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Data analysis and model building for understanding catchment processes: the case study of the Thur catchment
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  • Marco Dal Molin,
  • Mario Schirmer,
  • Massimiliano Zappa,
  • Fabrizio Fenicia
Marco Dal Molin
EAWAG Swiss Federal Institute of Aquatic Science and Technology

Corresponding Author:marco.dalmolin@eawag.ch

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Mario Schirmer
University of Neuch√Ętel
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Massimiliano Zappa
Swiss Federal Research Institute WSL
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Fabrizio Fenicia
CRP Gabriel Lippmann
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Abstract

The development of semi-distributed hydrological models that reflect the dominant processes controlling streamflow spatial variability is a challenging task. In small, well-instrumented headwater catchments the model can be built taking advantage of knowledge derived from extensive fieldwork activities; that is, however, not possible in much larger catchments where, usually, these models are actually needed. To address this problem, we propose a new methodology where we analyze the correlations between hydrological signatures, catchments characteristics, and climatic indices to get insights about the hydrological functioning of the catchment and to guide the decisions involved in the development of a semi-distributed model. The methodology is tested in the Thur catchment (Switzerland, 1702 km2); in a first stage we show how to identify catchment characteristics and climatic indices that control streamflow variability; in a second stage, we use these findings to develop a set of model experiments aimed at determining an appropriate model representation for the catchment. Results show that only models that account for the influencing factors indicated by the correlation analysis are able to represent correctly the observed streamflow signatures, confirming our understanding of the processes happening in the catchment.