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Advancing catchment hydrology to deal with predictions under change

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Kleidon,  Axel
Research Group Biospheric Theory and Modelling, Dr. A. Kleidon, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Citation

Ehret, U., Gupta, H. V., Sivapalan, M., Weijs, S. V., Schymanski, S. J., Blöschl, G., et al. (2014). Advancing catchment hydrology to deal with predictions under change. Hydrology and Earth System Sciences, 18(2), 649-671. doi:10.5194/hess-18-649-2014.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0013-F5A6-6
Abstract
Throughout its historical development, hydrology as an engineering discipline and earth science has relied strongly on the assumption of long-term stationary boundary conditions and system configurations, which allowed for simplified and sectoral descriptions of the dynamics of hydrological systems. However, in the face of rapid and extensive global changes (of climate, land use etc.) which affect all parts of the hydrological cycle, the general validity of this assumption appears doubtful. Likewise, so does the application of hydrological concepts based on stationarity to questions of hydrological change. The reason is that transient system behaviours often develop through feedbacks between the system constituents, and with the environment, generating effects that could often be neglected under stationary conditions. In this context, the aim of this paper is to present and discuss paradigms and theories potentially helpful to advancing hydrology towards the goal of understanding and predicting hydrological systems under change. For the sake of brevity we focus on catchment hydrology. We begin with a discussion of the general nature of explanation in hydrology and briefly review the history of catchment hydrology. We then propose and discuss several perspectives on catchments: as complex dynamical systems, self-organizing systems, co-evolving systems and open dissipative thermodynamic systems. We discuss the benefits of comparative hydrology and of taking an information-theoretic view of catchments, including the flow of information from data to models to predictions.