Mapping dominant runoff processes: an evaluation of different approaches using similarity measures and synthetic runoff simulations
The identification of landscapes with similar hydrological behaviour is useful for runoff and flood predictions in small ungauged catchments. An established method for landscape classification is based on the concept of dominant runoff process (DRP). The various DRP-mapping approaches differ with re...
Main Authors: | , , , , |
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Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2016-07-01
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Series: | Hydrology and Earth System Sciences |
Online Access: | http://www.hydrol-earth-syst-sci.net/20/2929/2016/hess-20-2929-2016.pdf |
Summary: | The identification of landscapes with similar hydrological behaviour is
useful for runoff and flood predictions in small ungauged catchments. An
established method for landscape classification is based on the concept of
dominant runoff process (DRP). The various DRP-mapping approaches differ with
respect to the time and data required for mapping. Manual approaches based on
expert knowledge are reliable but time-consuming, whereas automatic GIS-based
approaches are easier to implement but rely on simplifications which restrict
their application range. To what extent these simplifications are applicable
in other catchments is unclear. More information is also needed on how the
different complexities of automatic DRP-mapping approaches affect
hydrological simulations.
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In this paper, three automatic approaches were used to map two catchments on
the Swiss Plateau. The resulting maps were compared to reference maps
obtained with manual mapping. Measures of agreement and association, a class
comparison, and a deviation map were derived. The automatically derived DRP
maps were used in synthetic runoff simulations with an adapted version of the
PREVAH hydrological model, and simulation results compared with those from
simulations using the reference maps.
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The DRP maps derived with the automatic approach with highest complexity and
data requirement were the most similar to the reference maps, while those
derived with simplified approaches without original soil information differed
significantly in terms of both extent and distribution of the DRPs. The
runoff simulations derived from the simpler DRP maps were more uncertain due
to inaccuracies in the input data and their coarse resolution, but problems
were also linked with the use of topography as a proxy for the storage
capacity of soils.
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The perception of the intensity of the DRP classes also seems to vary among
the different authors, and a standardised definition of DRPs is still
lacking. Furthermore, we argue not to use expert knowledge for only model
building and constraining, but also in the phase of landscape
classification. |
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ISSN: | 1027-5606 1607-7938 |