Articles | Volume 28, issue 20
https://doi.org/10.5194/hess-28-4685-2024
https://doi.org/10.5194/hess-28-4685-2024
Research article
 | 
28 Oct 2024
Research article |  | 28 Oct 2024

Simulation-based inference for parameter estimation of complex watershed simulators

Robert Hull, Elena Leonarduzzi, Luis De La Fuente, Hoang Viet Tran, Andrew Bennett, Peter Melchior, Reed M. Maxwell, and Laura E. Condon

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Short summary
Large-scale hydrologic simulators are a needed tool to explore complex watershed processes and how they may evolve with a changing climate. However, calibrating them can be difficult because they are costly to run and have many unknown parameters. We implement a state-of-the-art approach to model calibration using neural networks with a set of experiments based on streamflow in the upper Colorado River basin.