CORE
🇺🇦
make metadata, not war
Services
Services overview
Explore all CORE services
Access to raw data
API
Dataset
FastSync
Content discovery
Recommender
Discovery
OAI identifiers
OAI Resolver
Managing content
Dashboard
Bespoke contracts
Consultancy services
Support us
Support us
Membership
Sponsorship
Community governance
Advisory Board
Board of supporters
Research network
About
About us
Our mission
Team
Blog
FAQs
Contact us
Does the complexity in temporal precipitation disaggregation matter for a lumped hydrological model?
Authors
H. Müller-Thomy
A.E. Sikorska-Senoner
Publication date
1 January 2019
Publisher
Abingdon : Taylor and Francis Ltd.
Doi
Cite
Abstract
Flood peaks and volumes are essential design variables and can be simulated by precipitation–runoff (P–R) modelling. The high-resolution precipitation time series that are often required for this purpose can be generated by various temporal disaggregation methods. Here, we compare a simple method (M1, one parameter), focusing on the effective precipitation duration for flood simulations, with a multiplicative cascade model (M2, 32/36 parameters). While M2 aims at generating realistic characteristics of precipitation time series, M1 aims only at accurately reproducing flood variables by P–R modelling. Both disaggregation methods were tested on precipitation time series of nine Swiss mesoscale catchments. The generated high-resolution time series served as input for P–R modelling using a lumped HBV model. The results indicate that differences identified in precipitation characteristics of disaggregated time series vanish when introduced into the lumped hydrological model. Moreover, flood peaks were more sensitive than flood volumes to the choice of disaggregation method. © 2019, © 2019 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group
Similar works
Full text
Open in the Core reader
Download PDF
Available Versions
Institutionelles Repositorium der Leibniz Universität Hannover
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:www.repo.uni-hannover.de:1...
Last time updated on 22/11/2020