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Supporting data for "Flexible forecast value metric suitable for a wide range of decisions: application using probabilistic subseasonal streamflow forecasts" by Laugesen et.al. (2023)

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Research Data Australia2024-12-14 收录
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https://researchdata.edu.au/supporting-flexible-forecast-etal-2023/2089640
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资源简介:
Includes input forecasts (CSV), forecast value datasets (HDF5), and generated figures (PNG, PDF). Organised into subdirectories for each figure.The code used for this work has been released as a software library, along with an associated publication. This is available at https://github.com/richardlaugesen/ruvpy and can now be used by researchers and industry to quantify the value of forecast for decision making using RUV (pip install ruvpy).ReferencesLaugesen, Richard and Thyer, Mark and McInerney, David and Kavetski, Dmitri, Software Library to Quantify the Value of Forecasts for Decision-Making: Case Study on Sensitivity to Damages. http://dx.doi.org/10.2139/ssrn.5001881 (under review)Laugesen, R., Thyer, M., McInerney, D., & Kavetski, D. (2023). Flexible forecast value metric suitable for a wide range of decisions: application using probabilistic subseasonal streamflow forecasts. Hydrology and Earth System Sciences, 27(4), 873-893. https://doi.org/10.5194/hess-27-873-2023Laugesen, R., Thyer, M., McInerney, D., & Kavetski, D. (2024). RUVPY software library to quantify the value of forecasts for decision-making using RUV (v0.9.0). Zenodo. https://doi.org/10.5281/zenodo.13939199
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The University of Adelaide
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