Application of an Ensemble Stationary-Based Category-Based Scoring Support Vector Regression to Improve Drought Prediction in the Upper Colorado River Basin

Application of an Ensemble Stationary-Based Category-Based Scoring Support Vector Regression to Improve Drought Prediction in the Upper Colorado River Basin

Recent above-normal temperatures, which exacerbated the impacts of precipitation deficits, are recognized as the primary driver of droughts in the Upper Colorado River Basin (UCRB), USA. This research aims to enhance drought prediction models by addressing structural changes in non-stationary temper...

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Bibliographic Details
Main Authors: Mohammad Hadi Bazrkar, Heechan Han, Tadesse Abitew, Seonggyu Park, Negin Zamani, Jaehak Jeong
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Atmosphere
Subjects:
Upper Colorado River Basin
drought
identification
categorization
prediction
non-stationarity
Online Access:https://www.mdpi.com/2073-4433/15/12/1505
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