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Evaluation of ocean-atmospheric indices as predictors for summer streamflow of the Yangtze River based on ROC analysis

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Abstract

Antecedent anomalies of sea surface temperature and atmospheric circulation are important signals for making long-term streamflow forecasts. In this study, four groups of ocean-atmospheric indices, i.e, El Niño Southern Oscillation (ENSO), the Northern Hemisphere atmospheric circulation, the Southern Hemisphere atmospheric circulation (SAC), and the Western Pacific and Indian Ocean SST (WPI), are evaluated for forecasting summer streamflow of the Yangtze River. The gradient boosting regression tree (GBRT) is used to forecast streamflow based on each group of indices. The score based on receiver operating characteristics (ROC) curves, i.e., area under the ROC curve (AUC), is used to evaluate skills of models for identifying the high category and the low category of summer streamflow. It is found that the ENSO group and the SAC group show higher AUC values. Furthermore, both AUC values of GBRT models and individual indices show that the low flow years are easier to be identified than the high flow years. The result of this study highlights the skill from the Southern Hemisphere circulation systems for forecasting summer streamflow of the Yangtze River. Results of relative influences of predictors in GBRT models and AUC of individual indices indicate some key ocean-atmospheric indices, such as the Multivariate ENSO Index and the 500-hPa height of the east of Australia.

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Acknowledgements

This research was financially supported by the National Natural Science Foundation of China (51479061), the Public Welfare Industry of Water Conservancy Ministry (201201068), the Public Welfare Industry of Science Research of Water Conservancy Ministry (201301066), and the Natural Science Foundation of Anhui Provinces Higher Education of China (2017ZR02zd).

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Correspondence to Ran-Ran He.

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He, RR., Chen, Y., Huang, Q. et al. Evaluation of ocean-atmospheric indices as predictors for summer streamflow of the Yangtze River based on ROC analysis. Stoch Environ Res Risk Assess 32, 1903–1918 (2018). https://doi.org/10.1007/s00477-018-1551-z

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