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HYPE Documentation
Quick links to often-used pages:
HYPE links
HYPE OSC (model code)
HYPE Open data access
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
SMHI Hydrology Research Dep., main developer and maintainer of the HYPE model
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 |
Average KGE | AKG | AVKGE |
Aver scalKGE | ASK | ASCKGE |
Spatial NSE | SR2 | SPATNSE |
Spatial RA | RRA | SPATRA |
Spatial RE | - | SPATRB |
Spatial Bias | SMB | SPATASB |
Spatial RMSE | SNR | SPATRMSE |
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 efficiency 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 |
akg | average of Kling-Gupta efficiency for subbasins | AVKGE |
asckg | average of Kling-Gupta efficiency rescaled to interval [-1,1] (C2M criteria applied to KGE, Mathevet et al. 2006) | ASCKGE |
mare | average of absolute relative bias for subbasins (Note: fraction. not %) (MAR in info.txt) | AVARB |
mdnr | median of normalised RMSE for subbasins | MEDNE |
mnw | average of Nash-Sutcliffe efficiencies adjusted for bias for subbasins | AVNSEW |
snr | spatial root mean square error | SPATRMSE |
smb | spatial mean absolute scaled bias on natural log transformed values | SPATASB |
Equation IDs for performance criteria set in info.txt are tabled here.
c | computed value |
r | recorded value |
cl | log transform of computed value, natural logarithm |
rl | log transform of recorded value, natural logarithm |
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 |
rm | average value of |
cd | standard deviation of |
rd | standard deviation of |
w | weight of 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
Natural logaritm of value:
x=r or c or rm or cm, x>0
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):
cm>0 and rm>0 and cd>0 and rd>0
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
Scaled bias (ScBias):
Scaled KGE (SCKGE):
Average Nash-Sutcliffe efficiency (AVNSE):
AVNSE arithmetric mean
or AVNSE weighted average
Median Nash-Sutcliffe efficiency (MEDNSE):
Spatial Nash-Sutcliffe efficiency (SPATNSE):
Regional Nash-Sutcliffe efficiency (REGNSE):
Average Nash-Sutcliffe efficiency adjusted for bias (AVNSEW):
AVNSEW arithmetric mean
or AVNSEW weighted average
Average efficiency with coefficient a (AVRA):
AVRA arithmetric mean
or AVRA weighted average
Median efficiency with coefficient a (MEDRA):
Spatial efficiency with coefficient a (SPATRA):
Regional efficiency with coefficient a (REGRA):
Average relative bias (AVRB):
AVRB arithmetric mean
or AVRB weighted average
Regional relative bias (REGRB):
Spatial relative bias (SPATRB):
Average Kling-Gupta efficiency (AVKGE):
AVKGE arithmetric mean
or AVKGE weighted average
Median Kling-Gupta efficiency (MEDKGE):
Average scaled Kling-Gupta efficiency (ASCKGE):
ASCKGE arithmetric mean
or ASCKGE weighted average
Spatial root mean square error (SPATRMSE):
Median of Normalised root mean square error (MEDNE):
Average of absolute relative bias (AVARB):
AVARB arithmetric mean
or AVARB weighted average
Average Pearson correlation coefficient (AVCC):
AVCC arithmetric mean
or AVCC weighted average
Average relative error of standard deviation (AVRSB):
AVRSB arithmetric mean
or AVRSB weighted average
Average Kendalls rank correlation coefficient (AVTAU):
AVTAU arithmetric mean
or AVTAU weighted average
Regional mean absolute error (REGMAE):
Spatial mean absolute scaled bias on log transformed values (SPATASB):
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.
Mathevet et al. 2006. A bounded version of the Nash-Sutcliffe criterion for better model assessment on large sets of basins. In: Large Sample Basin Experiments for Hydrological Model Parameterization: Results of the Model Parameter Experiment–MOPEX. IAHS Publ. 307, 2006, p. 211-219.