Articles | Volume 28, issue 5
Research article
06 Mar 2024
Research article |  | 06 Mar 2024

On optimization of calibrations of a distributed hydrological model with spatially distributed information on snow

Dipti Tiwari, Mélanie Trudel, and Robert Leconte


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2023-143', Anonymous Referee #1, 01 Oct 2023
    • AC1: 'Reply on RC1', Dipti Tiwari, 28 Nov 2023
  • RC2: 'Comment on hess-2023-143', Anonymous Referee #2, 30 Oct 2023
    • AC2: 'Reply on RC2', Dipti Tiwari, 28 Nov 2023

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
ED: Reconsider after major revisions (further review by editor and referees) (04 Dec 2023) by Fabrizio Fenicia
AR by Dipti Tiwari on behalf of the Authors (19 Dec 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (21 Dec 2023) by Fabrizio Fenicia
RR by Anonymous Referee #1 (27 Dec 2023)
ED: Publish as is (15 Jan 2024) by Fabrizio Fenicia
AR by Dipti Tiwari on behalf of the Authors (21 Jan 2024)
Short summary
Calibrating hydrological models with multi-objective functions enhances model robustness. By using spatially distributed snow information in the calibration, the model performance can be enhanced without compromising the outputs. In this study the HYDROTEL model was calibrated in seven different experiments, incorporating the SPAEF (spatial efficiency) metric alongside Nash–Sutcliffe efficiency (NSE) and root-mean-square error (RMSE), with the aim of identifying the optimal calibration strategy.