Risk Analysis of Reservoir Flood Routing Calculation Based on Inflow Forecast Uncertainty
by
Binquan Li 1,2,*
, Zhongmin Liang 1,3, Jianyun Zhang 2, Xueqing Chen 1,4, Xiaolei Jiang 1, Jun Wang 1 and Yiming Hu 5,6
, Zhongmin Liang 1,3, Jianyun Zhang 2, Xueqing Chen 1,4, Xiaolei Jiang 1, Jun Wang 1 and Yiming Hu 5,6
1
College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China
2
Hydrology and Water Resources Department, Nanjing Hydraulic Research Institute, Nanjing 210029, China
3
National Cooperative Innovation Center for Water Safety & Hydro-Science, Nanjing 210024, China
4
Hohai University Press, Nanjing 210024, China
5
State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China
6
Research Institute of Management Science, Business School, Hohai University, Nanjing 211100, China
*
Author to whom correspondence should be addressed.
Academic Editor: Athanasios Loukas
Water 2016, 8(11), 486; https://doi.org/10.3390/w8110486
Received: 4 September 2016 / Revised: 22 October 2016 / Accepted: 25 October 2016 / Published: 27 October 2016
Possible risks in reservoir flood control and regulation cannot be objectively assessed by deterministic flood forecasts, resulting in the probability of reservoir failure. We demonstrated a risk analysis of reservoir flood routing calculation accounting for inflow forecast uncertainty in a sub-basin of Huaihe River, China. The Xinanjiang model was used to provide deterministic flood forecasts, and was combined with the Hydrologic Uncertainty Processor (HUP) to quantify reservoir inflow uncertainty in the probability density function (PDF) form. Furthermore, the PDFs of reservoir water level (RWL) and the risk rate of RWL exceeding a defined safety control level could be obtained. Results suggested that the median forecast (50th percentiles) of HUP showed better agreement with observed inflows than the Xinanjiang model did in terms of the performance measures of flood process, peak, and volume. In addition, most observations (77.2%) were bracketed by the uncertainty band of 90% confidence interval, with some small exceptions of high flows. Results proved that this framework of risk analysis could provide not only the deterministic forecasts of inflow and RWL, but also the fundamental uncertainty information (e.g., 90% confidence band) for the reservoir flood routing calculation.
View Full-Text
Keywords:
reservoir flood routing calculation; inflow forecast uncertainty; Hydrologic Uncertainty Processor; Xinanjiang model; risk rate; Huaihe River
▼
Show Figures
Figure 1
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
MDPI and ACS Style
Li, B.; Liang, Z.; Zhang, J.; Chen, X.; Jiang, X.; Wang, J.; Hu, Y. Risk Analysis of Reservoir Flood Routing Calculation Based on Inflow Forecast Uncertainty. Water 2016, 8, 486.
Show more citation formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.
