Evaluating a landscape-scale daily water balance model to support spatially continuous representation of flow intermittency throughout stream networks
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Published:2020-11-12
Issue:11
Volume:24
Page:5279-5295
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ISSN:1607-7938
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Container-title:Hydrology and Earth System Sciences
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language:en
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Short-container-title:Hydrol. Earth Syst. Sci.
Author:
Yu SongyanORCID, Do Hong XuanORCID, van Dijk Albert I. J. M.ORCID, Bond Nick R., Lin Peirong, Kennard Mark J.
Abstract
Abstract. There is a growing interest globally in the spatial distribution and
temporal dynamics of intermittently flowing streams and rivers, and how this
varies in relation to climatic and other environmental factors. However,
biases in the distribution of stream gauges may give a misleading impression
of spatial-temporal variations in streamflow intermittency within river
networks. Here, we developed an approach to quantify catchment-wide
streamflow intermittency over long time frames and in a spatially explicit
manner, using readily accessible and spatially contiguous daily runoff data
from a national-scale water balance model. We examined the ability of the
water balance model to simulate streamflow in two hydro-climatically
distinctive (subtropical and temperate) regions in Australia, with a
particular focus on low-flow simulations. We also evaluated the effect of
model time step (daily vs. monthly) on flow intermittency estimation to
inform future model selection. The water balance model showed better
performance in the temperate region characterised by steady baseflow than in
the subtropical region with flashy hydrographs and frequent cease-to-flow
periods. The model tended to overestimate low-flow magnitude mainly due to
overestimation of gains (e.g. groundwater release to baseflow) during
low-flow periods. Modelled patterns of flow intermittency revealed highly
dynamic behaviour in space and time, with cease-to-flow events affecting
between 29 and 80 % of the river network over the period of
1911–2016, using a daily streamflow model. The daily flow model did not
perform better than the monthly flow model in quantifying flow intermittency
at a monthly time step, and model selection should depend on the intended
application of the model outputs. Our general approach to quantifying
spatio-temporal patterns of flow intermittency is transferable to other
parts of the world, and it can inform hydro-ecological understanding and
management of intermittent streams where limited gauging data are available.
Funder
University of Michigan China Scholarship Council Griffith University
Publisher
Copernicus GmbH
Subject
General Earth and Planetary Sciences,General Engineering,General Environmental Science
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