Articles | Volume 24, issue 6
https://doi.org/10.5194/hess-24-3189-2020
https://doi.org/10.5194/hess-24-3189-2020
Research article
 | 
19 Jun 2020
Research article |  | 19 Jun 2020

Multi-objective calibration by combination of stochastic and gradient-like parameter generation rules – the caRamel algorithm

Céline Monteil, Fabrice Zaoui, Nicolas Le Moine, and Frédéric Hendrickx

Related authors

Regional, multi-decadal analysis on the Loire River basin reveals that stream temperature increases faster than air temperature
Hanieh Seyedhashemi, Jean-Philippe Vidal, Jacob S. Diamond, Dominique Thiéry, Céline Monteil, Frédéric Hendrickx, Anthony Maire, and Florentina Moatar
Hydrol. Earth Syst. Sci., 26, 2583–2603, https://doi.org/10.5194/hess-26-2583-2022,https://doi.org/10.5194/hess-26-2583-2022, 2022
Short summary
Tailor-made spatial patterns for hydrological model parameters combining regionalisation methods
Laura Rouhier, Federico Garavaglia, Matthieu Le Lay, Timothée Michon, William Castaings, Nicolas Le Moine, Frédéric Hendrickx, Céline Monteil, and Pierre Ribstein
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2018-342,https://doi.org/10.5194/hess-2018-342, 2018
Manuscript not accepted for further review
Short summary

Related subject area

Subject: Water Resources Management | Techniques and Approaches: Modelling approaches
A generalised ecohydrological landscape classification for assessing ecosystem risk in Australia due to an altering water regime
Alexander Herr, Linda E. Merrin, Patrick J. Mitchell, Anthony P. O'Grady, Kate L. Holland, Richard E. Mount, David A. Post, Chris R. Pavey, and Ashley D. Sparrow
Hydrol. Earth Syst. Sci., 28, 1957–1979, https://doi.org/10.5194/hess-28-1957-2024,https://doi.org/10.5194/hess-28-1957-2024, 2024
Short summary
Process-based three-layer synergistic optimal-allocation model for complex water resource systems considering reclaimed water
Jing Liu, Yue-Ping Xu, Wei Zhang, Shiwu Wang, and Siwei Chen
Hydrol. Earth Syst. Sci., 28, 1325–1350, https://doi.org/10.5194/hess-28-1325-2024,https://doi.org/10.5194/hess-28-1325-2024, 2024
Short summary
Joint optimal operation of the South-to-North Water Diversion Project considering the evenness of water deficit
Bing-Yi Zhou, Guo-Hua Fang, Xin Li, Jian Zhou, and Hua-Yu Zhong
Hydrol. Earth Syst. Sci., 28, 817–832, https://doi.org/10.5194/hess-28-817-2024,https://doi.org/10.5194/hess-28-817-2024, 2024
Short summary
Employing the generalized Pareto distribution to analyze extreme rainfall events on consecutive rainy days in Thailand's Chi watershed: implications for flood management
Tossapol Phoophiwfa, Prapawan Chomphuwiset, Thanawan Prahadchai, Jeong-Soo Park, Arthit Apichottanakul, Watchara Theppang, and Piyapatr Busababodhin
Hydrol. Earth Syst. Sci., 28, 801–816, https://doi.org/10.5194/hess-28-801-2024,https://doi.org/10.5194/hess-28-801-2024, 2024
Short summary
How to account for irrigation withdrawals in a watershed model
Elisabeth Brochet, Youen Grusson, Sabine Sauvage, Ludovic Lhuissier, and Valérie Demarez
Hydrol. Earth Syst. Sci., 28, 49–64, https://doi.org/10.5194/hess-28-49-2024,https://doi.org/10.5194/hess-28-49-2024, 2024
Short summary

Cited articles

Baluja, S. and Caruana, R.: Removing the genetics from the standard genetic algorithm, in: Machine Learning Proceedings 1995, Morgan Kaufmann, San Francisco, USA, 38–46, 1995. a
Campo, L., Caparrini, F., and Castelli, F.: Use of multi-platform, multi-temporal remote-sensing data for calibration of a distributed hydrological model: an application in the Arno basin, Italy, Hydrol. Process., 20, 2693–2712, 2006. a
Coron, L., Thirel, G., Delaigue, O., Perrin, C., and Andréassian, V.: The Suite of Lumped GR Hydrological Models in an R package, Environ. Model. Softw., 94, 166–171, https://doi.org/10.1016/j.envsoft.2017.05.002, 2017. a, b, c
Coron, L., Delaigue, O., Thirel, G., Perrin, C., and Michel, C.: airGR: Suite of GR Hydrological Models for Precipitation-Runoff Modelling. R package version 1.3.2.23, available at: https://cran.r-project.org/package=airGR (last access: 15 June 2020), 2019. a, b, c
Deb, K., Pratap, A., Agarwal, S. Meyarivan, T.: A fast and elitist multiobjective genetic algorithm: NSGA-II, IEEE Trans. Evol. Comput., 6, 182–197, 2002. a, b, c
Download
Short summary
Environmental modelling is complex, and models often require the calibration of several parameters that are not able to be directly evaluated from a physical quantity or a field measurement. Based on our experience in hydrological modelling, we propose combining two algorithms to obtain a fast and accurate way of calibrating complex models (many parameters and many objectives). We built an R package, caRamel, so that this multi-objective calibration algorithm can be easily implemented.