z-logo
open-access-imgOpen Access
Simplification of one-dimensional hydraulic networks by automated processes evaluated on 1D/2D deterministic flood models
Author(s) -
Steffen Davidsen,
Roland Löwe,
Cecilie Thrysøe,
Karsten ArnbjergNielsen
Publication year - 2017
Publication title -
journal of hydroinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.654
H-Index - 50
eISSN - 1465-1734
pISSN - 1464-7141
DOI - 10.2166/hydro.2017.152
Subject(s) - flood myth , computation , node (physics) , flooding (psychology) , computer science , trimming , environmental science , algorithm , downstream (manufacturing) , mathematical optimization , mathematics , engineering , geography , structural engineering , psychology , operations management , archaeology , psychotherapist , operating system
Evaluation of pluvial flood risk is often based on computations using 1D/2D urban flood models. However, guidelines on choice of model complexity are missing, especially for 1D network models. This study presents a new automatic approach for simplification of 1D hydraulic networks (SAHM) using trimming and merging techniques, with performance evaluated in a 1D/2D case study. Decreasing the number of elements in the 1D model by 66% yielded a 35% decrease in computation time of the coupled 1D/2D simulation. The simplifications increased flow in some downstream branches and removing nodes eliminated connection to some areas. This promoted errors in 2D flood results with changes in spatial location of flooding in the reduced 1D/2D models. Applying delayed rain inputs to compensate for changes in travel time and preserving network volume by expanding node diameters did not improve overall results. Investigations on the expected annual damages ( EAD ) showed that differences in EAD are smaller than deviations in the simulated flooded areas, suggesting that spatial changes are limited to local displacements. Probably, minor improvements of the simplification procedure will further improve results of the reduced models.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom