Cited by 148Hydrology and Watershed Management StudiesHydrological Forecasting Using AIEnvironmental Monitoring and Data Management

The DOI matches its Crossref record.

Technical note: Pitfalls in using log-transformed flows within the KGE criterion

Open access
Santos, Léonard, Thirel, Guillaume, Perrin, Charles·2018·Hydrology and Earth System Sciences

Published version of a preprint

Abstract

Log-transformed discharge is often used to calculate performance criteria to better focus on low flows. This prior transformation limits the heteroscedasticity of model residuals and was largely applied in criteria based on squared residuals, like the Nash–Sutcliffe efficiency (NSE). In the recent years, NSE has been shown to have mathematical limitations and the Kling–Gupta efficiency (KGE) was proposed as an alternative to provide more balance between the expected qualities of a model (namely representing the water balance, flow variability and correlation). As in the case of NSE, several authors used the KGE criterion (or its improved version KGE ′ ) with a prior logarithmic transformation on flows. However, we show that the use of this transformation is not adapted to the case of the KGE (or KGE ′ ) criterion and may lead to several numerical issues, potentially resulting in a biased evaluation of model performance. We present the theoretical underpinning aspects of these issues and concrete modelling examples, showing that KGE ′ computed on log-transformed flows should be avoided. Alternatives are discussed.

Overview

Integrity signals

Registry

Crossref · 10.5194/hess-22-4583-2018

Cites

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

Cites

Still being checked.

Research works printed but not linked: 30

  1. Beck, H. E., van Dijk, A. I. J. M., de Roo, A., Miralles, D. G., McVicar, T. R., Schellekens, J., and Bruijnzeel, L. A.: Global-scale regionalization of hydrologic model parameters, Water Resour. Res., 52, 3599–3622, 10.1002/2015WR018247, 2016. · DOI
  2. Box, G. E. P. and Cox, D. R.: An Analysis of Transformations, J. Roy. Stat. Soc. B, 26, 211–252, 1964. · DOI
  3. Chapman, T. G.: Effects of groud-water storage and flow on the water balance, in: Proceedings of “Water resources, use and management”, 291–301, Australian Academy of Science, Melbourne Univ. Press, 1964.
  4. 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, 166–177, 10.1016/j.envsoft.2017.05.002, 2017. · DOI
  5. De Vos, N. J. and Rientjes, T. H. M.: Multi-objective performance comparison of an artificial neural network and a conceptual rainfall-runoff model, Hydrol. Sci. J., 52, 397–413, 10.1623/hysj.52.3.397, 2010. · DOI
  6. Ding, J.: Interactive comment on “Technical note: Pitfalls in using log-transformed flows within the KGE criterion” by Léonard Santos et al., Hydrol. Earth Syst. Sci. Discuss., 10.5194/hess-2018-298-SC2, 2018a. · DOI
  7. Ding, J.: Interactive comment on “Technical note: Pitfalls in using log-transformed flows within the KGE criterion” by Léonard Santos et al., Hydrol. Earth Syst. Sci. Discuss., 10.5194/hess-2018-298-SC5, 2018b. · DOI
  8. Ding, J. Y.: Discussion of “Inflow hydrograph from large unconfined aquifers” by Ibrahim, H. A. and Brutsaert, W. J., J. Irrig. Drain. Am. Soc. Civ. Eng., 92, 104–107, 1966. · DOI
  9. Ficchí, A., Perrin, C., and Andréassian, V.: Impact of temporal resolution of inputs on hydrological model performance: An analysis based on 2400 flood events, J. Hydrol., 538, 454–470, 10.1016/j.jhydrol.2016.04.016, 2016. · DOI
  10. Garcia, F., Folton, N., and Oudin, L.: Which objective function to calibrate rainfall–runoff models for low-flow index simulations?, Hydrol. Sci. J., 62, 1149–1166, 10.1080/02626667.2017.1308511, 2016. · DOI
  11. Gupta, H. V., Kling, H., Yilmaz, K. K., and Martinez, G. F.: Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling, J. Hydrol., 377, 80–91, 10.1016/j.jhydrol.2009.08.003, 2009. · DOI · Paper page
  12. Hogue, T. S., Sorooshian, S., Gupta, H., Holz, A., and Braatz, D.: A Multistep Automatic Calibration Scheme for River Forecasting Models, J. Hydrometeorol., 1, 524–542, 10.1175/1525-7541(2000)0012.0.CO;2, 2000. · DOI
  13. Ishihara, T. and Takagi, F.: A study on the variation of low flow, Bulletin of the Disaster Prevention Research Institute, 15, 75–98, http://hdl.handle.net/2433/124698, 1965.
  14. Klemeš, V.: Operational testing of hydrological simulation models, Hydrol. Sci. J., 31, 13–24, 10.1080/02626668609491024, 1986. · DOI
  15. Kling, H., Fuchs, M., and Paulin, M.: Runoff conditions in the upper Danube basin under ensemble of climate change scenarios, J. Hydrol., 424–425, 264–277, 10.1016/j.jhydrol.2012.01.011, 2012. · DOI · Paper page
  16. Krause, P., Boyle, D. P., and Bäse, F.: Comparison of different efficiency criteria for hydrological model assessment, Adv. Geosci., 5, 89–97, 10.5194/adgeo-5-89-2005, 2005. · DOI
  17. Leleu, I., Tonnelier, I., Puechberty, R., Gouin, P., Viquendi, I., Cobos, L., Foray, A., Baillon, M., and Ndima, P.-O.: Re-founding the national information system designed to manage and give access to hydrometric data, La Houille Blanche, 1, 25–32, 10.1051/lhb/2014004, 2014 (in French). · DOI
  18. Lyon, S. W., King, K., Polpanich, O., and Lacombe, G.: Assessing hydrologic changes across the Lower Mekong Basin, J. Hydrol.: Reg. Stud., 12, 303–314, 10.1016/j.ejrh.2017.06.007, 2017. · DOI
  19. Nash, J. E. and Sutcliffe, J. V.: River flow forecasting through conceptual models. Part I – A discussion of principles, J. Hydrol., 10, 282–290, 10.1016/0022-1694(70)90255-6, 1970. · DOI
  20. Nguyen, V. T. and Dietrich, J.: Modification of the SWAT model to simulate regional groundwater flow using a multicell aquifer, Hydrol. Process., 32, 939–953, 10.1002/hyp.11466, 2018. · DOI
  21. Oudin, L., Hervieu, F., Michel, C., Perrin, C., Andréassian, V., Anctil, F., and Loumagne, C.: Which potential evapotranspiration input for a lumped rainfall–runoff model?, J. Hydrol., 303, 290–306, 10.1016/j.jhydrol.2004.08.026, 2005. · DOI
  22. Oudin, L., Andréassian, V., Mathevet, T., Perrin, C., and Michel, C.: Dynamic averaging of rainfall-runoff model simulations from complementary model parameterizations, Water Resour. Res., 42, W07410, 10.1029/2005wr004636, 2006. · DOI
  23. Pechlivanidis, I. G., Jackson, B., McMillan, H., and Gupta, H.: Use of an entropy-based metric in multiobjective calibration to improve model performance, Water Resour. Res., 50, 8066–8083, 10.1002/2013WR014537, 2014. · DOI
  24. Perrin, C., Michel, C., and Andréassian, V.: Improvement of a parsimonious model for streamflow simulation, J. Hydrol., 279, 275–289, 10.1016/s0022-1694(03)00225-7, 2003. · DOI
  25. Pushpalatha, R., Perrin, C., Moine, N. L., and Andréassian, V.: A review of efficiency criteria suitable for evaluating low-flow simulations, J. Hydrol., 420–421, 171–182, 10.1016/j.jhydrol.2011.11.055, 2012. · DOI
  26. Quesada-Montano, B., Westerberg, I. K., Fuentes-Andino, D., Hidalgo, H. G., and Halldin, S.: Can climate variability information constrain a hydrological model for an ungauged Costa Rican catchment?, Hydrol. Process., 32, 830–846, 10.1002/hyp.11460, 2018. · DOI
  27. Schaefli, B. and Gupta, H. V.: Do Nash values have value?, Hydrol. Process., 21, 2075–2080, 10.1002/hyp.6825, 2007. · DOI
  28. Seeger, S. and Weiler, M.: Reevaluation of transit time distributions, mean transit times and their relation to catchment topography, Hydrol. Earth Syst. Sci., 18, 4751–4771, 10.5194/hess-18-4751-2014, 2014. · DOI
  29. Vázquez, R. F., Willems, P., and Feyen, J.: Improving the predictions of a MIKE SHE catchment-scale application by using a multi-criteria approach, Hydrol. Process., 22, 2159–2179, 10.1002/hyp.6815, 2008. · DOI
  30. Vidal, J.-P., Martin, E., Franchisteguy, L., Baillon, M., and Soubeyroux, J.-M.: A 50-year high-resolution atmospheric reanalysis over France with the Safran system, Int. J. Climatol., 30, 1627–1644, 10.1002/joc.2003, 2010. · DOI

