Abstract
From an outsider’s perspective, hydrology combines
field work with modelling, but mostly ignores the potential
for gaining understanding and conceiving new hypotheses
from controlled laboratory experiments. Sivapalan
(2009) pleaded for a question- and hypothesis-driven hydrology
where data analysis and top-down modelling approaches
lead to general explanations and understanding of general
trends and patterns. We discuss why and
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