In:
Hydrology and Earth System Sciences, Copernicus GmbH, Vol. 22, No. 7 ( 2018-07-10), p. 3663-3684
Abstract:
Abstract. The increasing diversity and resolution of spatially
distributed data on terrestrial systems greatly enhance the potential of
hydrological modeling. Optimal and parsimonious use of these data sources
requires, however, that we better understand (a) which system characteristics
exert primary controls on hydrological dynamics and (b) to what level of
detail do those characteristics need to be represented in a model. In this study we develop and test an approach to explore these questions
that draws upon information theoretic and thermodynamic reasoning, using
spatially distributed topographic information as a straightforward example.
Specifically, we subdivide a mesoscale catchment into 105 hillslopes and
represent each by a two-dimensional numerical hillslope model. These
hillslope models differ exclusively with respect to topography-related
parameters derived from a digital elevation model (DEM); the remaining setup and
meteorological forcing for each are identical. We analyze the degree of
similarity of simulated discharge and storage among the hillslopes as a
function of time by examining the Shannon information entropy. We
furthermore derive a “compressed” catchment model by clustering the
hillslope models into functional groups of similar runoff generation using
normalized mutual information (NMI) as a distance measure. Our results reveal that, within our given model environment, only a portion
of the entire amount of topographic information stored within a digital
elevation model is relevant for the simulation of distributed runoff and
storage dynamics. This manifests through a possible compression of the model
ensemble from the entire set of 105 hillslopes to only 6 hillslopes, each
representing a different functional group, which leads to no substantial
loss in model performance. Importantly, we find that the concept of
hydrological similarity is not necessarily time invariant. On the contrary,
the Shannon entropy as measure for diversity in the simulation ensemble
shows a distinct annual pattern, with periods of highly redundant
simulations, reflecting coherent and organized dynamics, and periods where
hillslopes operate in distinctly different ways. We conclude that the proposed approach provides a powerful framework for
understanding and diagnosing how and when process organization and
functional similarity of hydrological systems emerge in time. Our approach
is neither restricted to the model nor to model targets or the data source
we selected in this study. Overall, we propose that the concepts of
hydrological systems acting similarly (and thus giving rise to redundancy)
or displaying unique functionality (and thus being irreplaceable) are not
mutually exclusive. They are in fact of complementary nature, and systems
operate by gradually changing to different levels of organization in time.
Type of Medium:
Online Resource
ISSN:
1607-7938
DOI:
10.5194/hess-22-3663-2018
Language:
English
Publisher:
Copernicus GmbH
Publication Date:
2018
detail.hit.zdb_id:
2100610-6
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