Bayesian network models for environmental flow decision making in the Daly River, Northern Territory, Australia

Abstract

This paper reports the development and application of two Bayesian Network models to assist decision making on the environmental flows required to maintain the ecological health of the Daly River (Northern Territory, Australia). Currently, the Daly River is unregulated, with only a small volume of water extracted annually for agriculture. However, there is considerable pressure for further agricultural development in the catchment, particularly with demand for extra water extraction during the dry season (May-November). The abundances of two fish species-barramundi (Lates calcarifer) and sooty grunter (Hephaestus fuliginosus)-were chosen as the ecological endpoints for the models, which linked dry season flows to key aspects of the biology of each species. Where available, data were used to define flow-fish habitat relationships, but most of the relationships were defined by expert opinion because of a lack of quantified ecological knowledge. Recent field data on fish abundances were used to validate the models and gave prediction errors of 20-30%. The barramundi model indicated that the adult sub-population was key to overall fish abundance, with this sub-population particularly impacted by the timing of abstraction (early vs. late dry season). The sooty grunter model indicated that the juvenile sub-population dominated the overall abundance and that this was primarily due to the amount of hydraulically suitable riffle habitat. If current extraction entitlements were fully utilized, the models showed there would be significant impacts on the populations of these two fish species, with the probability of unacceptable abundances increasing to 43% from 25% for sooty grunter and from 36% for barramundi under natural conditions.