2.7.6.4 Receptor impact models

2.7.6.4.1 Percent foliage cover

Elicitation scenarios

Table 32 summarises the elicitation design matrix for the percent foliage cover of trees in the ‘Non-floodplain, terrestrial GDE’ landscape group. The first design point (design point identifier 1) sets the variability in percent foliage cover under the reference conditions (no drawdown).

The remaining design points represent hydrological scenarios that span the uncertainty in the values of the hydrological response variables in the relevant time period of hydrological history associated with the short-assessment (2013 to 2042) and long-assessment (2073 to 2102) periods.

Design point identifiers 2 through to 32 (as listed in Table 32) represent combinations of the two hydrological response variables (dmaxRef, tmaxRef), together with high and low values of Yref. The high and low values for Yref were calculated during the receptor impact modelling workshop following the experts’ response to the first design point, and then automatically included within the design for the elicitations at the subsequent design points.

Table 32 Elicitation design matrix for receptor impact model of annual percent canopy cover in the ‘Non-floodplain, terrestrial GDE’ landscape group

Design points for Yref in the future (short- and long-assessment periods) are calculated during the receptor impact modelling elicitation workshop using elicited values for the receptor impact variable in the reference period. All other design points (with identifiers) are either default values or values determined by groundwater and surface water modelling. dmaxRef and tmaxRef are as in Table 31. na = not applicable, GDE = groundwater-dependent ecosystem

Data: Bioregional Assessment Programme (Dataset 4)

Receptor impact model

The model fitted to the elicited values of mean percentage foliage cover takes the form:

where is an intercept term (a vector of ones), is a binary indicator variable scored 1 for the case of an assessment in the short- or long-assessment year, is a binary indicator variable scored 1 for the case of an assessment in the long-assessment year, is a continuous variable that represents the value of the receptor impact variable in the reference year (Yref, set to zero for the case of an assessment in the reference year), and are the (continuous or integer) values of the two hydrological response variables (dmaxRef, tmaxRef). Note that the modelling framework provides for more complex models, including the quadratic value of, and interactions between, the hydrological response variables but in this instance the simple linear model above was identified as the most parsimonious representation of the experts’ responses.

The (marginal) mean and 80% central credible intervals of the two hydrological response variable coefficients are summarised in the partial regression plot in Figure 37, whereas Table 33 summarises the same information for all six model coefficients.

Figure 37 (Top row) Predicted mean (black dot) and 80% central credible interval (grey line) of percent foliage cover under reference hydrological conditions. (Middle and bottom rows) Predicted future effect (mean = black line, 80% central credible interval = grey polygon) of each hydrological response variable on percent foliage cover

In the middle and bottom rows, all other hydrological response variables are held constant at the midpoint of their elicitation range (during the risk estimation process all hydrological response variables vary simultaneously). The dashed vertical lines show range of hydrological response variables used in the elicitation workshop. Reference = period from 1983 to 2012, Short = assessment period 2013 to 2042, Long = assessment period 2073 to 2102. dmaxRef is as in Table 31. Yrs2tmaxRef is the difference between tmaxRef and the assessment year that is relevant for the prediction (2012, 2042 or 2102). The numbers on the y-axis range from 0 to 1 as the receptor impact model was constructed using the proportion for the statistical modelling. They should be interpreted as a percent foliage cover ranging from 0 to 100%.

Data: Bioregional Assessment Programme (Dataset 4)

Table 33 Mean, 10th and 90th percentile of the coefficients of the receptor impact model for annual average percent canopy cover in the ‘Non-floodplain, terrestrial GDE’ landscape group in the Galilee subregion zone of potential hydrological change

Future is a binary variable scored 1 if the analysis case is in a short- or long-assessment period. Long is a binary variable scored 1 if the analysis case is in the assessment year. Yref is the value of the receptor impact variable in the reference assessment year; set to zero if case is in the reference assessment year. dmaxRef is as in Table 31. Yrs2tmaxRef is the difference between tmaxRef and the assessment year that is relevant for the prediction (2012, 2042 or 2102). GDE = groundwater-dependent ecosystem

Data: Bioregional Assessment Programme (Dataset 4)

The model indicates that the experts’ opinion provides strong evidence for Yref having a positive effect on average percent foliage cover. This suggests that given a set of hydrological response variable values in the future, a site with higher foliage cover at the 2012 reference point is more likely to have a higher foliage cover in the future than a site with a lower foliage cover value at this reference point. This reflects the lag in the response of foliage cover to changes in hydrological response variables that would be expected of mature trees with long life spans.

The model also indicates that the experts’ opinion provides evidence for dmaxRef and Yrs2tmaxRef having an almost negligible effect on average percent foliage cover (over the 10 m range in groundwater drawdown considered in the receptor impact modelling workshop). The model predicts that (holding all other hydrological response variables constant at the mid-point of their elicitation range) the mean of the average percent foliage cover will drop from roughly just under 48% without any change in groundwater level, to about 47% if the levels decrease by 10 m relative to the reference level in 2012. This may indicate that the groundwater dependency of the ‘Non-floodplain, terrestrial GDE’ landscape group is not well represented in the model. However, there is considerable uncertainty in these predictions, with an 80% chance that the foliage cover is between approximately 72% and 25% (Figure 37).

The summary statistics for the marginal distribution of the model coefficients (Table 33) for the two remaining model coefficients (future1 and long1) indicate that there is insufficient information in the expert-elicited data to determine the effect of either the future coefficient or the long coefficient. This situation is indicated by the opposite signs for the 10th and 90th percentiles for their respective coefficients in Table 33. These results are not surprising, as they suggest that the variation in the elicited values of the receptor impact variables can be adequately described by the other hydrological response variables.