Geography Reference
In-Depth Information
Main findings of Level 2 assessment
-
regional weather patterns, and the organisation of vege-
tation patterns in the context of water and energy vari-
ability. It is at the seasonal time scale that all of these
features have a collective impact on seasonal runoff
variability, through their impact on storage processes,
and in this sense the regime types are analogous to the
Budyko relationship that underpins annual runoff.
The performance of the regression and spatial prox-
imity methods for predicting seasonal runoff in
ungauged basins decreases with increasing aridity
for aridity indices larger than 1.
-
The dependence of performance on air temperature and
catchment elevation differs between regions and is related
to the role of aridity and snow at different elevations.
Just as in the case of annual runoff, process-based
methods of the derived distribution kind can be valuable
to help interpret index-type relationships of seasonal
flow regimes (i.e., regime types, regime behaviour) in
particular regions in the context of the relative variabil-
ity of water and energy availability and the attenuating
and/or accentuating effects of storage mechanisms. The
understanding gained can be used to interpret and
explain the differences between the regime types that
one finds in different regions.
-
The performance of geostatistical methods increases
with catchment area because the overlapping areas
between gauged and ungauged catchments tend to be
bigger.
-
Spatial proximity methods perform better than regres-
sion because the processes driving seasonal runoff
(seasonality in precipitation, storage) are smooth in
space, but this requires stream gauge data in the
region.
-
Geostatistical methods perform even better because
they are based on the assumption of smoothness of
the driving processes and take the stream network
structure into account.
The
and process-based approaches to the
study and prediction of seasonal flow regime represent
two schools of thought, coming from geography and
engineering. They represent, respectively, a holistic, co-
evolutionary view of catchment systems and a reductionist
or mechanistic view. This chapter, and for that matter the
topic itself, represents an attempt to achieve a synthesis of
these two schools of thought for improved predictions and
advancement of the science of hydrology.
'
regime type
'
6.6 Summary of key points
Seasonal flow regime is the signature that represents
the mean within-year variability of runoff. In relation
to annual runoff, the seasonal flow regime reflects
the processes of storage that operate on seasonal time
scales. Storage in soils and groundwater has the effect of
attenuating the relative differences in water (precipita-
tion) and energy (potential evaporation) availability
(both magnitude and timing), whereas storage in snow
and ice (glaciers) accentuates these differences. These
differences give rise to differences in regime types
across the world. Monsoons also introduce significant
seasonality, but tend to exhibit considerable inter-annual
variability.
Comparative assessment of all methods being used for
predictions of seasonal runoff in ungauged basins indi-
cated that predictive performance becomes worse with
increasing aridity (both Level 1 and Level 2 assessments).
Geostatistical methods that take the stream network struc-
ture into account were shown to work best at both Levels 1
and 2; this is because seasonal runoff variability tends to
be smooth in space, and so is easy to capture by spatial
correlations based on observations. Geostatistical methods
require stream gauges in the region of interest.
The seasonal flow regime can be seen as the
'
connective
Therefore, temperature variations in cold regions (where
snowfall is significant), and the relative amplitude and
timing of precipitation and temperature are the key con-
trols and similarity indices for the seasonal flow regime.
Other similarity indices include storage capacity in the
subsurface, and elevation and other topographic features
that govern snow storage. Co-evolutionary indices that
reflect and also impact seasonal flow regime include
vegetation cover and phenology.
tissue
or the backbone that connects runoff variability at
all other time scales and the associated signatures. Sea-
sonality affects annual runoff variability, it is a major
control of the flow duration curve, it helps set up the
antecedent soil moisture for flood estimation, and it is a
key control on low flows. Seasonal flow regime is the
most important diagnostic in the estimation of the com-
plete hydrograph. It is the key to predicting the other
runoff signatures.
'
A widely used method for predicting seasonal flow
regime is through delineation into
There needs to be a concerted and increased effort to look
at regime types from around the world in a comparative
manner, and to understand and classify them in terms of
the underlying climate and landscape controls, through a
synthesis of the process-based (reductionist) and geo-
graphic (holistic) world views. This will help advance
the cause of predictions everywhere.
. This
belongs to the category of index methods, and embraces
the natural organisation and co-evolution of catchments
in the environment, including features such as topo-
graphic elevation as a control on environmental variabil-
ity, distance from the ocean, position of the landscape in
'
regime types
'
Search WWH ::
Custom Search