Preprints
https://doi.org/10.5194/gmd-2022-135
https://doi.org/10.5194/gmd-2022-135
Submitted as: development and technical paper
23 May 2022
Submitted as: development and technical paper | 23 May 2022
Status: this preprint is currently under review for the journal GMD.

Modular Assessment of Rainfall–Runoff Models Toolbox (MARRMoT) v2.1: an object-oriented implementation of 47 of your favourite hydrologic models for improved speed and readability

Luca Trotter1, Wouter J. M. Knoben2, Keirnan J. A. Fowler1, Margarita Saft1, and Murray C. Peel1 Luca Trotter et al.
  • 1Department of Infrastructure Engineering, University of Melbourne, Melbourne, Parkville VIC 3052, Australia
  • 2Centre for Hydrology, University of Saskatchewan, Canmore, Alberta T1W 3G1, Canada

Abstract. The Modular Assessment of Rainfall–Runoff Models Toolbox (MARRMoT) is a flexible modelling framework reproducing the behaviour of 47 established hydrological models. MARRMoT can be used to calibrate and run models in a user-friendly and consistent way and is designed to facilitate the sharing of model code for reproducibility and to support intercomparison between hydrological models. Additionally, it allows users to create or modify models using components of existing ones. We present a new MARRMoT release (v2.1) designed for improved speed and ease of use. Whereas improved computational efficiency was the main driver for this redevelopment, MARRMoT v2.1 also succeeds in drastically reducing the verbosity and repetitiveness of the code, which improves readability and facilitates debugging. The process to create new models or modify existing ones within the toolbox is also simplified in this version, making MARRMoT v2.1 accessible for researchers and practitioners at all levels of expertise. These improvements were achieved by implementing an object-oriented structure and aggregating all common model operations into a single class definition that all models inherit from. The new modelling framework maintains and improves on several of the good practices built into the original MARRMoT and includes a number of new features such as the possibility of retrieving more output in different formats, which simplifies troubleshooting, and a new functionality that simplifies the calibration process. We compare outputs of 36 of the models in the framework to an earlier published analysis and demonstrate that MARRMoT v2.1 is highly consistent with the previous version of MARRMoT (v1.4), while achieving a 3.6-fold improvement in runtime on average. The new version of the toolbox and user manual, including several workflow examples for common application, are available from GitHub (https://github.com/wknoben/MARRMoT, last accessed 12/5/2022. DOI: 10.5281/zenodo.6484372).

Luca Trotter et al.

Status: open (until 18 Jul 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2022-135', Anonymous Referee #1, 02 Jun 2022 reply

Luca Trotter et al.

Model code and software

MARRMoT v2.1 Luca Trotter and Wouter Knoben https://doi.org/10.5281/zenodo.6484372

Luca Trotter et al.

Viewed

Total article views: 350 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
284 58 8 350 13 2 2
  • HTML: 284
  • PDF: 58
  • XML: 8
  • Total: 350
  • Supplement: 13
  • BibTeX: 2
  • EndNote: 2
Views and downloads (calculated since 23 May 2022)
Cumulative views and downloads (calculated since 23 May 2022)

Viewed (geographical distribution)

Total article views: 327 (including HTML, PDF, and XML) Thereof 327 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 30 Jun 2022
Download
Short summary
MARRMoT is a piece of software that emulates 47 common models for hydrological simulations. It can be used to run and calibrate these models within a common environment as well as to easily modify them. We restructured and recoded MARRMoT in order to make the models run faster and to simplify their use, while also providing some new features. This new MARRMoT version runs models on average 3.6 times faster while maintaining very strong consistency in their outputs to the previous version.