Recommendations - Runoff Prediction in Ungauged Basins: Synthesis across Processes, Places and Scales - page 386

catchments as real objects rather than abstractions. Stu-
dents need to understand runoff signatures and understand
the interconnections between patterns of runoff, vegeta-
tion, drainage networks and geochemistry. Their education
must, of necessity, be interdisciplinary and should include
a range of techniques, from differential equations to under-
standing Newtonian dynamics to pattern-based approaches
to assist with reading processes from the structure of the
landscape.

within the socioeconomic context of the region of interest.
This can be achieved through a coordinated web of efforts-
such as WaterNet in Southern Africa, UNESCO-
IHP RSC in Asia and the Pacific, MOPEX in America
and FRIEND in Europe. The International Association
of Hydrological Sciences can play a catalytic role in
this process since their scope is global and their focus is
on science. All of these activities will lead to the emer-
gence of global comparative hydrology as a quantitative
science able to face up to the prediction challenges of
the future.

13.3.2 Collaborative endeavour
To succeed in what was proposed above, collaboration is
needed along three axes: Collaboration across processes
involves linking different disciplines with different dis-
courses that may be difficult but important to accommo-
date, such as social sciences versus natural sciences,
engineering versus natural sciences. Collaboration across
places involves linking researchers in different parts of the
world to enable sharing experiences about different places.
Collaboration across scales involves linking individuals to
research groups of various sizes as a part of team science,
which may need to overcome the challenges of communi-
cation, governance and funding, and to foster a culture of
collaboration.

13.4 Best practice recommendations for
predicting runoff in ungauged basins
Step 1 Read the landscape: Go out to your catchment,

look around, see what the landscape tells you, create
a photo documentation, look at the hydrogeology,
ask people about previous events, obtain global,
regional and local data, map hydraulic structures
and other modifications. If possible, install a stream
gauge.
Step 2

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Runoff signatures and processes: Analyse all
runoff signatures in nearby catchments to get an
understanding of the hydrology of the catchment
beyond the signature of interest. Runoff signatures
include annual runoff, seasonal runoff, flow duration
curve, low flows, floods and hydrographs.
Step 3

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13.3.3 Knowledge accumulation
Team science requires a change in the mode of collabor-
ation to succeed. We need a better communication culture
that allows us to learn from each other, i.e., to communi-
cate information rather than just data, to be able to benefit
better from each other

Process similarity and grouping: On the
basis of the first two steps and process similarity
measures, find similar gauged catchments to assist
in predicting runoff in the ungauged basin (grouping
of landscape units and catchments). The similarity
can be based on short-term and co-evolutionary
processes.
Step 4

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s work. Rather than reporting on
modelling successes in the authors

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catchments, the infor-
mation needs to be generalisable to make it useful to the
reader. Also, all experiments and analyses need to be
repeatable by peers. This may need development and
implementation of a universal protocol on reporting scien-
tific results in the hydrological literature as well as estab-
lishment of freely accessible data repositories. Knowledge
accumulation should be the overarching goal of hydro-
logical research.

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Model: Build statistical and/or process-based
model for the signature of interest; regionalise the
parameters from similar catchments, taking advan-
tage of a-priori information, dynamic proxy data and
any other information on processes, including from
the other signatures; account for correlations along
the stream network. There is always more informa-
tion than the hydrograph

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use it.

13.3.4 Hydrology, a global science
The world is our laboratory, and hydrology should become
a truly global science. This transformation needs to be
supported and nurtured. We need coordinating action to
bring people from different regions of the world together
on an equal footing. There may be mutual benefits by
bringing people together to share experiences of using a
diverse mix of high technology and creativity to come
up with appropriate solutions to prediction problems

Step 5 Interpretation: Interpret the parameters of the

model hydrologically and justify their values against
what was learned during field trips and other data, to
improve parameter choice and uncertainty estima-
tion. Parameters are, e.g., regression coefficients
and runoff model parameters.
Step 6

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Uncertainty: Assess uncertainty of predicted
runoff by combining error propagation methods,
regional

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cross-validation and hydrological