Abstract
A real-time operation method of a multi-purpose reservoir for flood management considering an ensemble streamflow prediction (ESP) is investigated in this study. The ESP is derived by a distributed rainfall-runoff model from an operational ensemble prediction of precipitation. Japan Meteorological Agency’s One-week Ensemble Forecast of precipitation, which is provided every day and has 51 ensemble members of six-hour precipitations for the coming eight days, is employed here. ESPs with 51 members for the coming eight days are calculated from the ensemble predictions of basin precipitation by use of Hydrological River Basin Environment Assessment Model (Hydro-BEAM), a distributed rainfall-runoff model. Reservoir states such as release or storage are then estimated for each ensemble member of the streamflow predictions to support preliminary release operation. Chance and the expected amount of recovery in storage water at the end of the flood event are also estimated for each scenario of reservoir operation to estimate impacts of the preliminary release operation on water supply operation in the following period, in order to help reservoir manager with making a decision on preliminary release considering the prediction and its uncertainty. The presented method was applied to Nagayasuguchi Reservoir in the Naka River basin in Japan, demonstrating the effectiveness and potential to provide useful information for real-time preliminary release operation of reservoirs.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
IPCC. (2013). Climate Change 2013: The Physical Science Basis (1535Â pp). Cambridge, United Kingdom and New York, NY, USA: Cambridge University Press (Stocker, T. F., D. Qin, G. -K. Plattner, M. Tignor, S. K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex & P.M. Midgley (eds.) Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change).
Faber, B. A., & Stedinger, J. (2001). Reservoir optimization using sampling SDP with ensemble streamflow prediction (ESP) forecasts. Journal of Hydrology, 249, 113–133.
Kim, Y. O., Eum, H. I., Lee, E. G., & Ko, I. H. (2007). Optimizing operational policies of a Korean multireservoir system using sampling stochastic dynamic programming with ensemble streamflow prediction. Journal of Water Resources Planning and Management, 133(1), 4–14.
Nohara, D., Tsuboi, A., & Hori, T. (2009). Long-term reservoir operation optimized by DP models with one-month ensemble forecast of precipitation. IAHS Publications, 331, 284–295.
Alemu, E. T., Palmer, R. N., Polebitski, A., & Meaker, B. (2011). Decision support system for optimizing reservoir operation using ensemble streamflow predictions. Journal of Water Resources Planning and Management, 137(1), 72–82.
Masuda, H., & Oishi, S. (2013). Study on optimization of the integrated operation using ensemble prediction in the upper reaches of the Nabari river. In Proceedings of the 35th IAHR World Congress, S10065.
Kojiri, T., Tokai, A., & Kinai, Y. (1998). Assessment of river basin environment through simulation with water quality and quantity. Annuals of Disaster Prevention Research Institute, Kyoto University, 41(2), 119–134.
Kojiri, T. (2006). Hydrological river basin assessment model (Hydro-BEAM). In V. P. Singh & D. K. Frevent (Eds.), Watershed models (pp. 613–626). Boca Raton, FL, USA: Taylor & Francis, CRC Press.
Sato, Y., Kojiri, T., Michihiro, Y., Suzuki, Y., & Nakakita, E. (2013). Assessment of climate change impacts on river discharge in Japan using the super-high-resolution MRI-AGCM. Hydrological Processes, 27, 3264–3279.
Acknowledgements
This work was supported by JSPS KAKENHI Grant Number 25420523. Data of One-week Ensemble Forecast of JMA, which has been collected in Kyoto University Active Geosphere Investigations for the 21st Century COE Program and been offered on the web site of GFD Dennou Club, was used in this study. The authors would like to express sincere appreciation to all of them.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer Science+Business Media Singapore
About this chapter
Cite this chapter
Nohara, D., Nishioka, Y., Hori, T., Sato, Y. (2016). Real-Time Reservoir Operation for Flood Management Considering Ensemble Streamflow Prediction and Its Uncertainty. In: Gourbesville, P., Cunge, J., Caignaert, G. (eds) Advances in Hydroinformatics. Springer Water. Springer, Singapore. https://doi.org/10.1007/978-981-287-615-7_23
Download citation
DOI: https://doi.org/10.1007/978-981-287-615-7_23
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-287-614-0
Online ISBN: 978-981-287-615-7
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)