Data

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)

Adelaide University
Laugesen, Richard ; Thyer, Mark ; McInerney, David ; Kavetski, Dmitri
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25909/19153055.v2&rft.title=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)&rft.identifier=10.25909/19153055.v2&rft.publisher=The University of Adelaide&rft.description=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&rft.creator=Laugesen, Richard &rft.creator=Thyer, Mark &rft.creator=McInerney, David &rft.creator=Kavetski, Dmitri &rft.edition=2&rft_rights= https://creativecommons.org/licenses/by/4.0/&rft_subject=Surface water hydrology&rft_subject=Computational modelling and simulation in earth sciences&rft_subject=Modelling and simulation&rft_subject=Time series and spatial modelling&rft_subject=Environment and resource economics&rft_subject=Economic models and forecasting&rft_subject=forecast value&rft_subject=forecast verification&rft_subject=water resources&rft_subject=economic modelling&rft_subject=subseasonal&rft_subject=streamflow forecasting&rft_subject=australia&rft_subject=murray-darling basin&rft.type=dataset&rft.language=English Access the data
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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).

References

Laugesen, 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-27-873-2023

Laugesen, 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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Subjects
Computational modelling and simulation in earth sciences | Economic models and forecasting | Environment and resource economics | Modelling and simulation | Surface water hydrology | Time series and spatial modelling | australia | economic modelling | forecast value | forecast verification | murray-darling basin | streamflow forecasting | subseasonal | water resources |

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Identifiers
ACN 633 798 857