Abstract

Traditional design flood estimation approaches have focused on peak discharges and have often neglected other hydrograph characteristics such as hydrograph volume and shape. Synthetic design hydrograph estimation procedures overcome this deficiency by jointly considering peak discharge, hydrograph volume, and shape. Such procedures have recently been extended to allow for the consideration of process variability within a catchment by a flood-type specific construction of design hydrographs. However, they depend on observed runoff time series and are not directly applicable in ungauged catchments where such series are not available. To obtain reliable flood estimates, there is a need for an approach that allows for the consideration of process variability in the construction of synthetic design hydrographs in ungauged catchments. In this study, we therefore propose an approach that combines a bivariate index flood approach with event-type specific synthetic design hydrograph construction. First, regions of similar flood reactivity are delineated and a classification rule that enables the assignment of ungauged catchments to one of these reactivity regions is established. Second, event-type specific synthetic design hydrographs are constructed using the pooled data divided by event type from the corresponding reactivity region in a bivariate index flood procedure. The approach was tested and validated on a dataset of 163 Swiss catchments. The results indicated that 1) random forest is a suitable classification model for the assignment of an ungauged catchment to one of the reactivity regions, 2) the combination of a bivariate index flood approach and event-type specific synthetic design hydrograph construction enables the consideration of event types in ungauged catchments, and 3) the use of probabilistic class memberships in regional synthetic design hydrograph construction helps to alleviate the problem of misclassification. Event-type specific synthetic design hydrograph sets enable the inclusion of process variability into design flood estimation and can be used as a compromise between single best estimate synthetic design hydrographs and continuous simulation studies.

Keywords

Classification; Random forest; Homogeneous regions; Regionalization; Mixtures; Floods

Published in

Advances in Water Resources
2018, Volume: 112, pages: 235-244
Publisher: ELSEVIER SCI LTD

UKÄ Subject classification

Oceanography, Hydrology, Water Resources


Publication identifier

DOI: https://doi.org/10.1016/j.advwatres.2017.12.018

Permanent link to this page (URI)

https://res.slu.se/id/publ/98769