Title
Assessing the performance of global hydrological models for capturing peak river flows in the Amazon basin
Date Issued
18 July 2019
Access level
open access
Resource Type
journal article
Author(s)
Towner J.
Cloke H.L.
Zsoter E.
Flamig Z.
Hoch J.M.
De Perez E.C.
Stephens E.M.
Publisher(s)
Copernicus GmbH
Abstract
Extreme flooding impacts millions of people that live within the Amazon floodplain. Global hydrological models (GHMs) are frequently used to assess and inform the management of flood risk, but knowledge on the skill of available models is required to inform their use and development. This paper presents an intercomparison of eight different GHMs freely available from collaborators of the Global Flood Partnership (GFP) for simulating floods in the Amazon basin. To gain insight into the strengths and shortcomings of each model, we assess their ability to reproduce daily and annual peak river flows against gauged observations at 75 hydrological stations over a 19-year period (1997-2015). As well as highlighting regional variability in the accuracy of simulated streamflow, these results indicate that (a) the meteorological input is the dominant control on the accuracy of both daily and annual maximum river flows, and (b) groundwater and routing calibration of Lisflood based on daily river flows has no impact on the ability to simulate flood peaks for the chosen river basin. These findings have important relevance for applications of large-scale hydrological models, including analysis of the impact of climate variability, assessment of the influence of long-term changes such as land-use and anthropogenic climate change, the assessment of flood likelihood, and for flood forecasting systems.
Start page
3057
End page
3080
Volume
23
Issue
7
Language
English
OCDE Knowledge area
Oceanografía, Hidrología, Recursos hídricos
Scopus EID
2-s2.0-85069531707
Source
Hydrology and Earth System Sciences
ISSN of the container
1027-5606
Sponsor(s)
Financial support. This research has been supported by the SCE- Acknowledgements. Jamie Towner is grateful for financial support from the Natural Environment Research Council (NERC) as part of the SCENARIO Doctoral Training Partnership (grant agreement NE/L002566/1). The first author is grateful for travel support and funding provided by the Red Cross Red Crescent Climate Centre, to the research and national services, SO-HYBAM, IRD, SENAMHI, ANA, and INAMHI, for providing observed river discharge data, and to the ECMWF for computer access and technical support. Finally, specific thanks go to Christel Prudhomme and the Environmental Forecasts team in the Evaluation Section at the ECMWF for their advice and support throughout the analysis and writing of the manuscript.
Sources of information: Directorio de Producción Científica Scopus