The Monte Carlo simulations permit the probabilistic prediction of receptor impact variables. The receptor impact models include the ability to capture direct, indirect and cumulative impacts through the hydrological response variables. In addition, ecological lags imposed through the receptor impact variable are also captured by the above method. For example, the long-term response for a long-lived terrestrial species such as large woody riparian vegetation may be more sensitive to the previous history of the receptor within an assessment unit compared to a short-lived aquatic species. The approach can flexibly estimate a function of the receptor impact variable, such as actual or relative change, quantiles or averages. The range or distribution of receptor impact variable outcomes will be summarised for baseline (all years) and for the change due to additional coal resource development for future assessment years at landscape class level. The change due to additional coal resource development may be expressed in relative terms or actual terms and may depend on the specific receptor impact variable. These responses can be aggregated from the assessment units to the landscape class level to assess overall impacts of development within the bioregion or subregion.
