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Data Repository for 'Bootstrap aggregation and cross-validation methods to reduce overfitting in reservoir control policy search'
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| Type: | Resource | |
| Storage: | The size of this resource is 8.3 MB | |
| Created: | Jan 20, 2020 at 7:42 p.m. (UTC) | |
| Last updated: | Jun 24, 2020 at 1:46 p.m. (UTC) (Metadata update) | |
| Published date: | Jun 24, 2020 at 1:46 p.m. (UTC) | |
| DOI: | 10.4211/hs.b8f87a7b680d44cebfb4b3f4f4a6a447 | |
| Citation: | See how to cite this resource |
| Sharing Status: | Published |
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| Views: | 3878 |
| Downloads: | 67 |
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Abstract
Policy search methods provide a heuristic mapping between observations and decisions and have been widely used in reservoir control studies. However, recent studies have observed a tendency for policy search methods to overfit to the hydrologic data used in training, particularly the sequence of flood and drought events. This technical note develops an extension of bootstrap aggregation (bagging) and cross-validation techniques, inspired by the machine learning literature, to improve control policy performance on out-of-sample hydrology. We explore these methods using a case study of Folsom Reservoir, California using control policies structured as binary trees and daily streamflow resampling based on the paleo-inflow record. Results show that calibration-validation strategies for policy selection and certain ensemble aggregation methods can improve out-of-sample tradeoffs between water supply and flood risk objectives over baseline performance given fixed computational costs. These results highlight the potential to improve policy search methodologies by leveraging well-established model training strategies from machine learning.
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| This resource is referenced by | Brodeur, Z., Herman, J. D., & Steinschneider, S. S. (2020). Bootstrap aggregation and cross-validation methods to reduce overfitting in reservoir control policy search. Accepted in AGU Journal Water Resources Research, June 2020 |
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This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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