Abstract: Evaluating the Implications of Climate Phenomenon Indices in Supporting Reservoir Operation Using the Artificial Neural Network and Decision-Tree Methods: A Case Study on Trinity Lake in Northern California (2016 AGU Fall Meeting)

Evaluating the Implications of Climate Phenomenon Indices in Supporting Reservoir Operation Using the Artificial Neural Network and Decision-Tree Methods: A Case Study on Trinity Lake in Northern California

Tiantian Yang¹, Ata Akbari Asanjan¹, Xiaogang Gao¹ and Soroosh Sorooshian², (1)University of California Irvine, Irvine, CA, United States, (2)University of California, Irvine, Department of Civil and Environmental Engineering, Irvine, United States

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