscillations. The long-term precipitation predictions for the Upper Colorado River Basin can be successfully obtained using a combination of PDO, NAO, and AMO indices, whereas coupling AMO and ENSO results in improved precipitation predictions for the Lower Colorado River Basin. The results also show that the SVM model provides better precipitation estimates compared to the Artificial Neural Network and Multivariate Linear Regression models. The annual precipitation estimates obtained using the modified SVM modeling framework may assist water managers in statistically understanding the hydrologic response in relation to large scale climate patterns within the Colorado River Basin. |
format |
Article in Journal/Newspaper |
author |
Kalra, Ajay Ahmad, Sajjad |
author_facet |
Kalra, Ajay Ahmad, Sajjad |
author_sort |
Kalra, Ajay |
title |
Estimating annual precipitation for the Colorado River Basin using oceanic-atmospheric oscillations |
title_short |
Estimating annual precipitation for the Colorado River Basin using oceanic-atmospheric oscillations |
title_full |
Estimating annual precipitation for the Colorado River Basin using oceanic-atmospheric oscillations |
title_fullStr |
Estimating annual precipitation for the Colorado River Basin using oceanic-atmospheric oscillations |
title_full_unstemmed |
Estimating annual precipitation for the Colorado River Basin using oceanic-atmospheric oscillations |
title_sort |
estimating annual precipitation for the colorado river basin using oceanic-atmospheric oscillations |
publisher |
Digital Scholarship@UNLV |
publishDate |
2012 |
url |
https://digitalscholarship.unlv.edu/fac_articles/83 https://digitalscholarship.unlv.edu/cgi/viewcontent.cgi?article=1082&context=fac_articles |
geographic |
Pacific |
geographic_facet |
Pacific |
genre |
North Atlantic North Atlantic oscillation |
genre_facet |
North Atlantic North Atlantic oscillation |
op_source |
Civil & Environmental Engineering and Construction Faculty Publications |
op_relation |
https://digitalscholarship.unlv.edu/fac_articles/83 https://digitalscholarship.unlv.edu/cgi/viewcontent.cgi?article=1082&context=fac_articles |
_version_ |
1766133211477311488 |