Estimation of instantaneous peak flows from maximum mean daily flows using the HBV hydrological model

authored by: J. Ding, M. Wallner, H. Müller, U. Haberlandt
Abstract: The record length and quality of instantaneous peak flows (IPFs) have a great influence on flood design, but these high resolution flow data are not always available. The primary aim of this study is to compare different strategies to derive frequency distributions of IPFs using the Hydrologiska Byråns Vattenbalansavdelning (HBV) hydrologic model. The model is operated on a daily and an hourly time step for 18 catchments in the Aller-Leine basin, Germany. Subsequently, general extreme value (GEV) distributions are fitted to the simulated annual series of daily and hourly extreme flows. The resulting maximum mean daily flow (MDF) quantiles from daily simulations are transferred into IPF quantiles using a multiple regression model, which enables a direct comparison with the simulated hourly quantiles. As long climate records with a high temporal resolution are not available, the hourly simulations require a disaggregation of the daily rainfall. Additionally, two calibrations strategies are applied: (1) a calibration on flow statistics; (2) a calibration on hydrographs. The results show that: (1) the multiple regression model is capable of predicting IPFs with the simulated MDFs; (2) both daily simulations with post-correction of flows and hourly simulations with pre-processing of precipitation enable a reasonable estimation of IPFs; (3) the best results are achieved using disaggregated rainfall for hourly modelling with calibration on flow statistics; and (4) if the IPF observations are not sufficient for model calibration on flow statistics, the transfer of MDFs via multiple regressions is a good alternative for estimating IPFs.
Organisation(s): Institute of Hydrology and Water Resources Management
External Organisation(s): Federal Institute for Geosciences and Natural Resources (BGR)
Type: Article
Journal: Hydrological processes
Volume: 30
Pages: 1431-1448
No. of pages: 18
ISSN: 0885-6087
Publication date: 30.04.2016
Publication status: Published
Peer reviewed: Yes
ASJC Scopus subject areas: Water Science and Technology
Sustainable Development Goals: SDG 13 - Climate Action
Electronic version(s): https://doi.org/10.15488/1680 (Access: Closed)
https://doi.org/10.1002/hyp.10725 (Access: Closed)