HYPE Model Documentation

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start:hype_file_reference:info.txt:criteria

Available performance criteria

Performance criteria that can be chosen as objective function for calibration in info.txt. The criteria are calculated for the model domain, based on performances at individual subbasins where observations exists. Four kinds of combination of the individual subbasins are used:

• average/median: criteria calculated in subbasins individually, and then combined (equal weight to each station, irrespective of time series length)
• regional: criteria calculated on a combined long time series over all subbasins (thus weighted by data lengths)
• spatial: time series att each subbasin is collapsed to a single long-term average, these averages are then combined to a “spatial series” over all subbasins, and the criteria calculated over those
• weighted average: criteria calculated in subbasins individually, and then combined as an weighted average with different weight (based on trust) to each station. The use of weighted average instead of arithmetic average is decided by a flag in info.txt (`weightsub`).

Available performance criteria for domain-wide model evaluation are listed in the table below. The following criteria will use weighted average in case of flag set for weighted subbasins; `MR2`, `MRA`, `MRE`, `MRS`, `MCC`, `AKG`, `MNW`, `ASK`, `TAU`, and `MAR`. Equation definitions for criteria calculation are described here.

Note: As described in info.txt, up to 100 performance criteria can be combined for model evaluation. However, for HYPE-internal computational reasons, criteria `TAU`, `MRA`, `RRA`, and `SRA` criteria must be defined as one of the first four criteria in info.txt (e.g. as `crit 1 criterion MRA`).

Criterion ID Description Equation ID
`MR2` average of Nash-Sutcliffe efficiency for all subbasins with observations. AVNSE
`MRE` average of the relative bias for all subbasins (Note: fraction, not %). AVRB
`MRA` average value of subbasin values of efficiency (RA) similar to Nash-Sutcliffe with coefficient a instead of a square. AVRA
`MCC` Pearson correlation coefficient, average of all subbasins with observations. AVCC
`MRS` error in standard deviation, average of all subbasins with observations. AVRSB
`MAR ` average of absolute relative bias for all subbasins (Note: fraction, not %). AVARB
`MNW` average of Nash-Sutcliffe efficiency adjusted for bias for all subbasins with observations. AVNSEW
`AKG` average of Kling-Gupta efficiency for all subbasins with observations. AVKGE
`ASK` average of rescaled Kling-Gupta efficiency for all subbasins with observations. ASCKGE
`RR2 ` regional Nash-Sutcliffe efficiency (all data combined in one long time series). REGNSE
`RRE ` regional relative bias (all data combined in one long time series). REGRB
`RRA ` regional efficiency similar to Nash-Sutcliffe with coefficient a instead of a square. REGRA
`MD2 ` median of Nash-Sutcliffe efficiency for all subbasins with observations. MEDNSE
`MDA ` median of all subbasins’ RA (efficiency similar to Nash-Sutcliffe with coefficient a instead of a square). MEDRA
`MKG ` median of all subbasins’ Kling-Gupta efficiency. MEDKGE
`MNR ` median of all subbasins’ normalised RMSE. MEDNE
`SR2 ` spatial Nash-Sutcliffe efficiency calculated using annual means for all subbasins (requires at least 5 years and 5 subbasins with data) to calculate the Nash-Sutcliffe efficiency. SPATNSE
`SRA ` Spatial efficiency similar to Nash-Sutcliffe with coefficient a instead of a square. SPATRA
`SNR ` Spatial RMSE. SPATRMSE
`SMB ` Spatial mean absolute scaled bias on log transformed values. SPATASB
`TAU ` average of Kendall's rank correlation coefficient (Tau) value for all subbasins. AVTAU