Dadson, Simon
ORCID: https://orcid.org/0000-0002-6144-4639; Ashpole, Ian; Harris, Phil; Davies, Helen; Clark, Douglas
ORCID: https://orcid.org/0000-0003-1348-7922; Blyth, Eleanor
ORCID: https://orcid.org/0000-0002-5052-238X; Taylor, Christopher
ORCID: https://orcid.org/0000-0002-0120-3198.
2010
Wetland inundation dynamics in a model of land-surface climate: Evaluation in the Niger Inland Delta region.
Geophysical Research Abstracts, 12, EGU2010-5234.
Abstract
Observed river gauging data show significant evaporative losses from the land and water surface in the Niger
Inland delta. These losses indicate an important potential feedback between the land-surface and atmosphere.
Moreover, the reduction in river flow downstream of the wetland has clear implications for water management in
the region and beyond. Here we have modelled the evaporative losses that occur over the Niger Inland Delta by
adding an over-bank flow parameterization to the Joint UK Land-Environment Simulator (JULES) land-surface
model. The hydrological component of this model comprises a probability-distributed model of soil moisture
and runoff production (PDM) coupled with a discrete approximation to the 1D kinematic wave equation to route
river water down-slope (G2G). We use sub-grid-resolution topographic data to derive a two-parameter frequency
distribution of inundated areas for each grid-box which we then employ to represent over-bank inundation in the
model. The model was driven using data from the ALMIP experiment (ALMIP stands for AMMA Land-surface
Model Inter-comparison Project, wherein AMMA stands for African Monsoon Multidisciplinary Analyses). The
model reproduces the salient features of the observed river flow and inundation patterns; these include significant
evaporative losses from the inundated region accounting for doubling of the total land-atmosphere water flux during
periods of greatest flooding. Our predictions of inundated area are in good agreement with observed estimates of
the extent of inundation obtained using satellite infra-red and microwave remote sensing
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