understanding hydrologic variability across europe through catchment classification
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ID: 249079
2017
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Abstract
This study contributes to better understanding the physical controls on
spatial patterns of pan-European flow signatures – taking advantage of large
open datasets for catchment classification and comparative hydrology.
Similarities in 16 flow signatures and 35 catchment descriptors were explored
for 35 215 catchments and 1366 river gauges across Europe. Correlation
analyses and stepwise regressions were used to identify the best explanatory
variables for each signature. Catchments were clustered and analyzed for
similarities in flow signature values, physiography and the combination of
the two. We found the following. (i) A 15 to 33 % (depending on the
classification used) improvement in regression model skills when combined
with catchment classification versus simply using all catchments at once.
(ii) Twelve out of 16 flow signatures were mainly controlled by climatic
characteristics, especially those related to average and high flows. For the
baseflow index, geology was more important and topography was the main
control for the flashiness of flow. For most of the flow signatures, the
second most important descriptor is generally land cover (mean flow, high
flows, runoff coefficient, ET, variability of reversals). (iii) Using a
classification and regression tree (CART), we further show that Europe can be
divided into 10 classes with both similar flow signatures and physiography.
The most dominant separation found was between energy-limited and
moisture-limited catchments. The CART analyses also separated different
explanatory variables for the same class of catchments. For example, the
damped peak response for one class was explained by the presence of large
water bodies for some catchments, while large flatland areas explained it for
other catchments in the same class. In conclusion, we find that this type of
comparative hydrology is a helpful tool for understanding hydrological
variability, but is constrained by unknown human impacts on the water cycle
and by relatively crude explanatory variables.
| Reference Key |
kuentz2017hydrologyunderstanding
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|---|---|
| Authors | ;A. Kuentz;B. Arheimer;Y. Hundecha;T. Wagener;T. Wagener |
| Journal | materials research bulletin |
| Year | 2017 |
| DOI |
10.5194/hess-21-2863-2017
|
| URL | |
| Keywords |
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