Articles | Volume 27, issue 9
https://doi.org/10.5194/hess-27-1827-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-27-1827-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
09 May 2023
Research article |
| 09 May 2023
| 09 May 2023
A signal-processing-based interpretation of the Nash–Sutcliffe efficiency
Institute of Engineering Innovation, University of Tokyo, Tokyo 113-8656, Japan
Department of Observation and Data Assimilation Research, Meteorological Research Institute, Tsukuba, Ibaraki 305-0052, Japan
Yohei Sawada
Institute of Engineering Innovation, University of Tokyo, Tokyo 113-8656, Japan
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- Optimizing the hydraulic performance of a baffled horizontal subsurface flow constructed wetland through computational fluid dynamics modelling J. Wei et al. 10.1016/j.jenvman.2023.119776
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- Towards a generic model evaluation metric for non-normally distributed measurements in water quality and ecosystem models T. Fu & C. Zhang 10.1016/j.ecoinf.2024.102470
- Combined dam-break modes between upper and lower reservoirs of pumped storage hydropower stations and associated flood risk assessment B. Zhu et al. 10.2166/ws.2024.223
- A short history of philosophies of hydrological model evaluation and hypothesis testing K. Beven 10.1002/wat2.1761
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- Rainfall-runoff modeling based on HEC-HMS model: a case study in an area with increased groundwater discharge potential M. Herbei et al. 10.3389/frwa.2024.1474990
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- Technical Note: The divide and measure nonconformity – how metrics can mislead when we evaluate on different data partitions D. Klotz et al. 10.5194/hess-28-3665-2024
20 citations as recorded by crossref.
- Optimizing the hydraulic performance of a baffled horizontal subsurface flow constructed wetland through computational fluid dynamics modelling J. Wei et al. 10.1016/j.jenvman.2023.119776
- Hypothesis Testing for the Difference between Two Nash–Sutcliffe Efficiencies for Comparing Hydrological Model Performance D. Liu 10.1061/JHYEFF.HEENG-6035
- Impact of climate change on the streamflow in northern Patagonia J. Rivera et al. 10.2166/wcc.2024.492
- Australia’s 2019/20 Black Summer fire weather exceptionally rare over the last 2000 years D. Udy et al. 10.1038/s43247-024-01470-z
- Influence of the External Environment on the Moisture Spectrum of Norway Spruce (Picea abies (L.) KARST.) M. Lexa et al. 10.3390/f14071342
- A Review on Soil Moisture Dynamics Monitoring in Semi-Arid Ecosystems: Methods, Techniques, and Tools Applied at Different Scales E. Duarte & A. Hernandez 10.3390/app14177677
- Advanced ERT techniques for methane potential evaluation in controlled dump sites: A forward modeling approach P. Boonsakul et al. 10.1016/j.rineng.2024.103256
- Assessing the impacts of climate and land cover change on groundwater recharge in a semi-arid region of Southern India N. Chandra & S. Sahoo 10.1007/s00704-024-05065-8
- Beyond a fixed number: Investigating uncertainty in popular evaluation metrics of ensemble flood modeling using bootstrapping analysis T. Huang & V. Merwade 10.1111/jfr3.12982
- Towards a generic model evaluation metric for non-normally distributed measurements in water quality and ecosystem models T. Fu & C. Zhang 10.1016/j.ecoinf.2024.102470
- Combined dam-break modes between upper and lower reservoirs of pumped storage hydropower stations and associated flood risk assessment B. Zhu et al. 10.2166/ws.2024.223
- A short history of philosophies of hydrological model evaluation and hypothesis testing K. Beven 10.1002/wat2.1761
- CROPGRIDS: a global geo-referenced dataset of 173 crops F. Tang et al. 10.1038/s41597-024-03247-7
- Prediction of Sea Level Using Double Data Decomposition and Hybrid Deep Learning Model for Northern Territory, Australia N. Raj et al. 10.3390/math12152376
- Long-term AI prediction of ammonium levels in rivers using transformer and ensemble models A. Ali & A. Ahmed 10.1016/j.clwat.2024.100051
- Hydraulic Characterization of Green Roof Substrates by Evaporation Experiments D. Autovino et al. 10.3390/app14041617
- Rainfall-runoff modeling based on HEC-HMS model: a case study in an area with increased groundwater discharge potential M. Herbei et al. 10.3389/frwa.2024.1474990
- Comparison of the performances of six empirical mass transfer-based reference evapotranspiration estimation models in semi-arid conditions S. Usta 10.7717/peerj.18549
- Applications, technologies, and evaluation methods in smart aquaponics: a systematic literature review M. Anila & O. Daramola 10.1007/s10462-024-11003-x
- Technical Note: The divide and measure nonconformity – how metrics can mislead when we evaluate on different data partitions D. Klotz et al. 10.5194/hess-28-3665-2024
Latest update: 13 Dec 2024
Short summary
The Nash–Sutcliffe efficiency (NSE) is a widely used score in hydrology, but it is not common in the other environmental sciences. One of the reasons for its unpopularity is that its scientific meaning is somehow unclear in the literature. This study attempts to establish a solid foundation for NSE from the viewpoint of signal progressing. This approach is shown to yield profound explanations to many open problems related to NSE. A generalized NSE that can be used in general cases is proposed.
The Nash–Sutcliffe efficiency (NSE) is a widely used score in hydrology, but it is not common in...
