Technical Note: The normal quantile transformation and its application in a flood forecasting system

K. Bogner*, F. Pappenberger, H. L. Cloke

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

46 Citations (Scopus)

Abstract

The Normal Quantile Transform (NQT) has been used in many hydrological and meteorological applications in order to make the Cumulated Distribution Function (CDF) of the observed, simulated and forecast river discharge, water level or precipitation data Gaussian. It is also the heart of the meta-Gaussian model for assessing the total predictive uncertainty of the Hydrological Uncertainty Processor (HUP) developed by Krzysztofowicz. In the field of geo-statistics this transformation is better known as the Normal-Score Transform. In this paper some possible problems caused by small sample sizes when applying the NQT in flood forecasting systems will be discussed and a novel way to solve the problem will be outlined by combining extreme value analysis and non-parametric regression methods. The method will be illustrated by examples of hydrological stream-flow forecasts.

Original languageEnglish
Pages (from-to)1085-1094
Number of pages10
JournalHydrology and Earth System Sciences
Volume16
Issue number4
DOIs
Publication statusPublished - 9 Apr 2012

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