Software

Code and data for 'Tailored Calibration of Stochastic Weather Generators for Enhanced Hydrological System Evaluation' by McInerney et al

The University of Adelaide
David McInerney (Aggregated by) Dmitri Kavetski (Aggregated by) Dr Mark Thyer (Aggregated by) Holger Maier (Aggregated by) Mark Thyer (Aggregated by)
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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:doi10.25909/29346932.v1&rft.title=Code and data for 'Tailored Calibration of Stochastic Weather Generators for Enhanced Hydrological System Evaluation' by McInerney et al&rft.identifier=https://doi.org/10.25909/29346932.v1&rft.publisher=The University of Adelaide&rft.description=This archive contains R code and data files for running simulations and producing figures for the paper titled 'Tailored Calibration of Stochastic Weather Generators for Enhanced Hydrological System Evaluation' by McInerney et al (under review).These scripts use the foreSIGHT R package (https://github.com/ClimateAnalytics/foreSIGHT). Observed climate and streamflow data are obtained from the CAMELS-AUS dataset (Fowler et al., 2021).ReferencesFowler, K., Acharya, S., Addor, N., Chou, C. & Peel, M. C. 2021. CAMELS-AUS: hydrometeorological time series and landscape attributes for 222 catchments in Australia. Earth Syst. Sci. Data, 13, 3847-3867.McInerney, D., Westra, S., Leonard, M., Kavetski, D., Thyer, M., Maier, H.R. Tailored Calibration of Stochastic Weather Generators for Enhanced Hydrological System Evaluation. Journal of Hydrology (under review) &rft.creator=David McInerney&rft.creator=Dmitri Kavetski&rft.creator=Dr Mark Thyer&rft.creator=Holger Maier&rft.creator=Mark Thyer&rft.creator=Michael Leonard&rft.creator=Seth Westra&rft.date=2025&rft_rights=MIT&rft_subject=Stochastic weather generator&rft_subject=stochastic model&rft_subject=tailored calibration&rft_subject=simulated method of moments&rft_subject=climate impact assessment&rft_subject=global optimization&rft_subject=Surface water hydrology&rft_subject=Water resources engineering&rft_subject=Optimisation&rft.type=Computer Program&rft.language=English Access the software
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This archive contains R code and data files for running simulations and producing figures for the paper titled 'Tailored Calibration of Stochastic Weather Generators for Enhanced Hydrological System Evaluation' by McInerney et al (under review).

These scripts use the foreSIGHT R package (https://github.com/ClimateAnalytics/foreSIGHT). Observed climate and streamflow data are obtained from the CAMELS-AUS dataset (Fowler et al., 2021).

References

Fowler, K., Acharya, S., Addor, N., Chou, C. & Peel, M. C. 2021. CAMELS-AUS: hydrometeorological time series and landscape attributes for 222 catchments in Australia. Earth Syst. Sci. Data, 13, 3847-3867.

McInerney, D., Westra, S., Leonard, M., Kavetski, D., Thyer, M., Maier, H.R. Tailored Calibration of Stochastic Weather Generators for Enhanced Hydrological System Evaluation. Journal of Hydrology (under review)

Issued: 2025-06-18

Created: 2025-06-18

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Optimisation | Stochastic weather generator | Surface water hydrology | Water resources engineering | climate impact assessment | global optimization | simulated method of moments | stochastic model | tailored calibration |

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