Hydrology and Earth System Sciences
www.hydrol-earth-syst-sci.net
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12
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2008
10.5194/hess-12-769-2008
http://www.hydrol-earth-syst-sci.net/12/769/2008/
http://www.hydrol-earth-syst-sci.net/12/769/2008/hess-12-769-2008.html
http://www.hydrol-earth-syst-sci.net/12/769/2008/hess-12-769-2008.pdf
769
796
2008-05-23
Which spatial discretization for distributed hydrological models? Proposition of a methodology and illustration for medium to large-scale catchments
J. Dehotin
dehotin@lyon.cemagref.fr
I. Braud
Cemagref Lyon, Research Unit Hydrology and Hydraulics, 3bis Quai Chauveau, CP 220, 69336 Lyon Cédex 9, France
Distributed hydrological models are valuable tools to derive distributed
estimation of water balance components or to study the impact of land-use or
climate change on water resources and water quality. In these models, the
choice of an appropriate spatial discretization is a crucial issue. It is
obviously linked to the available data, their spatial resolution and the
dominant hydrological processes. For a given catchment and a given data set,
the "optimal" spatial discretization should be adapted to the modelling
objectives, as the latter determine the dominant hydrological processes
considered in the modelling. For small catchments, landscape heterogeneity
can be represented explicitly, whereas for large catchments such fine
representation is not feasible and simplification is needed. The question is
thus: is it possible to design a flexible methodology to represent landscape
heterogeneity efficiently, according to the problem to be solved? This
methodology should allow a controlled and objective trade-off between
available data, the scale of the dominant water cycle components and the
modelling objectives.
<br><br>
In this paper, we propose a general methodology for such catchment
discretization. It is based on the use of nested discretizations. The first
level of discretization is composed of the sub-catchments, organised by the
river network topology. The sub-catchment variability can be described using
a second level of discretizations, which is called hydro-landscape units.
This level of discretization is only performed if it is consistent with the
modelling objectives, the active hydrological processes and data
availability. The hydro-landscapes take into account different geophysical
factors such as topography, land-use, pedology, but also suitable
hydrological discontinuities such as ditches, hedges, dams, etc. For
numerical reasons these hydro-landscapes can be further subdivided into
smaller elements that will constitute the modelling units (third level of
discretization).
<br><br>
The first part of the paper presents a review about catchment discretization
in hydrological models from which we derived the principles of our general
methodology. The second part of the paper focuses on the derivation of
hydro-landscape units for medium to large scale catchments. For this
sub-catchment discretization, we propose the use of principles borrowed from
landscape classification. These principles are independent of the catchment
size. They allow retaining suitable features required in the catchment
description in order to fulfil a specific modelling objective. The method
leads to unstructured and homogeneous areas within the sub-catchments, which
can be used to derive modelling meshes. It avoids map smoothing by
suppressing the smallest units, the role of which can be very important in
hydrology, and provides a confidence map (the distance map) for the
classification. The confidence map can be used for further uncertainty
analysis of modelling results. The final discretization remains consistent
with the resolution of input data and that of the source maps. The last part
of the paper illustrates the method using available data for the upper
Saône catchment in France. The interest of the method for an efficient
representation of landscape heterogeneity is illustrated by a comparison
with more traditional mapping approaches. Examples of possible models, which
can be built on this spatial discretization, are finally given as
perspectives for the work.
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