Medium-term storage volume prediction for optimum reservoir management: A hybrid data-driven approach
Embargoed until: 2019-06-01
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A hybrid regressive and probabilistic model was developed that is able to forecast, six weeks ahead, the storage volume of Little Nerang dam. This is a small elevated Australian drinking water reservoir, gravity-fed to a nearby water treatment plant while a lower second main water supply source (Hinze dam) requires considerable pumping. The model applies a Monte Carlo approach combined with nonlinear threshold autoregressive models using the seasonal streamflow forecasts from the Bureau of Meteorology as input and it was validated over different historical conditions. Treatment operators can use the model for quantifying depletion rates and spill likelihood for the forthcoming six weeks, based on the seasonal climatic conditions and different intake scenarios. Greater utilization of the Little Nerang reservoir source means a reduced supply requirement from the Hinze dam source that needs considerable energy costs for pumping, leading to a lower cost water supply solution for the region.
Journal of Cleaner Production
© 2017 Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (http://creativecommons.org/licenses/by-nc-nd/4.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited.
Environmental Engineering not elsewhere classified