05 Aug 2022
05 Aug 2022
Status: this preprint is currently under review for the journal HESS.

Why our rainfall-runoff models keep underestimating the peak flows?

András Bárdossy and Faizan Anwar András Bárdossy and Faizan Anwar
  • Institute for Water and Environmental System Modeling, University of Stuttgart, 70569 Stuttgart, Germany

Abstract. In this paper the question of how interpolation of precipitation in space by using various spatial gauge densities affects the rainfall-runoff model discharge if all other input variables are kept constant is investigated. This was done using a physically-based model as the reference with a reconstructed spatially variable precipitation and a conceptual model calibrated to match the reference model output. Both models were run with distributed and lumped inputs. Results showed that all considered interpolation methods resulted in underestimation of the total precipitation volume and that the underestimation was directly proportional to the amount. The underestimation was very severe for low observation densities and disappeared only for very high density precipitation observation networks. This result was confirmed by using observed precipitation with different observation densities. Model runoffs showed worse performance for their highest discharges. Using lumped inputs for the models showed deteriorating performance for peak flows as well even when using simulated precipitation.

András Bárdossy and Faizan Anwar

Status: open (extended)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on hess-2022-281', Abdolreza Bahremand, 07 Aug 2022 reply
  • RC1: 'Comment on hess-2022-281', Keith Beven, 12 Aug 2022 reply
    • AC1: 'Reply on RC1', Faizan Anwar, 17 Aug 2022 reply
      • RC2: 'Reply on AC1', Keith Beven, 17 Aug 2022 reply

András Bárdossy and Faizan Anwar

András Bárdossy and Faizan Anwar


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Short summary
This study concerns rainfall-runoff modelers only.