Preprints
https://doi.org/10.5194/hess-2024-264
https://doi.org/10.5194/hess-2024-264
03 Sep 2024
 | 03 Sep 2024
Status: a revised version of this preprint is currently under review for the journal HESS.

Impact of Runoff Schemes on Global Flow Discharge: A Comprehensive Analysis Using the Noah-MP and CaMa-Flood Models

Mohamed Hamitouche, Giorgia Fosser, Alessandro Anav, Cenlin He, and Tzu-Shun Lin

Abstract. Accurate estimation of flow discharge is crucial for hydrological modelling, water resources planning, and flood prediction. This study examines seven common runoff schemes within the widely-used Noah-MP land surface model and evaluates their performance, using ERA5-Land runoff data as a benchmark for assessing runoff and in-situ streamflow observations for evaluating discharge across the globe. Then, to assess the sensitivity of global river discharge to runoff, we simulate the discharge, using the CaMa-Flood model, across various climatic regions. The results indicated significant variability in the accuracy of the runoff schemes, with model experiments that use TOPMODEL-based runoff schemes, which are based on topography, underestimates runoff across many regions, particularly in the Northern Hemisphere, while experiments using the other runoff schemes (Schaake, BATS, VIC, and XAJ) showed improved performance. Dynamic VIC consistently overestimated runoff globally. Seasonal analysis reveals substantial regional and seasonal variability. ERA5-Land and several Noah-MP schemes successfully replicated general discharge patterns of in-situ observations, with ERA5-Land and Noah-MP Schaake-scheme simulations closely aligning with observed data. The Noah-MP simulations demonstrated robust versatility across various land covers, soil types, basin sizes, and topographies, indicating its broad applicability. Despite overall good performance, significant biases in high-flow extremes highlight the need for continued model improvement or calibration. This study underscores the importance of improving land and hydrological models for accurate water resource management and climate adaptation strategies.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Mohamed Hamitouche, Giorgia Fosser, Alessandro Anav, Cenlin He, and Tzu-Shun Lin

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-2024-264', Anonymous Referee #1, 16 Oct 2024
    • AC1: 'Reply on RC1', Mohamed Hamitouche, 06 Nov 2024
  • RC2: 'Comment on hess-2024-264', Anonymous Referee #2, 17 Oct 2024
    • AC2: 'Reply on RC2', Mohamed Hamitouche, 06 Nov 2024
Mohamed Hamitouche, Giorgia Fosser, Alessandro Anav, Cenlin He, and Tzu-Shun Lin
Mohamed Hamitouche, Giorgia Fosser, Alessandro Anav, Cenlin He, and Tzu-Shun Lin

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Short summary
This study evaluates how different methods of simulating runoff impact river flow predictions globally. By comparing seven approaches within the Noah-MP land surface model, we found significant differences in accuracy, with some methods underestimating or overestimating runoff. The results are crucial for improving water resource management and flood prediction. Our work highlights the need for precise modeling to better prepare for climate-related challenges.