Using Paleo Reconstructions to Improve Streamflow Forecast Lead Time in the Western United States
Abstract In water stressed regions, water managers are exploring new horizons that would help in long‐range streamflow forecasts. Oceanic‐atmospheric oscillations have been shown to influence streamflow variability. In this study, long‐lead time streamflow forecasts are made using a multiclass kerne...
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crwiley:10.1111/jawr.12088 2024-06-23T07:55:12+00:00 Using Paleo Reconstructions to Improve Streamflow Forecast Lead Time in the Western United States Carrier, Christopher Kalra, Ajay Ahmad, Sajjad National Science Foundation 2013 http://dx.doi.org/10.1111/jawr.12088 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fjawr.12088 https://onlinelibrary.wiley.com/doi/pdf/10.1111/jawr.12088 en eng Wiley http://onlinelibrary.wiley.com/termsAndConditions#vor JAWRA Journal of the American Water Resources Association volume 49, issue 6, page 1351-1366 ISSN 1093-474X 1752-1688 journal-article 2013 crwiley https://doi.org/10.1111/jawr.12088 2024-06-11T04:51:53Z Abstract In water stressed regions, water managers are exploring new horizons that would help in long‐range streamflow forecasts. Oceanic‐atmospheric oscillations have been shown to influence streamflow variability. In this study, long‐lead time streamflow forecasts are made using a multiclass kernel‐based data‐driven support vector machine ( SVM ) model. The extended streamflow records based on tree ring reconstructions were used to provide a longer time series data. Reconstructed data were used from 1658 to 1952 and the instrumental record was used from 1953 to 2007. Reconstructions for oceanic‐atmospheric oscillations included the El Niño‐Southern Oscillation, Pacific Decadal Oscillation, Atlantic Multidecadal Oscillation, and North Atlantic Oscillation. Streamflow forecasts using all four oscillations were made with one‐year to five‐year lead times for 21 gages in the western United States. This is the first study that uses both instrumental and reconstructed data of oscillations in SVM model to improve streamflow forecast lead time. SVM model was able to provide “satisfactory” to “very good” forecasts with one‐ to five‐year lead time for the selected gages. The use of all the oscillation indices helped in achieving better predictability compared to using individual oscillations. The SVM modeling results are better when compared with multiple linear regression model forecasts. The findings are statistical in nature and are expected to be useful for long‐term water resources planning and management. Article in Journal/Newspaper North Atlantic North Atlantic oscillation Wiley Online Library Pacific JAWRA Journal of the American Water Resources Association 49 6 1351 1366 |
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English |
description |
Abstract In water stressed regions, water managers are exploring new horizons that would help in long‐range streamflow forecasts. Oceanic‐atmospheric oscillations have been shown to influence streamflow variability. In this study, long‐lead time streamflow forecasts are made using a multiclass kernel‐based data‐driven support vector machine ( SVM ) model. The extended streamflow records based on tree ring reconstructions were used to provide a longer time series data. Reconstructed data were used from 1658 to 1952 and the instrumental record was used from 1953 to 2007. Reconstructions for oceanic‐atmospheric oscillations included the El Niño‐Southern Oscillation, Pacific Decadal Oscillation, Atlantic Multidecadal Oscillation, and North Atlantic Oscillation. Streamflow forecasts using all four oscillations were made with one‐year to five‐year lead times for 21 gages in the western United States. This is the first study that uses both instrumental and reconstructed data of oscillations in SVM model to improve streamflow forecast lead time. SVM model was able to provide “satisfactory” to “very good” forecasts with one‐ to five‐year lead time for the selected gages. The use of all the oscillation indices helped in achieving better predictability compared to using individual oscillations. The SVM modeling results are better when compared with multiple linear regression model forecasts. The findings are statistical in nature and are expected to be useful for long‐term water resources planning and management. |
author2 |
National Science Foundation |
format |
Article in Journal/Newspaper |
author |
Carrier, Christopher Kalra, Ajay Ahmad, Sajjad |
spellingShingle |
Carrier, Christopher Kalra, Ajay Ahmad, Sajjad Using Paleo Reconstructions to Improve Streamflow Forecast Lead Time in the Western United States |
author_facet |
Carrier, Christopher Kalra, Ajay Ahmad, Sajjad |
author_sort |
Carrier, Christopher |
title |
Using Paleo Reconstructions to Improve Streamflow Forecast Lead Time in the Western United States |
title_short |
Using Paleo Reconstructions to Improve Streamflow Forecast Lead Time in the Western United States |
title_full |
Using Paleo Reconstructions to Improve Streamflow Forecast Lead Time in the Western United States |
title_fullStr |
Using Paleo Reconstructions to Improve Streamflow Forecast Lead Time in the Western United States |
title_full_unstemmed |
Using Paleo Reconstructions to Improve Streamflow Forecast Lead Time in the Western United States |
title_sort |
using paleo reconstructions to improve streamflow forecast lead time in the western united states |
publisher |
Wiley |
publishDate |
2013 |
url |
http://dx.doi.org/10.1111/jawr.12088 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fjawr.12088 https://onlinelibrary.wiley.com/doi/pdf/10.1111/jawr.12088 |
geographic |
Pacific |
geographic_facet |
Pacific |
genre |
North Atlantic North Atlantic oscillation |
genre_facet |
North Atlantic North Atlantic oscillation |
op_source |
JAWRA Journal of the American Water Resources Association volume 49, issue 6, page 1351-1366 ISSN 1093-474X 1752-1688 |
op_rights |
http://onlinelibrary.wiley.com/termsAndConditions#vor |
op_doi |
https://doi.org/10.1111/jawr.12088 |
container_title |
JAWRA Journal of the American Water Resources Association |
container_volume |
49 |
container_issue |
6 |
container_start_page |
1351 |
op_container_end_page |
1366 |
_version_ |
1802647672279007232 |