Assessing the performance of global hydrological models for capturing peak river flows in the Amazon basin
<p>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 p...
Main Authors: | , , , , , , , |
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Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2019-07-01
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Series: | Hydrology and Earth System Sciences |
Online Access: | https://www.hydrol-earth-syst-sci.net/23/3057/2019/hess-23-3057-2019.pdf |
Summary: | <p>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.</p> |
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ISSN: | 1027-5606 1607-7938 |