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Articles | Volume 23, issue 2
https://doi.org/10.5194/hess-23-1015-2019
https://doi.org/10.5194/hess-23-1015-2019
Research article
 | 
19 Feb 2019
Research article |  | 19 Feb 2019

Identifying rainfall-runoff events in discharge time series: a data-driven method based on information theory

Stephanie Thiesen, Paul Darscheid, and Uwe Ehret

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Cited articles

Bellman, R.: Dynamic Programming, Princeton University Press, Princeton, USA, 1957. 
Blower, G. and Kelsall, J. E.: Nonlinear Kernel Density Estimation for Binned Data: Convergence in Entropy, Bernoulli, 8, 423–449, 2002. 
Blume, T., Zehe, E., and Bronstert, A.: Rainfall-runoff response, event-based runoff coefficients and hydrograph separation, Hydrolog. Sci. J., 52, 843–862, https://doi.org/10.1623/hysj.52.5.843, 2007. 
Brunsell, N. A.: A multiscale information theory approach to assess spatial-temporal variability of daily precipitation, J. Hydrol., 385, 165–172, https://doi.org/10.1016/j.jhydrol.2010.02.016, 2010. 
Chapman, T. G.: Entropy as a measure of hydrologic data uncertainty and model performance, J. Hydrol., 85, 111–126, https://doi.org/10.1016/0022-1694(86)90079-X, 1986. 
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We present a data-driven approach created to explore the full information of data sets, avoiding...