Statistical Modelling of Annual Maxima in Hydrology

Authors

  • Johannes Hofrichter Institute of Applied Statistics, Joanneum Research, Austria
  • Till Harum Institute of Water Resources Management, Joanneum Research, Austria
  • Herwig Friedl Institute of Statistics, Graz University of Technology

DOI:

https://doi.org/10.17713/ajs.v35i1.345

Abstract

In this paper conditional modelling of annual maxima for predicting flood water is considered. The aim is to predict flood water of rivers, where no data about discharge but data about properties of the catchment of the rivers are available. A generalized linear mixed model is used to model the annual maxima depending on properties of the catchment and to take the correlation among measurements of one year into account. The fitted means and variances according to this model are plugged into the method of moment estimates of the parameters of the Gumbel distribution to obtain some extreme quantiles. These quantiles are commonly used to predict flood water of rivers. This approach is applied to data from Styria (Austria). The result is a satisfactory model for predicting flood water for rivers, where no data about the discharge are available.

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Published

2016-04-03

How to Cite

Hofrichter, J., Harum, T., & Friedl, H. (2016). Statistical Modelling of Annual Maxima in Hydrology. Austrian Journal of Statistics, 35(1), 21–30. https://doi.org/10.17713/ajs.v35i1.345

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Articles