Preprints
https://doi.org/10.5194/hess-2021-467
https://doi.org/10.5194/hess-2021-467
 
15 Sep 2021
15 Sep 2021
Status: a revised version of this preprint is currently under review for the journal HESS.

Analysis of high streamflow extremes in climate change studies: How do we calibrate hydrological models?

Bruno Majone1, Diego Avesani1, Patrick Zulian1, Aldo Fiori2, and Alberto Bellin1 Bruno Majone et al.
  • 1Department of Civil, Environmental and Mechanical Engineering, University of Trento, Trento, I-38123, Italy
  • 2Department of Engineering, Roma Tre University, Roma, I- 00154, Italy

Abstract. Climate change impact studies on hydrological extremes often rely on the use of hydrological models with parameters inferred by using observational data of daily streamflow. In this work we show that this is an error prone procedure when the interest is to develop reliable Empirical Cumulative Distribution Function curves of annual streamflow maximum. As an alternative approach we introduce a methodology, coined Hydrological Calibration of eXtremes (HyCoX), in which the calibration of the hydrological model is carried out by directly targeting the probability distribution of high flow extremes. In particular, hydrological simulations conducted during a reference period, as driven by climate models’ outputs, are constrained to maximize the probability that the modeled and observed high flow extremes belong to the same population. The application to the Adige river catchment (southeastern Alps, Italy) by means of HYPERstreamHS, a distributed hydrological model, showed that this procedure preserves statistical coherence and produce reliable quantiles of the annual maximum streamflow to be used in assessment studies.

Bruno Majone et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2021-467', Anonymous Referee #1, 22 Oct 2021
    • AC1: 'Reply on RC1', BRUNO MAJONE, 06 Dec 2021
  • RC2: 'Comment on hess-2021-467', Anonymous Referee #2, 21 Nov 2021
    • AC2: 'Reply on RC2', BRUNO MAJONE, 06 Dec 2021

Bruno Majone et al.

Bruno Majone et al.

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Short summary
In this work we introduce a methodology for devising reliable high streamflow future scenarios from climate change simulations. The calibration of a hydrological model is carried out maximizing the probability that the modeled and observed high flow extremes belong to the same statistical population. The application to the Adige river catchment (southeastern Alps, Italy) showed that this procedure produces reliable quantiles of the annual maximum streamflow to be used in assessment studies.