Appropriate flow forecasting for reservoir operation

Appropriate modelling seeks for a complexity-accuracy-uncertainty consistent system that is as simple as possible, but compatible for its task. Appropriate flood forecasting methods have a sound practical background, in this research, they are oriented to satisfy the requirements of reservoir operation. The specifications of the models are determined by the physical characteristics of the river basin and the requirements from the reservoir operation, i.e., which hydrological processes should be considered. In order to appropriately operate a single model, a number of influencing factors need to be specified: spatio-temporal resolution, model complexity, uncertainties, and their mutual relationships and consistencies. Therefore the objective of this research is to answer the following questions:

How to find the appropriate flood forecasting models, and how to apply them in an appropriate way to fulfil the requirements of reservoir operation


1) Selection of appropriate flood forecasting models. The criteria of selecting the appropriate flood forecasting models are first of all based on requirements from the reservoir operation, and secondly the physical reality of the river basin which will determine if there is a realistic solution toward the requirements.

2) Appropriate application of models:

Appropriate spatio-temporal resolution of input data. Sampling the rainfall data properly (both spatially & temporally) depends not only on the local precipitation patterns in the basin, but also on the hydrological response characteristics therein.

Appropriate model complexity. The amount of the subbasins in the model and the hydrological processes included in each subbasin determine the descerning of “lumped” and “distributed” models, whose appropriate scale need to be identified.

None of the uncertainties derived from the aspects mentioned above should dominate the output uncertainty. A consistent system could tolerate the variation of uncertainties from the sources, and prevent significant effect on output uncertainty.


1) Reservoir simulations to define the requirements on flood forecasting.

2) Existing models are categorized with criteria of enclosed hydrological sub-processes, type of basin intended to handle, sort of data needed and operational performance.

3) Representatives of data-driven (ANN) and physics-based model (HBV) are selected to execute appropriate modelling investigation.

4) Uncertainties are evaluated to guarantee the results are practically usable for the reservoir operation.

Persons involved

dr. Xiaohua Dong (PhD student)

dr. ir. C. Marjolein Dohmen-Janssen (daily supervisor)

dr. ir. Martijn J. Booij (daily supervisor)

prof. dr. Suzanne J.M.H. Hulscher (promotor)

Publications [see ‘Publications’ for PDF-file or request free hard copy]

Dong, X., 2005. Appropriate flow forecasting for reservoir operation. PhD-thesis. University of Twente, Enschede, 134 pp., ISBN 90-365-2226-9.

Dong, X., Dohmen-Janssen, C.M. and Booij, M.J., 2005. Appropriate spatial sampling of rainfall for flow simulation. Hydrological Sciences Journal, 50, 279-298.

Dong, X., Dohmen-Janssen, C.M., Booij, M.J. and Hulscher, S.J.M.H., 2005. Requirements and benefits of flow forecasting for improving hydropower generation. In: Vrijling, J.K., Ruijgh, E., Stalenberg, B., Van Gelder, P.H.A.J.M., Verlaan, M., Zijderveld, A. and Waarts, P. (Eds.), Book of Abstracts International Symposium on Stochastic Hydraulics 2005, 23-24 May 2005, Nijmegen, the Netherlands, 60-62.

Dong, X., Dohmen-Janssen, C.M., Booij, M.J. and Hulscher, S.J.M.H., 2005. Requirements on flow forecasting based on a benefit analysis of reservoir operation. In: Proc. International Conference of Reservoir Operation and River management (Vol. 1), 17-23 September 2005, Guangzhou and Three Gorges, China.

Dong, X., Dohmen-Janssen, C.M., Booij, M. and Hulscher, S., 2006. Effect of flow forecasting quality on benefits of reservoir operation - a case study for the Geheyan reservoir (China). Hydrology and Earth System Sciences Discussions, 3, 3771-3814.