Abstract

Water is a limited and highly valuable resource. In many parts of the world, water agencies allocate water according to agreed entitlement systems. The allocations are largely based on water already available in storages and rivers. Water agencies may also issue seasonal water allocation outlooks by anticipating future inflows to the storages and rivers. These outlooks are meant to assist water entitlement holders to plan for their crop planting, irrigation, and participation in water markets. Currently, these outlooks are generally based on historical inflow observations (climatology) and are often determined for a small selection of possible climatic scenarios (e.g., extreme dry, dry, average, and wet). These outlooks have large uncertainties, which require users to manage high risks themselves, leading to inefficient water use. In this study, we investigate the use of ensemble seasonal inflow forecasts to improve the production of seasonal water allocation outlooks through a case study of the Goulburn system in central Victoria, Australia. This is a complex system with active water trade both within the region and outside with the larger connected southern Murray-Darling Basin. In this case study, we integrate Australian Bureau of Meteorology’s seasonal streamflow forecasts with Goulburn-Murray Water’s water allocation to produce fully probabilistic water allocation outlooks. We evaluate the outlooks for three irrigation seasons from 2017 to 2020. We compare these outlooks with those produced from using inflows based on climatology only, an approach akin to the current practice of Goulburn-Murray Water. Using seasonal streamflow forecasts resulted in outlooks up to 60% (average 20%) closer to actual determinations, with uncertainty reduced by up to 65% (average 19%) Improvements were most obvious for short lead times and later in the irrigation season. This is a clear demonstration of how integration of streamflow forecasts can improve end-user products, which can lead to more efficient water use and water market participation.

Practical Applications

This paper demonstrates how skillful forecasts of streamflow can be used to produce meaningful products for end users. Specifically, improvements are made to outlooks of water that will be made available to irrigators in dry years. The new outlooks are up to 60% closer, with up to 65% less uncertainty. These improved outlooks allow entitlement holders to more confidently plan for the irrigation season, leading in turn to more efficient water use. The method presented here should provide benefits for any water management systems where skillful streamflow forecasts are available. Beyond its use for high-reliability water share outlooks, it could easily be adapted for other water manager applications such as outlooks of low-reliability water shares in very dry years, or risk of spill (insufficient storage capacity) in wet years.

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Data Availability Statement

Some data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request. Some data, models, or code used during the study were provided by a third party. Direct requests for these materials may be made to the provider as indicated in the Acknowledgments.

Acknowledgments

The authors declare that there is no real or perceived conflict of interest regarding the publication of this article. This study is funded by the ARC Linkage Project (LP170100922). Wenyan Wu acknowledges support from the Australian Research Council via the Discovery Early Career Researcher Award (DE210100117). The seasonal streamflow forecasts can be found from the website of the Australia Bureau of Meteorology (BoM 2022). The water balance model for Goulburn system was provided by Goulburn-Murray Water (GMW): https://www.g-mwater.com.au/. The water balance models are protected and may only be accessed with permission from Goulburn-Murray Water.
Author contributions: Tristan D. J. Graham contributed to the software, formal analysis, visualization, and writing (original draft and editing). Quan J. Wang contributed to the conceptualization, funding acquisition, methodology, software, and writing (review and editing). Yating Tang contributed to the software, formal analysis, and writing (original draft). Andrew Western contributed to the conceptualization, funding acquisition, methodology, and writing (review). Wenyan Wu contributed to the writing (review). Guy Ortlipp contributed to the data curation and writing (review). Mark Bailey contributed to the data curation. Senlin Zhou contributed to the data curation. Kirsti Hakala contributed to the writing (review). Qichun Yang contributed to the writing (review).

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Go to Journal of Water Resources Planning and Management
Journal of Water Resources Planning and Management
Volume 149Issue 9September 2023

History

Received: Dec 27, 2022
Accepted: May 2, 2023
Published online: Jul 10, 2023
Published in print: Sep 1, 2023
Discussion open until: Dec 10, 2023

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Research Fellow, Dept. of Infrastructure Engineering, Univ. of Melbourne, Parkville, VIC 3010, Australia (corresponding author). ORCID: https://orcid.org/0000-0001-8272-0594. Email: [email protected]
Professor, Dept. of Infrastructure Engineering, Univ. of Melbourne, Parkville, VIC 3010, Australia. ORCID: https://orcid.org/0000-0002-8787-2738. Email: [email protected]
Yating Tang [email protected]
Modeler, NSW Department of Planning and Environment, 4 Parramatta Square, 12 Darcy St., Paramatta, NSW 2150, Australia. Email: [email protected]
Professor, Dept. of Infrastructure Engineering, Univ. of Melbourne, Parkville, VIC 3010, Australia. ORCID: https://orcid.org/0000-0003-4982-146X. Email: [email protected]
Senior Lecturer, Dept. of Infrastructure Engineering, Univ. of Melbourne, Parkville, VIC 3010, Australia. ORCID: https://orcid.org/0000-0003-3907-1570. Email: [email protected]
Coordinator, River Operations, Goulburn-Murray Water, 40 Casey St., Tatura, VIC 3616, Australia. ORCID: https://orcid.org/0009-0005-3700-5774. Email: [email protected]
Manager, Water Resources, Goulburn-Murray Water, 40 Casey St., Tatura, VIC 3616, Australia. ORCID: https://orcid.org/0000-0003-2783-1675. Email: [email protected]
Senlin Zhou [email protected]
Senior Hydrologist, Water Forecasting Team, Australian Bureau of Meteorology, 700 Collins St., Docklands, VIC 3008, Australia. Email: [email protected]
Research Fellow, Dept. of Infrastructure Engineering, Univ. of Melbourne, Parkville, VIC 3010, Australia. ORCID: https://orcid.org/0000-0002-4914-8845. Email: [email protected]
Qichun Yang [email protected]
Research Assistant Professor, Thrust of Earth, Ocean, and Atmospheric Sciences, Hong Kong Univ. of Science and Technology, Guangzhou 511453, China. Email: [email protected]

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