Accessibility navigation


Reducing inconsistencies in point observations of maximum flood inundation level

Parkes, B. L., Cloke, H. L., Pappenberger, F., Neal, J. and Demeritt, D. (2013) Reducing inconsistencies in point observations of maximum flood inundation level. Earth Interactions, 17 (6). pp. 1-27. ISSN 1087-3562

[img]
Preview
Text - Published Version
· Please see our End User Agreement before downloading.

2MB

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item DOI: 10.1175/2012EI000475.1

Abstract/Summary

Flood simulation models and hazard maps are only as good as the underlying data against which they are calibrated and tested. However, extreme flood events are by definition rare, so the observational data of flood inundation extent are limited in both quality and quantity. The relative importance of these observational uncertainties has increased now that computing power and accurate lidar scans make it possible to run high-resolution 2D models to simulate floods in urban areas. However, the value of these simulations is limited by the uncertainty in the true extent of the flood. This paper addresses that challenge by analyzing a point dataset of maximum water extent from a flood event on the River Eden at Carlisle, United Kingdom, in January 2005. The observation dataset is based on a collection of wrack and water marks from two postevent surveys. A smoothing algorithm for identifying, quantifying, and reducing localized inconsistencies in the dataset is proposed and evaluated showing positive results. The proposed smoothing algorithm can be applied in order to improve flood inundation modeling assessment and the determination of risk zones on the floodplain.

Item Type:Article
Refereed:Yes
Divisions:Interdisciplinary centres and themes > Walker Institute
Faculty of Science > School of Archaeology, Geography and Environmental Science > Earth Systems Science
Faculty of Science > School of Archaeology, Geography and Environmental Science > Department of Geography and Environmental Science
ID Code:35476
Uncontrolled Keywords:Hydraulic modeling, Model calibration, Model validation, Uncertainty, Error correction
Publisher:American Meteorological Society

Downloads

Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation