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### HYPE Documentation

*Quick links to often-used pages:*

### HYPE links

HYPE OSC (model code)

HYPE Open data access

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SMHI Hydrology Research Dep., main developer and maintainer of the HYPE model

*Quick links to often-used pages:*

HYPE OSC (model code)

HYPE Open data access

Flow visualisation

SMHI Hydrology Research Dep., main developer and maintainer of the HYPE model

start:hype_file_reference:info.txt:criteria_equations

Performance criteria are used in several files. Different criterion is given in subass.txt and simass.txt files. In addition criteria can be selected in info.txt. Below is listed the code/heading used in each file together with the equation identificator. Further down all the equations are defined.

Equation IDs for subbasin assessment criteria (subassX.txt):

Heading | Description | Equation ID |
---|---|---|

`NSE` | Nash-Sutcliffe efficiency | NSE |

`CC` | Pearson correlation coefficient (Kling-Gupta efficiency, part 1) | CC |

`RE(%)` | relative bias in percent | RE% |

`RSDE(%)` | relative error in standard deviation in percent | RS% |

`Sim` | average of simulated variable | cm |

`Rec` | average of observed variable | rm |

`SDSim` | standard deviation of simulated variable | cd |

`SDRec` | standard deviation of observed variable | rd |

`MAE` | mean absolute error | MAE |

`RMSE` | root mean square error | RMSE |

`Bias` | bias | Bias |

`SDE` | Error of standard deviation | ES |

`KGE` | Kling-Gupta efficiency | KGE |

`KGESD` | Kling-Gupta efficiency, part 2 | KGESD |

`KGEM` | Kling-Gupta efficiency, part 3 | KGEM |

`NRMSE` | normalised root mean square error | NE |

`NSEW` | Nash-Sutcliffe efficiency adjusted for bias | NSEW |

Equation IDs for simulation assessment criteria (simass.txt):

Name | Code | Equation ID |
---|---|---|

Regional NSE | `RR2` | REGNSE |

Regional RA | `RRA` | REGRA |

Regional RE | `RRE` | REGRB |

Regional MAE | `-` | REGMAE |

Average NSE | `MR2` | AVNSE |

Average RA | `MRA` | AVRA |

Average RE | `MRE` | AVRB |

Average RSDE | `MRS` | AVRSB |

Average CC | `MCC` | AVCC |

Average ARE | `MAR` | AVARB |

Spatial NSE | `SR2` | SPATNSE |

Spatial RA | `RRA` | SPATRA |

Spatial RE | `-` | SPATRB |

Kendalls Tau | `TAU` | AVTAU |

Median NSE | `MD2` | MEDNSE |

Median RA | `MDA` | MEDRA |

Median KGE | `MKG` | MEDKGE |

Median NRMSE | `MNR` | MEDNE |

Mean NSEW | `MNW` | AVNSEW |

Equation IDs for calibration simulation assessment criteria (bestsims.txt and allsim.txt):

Heading | Description | Equation ID |
---|---|---|

`rr2` | regional Nash-Sutcliffe efficiency (data from all subbasins combined in one data series) | REGNSE |

`sr2` | spatial Nash-Sutcliffe efficiency, calculated using annual means for all subbasins (requires at least 5 years and 5 subbasins with data) to form one data series to calculate the Nash-Sutcliffe efficiency on | SPATNSE |

`mr2` | average of Nash-Sutcliffe efficiencies for subbasins | AVNSE |

`rmae` | regional mean absolute error (data from all subbasins combined in one data series) | REGMAE |

`sre` | spatial relative bias (calculated on annual means for all subbasins) | SPATRB |

`rre` | regional relative bias (data from all subbasins combined in one data series) | REGRB |

`mre` | average of the relative bias for all subbasins (Note: fraction, not %) | AVRB |

`rra` | regional RA, similar to regional NSE, RA is a Nash-Sutcliffe like criterion where the square in the Nash-Sutcliffe formula is exchanged with a coefficient value | REGRA |

`sra` | spatial RA, similar to spatial NSE, RA is a Nash-Sutcliffe like criterion where the square in the Nash-Sutcliffe formula is exchanged for a coefficient value | SPATRA |

`mra` | average value of RA for subbasins, RA is a Nash-Sutcliffe like criterion where the square in the Nash-Sutcliffe formula is exchanged with a coefficient value | AVRA |

`tau` | average of Kendall's Tau value for subbasins | AVTAU |

`md2` | median of Nash-Sutcliffe efficiency for subbasins | MEDNSE |

`mda` | median of all subbasins’ RA (Nash-Sutcliffe like criteria where the square is exchanged with a coefficient value) | MEDRA |

`mrs` | average of error in standard deviation for subbasins | AVRSB |

`mcc` | Pearson correlation coefficient, average of all subbasins with observations | AVCC |

`mdkg` | median of Kling-Gupta efficiency (MKG in info.txt) for subbasins | MEDKGE |

`mare` | average of absolute relative bias for subbasins (Note: fraction. not %) (MAR in info.txt) | AVARB |

`mnr` | median of normalised RMSE for subbasins | MEDNE |

`mnw` | average of Nash-Sutcliffe efficiencies adjusted for bias for subbasins | AVNSEW |

Equation IDs for performance criteria set in info.txt are tabled here.

c | computed value |

r | recorded value |

i | index for time steps with observations in a time series of a station |

mi | number of values in a time series of a station |

j | index of stations |

mj | number of stations |

ij | index over time steps with observations for all stations |

mij | number of time steps with obsevations for all stations |

cm | average value of for a station |

rm | average value of for a station |

cd | standard deviation of for a station |

rd | standard deviation of for a station |

Average value for a time series of a station:

*x=r* or *c*

Standard deviation of a time series of a station:

*x=r* or *c*

Nash-Sutcliffe Efficiency (*NSE* or R2):

Efficiency with coefficient a (*RA*):

Bias:

Relative bias (*RB* or RE):

Relative bias in percent (*RE%*):

Error of standard deviation (*ES*):

Relative error of standard deviation (*RS*):

Relative error of standard deviation in percent (*RS%*):

Mean absolute error (*MAE*):

Kling-Gupta efficiency (*KGE*):

Pearson correlation coefficient, Kling-Gupta efficiency part 1 (*CC*):

Kling-Gupta efficiency part 2 (*KGESD*):

Kling-Gupta efficiency part 3 (*KGEM*):

Root mean square error (*RMSE*):

Normalised root mean square error (*NE*):

Kendalls rank correlation coefficient, tau-b, with adjustments for ties (*TAU*):

Nash-Sutcliffe Efficiency adjusted for bias (*NSEW*). Introduced in Lindström (2016):

where

= number of concordant pairs ()

= number of discordant pairs ()

= number of compared pairs

= number of compared pairs that ties in the computed values

= number of compared pairs that ties in the recorded values

Average Nash-Sutcliffe efficiency (*AVNSE*):

Median Nash-Sutcliffe efficiency (*MEDNSE*):

Spatial Nash-Sutcliffe efficiency (*SPATNSE*):

Regional Nash-Sutcliffe efficiency (*REGNSE*):

Average efficiency with coefficient a (*AVRA*):

Median efficiency with coefficient a (*MEDRA*):

Spatial efficiency with coefficient a (*SPATRA*):

Regional efficiency with coefficient a (*REGRA*):

Average relative bias (*AVRB*):

Regional relative bias (*REGRB*):

Spatial relative bias (*SPATRB*):

Average Kling-Gupta efficiency (*AVKGE*):

Median Kling-Gupta efficiency (*MEDKGE*):

Median of Normalised root mean square error (*MEDNE*):

Average of absolute relative bias (*AVARB*):

Average Pearson correlation coefficient (*AVCC*):

Average relative error of standard deviation (*AVRSB*):

Average Kendalls rank correlation coefficient (*AVTAU*):

Regional mean absolute error (*REGMAE*):

Average Nash-Sutcliffe efficiency adjusted for bias (*AVNSEW*):

Lindström, G., 2016. Lake water levels for calibration of the S-HYPE model. Hydrology Research 47.4:672-682. doi: 10.2166/nh.2016.019.

start/hype_file_reference/info.txt/criteria_equations.txt · Last modified: 2019/08/28 14:57 by cpers

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