Cited by

Sorted by citations

See all 148

Metadata

Authors
Santos, L., Thirel, G., & Perrin, C.
Affiliations
Hydrosystèmes continentaux anthropisés : ressources, risques, restauration (FR)
Venue
Hydrology and Earth System Sciences
Published
2018-08-30
Volume
22
Issue
8
Pages
4583-4591
ISSN
  • 1027-5606 (ISSN-L)
  • 1607-7938
OpenAlex
W2806387338
Cited by
148
References
0
Citations by year
2026: 22 · 2025: 18 · 2024: 24 · 2023: 17 · 2022: 15 · 2021: 28 · 2020: 16 · 2019: 5 · 2018: 3
FWCI
5.70
Type
journal article
Language
en
Open access
Locations
  • Hydrology and earth system sciences (publishedVersion, cc-by)
  • HAL (submittedVersion, other-oa)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
  • Cemadoc (Cemagref / IRSTEA) (submittedVersion)
  • Biogeosciences (European Geosciences Union) (submittedVersion, cc-by)
Topics
  • Physical Sciences › Environmental Science › Water Science and Technology › Hydrology and Watershed Management Studies
  • Physical Sciences › Environmental Science › Environmental Engineering › Hydrological Forecasting Using AI
  • Physical Sciences › Environmental Science › Management, Monitoring, Policy and Law › Environmental Monitoring and Data Management
Keywords
Kling-Gupta efficiency, Nash-Sutcliffe efficiency, model evaluation, low flow, heteroscedasticity, model residuals, hydrological model calibration, Køge

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Technical note: Pitfalls in using log-transformed flows within the KGE criterion. https://app.cochat.ai/papers/10.5194/hess-22-4583-2018
The paper
Santos, L., Thirel, G., & Perrin, C. (2018). Technical note: Pitfalls in using log-transformed flows within the KGE criterion. Hydrology and Earth System Sciences. https://doi.org/10.5194/hess-22-4583-2018