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Table 3.5
Explanation of how RIVPACS calculates a prediction (in this case, ASPT index). The example
is a simplified model with only 5 end groups, A-E. RIVPACS IV GB model has 43 end groups; NI
model has 11 end groups.

End group Probability of site Average of values of Contribution of
being in end group ASPT in reference end group to
sites in the end group prediction of ASPT
(p) × =
A 0.3 6.3 1.89
B 0.2 8.2 1.64
C 0.4 6.0 2.4

D 0.08 5.4 0.432
E 0.02 5.3 0.106

Σ = 1
Predicted value of ASPT at site = Σ = 6.47

3.3 Predicting reference values for WHPT indices

Not all RIVPACS reference sites are in WFD reference quality (a process that we call adjustment) and then ensure
state, which is somewhere in High status. The High/Good that standardised quality is the WFD reference state (in a
boundary is the median quality of RIVPACS III+ reference step we call conversion).
sites, so half of them must be in Good status or worse (Figure
3.9, Figure 3.15 and Figure 3.16). The environmental quality RICT2 can transform RIVPACS predictions for WHPT ASPT
that RIVPACS predictions reflect therefore varies according and WHPT NTaxa into reference values that are needed
to the environmental quality of the reference samples on for WFD status classification. If you want to create WFD-
which each prediction is based. To ensure comparability compatible class boundaries for other indices, you will
between predictions, and between classifications based on need to follow the process of adjustment and conversion
them across different river types, we must standardise the described below.
predictions to ensure that they always relate to the same

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