The application of ensemble precipitation forecasts to reservoir operation

Abstract

Although inflow forecasts are useful information that can be used for improving reservoir operation efficiency, uncertainty is still a challenge for getting sound operation results. Ensemble precipitation forecasts can take uncertainties under consideration, so they have been a research topic for improving reservoir operations. In this paper, a rainfall–runoff model, combined of a multiple linear regression model (for non-flood seasons) and the Xinanjiang model (for flood seasons), for inflow forecasts and a stochastic dynamic programming model for reservoir operations are developed in order to effectively use the ensemble precipitation forecast. To explore the best way for using the ensemble precipitation forecast, two post-processing techniques, i.e., ensemble forecast averaging (EFA) and interval value (IV), are tested. The ensemble precipitation forecast from the European Centre for Medium-Range Weather Forecasts (ECMWF) was chosen due to its high accuracy, and the Huanren reservoir, located in China, was used to test the newly developed models. The results show that, compared with the traditional rule curve, hydropower generation increases by 4.86% and 4.55%, respectively, when EFA and IV are used, which indicates that the use of ensemble forecasts facilitates considerable improvements in operating performance.

Flash-flood hazard assessment using ensembles and Bayesian-based machine learning models: Application of the simulated annealing feature selection method

“…The BayesGLM model has never been used for flood susceptibility mapping or any other hydrological modeling up until now. But the popularity of boosting in the advancement of ensemble machine learning methods for hydrological modeling including the flood prediction has been fast-growing due to their accuracy (Antonetti et al, 2019;Berkhahn et al, 2019;Gomez et al, 2019;Lee et al, 2017;Peng et al, 2019;Tian et al, 2019).…”

AI-based techniques for multi-step streamflow forecasts: application for multi-objective reservoir operation optimization and performance assessment

“…The combined effects of price and streamflow forecasts on water resource allocation are worth investigating in future studies. Our study also suffers from the drawback that instead of using the short-term weather forecasts from the Global Forecast System (GFS) or European Centre for Medium-Range Weather Forecasts (ECMWF) model (Choong and El-Shafie, 2015;Schwanenberg et al, 2015;Peng et al, 2018;Ahmad and Hossain, 2019;, we used the observed weather conditions as alternatives, which may result in an overestimation in forecast quality. However, forecast uncertainty and error generally grow with lead time.…”

AI-based techniques for multi-step streamflow forecasts: Application for multi-objective reservoir operation optimization and performance assessment

“…The combined effects of price and streamflow forecasts on water resource allocation are worth investigating in future studies. Another limitation is that instead of the short-term weather forecasts from the Global Forecast System (GFS) or European Centre for Medium-Range Weather Forecasts (ECMWF) model (Choong and El-Shafie, 2015;Schwanenberg et al, 2015;Peng et al, 2018;Ahmad and Hossain, 2019;, we used the observed weather conditions as alternatives, which may result in an overestimation in forecast quality. However, forecast uncertainty and error that generally grow up with lead time.…”