Reducing Predictive Uncertainty in Real-Time Reservoir Operations by Coupling LARS-WG with ARNO Continuous Rainfall–Runoff Model
Publication: Journal of Hydrologic Engineering
Volume 26, Issue 10
Abstract
In reservoirs with relatively low capacity-inflow () ratios, real-time daily operations provide the possibility of minimizing the risk of failure and meeting downstream demands sustainably even during extreme droughts. In the present study, it has been attempted to generate synthetic daily precipitation and maximum and minimum temperature data using the widely applied weather generator Long Ashton Research Station weather generator (LARS-WG). The synthetic meteorological data were then inserted into the Arno River (ARNO) daily rainfall–runoff (R-R) model to reproduce long-term daily streamflow scenarios and subsequently used to determine optimal daily releases and operating policies. The daily R-R model can also produce appropriate predictions of future inflows to the reservoir, which can be applied to implementing real-time operations in daily time steps. The methodology used in this study provides two main advantages: (1) the capability to determine optimal daily releases for streamflow sequences, which can be applied to make optimal real-time decisions even by considering the unregulated downstream flow regime, and (2) the ability to predict future inflows and determine real-time decisions, which can be used to decrease predictive uncertainties of future releases.
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Data Availability Statement
The following data, models, or codes generated or used during the study are available from the corresponding author by request: hydro-meteorological data (observed and produced), the modified ARNO model calibrated for Karaj River basin, all MATLAB codes developed for real-time applications, the PSO code used to solve deterministic optimization operations, and other codes used to implement the stretched-thread algorithm. The LARS-WG model is available at http://www.iacr.bbsrc.ac.uk/mas-models/larswg.html.
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Journal of Hydrologic Engineering
Volume 26 • Issue 10 • October 2021
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© 2021 American Society of Civil Engineers.
History
Received: Oct 4, 2020
Accepted: Mar 5, 2021
Published online: Jul 23, 2021
Published in print: Oct 1, 2021
Discussion open until: Dec 23, 2021
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